From e96d44102fd52458a7292a2295237c83d1bef030 Mon Sep 17 00:00:00 2001 From: Sebastian Fischer Date: Thu, 3 Jul 2025 16:42:48 +0200 Subject: [PATCH 1/3] FIX: small bug with calling gem5 --- LinProg_Scripts/run_para_explore_gem5.sh | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/LinProg_Scripts/run_para_explore_gem5.sh b/LinProg_Scripts/run_para_explore_gem5.sh index 49691fc..2e9d3a8 100755 --- a/LinProg_Scripts/run_para_explore_gem5.sh +++ b/LinProg_Scripts/run_para_explore_gem5.sh @@ -18,11 +18,11 @@ script_start=$(date +%s) csv_file="/home/sfischer/Documents/projects/wk_LinProg/optimization_results/inception70/resultsGem5.csv" -for noc_factor in $(seq 1.0 -0.1 0.1); do - for comp_factor in $(seq 1.0 -0.1 0.1); do +# for noc_factor in $(seq 1.0 -0.1 0.1); do +# for comp_factor in $(seq 1.0 -0.1 0.1); do -# for noc_factor in 0.1; do -# for comp_factor in 0.1; do +for noc_factor in 0.1; do + for comp_factor in 1.0; do echo "---------------------------------------------" echo "Running LinProg with noc_factor=$noc_factor and comp_factor=$comp_factor" @@ -54,7 +54,7 @@ for noc_factor in $(seq 1.0 -0.1 0.1); do # ./run_linProg.sh "NoOpt_NoC_${noc_factor}_Comp_${comp_factor}" # Call your run_linProg.sh and capture the output - time_per_rep_microseconds=$(./run_linProg.sh "NoOpt_NoC_${noc_factor}_Comp_${comp_factor}" | tail -1) + time_per_rep_microseconds=$(./run_linProg.sh "Opt_NoC_${noc_factor}_Comp_${comp_factor}" | tail -1) # Write to CSV write_to_csv "$csv_file" "$noc_factor" "$comp_factor" "$time_per_rep_microseconds" From 2686f386faa865b6284c8327904d065d670a316b Mon Sep 17 00:00:00 2001 From: Sebastian Fischer Date: Thu, 3 Jul 2025 16:43:40 +0200 Subject: [PATCH 2/3] ADD: small changes to make gem5 sim callable from other script --- simulation/scripts/run_linProg.sh | 23 +++++++++++++++-------- 1 file changed, 15 insertions(+), 8 deletions(-) diff --git a/simulation/scripts/run_linProg.sh b/simulation/scripts/run_linProg.sh index 4e4d532..86c43f6 100755 --- a/simulation/scripts/run_linProg.sh +++ b/simulation/scripts/run_linProg.sh @@ -32,28 +32,35 @@ runSimAndAnaly(){ cd /home/sfischer/Documents/projects/wk_LinProg/simulation/scripts echo "Starting the Analysis!" - python3 MESI_Analysis_Gemmini.py \ + # python3 MESI_Analysis_Gemmini.py \ + # --link_width $width \ + # --repetition $repetition \ + # --workload $workload \ + # --strategy $strategy + + time_per_rep_microseconds=$(python3 MESI_Analysis_Gemmini.py \ --link_width $width \ --repetition $repetition \ --workload $workload \ - --strategy $strategy - - rm -rf /home/sfischer/Documents/projects/wk_LinProg/simulation/results/log_raw/* + --strategy $strategy | tail -1) + + # rm -rf /home/sfischer/Documents/projects/wk_LinProg/simulation/results/log_raw/* } link_width_bits_list=(576) #max 72B = 576bit must be devisible by 8 (in gem5 used as byte) -repetitions_list=(100) +repetitions_list=(50) scratchpad_size_list=(10000) compression_factor_list=(1) # 1 = no compression # workload="MobileNetV2_20Layer_1C10A_R100_1GHz_fast3" -workload="LinProgTest" +workload="LinProg_opt" -strategy_mode="Test2Thr100" +# strategy_mode="Inception70_NoOpt_1x_fast2" +strategy_mode="${1:-Inception70_NoOpt_1x_fast3}" folder_path_2gem5="/home/sfischer/Documents/projects/wk_gem5_SysXelerator_v2" @@ -83,7 +90,7 @@ for LINK_WIDTH_BITS in "${link_width_bits_list[@]}"; do done done - +echo "$time_per_rep_microseconds" From 3fbea57fa8616505f6b37aba372ad6b90e5ed3b5 Mon Sep 17 00:00:00 2001 From: Sebastian Fischer Date: Thu, 3 Jul 2025 16:44:07 +0200 Subject: [PATCH 3/3] ADD: new simulations --- .gitignore | 852 + LinProg_Scripts/Analyse_LinProg_results.ipynb | 14091 ++-- LinProg_Scripts/CombinedMapping.txt | 10 +- LinProg_Scripts/LinProgResults.json | 119 +- LinProg_Scripts/NoC_LinProg.ipynb | 4028 +- LinProg_Scripts/PE_graph.graphml | 82 +- LinProg_Scripts/PE_graph.pkl | Bin 468 -> 782 bytes LinProg_Scripts/ResultHeatmap.py | 62 +- LinProg_Scripts/Task_LinProg.ipynb | 593 +- LinProg_Scripts/Task_graph.graphml | 730 +- LinProg_Scripts/Task_graph.pkl | Bin 1406 -> 4082 bytes LinProg_Scripts/graph_plot.pkl | Bin 918 -> 991 bytes LinProg_Scripts/run_para_explor.sh | 6 +- LinProg_Scripts/task_graph_NoInit.pkl | Bin 1898 -> 5915 bytes LinProg_Scripts/task_graph_feedback.pkl | Bin 2094 -> 7464 bytes XML/LinProg_test/data.xml | 2765 +- XML/LinProg_test/dataNoInit.xml | 2257 +- XML/LinProg_test/map.xml | 368 +- XML/LinProg_test/mapNoInit.xml | 260 +- XML/LinProg_test/map_addition.xml | 856 +- XML/LinProg_test/map_additionNoInit.xml | 436 +- XML_Scripts/Graph2XML.ipynb | 373 +- XML_Scripts/mappingXML.ipynb | 6 +- .../FullOpt_5x/FullOpt_LinProg_5x_heatmap.png | Bin 0 -> 69030 bytes .../inception70/FullOpt_5x/resultsLinProg.csv | 37 + .../No_mem_Fullopt_5x_NoC0.1_Comp0.1.pkl | Bin 0 -> 15042814 bytes .../No_mem_Fullopt_5x_NoC0.1_Comp1.0.pkl | Bin 0 -> 15042814 bytes .../Noopt_5x_new/noOpt_gem5_5x_heatmap.png | Bin 88435 -> 121571 bytes .../Opt_noChange_5x_new/Opt_5x_heatmap.png | Bin 0 -> 115797 bytes .../Opt_gem5_5x_heatmap.png | Bin 0 -> 119638 bytes .../Opt_noChange_5x_new/resultsGem5.csv | 101 + .../Opt_noChange_5x_new/resultsLinProg.csv | 101 + .../inception70/resultsGem5.csv | 3 + .../inception70/resultsLinProg.csv | 3 + .../scripts/Detailed_gem5_results.ipynb | 57420 +--------------- 35 files changed, 17577 insertions(+), 67982 deletions(-) create mode 100644 optimization_results/inception70/FullOpt_5x/FullOpt_LinProg_5x_heatmap.png create mode 100644 optimization_results/inception70/FullOpt_5x/resultsLinProg.csv create mode 100644 optimization_results/inception70/No_mem_Fullopt_5x_NoC0.1_Comp0.1.pkl create mode 100644 optimization_results/inception70/No_mem_Fullopt_5x_NoC0.1_Comp1.0.pkl create mode 100644 optimization_results/inception70/Opt_noChange_5x_new/Opt_5x_heatmap.png create mode 100644 optimization_results/inception70/Opt_noChange_5x_new/Opt_gem5_5x_heatmap.png create mode 100644 optimization_results/inception70/Opt_noChange_5x_new/resultsGem5.csv create mode 100644 optimization_results/inception70/Opt_noChange_5x_new/resultsLinProg.csv create mode 100644 optimization_results/inception70/resultsGem5.csv create mode 100644 optimization_results/inception70/resultsLinProg.csv diff --git a/.gitignore b/.gitignore index c20c5a8..5ee0fbf 100644 --- a/.gitignore +++ b/.gitignore @@ -194,3 +194,855 @@ XML/LinProg_test/map_addition_old.xml XML/LinProg_test/map_additionNoInit_old.xml XML/LinProg_test/LinProgResults.json LinProg_Scripts/test.py +optimization_results/inception70/NoOpt/No_mem_NoC0.1_Comp0.1.pkl +optimization_results/inception70/NoOpt/No_mem_NoC0.1_Comp0.2.pkl +optimization_results/inception70/NoOpt/No_mem_NoC0.1_Comp0.3.pkl +optimization_results/inception70/NoOpt/No_mem_NoC0.1_Comp0.4.pkl +optimization_results/inception70/NoOpt/No_mem_NoC0.1_Comp0.5.pkl 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"execution_count": null, "id": "48a3a0ef", "metadata": {}, "outputs": [ @@ -10,7 +10,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Memory mapping: {0: 0, 10: 6439, 11: 1775, 12: 1456, 13: 1426, 14: 0, 15: 11745, 1: 0, 2: 274, 3: 0, 4: 0, 5: 2554, 6: 0, 7: 0, 8: 3913, 9: 0}\n", + "Memory mapping: {0: 1191, 10: 0, 11: 0, 12: 0, 13: 0, 14: 0, 15: 0, 1: 274, 2: 1924, 3: 2554, 4: 7716, 5: 265, 6: 12630, 7: 3028, 8: 0, 9: 0}\n", "\n", "All constraints in the model:\n", "_C1: -t0_end_ + t_comp_0 <= 0\n", @@ -118421,5958 +118421,5948 @@ "_C118406: same_68_69 - same_68_69_and_0 - same_68_69_and_1 - same_68_69_and_10 - same_68_69_and_11 - same_68_69_and_12 - same_68_69_and_13 - same_68_69_and_14 - same_68_69_and_15 - same_68_69_and_2 - same_68_69_and_3 - same_68_69_and_4 - same_68_69_and_5 - same_68_69_and_6 - same_68_69_and_7 - same_68_69_and_8 - same_68_69_and_9 = -0.0\n", "_C118407: same_69_69 = 1\n", "_C118408: t_0_map_0 + t_0_map_1 + t_0_map_10 + t_0_map_11 + t_0_map_12 + t_0_map_13 + t_0_map_14 + t_0_map_15 + t_0_map_2 + t_0_map_3 + t_0_map_4 + t_0_map_5 + t_0_map_6 + t_0_map_7 + t_0_map_8 + t_0_map_9 = 1.0\n", - "_C118409: -t0_end_ + t0_start + t_comp_0 <= 0\n", - "_C118410: t_comp_0 = 6\n", + "_C118409: -t0_end_ + t0_start + t_comp_0 + t_send_0 <= 0\n", + "_C118410: t_comp_0 = 4\n", "_C118411: t_mem_0 = 1078\n", "_C118412: t_1_map_0 + t_1_map_1 + t_1_map_10 + t_1_map_11 + t_1_map_12 + t_1_map_13 + t_1_map_14 + t_1_map_15 + t_1_map_2 + t_1_map_3 + t_1_map_4 + t_1_map_5 + t_1_map_6 + t_1_map_7 + t_1_map_8 + t_1_map_9 = 1.0\n", - "_C118413: -t1_end_ + t1_start + t_comp_1 <= 0\n", - "_C118414: t0_end_ - t1_start + t_send_0 <= 0\n", - "_C118415: t_comp_1 = 56\n", + "_C118413: -t1_end_ + t1_start + t_comp_1 + t_send_1 <= 0\n", + "_C118414: t0_end_ - t1_start <= 0\n", + "_C118415: t_comp_1 = 34\n", "_C118416: t_mem_1 = 38\n", "_C118417: t_2_map_0 + t_2_map_1 + t_2_map_10 + t_2_map_11 + t_2_map_12 + t_2_map_13 + t_2_map_14 + t_2_map_15 + t_2_map_2 + t_2_map_3 + t_2_map_4 + t_2_map_5 + t_2_map_6 + t_2_map_7 + t_2_map_8 + t_2_map_9 = 1.0\n", - "_C118418: -t2_end_ + t2_start + t_comp_2 <= 0\n", - "_C118419: t1_end_ - t2_start + t_send_1 <= 0\n", - "_C118420: t_comp_2 = 112\n", + "_C118418: -t2_end_ + t2_start + t_comp_2 + t_send_2 <= 0\n", + "_C118419: t1_end_ - t2_start <= 0\n", + "_C118420: t_comp_2 = 67\n", "_C118421: t_mem_2 = 75\n", "_C118422: t_3_map_0 + t_3_map_1 + t_3_map_10 + t_3_map_11 + t_3_map_12 + t_3_map_13 + t_3_map_14 + t_3_map_15 + t_3_map_2 + t_3_map_3 + t_3_map_4 + t_3_map_5 + t_3_map_6 + t_3_map_7 + t_3_map_8 + t_3_map_9 = 1.0\n", - "_C118423: -t3_end_ + t3_start + t_comp_3 <= 0\n", - "_C118424: t2_end_ - t3_start + t_send_2 <= 0\n", + "_C118423: -t3_end_ + t3_start + t_comp_3 + t_send_3 <= 0\n", + "_C118424: t2_end_ - t3_start <= 0\n", "_C118425: t_comp_3 = 1\n", "_C118426: t_mem_3 = 0\n", "_C118427: t_4_map_0 + t_4_map_1 + t_4_map_10 + t_4_map_11 + t_4_map_12 + t_4_map_13 + t_4_map_14 + t_4_map_15 + t_4_map_2 + t_4_map_3 + t_4_map_4 + t_4_map_5 + t_4_map_6 + t_4_map_7 + t_4_map_8 + t_4_map_9 = 1.0\n", - "_C118428: -t4_end_ + t4_start + t_comp_4 <= 0\n", - "_C118429: t2_end_ - t4_start + t_send_2 <= 0\n", - "_C118430: t_comp_4 = 83\n", + "_C118428: -t4_end_ + t4_start + t_comp_4 + t_send_4 <= 0\n", + "_C118429: t2_end_ - t4_start <= 0\n", + "_C118430: t_comp_4 = 50\n", "_C118431: t_mem_4 = 223\n", "_C118432: t_5_map_0 + t_5_map_1 + t_5_map_10 + t_5_map_11 + t_5_map_12 + t_5_map_13 + t_5_map_14 + t_5_map_15 + t_5_map_2 + t_5_map_3 + t_5_map_4 + t_5_map_5 + t_5_map_6 + t_5_map_7 + t_5_map_8 + t_5_map_9 = 1.0\n", - "_C118433: -t5_end_ + t5_start + t_comp_5 <= 0\n", - "_C118434: t3_end_ - t5_start + t_send_3 <= 0\n", - "_C118435: t4_end_ - t5_start + t_send_4 <= 0\n", + "_C118433: -t5_end_ + t5_start + t_comp_5 + t_send_5 <= 0\n", + "_C118434: t3_end_ - t5_start <= 0\n", + "_C118435: t4_end_ - t5_start <= 0\n", "_C118436: t_comp_5 = 0\n", "_C118437: t_mem_5 = 0\n", "_C118438: t_6_map_0 + t_6_map_1 + t_6_map_10 + t_6_map_11 + t_6_map_12 + t_6_map_13 + t_6_map_14 + t_6_map_15 + t_6_map_2 + t_6_map_3 + t_6_map_4 + t_6_map_5 + t_6_map_6 + t_6_map_7 + t_6_map_8 + t_6_map_9 = 1.0\n", - "_C118439: -t6_end_ + t6_start + t_comp_6 <= 0\n", - "_C118440: t5_end_ - t6_start + t_send_5 <= 0\n", - "_C118441: t_comp_6 = 16\n", + "_C118439: -t6_end_ + t6_start + t_comp_6 + t_send_6 <= 0\n", + "_C118440: t5_end_ - t6_start <= 0\n", + "_C118441: t_comp_6 = 10\n", "_C118442: t_mem_6 = 42\n", "_C118443: t_7_map_0 + t_7_map_1 + t_7_map_10 + t_7_map_11 + t_7_map_12 + t_7_map_13 + t_7_map_14 + t_7_map_15 + t_7_map_2 + t_7_map_3 + t_7_map_4 + t_7_map_5 + t_7_map_6 + t_7_map_7 + t_7_map_8 + t_7_map_9 = 1.0\n", - "_C118444: -t7_end_ + t7_start + t_comp_7 <= 0\n", - "_C118445: t6_end_ - t7_start + t_send_6 <= 0\n", - "_C118446: t_comp_7 = 78\n", + "_C118444: -t7_end_ + t7_start + t_comp_7 + t_send_7 <= 0\n", + "_C118445: t6_end_ - t7_start <= 0\n", + "_C118446: t_comp_7 = 47\n", "_C118447: t_mem_7 = 223\n", "_C118448: t_8_map_0 + t_8_map_1 + t_8_map_10 + t_8_map_11 + t_8_map_12 + t_8_map_13 + t_8_map_14 + t_8_map_15 + t_8_map_2 + t_8_map_3 + t_8_map_4 + t_8_map_5 + t_8_map_6 + t_8_map_7 + t_8_map_8 + t_8_map_9 = 1.0\n", - "_C118449: -t8_end_ + t8_start + t_comp_8 <= 0\n", - "_C118450: t5_end_ - t8_start + t_send_5 <= 0\n", - "_C118451: t_comp_8 = 16\n", + "_C118449: -t8_end_ + t8_start + t_comp_8 + t_send_8 <= 0\n", + "_C118450: t5_end_ - t8_start <= 0\n", + "_C118451: t_comp_8 = 10\n", "_C118452: t_mem_8 = 42\n", "_C118453: t_9_map_0 + t_9_map_1 + t_9_map_10 + t_9_map_11 + t_9_map_12 + t_9_map_13 + t_9_map_14 + t_9_map_15 + t_9_map_2 + t_9_map_3 + t_9_map_4 + t_9_map_5 + t_9_map_6 + t_9_map_7 + t_9_map_8 + t_9_map_9 = 1.0\n", - "_C118454: -t9_end_ + t9_start + t_comp_9 <= 0\n", - "_C118455: t8_end_ - t9_start + t_send_8 <= 0\n", - "_C118456: t_comp_9 = 43\n", + "_C118454: -t9_end_ + t9_start + t_comp_9 + t_send_9 <= 0\n", + "_C118455: t8_end_ - t9_start <= 0\n", + "_C118456: t_comp_9 = 26\n", "_C118457: t_mem_9 = 116\n", "_C118458: t_10_map_0 + t_10_map_1 + t_10_map_10 + t_10_map_11 + t_10_map_12 + t_10_map_13 + t_10_map_14 + t_10_map_15 + t_10_map_2 + t_10_map_3 + t_10_map_4 + t_10_map_5 + t_10_map_6 + t_10_map_7 + t_10_map_8 + t_10_map_9 = 1.0\n", - "_C118459: -t10_end_ + t10_start + t_comp_10 <= 0\n", - "_C118460: -t10_start + t9_end_ + t_send_9 <= 0\n", - "_C118461: t_comp_10 = 43\n", + "_C118459: -t10_end_ + t10_start + t_comp_10 + t_send_10 <= 0\n", + "_C118460: -t10_start + t9_end_ <= 0\n", + "_C118461: t_comp_10 = 26\n", "_C118462: t_mem_10 = 116\n", "_C118463: t_11_map_0 + t_11_map_1 + t_11_map_10 + t_11_map_11 + t_11_map_12 + t_11_map_13 + t_11_map_14 + t_11_map_15 + t_11_map_2 + t_11_map_3 + t_11_map_4 + t_11_map_5 + t_11_map_6 + t_11_map_7 + t_11_map_8 + t_11_map_9 = 1.0\n", - "_C118464: -t11_end_ + t11_start + t_comp_11 <= 0\n", - "_C118465: t10_end_ - t11_start + t_send_10 <= 0\n", - "_C118466: t_comp_11 = 78\n", + "_C118464: -t11_end_ + t11_start + t_comp_11 + t_send_11 <= 0\n", + "_C118465: t10_end_ - t11_start <= 0\n", + "_C118466: t_comp_11 = 47\n", "_C118467: t_mem_11 = 223\n", "_C118468: t_12_map_0 + t_12_map_1 + t_12_map_10 + t_12_map_11 + t_12_map_12 + t_12_map_13 + t_12_map_14 + t_12_map_15 + t_12_map_2 + t_12_map_3 + t_12_map_4 + t_12_map_5 + t_12_map_6 + t_12_map_7 + t_12_map_8 + t_12_map_9 = 1.0\n", - "_C118469: -t12_end_ + t12_start + t_comp_12 <= 0\n", - "_C118470: -t12_start + t7_end_ + t_send_7 <= 0\n", - "_C118471: t11_end_ - t12_start + t_send_11 <= 0\n", + "_C118469: -t12_end_ + t12_start + t_comp_12 + t_send_12 <= 0\n", + "_C118470: -t12_start + t7_end_ <= 0\n", + "_C118471: t11_end_ - t12_start <= 0\n", "_C118472: t_comp_12 = 0\n", "_C118473: t_mem_12 = 0\n", "_C118474: t_13_map_0 + t_13_map_1 + t_13_map_10 + t_13_map_11 + t_13_map_12 + t_13_map_13 + t_13_map_14 + t_13_map_15 + t_13_map_2 + t_13_map_3 + t_13_map_4 + t_13_map_5 + t_13_map_6 + t_13_map_7 + t_13_map_8 + t_13_map_9 = 1.0\n", - "_C118475: -t13_end_ + t13_start + t_comp_13 <= 0\n", - "_C118476: t12_end_ - t13_start + t_send_12 <= 0\n", - "_C118477: t_comp_13 = 114\n", + "_C118475: -t13_end_ + t13_start + t_comp_13 + t_send_13 <= 0\n", + "_C118476: t12_end_ - t13_start <= 0\n", + "_C118477: t_comp_13 = 69\n", "_C118478: t_mem_13 = 1329\n", "_C118479: t_14_map_0 + t_14_map_1 + t_14_map_10 + t_14_map_11 + t_14_map_12 + t_14_map_13 + t_14_map_14 + t_14_map_15 + t_14_map_2 + t_14_map_3 + t_14_map_4 + t_14_map_5 + t_14_map_6 + t_14_map_7 + t_14_map_8 + t_14_map_9 = 1.0\n", - "_C118480: -t14_end_ + t14_start + t_comp_14 <= 0\n", - "_C118481: t12_end_ - t14_start + t_send_12 <= 0\n", + "_C118480: -t14_end_ + t14_start + t_comp_14 + t_send_14 <= 0\n", + "_C118481: t12_end_ - t14_start <= 0\n", "_C118482: t_comp_14 = 1\n", "_C118483: t_mem_14 = 0\n", "_C118484: t_15_map_0 + t_15_map_1 + t_15_map_10 + t_15_map_11 + t_15_map_12 + t_15_map_13 + t_15_map_14 + t_15_map_15 + t_15_map_2 + t_15_map_3 + t_15_map_4 + t_15_map_5 + t_15_map_6 + t_15_map_7 + t_15_map_8 + t_15_map_9 = 1.0\n", - "_C118485: -t15_end_ + t15_start + t_comp_15 <= 0\n", - "_C118486: t13_end_ - t15_start + t_send_13 <= 0\n", - "_C118487: t14_end_ - t15_start + t_send_14 <= 0\n", + "_C118485: -t15_end_ + t15_start + t_comp_15 + t_send_15 <= 0\n", + "_C118486: t13_end_ - t15_start <= 0\n", + "_C118487: t14_end_ - t15_start <= 0\n", "_C118488: t_comp_15 = 0\n", "_C118489: t_mem_15 = 0\n", "_C118490: t_16_map_0 + t_16_map_1 + t_16_map_10 + t_16_map_11 + t_16_map_12 + t_16_map_13 + t_16_map_14 + t_16_map_15 + t_16_map_2 + t_16_map_3 + t_16_map_4 + t_16_map_5 + t_16_map_6 + t_16_map_7 + t_16_map_8 + t_16_map_9 = 1.0\n", - "_C118491: -t16_end_ + t16_start + t_comp_16 <= 0\n", - "_C118492: t15_end_ - t16_start + t_send_15 <= 0\n", - "_C118493: t_comp_16 = 13\n", + "_C118491: -t16_end_ + t16_start + t_comp_16 + t_send_16 <= 0\n", + "_C118492: t15_end_ - t16_start <= 0\n", + "_C118493: t_comp_16 = 8\n", "_C118494: t_mem_16 = 149\n", "_C118495: t_17_map_0 + t_17_map_1 + t_17_map_10 + t_17_map_11 + t_17_map_12 + t_17_map_13 + t_17_map_14 + t_17_map_15 + t_17_map_2 + t_17_map_3 + t_17_map_4 + t_17_map_5 + t_17_map_6 + t_17_map_7 + t_17_map_8 + t_17_map_9 = 1.0\n", - "_C118496: -t17_end_ + t17_start + t_comp_17 <= 0\n", - "_C118497: t15_end_ - t17_start + t_send_15 <= 0\n", - "_C118498: t_comp_17 = 9\n", + "_C118496: -t17_end_ + t17_start + t_comp_17 + t_send_17 <= 0\n", + "_C118497: t15_end_ - t17_start <= 0\n", + "_C118498: t_comp_17 = 6\n", "_C118499: t_mem_17 = 100\n", "_C118500: t_18_map_0 + t_18_map_1 + t_18_map_10 + t_18_map_11 + t_18_map_12 + t_18_map_13 + t_18_map_14 + t_18_map_15 + t_18_map_2 + t_18_map_3 + t_18_map_4 + t_18_map_5 + t_18_map_6 + t_18_map_7 + t_18_map_8 + t_18_map_9 = 1.0\n", - "_C118501: -t18_end_ + t18_start + t_comp_18 <= 0\n", - "_C118502: t17_end_ - t18_start + t_send_17 <= 0\n", - "_C118503: t_comp_18 = 19\n", + "_C118501: -t18_end_ + t18_start + t_comp_18 + t_send_18 <= 0\n", + "_C118502: t17_end_ - t18_start <= 0\n", + "_C118503: t_comp_18 = 12\n", "_C118504: t_mem_18 = 223\n", "_C118505: t_19_map_0 + t_19_map_1 + t_19_map_10 + t_19_map_11 + t_19_map_12 + t_19_map_13 + t_19_map_14 + t_19_map_15 + t_19_map_2 + t_19_map_3 + t_19_map_4 + t_19_map_5 + t_19_map_6 + t_19_map_7 + t_19_map_8 + t_19_map_9 = 1.0\n", - "_C118506: -t19_end_ + t19_start + t_comp_19 <= 0\n", - "_C118507: t15_end_ - t19_start + t_send_15 <= 0\n", - "_C118508: t_comp_19 = 9\n", + "_C118506: -t19_end_ + t19_start + t_comp_19 + t_send_19 <= 0\n", + "_C118507: t15_end_ - t19_start <= 0\n", + "_C118508: t_comp_19 = 6\n", "_C118509: t_mem_19 = 100\n", "_C118510: t_20_map_0 + t_20_map_1 + t_20_map_10 + t_20_map_11 + t_20_map_12 + t_20_map_13 + t_20_map_14 + t_20_map_15 + t_20_map_2 + t_20_map_3 + t_20_map_4 + t_20_map_5 + t_20_map_6 + t_20_map_7 + t_20_map_8 + t_20_map_9 = 1.0\n", - "_C118511: -t20_end_ + t20_start + t_comp_20 <= 0\n", - "_C118512: t19_end_ - t20_start + t_send_19 <= 0\n", - "_C118513: t_comp_20 = 19\n", + "_C118511: -t20_end_ + t20_start + t_comp_20 + t_send_20 <= 0\n", + "_C118512: t19_end_ - t20_start <= 0\n", + "_C118513: t_comp_20 = 12\n", "_C118514: t_mem_20 = 223\n", "_C118515: t_21_map_0 + t_21_map_1 + t_21_map_10 + t_21_map_11 + t_21_map_12 + t_21_map_13 + t_21_map_14 + t_21_map_15 + t_21_map_2 + t_21_map_3 + t_21_map_4 + t_21_map_5 + t_21_map_6 + t_21_map_7 + t_21_map_8 + t_21_map_9 = 1.0\n", - "_C118516: -t21_end_ + t21_start + t_comp_21 <= 0\n", - "_C118517: t20_end_ - t21_start + t_send_20 <= 0\n", - "_C118518: t_comp_21 = 29\n", + "_C118516: -t21_end_ + t21_start + t_comp_21 + t_send_21 <= 0\n", + "_C118517: t20_end_ - t21_start <= 0\n", + "_C118518: t_comp_21 = 18\n", "_C118519: t_mem_21 = 333\n", "_C118520: t_22_map_0 + t_22_map_1 + t_22_map_10 + t_22_map_11 + t_22_map_12 + t_22_map_13 + t_22_map_14 + t_22_map_15 + t_22_map_2 + t_22_map_3 + t_22_map_4 + t_22_map_5 + t_22_map_6 + t_22_map_7 + t_22_map_8 + t_22_map_9 = 1.0\n", - "_C118521: -t22_end_ + t22_start + t_comp_22 <= 0\n", - "_C118522: t15_end_ - t22_start + t_send_15 <= 0\n", + "_C118521: -t22_end_ + t22_start + t_comp_22 + t_send_22 <= 0\n", + "_C118522: t15_end_ - t22_start <= 0\n", "_C118523: t_comp_22 = 1\n", "_C118524: t_mem_22 = 0\n", "_C118525: t_23_map_0 + t_23_map_1 + t_23_map_10 + t_23_map_11 + t_23_map_12 + t_23_map_13 + t_23_map_14 + t_23_map_15 + t_23_map_2 + t_23_map_3 + t_23_map_4 + t_23_map_5 + t_23_map_6 + t_23_map_7 + t_23_map_8 + t_23_map_9 = 1.0\n", - "_C118526: -t23_end_ + t23_start + t_comp_23 <= 0\n", - "_C118527: t22_end_ - t23_start + t_send_22 <= 0\n", - "_C118528: t_comp_23 = 13\n", + "_C118526: -t23_end_ + t23_start + t_comp_23 + t_send_23 <= 0\n", + "_C118527: t22_end_ - t23_start <= 0\n", + "_C118528: t_comp_23 = 8\n", "_C118529: t_mem_23 = 149\n", "_C118530: t_24_map_0 + t_24_map_1 + t_24_map_10 + t_24_map_11 + t_24_map_12 + t_24_map_13 + t_24_map_14 + t_24_map_15 + t_24_map_2 + t_24_map_3 + t_24_map_4 + t_24_map_5 + t_24_map_6 + t_24_map_7 + t_24_map_8 + t_24_map_9 = 1.0\n", - "_C118531: -t24_end_ + t24_start + t_comp_24 <= 0\n", - "_C118532: t16_end_ - t24_start + t_send_16 <= 0\n", - "_C118533: t18_end_ - t24_start + t_send_18 <= 0\n", - "_C118534: t21_end_ - t24_start + t_send_21 <= 0\n", - "_C118535: t23_end_ - t24_start + t_send_23 <= 0\n", + "_C118531: -t24_end_ + t24_start + t_comp_24 + t_send_24 <= 0\n", + "_C118532: t16_end_ - t24_start <= 0\n", + "_C118533: t18_end_ - t24_start <= 0\n", + "_C118534: t21_end_ - t24_start <= 0\n", + "_C118535: t23_end_ - t24_start <= 0\n", "_C118536: t_comp_24 = 0\n", "_C118537: t_mem_24 = 0\n", "_C118538: t_25_map_0 + t_25_map_1 + t_25_map_10 + t_25_map_11 + t_25_map_12 + t_25_map_13 + t_25_map_14 + t_25_map_15 + t_25_map_2 + t_25_map_3 + t_25_map_4 + t_25_map_5 + t_25_map_6 + t_25_map_7 + t_25_map_8 + t_25_map_9 = 1.0\n", - "_C118539: -t25_end_ + t25_start + t_comp_25 <= 0\n", - "_C118540: t24_end_ - t25_start + t_send_24 <= 0\n", - "_C118541: t_comp_25 = 13\n", + "_C118539: -t25_end_ + t25_start + t_comp_25 + t_send_25 <= 0\n", + "_C118540: t24_end_ - t25_start <= 0\n", + "_C118541: t_comp_25 = 8\n", "_C118542: t_mem_25 = 149\n", "_C118543: t_26_map_0 + t_26_map_1 + t_26_map_10 + t_26_map_11 + t_26_map_12 + t_26_map_13 + t_26_map_14 + t_26_map_15 + t_26_map_2 + t_26_map_3 + t_26_map_4 + t_26_map_5 + t_26_map_6 + t_26_map_7 + t_26_map_8 + t_26_map_9 = 1.0\n", - "_C118544: -t26_end_ + t26_start + t_comp_26 <= 0\n", - "_C118545: t24_end_ - t26_start + t_send_24 <= 0\n", - "_C118546: t_comp_26 = 9\n", + "_C118544: -t26_end_ + t26_start + t_comp_26 + t_send_26 <= 0\n", + "_C118545: t24_end_ - t26_start <= 0\n", + "_C118546: t_comp_26 = 6\n", "_C118547: t_mem_26 = 100\n", "_C118548: t_27_map_0 + t_27_map_1 + t_27_map_10 + t_27_map_11 + t_27_map_12 + t_27_map_13 + t_27_map_14 + t_27_map_15 + t_27_map_2 + t_27_map_3 + t_27_map_4 + t_27_map_5 + t_27_map_6 + t_27_map_7 + t_27_map_8 + t_27_map_9 = 1.0\n", - "_C118549: -t27_end_ + t27_start + t_comp_27 <= 0\n", - "_C118550: t26_end_ - t27_start + t_send_26 <= 0\n", - "_C118551: t_comp_27 = 19\n", + "_C118549: -t27_end_ + t27_start + t_comp_27 + t_send_27 <= 0\n", + "_C118550: t26_end_ - t27_start <= 0\n", + "_C118551: t_comp_27 = 12\n", "_C118552: t_mem_27 = 223\n", "_C118553: t_28_map_0 + t_28_map_1 + t_28_map_10 + t_28_map_11 + t_28_map_12 + t_28_map_13 + t_28_map_14 + t_28_map_15 + t_28_map_2 + t_28_map_3 + t_28_map_4 + t_28_map_5 + t_28_map_6 + t_28_map_7 + t_28_map_8 + t_28_map_9 = 1.0\n", - "_C118554: -t28_end_ + t28_start + t_comp_28 <= 0\n", - "_C118555: t24_end_ - t28_start + t_send_24 <= 0\n", - "_C118556: t_comp_28 = 9\n", + "_C118554: -t28_end_ + t28_start + t_comp_28 + t_send_28 <= 0\n", + "_C118555: t24_end_ - t28_start <= 0\n", + "_C118556: t_comp_28 = 6\n", "_C118557: t_mem_28 = 100\n", "_C118558: t_29_map_0 + t_29_map_1 + t_29_map_10 + t_29_map_11 + t_29_map_12 + t_29_map_13 + t_29_map_14 + t_29_map_15 + t_29_map_2 + t_29_map_3 + t_29_map_4 + t_29_map_5 + t_29_map_6 + t_29_map_7 + t_29_map_8 + t_29_map_9 = 1.0\n", - "_C118559: -t29_end_ + t29_start + t_comp_29 <= 0\n", - "_C118560: t28_end_ - t29_start + t_send_28 <= 0\n", - "_C118561: t_comp_29 = 19\n", + "_C118559: -t29_end_ + t29_start + t_comp_29 + t_send_29 <= 0\n", + "_C118560: t28_end_ - t29_start <= 0\n", + "_C118561: t_comp_29 = 12\n", "_C118562: t_mem_29 = 223\n", "_C118563: t_30_map_0 + t_30_map_1 + t_30_map_10 + t_30_map_11 + t_30_map_12 + t_30_map_13 + t_30_map_14 + t_30_map_15 + t_30_map_2 + t_30_map_3 + t_30_map_4 + t_30_map_5 + t_30_map_6 + t_30_map_7 + t_30_map_8 + t_30_map_9 = 1.0\n", - "_C118564: -t30_end_ + t30_start + t_comp_30 <= 0\n", - "_C118565: t29_end_ - t30_start + t_send_29 <= 0\n", - "_C118566: t_comp_30 = 29\n", + "_C118564: -t30_end_ + t30_start + t_comp_30 + t_send_30 <= 0\n", + "_C118565: t29_end_ - t30_start <= 0\n", + "_C118566: t_comp_30 = 18\n", "_C118567: t_mem_30 = 333\n", "_C118568: t_31_map_0 + t_31_map_1 + t_31_map_10 + t_31_map_11 + t_31_map_12 + t_31_map_13 + t_31_map_14 + t_31_map_15 + t_31_map_2 + t_31_map_3 + t_31_map_4 + t_31_map_5 + t_31_map_6 + t_31_map_7 + t_31_map_8 + t_31_map_9 = 1.0\n", - "_C118569: -t31_end_ + t31_start + t_comp_31 <= 0\n", - "_C118570: t24_end_ - t31_start + t_send_24 <= 0\n", + "_C118569: -t31_end_ + t31_start + t_comp_31 + t_send_31 <= 0\n", + "_C118570: t24_end_ - t31_start <= 0\n", "_C118571: t_comp_31 = 1\n", "_C118572: t_mem_31 = 0\n", "_C118573: t_32_map_0 + t_32_map_1 + t_32_map_10 + t_32_map_11 + t_32_map_12 + t_32_map_13 + t_32_map_14 + t_32_map_15 + t_32_map_2 + t_32_map_3 + t_32_map_4 + t_32_map_5 + t_32_map_6 + t_32_map_7 + t_32_map_8 + t_32_map_9 = 1.0\n", - "_C118574: -t32_end_ + t32_start + t_comp_32 <= 0\n", - "_C118575: t31_end_ - t32_start + t_send_31 <= 0\n", - "_C118576: t_comp_32 = 13\n", + "_C118574: -t32_end_ + t32_start + t_comp_32 + t_send_32 <= 0\n", + "_C118575: t31_end_ - t32_start <= 0\n", + "_C118576: t_comp_32 = 8\n", "_C118577: t_mem_32 = 149\n", "_C118578: t_33_map_0 + t_33_map_1 + t_33_map_10 + t_33_map_11 + t_33_map_12 + t_33_map_13 + t_33_map_14 + t_33_map_15 + t_33_map_2 + t_33_map_3 + t_33_map_4 + t_33_map_5 + t_33_map_6 + t_33_map_7 + t_33_map_8 + t_33_map_9 = 1.0\n", - "_C118579: -t33_end_ + t33_start + t_comp_33 <= 0\n", - "_C118580: t25_end_ - t33_start + t_send_25 <= 0\n", - "_C118581: t27_end_ - t33_start + t_send_27 <= 0\n", - "_C118582: t30_end_ - t33_start + t_send_30 <= 0\n", - "_C118583: t32_end_ - t33_start + t_send_32 <= 0\n", + "_C118579: -t33_end_ + t33_start + t_comp_33 + t_send_33 <= 0\n", + "_C118580: t25_end_ - t33_start <= 0\n", + "_C118581: t27_end_ - t33_start <= 0\n", + "_C118582: t30_end_ - t33_start <= 0\n", + "_C118583: t32_end_ - t33_start <= 0\n", "_C118584: t_comp_33 = 0\n", "_C118585: t_mem_33 = 0\n", "_C118586: t_34_map_0 + t_34_map_1 + t_34_map_10 + t_34_map_11 + t_34_map_12 + t_34_map_13 + t_34_map_14 + t_34_map_15 + t_34_map_2 + t_34_map_3 + t_34_map_4 + t_34_map_5 + t_34_map_6 + t_34_map_7 + t_34_map_8 + t_34_map_9 = 1.0\n", - "_C118587: -t34_end_ + t34_start + t_comp_34 <= 0\n", - "_C118588: t33_end_ - t34_start + t_send_33 <= 0\n", - "_C118589: t_comp_34 = 13\n", + "_C118587: -t34_end_ + t34_start + t_comp_34 + t_send_34 <= 0\n", + "_C118588: t33_end_ - t34_start <= 0\n", + "_C118589: t_comp_34 = 8\n", "_C118590: t_mem_34 = 149\n", "_C118591: t_35_map_0 + t_35_map_1 + t_35_map_10 + t_35_map_11 + t_35_map_12 + t_35_map_13 + t_35_map_14 + t_35_map_15 + t_35_map_2 + t_35_map_3 + t_35_map_4 + t_35_map_5 + t_35_map_6 + t_35_map_7 + t_35_map_8 + t_35_map_9 = 1.0\n", - "_C118592: -t35_end_ + t35_start + t_comp_35 <= 0\n", - "_C118593: t33_end_ - t35_start + t_send_33 <= 0\n", - "_C118594: t_comp_35 = 9\n", + "_C118592: -t35_end_ + t35_start + t_comp_35 + t_send_35 <= 0\n", + "_C118593: t33_end_ - t35_start <= 0\n", + "_C118594: t_comp_35 = 6\n", "_C118595: t_mem_35 = 100\n", "_C118596: t_36_map_0 + t_36_map_1 + t_36_map_10 + t_36_map_11 + t_36_map_12 + t_36_map_13 + t_36_map_14 + t_36_map_15 + t_36_map_2 + t_36_map_3 + t_36_map_4 + t_36_map_5 + t_36_map_6 + t_36_map_7 + t_36_map_8 + t_36_map_9 = 1.0\n", - "_C118597: -t36_end_ + t36_start + t_comp_36 <= 0\n", - "_C118598: t35_end_ - t36_start + t_send_35 <= 0\n", - "_C118599: t_comp_36 = 19\n", + "_C118597: -t36_end_ + t36_start + t_comp_36 + t_send_36 <= 0\n", + "_C118598: t35_end_ - t36_start <= 0\n", + "_C118599: t_comp_36 = 12\n", "_C118600: t_mem_36 = 223\n", "_C118601: t_37_map_0 + t_37_map_1 + t_37_map_10 + t_37_map_11 + t_37_map_12 + t_37_map_13 + t_37_map_14 + t_37_map_15 + t_37_map_2 + t_37_map_3 + t_37_map_4 + t_37_map_5 + t_37_map_6 + t_37_map_7 + t_37_map_8 + t_37_map_9 = 1.0\n", - "_C118602: -t37_end_ + t37_start + t_comp_37 <= 0\n", - "_C118603: t33_end_ - t37_start + t_send_33 <= 0\n", - "_C118604: t_comp_37 = 9\n", + "_C118602: -t37_end_ + t37_start + t_comp_37 + t_send_37 <= 0\n", + "_C118603: t33_end_ - t37_start <= 0\n", + "_C118604: t_comp_37 = 6\n", "_C118605: t_mem_37 = 100\n", "_C118606: t_38_map_0 + t_38_map_1 + t_38_map_10 + t_38_map_11 + t_38_map_12 + t_38_map_13 + t_38_map_14 + t_38_map_15 + t_38_map_2 + t_38_map_3 + t_38_map_4 + t_38_map_5 + t_38_map_6 + t_38_map_7 + t_38_map_8 + t_38_map_9 = 1.0\n", - "_C118607: -t38_end_ + t38_start + t_comp_38 <= 0\n", - "_C118608: t37_end_ - t38_start + t_send_37 <= 0\n", - "_C118609: t_comp_38 = 19\n", + "_C118607: -t38_end_ + t38_start + t_comp_38 + t_send_38 <= 0\n", + "_C118608: t37_end_ - t38_start <= 0\n", + "_C118609: t_comp_38 = 12\n", "_C118610: t_mem_38 = 223\n", "_C118611: t_39_map_0 + t_39_map_1 + t_39_map_10 + t_39_map_11 + t_39_map_12 + t_39_map_13 + t_39_map_14 + t_39_map_15 + t_39_map_2 + t_39_map_3 + t_39_map_4 + t_39_map_5 + t_39_map_6 + t_39_map_7 + t_39_map_8 + t_39_map_9 = 1.0\n", - "_C118612: -t39_end_ + t39_start + t_comp_39 <= 0\n", - "_C118613: t38_end_ - t39_start + t_send_38 <= 0\n", - "_C118614: t_comp_39 = 29\n", + "_C118612: -t39_end_ + t39_start + t_comp_39 + t_send_39 <= 0\n", + "_C118613: t38_end_ - t39_start <= 0\n", + "_C118614: t_comp_39 = 18\n", "_C118615: t_mem_39 = 333\n", "_C118616: t_40_map_0 + t_40_map_1 + t_40_map_10 + t_40_map_11 + t_40_map_12 + t_40_map_13 + t_40_map_14 + t_40_map_15 + t_40_map_2 + t_40_map_3 + t_40_map_4 + t_40_map_5 + t_40_map_6 + t_40_map_7 + t_40_map_8 + t_40_map_9 = 1.0\n", - "_C118617: -t40_end_ + t40_start + t_comp_40 <= 0\n", - "_C118618: t33_end_ - t40_start + t_send_33 <= 0\n", + "_C118617: -t40_end_ + t40_start + t_comp_40 + t_send_40 <= 0\n", + "_C118618: t33_end_ - t40_start <= 0\n", "_C118619: t_comp_40 = 1\n", "_C118620: t_mem_40 = 0\n", "_C118621: t_41_map_0 + t_41_map_1 + t_41_map_10 + t_41_map_11 + t_41_map_12 + t_41_map_13 + t_41_map_14 + t_41_map_15 + t_41_map_2 + t_41_map_3 + t_41_map_4 + t_41_map_5 + t_41_map_6 + t_41_map_7 + t_41_map_8 + t_41_map_9 = 1.0\n", - "_C118622: -t41_end_ + t41_start + t_comp_41 <= 0\n", - "_C118623: t40_end_ - t41_start + t_send_40 <= 0\n", - "_C118624: t_comp_41 = 13\n", + "_C118622: -t41_end_ + t41_start + t_comp_41 + t_send_41 <= 0\n", + "_C118623: t40_end_ - t41_start <= 0\n", + "_C118624: t_comp_41 = 8\n", "_C118625: t_mem_41 = 149\n", "_C118626: t_42_map_0 + t_42_map_1 + t_42_map_10 + t_42_map_11 + t_42_map_12 + t_42_map_13 + t_42_map_14 + t_42_map_15 + t_42_map_2 + t_42_map_3 + t_42_map_4 + t_42_map_5 + t_42_map_6 + t_42_map_7 + t_42_map_8 + t_42_map_9 = 1.0\n", - "_C118627: -t42_end_ + t42_start + t_comp_42 <= 0\n", - "_C118628: t34_end_ - t42_start + t_send_34 <= 0\n", - "_C118629: t36_end_ - t42_start + t_send_36 <= 0\n", - "_C118630: t39_end_ - t42_start + t_send_39 <= 0\n", - "_C118631: t41_end_ - t42_start + t_send_41 <= 0\n", + "_C118627: -t42_end_ + t42_start + t_comp_42 + t_send_42 <= 0\n", + "_C118628: t34_end_ - t42_start <= 0\n", + "_C118629: t36_end_ - t42_start <= 0\n", + "_C118630: t39_end_ - t42_start <= 0\n", + "_C118631: t41_end_ - t42_start <= 0\n", "_C118632: t_comp_42 = 0\n", "_C118633: t_mem_42 = 0\n", "_C118634: t_43_map_0 + t_43_map_1 + t_43_map_10 + t_43_map_11 + t_43_map_12 + t_43_map_13 + t_43_map_14 + t_43_map_15 + t_43_map_2 + t_43_map_3 + t_43_map_4 + t_43_map_5 + t_43_map_6 + t_43_map_7 + t_43_map_8 + t_43_map_9 = 1.0\n", - "_C118635: -t43_end_ + t43_start + t_comp_43 <= 0\n", - "_C118636: t42_end_ - t43_start + t_send_42 <= 0\n", - "_C118637: t_comp_43 = 13\n", + "_C118635: -t43_end_ + t43_start + t_comp_43 + t_send_43 <= 0\n", + "_C118636: t42_end_ - t43_start <= 0\n", + "_C118637: t_comp_43 = 8\n", "_C118638: t_mem_43 = 149\n", "_C118639: t_44_map_0 + t_44_map_1 + t_44_map_10 + t_44_map_11 + t_44_map_12 + t_44_map_13 + t_44_map_14 + t_44_map_15 + t_44_map_2 + t_44_map_3 + t_44_map_4 + t_44_map_5 + t_44_map_6 + t_44_map_7 + t_44_map_8 + t_44_map_9 = 1.0\n", - "_C118640: -t44_end_ + t44_start + t_comp_44 <= 0\n", - "_C118641: t42_end_ - t44_start + t_send_42 <= 0\n", - "_C118642: t_comp_44 = 9\n", + "_C118640: -t44_end_ + t44_start + t_comp_44 + t_send_44 <= 0\n", + "_C118641: t42_end_ - t44_start <= 0\n", + "_C118642: t_comp_44 = 6\n", "_C118643: t_mem_44 = 100\n", "_C118644: t_45_map_0 + t_45_map_1 + t_45_map_10 + t_45_map_11 + t_45_map_12 + t_45_map_13 + t_45_map_14 + t_45_map_15 + t_45_map_2 + t_45_map_3 + t_45_map_4 + t_45_map_5 + t_45_map_6 + t_45_map_7 + t_45_map_8 + t_45_map_9 = 1.0\n", - "_C118645: -t45_end_ + t45_start + t_comp_45 <= 0\n", - "_C118646: t44_end_ - t45_start + t_send_44 <= 0\n", - "_C118647: t_comp_45 = 19\n", + "_C118645: -t45_end_ + t45_start + t_comp_45 + t_send_45 <= 0\n", + "_C118646: t44_end_ - t45_start <= 0\n", + "_C118647: t_comp_45 = 12\n", "_C118648: t_mem_45 = 223\n", "_C118649: t_46_map_0 + t_46_map_1 + t_46_map_10 + t_46_map_11 + t_46_map_12 + t_46_map_13 + t_46_map_14 + t_46_map_15 + t_46_map_2 + t_46_map_3 + t_46_map_4 + t_46_map_5 + t_46_map_6 + t_46_map_7 + t_46_map_8 + t_46_map_9 = 1.0\n", - "_C118650: -t46_end_ + t46_start + t_comp_46 <= 0\n", - "_C118651: t42_end_ - t46_start + t_send_42 <= 0\n", - "_C118652: t_comp_46 = 9\n", + "_C118650: -t46_end_ + t46_start + t_comp_46 + t_send_46 <= 0\n", + "_C118651: t42_end_ - t46_start <= 0\n", + "_C118652: t_comp_46 = 6\n", "_C118653: t_mem_46 = 100\n", "_C118654: t_47_map_0 + t_47_map_1 + t_47_map_10 + t_47_map_11 + t_47_map_12 + t_47_map_13 + t_47_map_14 + t_47_map_15 + t_47_map_2 + t_47_map_3 + t_47_map_4 + t_47_map_5 + t_47_map_6 + t_47_map_7 + t_47_map_8 + t_47_map_9 = 1.0\n", - "_C118655: -t47_end_ + t47_start + t_comp_47 <= 0\n", - "_C118656: t46_end_ - t47_start + t_send_46 <= 0\n", - "_C118657: t_comp_47 = 19\n", + "_C118655: -t47_end_ + t47_start + t_comp_47 + t_send_47 <= 0\n", + "_C118656: t46_end_ - t47_start <= 0\n", + "_C118657: t_comp_47 = 12\n", "_C118658: t_mem_47 = 223\n", "_C118659: t_48_map_0 + t_48_map_1 + t_48_map_10 + t_48_map_11 + t_48_map_12 + t_48_map_13 + t_48_map_14 + t_48_map_15 + t_48_map_2 + t_48_map_3 + t_48_map_4 + t_48_map_5 + t_48_map_6 + t_48_map_7 + t_48_map_8 + t_48_map_9 = 1.0\n", - "_C118660: -t48_end_ + t48_start + t_comp_48 <= 0\n", - "_C118661: t47_end_ - t48_start + t_send_47 <= 0\n", - "_C118662: t_comp_48 = 29\n", + "_C118660: -t48_end_ + t48_start + t_comp_48 + t_send_48 <= 0\n", + "_C118661: t47_end_ - t48_start <= 0\n", + "_C118662: t_comp_48 = 18\n", "_C118663: t_mem_48 = 333\n", "_C118664: t_49_map_0 + t_49_map_1 + t_49_map_10 + t_49_map_11 + t_49_map_12 + t_49_map_13 + t_49_map_14 + t_49_map_15 + t_49_map_2 + t_49_map_3 + t_49_map_4 + t_49_map_5 + t_49_map_6 + t_49_map_7 + t_49_map_8 + t_49_map_9 = 1.0\n", - "_C118665: -t49_end_ + t49_start + t_comp_49 <= 0\n", - "_C118666: t42_end_ - t49_start + t_send_42 <= 0\n", + "_C118665: -t49_end_ + t49_start + t_comp_49 + t_send_49 <= 0\n", + "_C118666: t42_end_ - t49_start <= 0\n", "_C118667: t_comp_49 = 1\n", "_C118668: t_mem_49 = 0\n", "_C118669: t_50_map_0 + t_50_map_1 + t_50_map_10 + t_50_map_11 + t_50_map_12 + t_50_map_13 + t_50_map_14 + t_50_map_15 + t_50_map_2 + t_50_map_3 + t_50_map_4 + t_50_map_5 + t_50_map_6 + t_50_map_7 + t_50_map_8 + t_50_map_9 = 1.0\n", - "_C118670: -t50_end_ + t50_start + t_comp_50 <= 0\n", - "_C118671: t49_end_ - t50_start + t_send_49 <= 0\n", - "_C118672: t_comp_50 = 13\n", + "_C118670: -t50_end_ + t50_start + t_comp_50 + t_send_50 <= 0\n", + "_C118671: t49_end_ - t50_start <= 0\n", + "_C118672: t_comp_50 = 8\n", "_C118673: t_mem_50 = 149\n", "_C118674: t_51_map_0 + t_51_map_1 + t_51_map_10 + t_51_map_11 + t_51_map_12 + t_51_map_13 + t_51_map_14 + t_51_map_15 + t_51_map_2 + t_51_map_3 + t_51_map_4 + t_51_map_5 + t_51_map_6 + t_51_map_7 + t_51_map_8 + t_51_map_9 = 1.0\n", - "_C118675: -t51_end_ + t51_start + t_comp_51 <= 0\n", - "_C118676: t43_end_ - t51_start + t_send_43 <= 0\n", - "_C118677: t45_end_ - t51_start + t_send_45 <= 0\n", - "_C118678: t48_end_ - t51_start + t_send_48 <= 0\n", - "_C118679: t50_end_ - t51_start + t_send_50 <= 0\n", + "_C118675: -t51_end_ + t51_start + t_comp_51 + t_send_51 <= 0\n", + "_C118676: t43_end_ - t51_start <= 0\n", + "_C118677: t45_end_ - t51_start <= 0\n", + "_C118678: t48_end_ - t51_start <= 0\n", + "_C118679: t50_end_ - t51_start <= 0\n", "_C118680: t_comp_51 = 0\n", "_C118681: t_mem_51 = 0\n", "_C118682: t_52_map_0 + t_52_map_1 + t_52_map_10 + t_52_map_11 + t_52_map_12 + t_52_map_13 + t_52_map_14 + t_52_map_15 + t_52_map_2 + t_52_map_3 + t_52_map_4 + t_52_map_5 + t_52_map_6 + t_52_map_7 + t_52_map_8 + t_52_map_9 = 1.0\n", - "_C118683: -t52_end_ + t52_start + t_comp_52 <= 0\n", - "_C118684: t51_end_ - t52_start + t_send_51 <= 0\n", - "_C118685: t_comp_52 = 108\n", + "_C118683: -t52_end_ + t52_start + t_comp_52 + t_send_52 <= 0\n", + "_C118684: t51_end_ - t52_start <= 0\n", + "_C118685: t_comp_52 = 65\n", "_C118686: t_mem_52 = 5311\n", "_C118687: t_53_map_0 + t_53_map_1 + t_53_map_10 + t_53_map_11 + t_53_map_12 + t_53_map_13 + t_53_map_14 + t_53_map_15 + t_53_map_2 + t_53_map_3 + t_53_map_4 + t_53_map_5 + t_53_map_6 + t_53_map_7 + t_53_map_8 + t_53_map_9 = 1.0\n", - "_C118688: -t53_end_ + t53_start + t_comp_53 <= 0\n", - "_C118689: t51_end_ - t53_start + t_send_51 <= 0\n", - "_C118690: t_comp_53 = 26\n", + "_C118688: -t53_end_ + t53_start + t_comp_53 + t_send_53 <= 0\n", + "_C118689: t51_end_ - t53_start <= 0\n", + "_C118690: t_comp_53 = 16\n", "_C118691: t_mem_53 = 296\n", "_C118692: t_54_map_0 + t_54_map_1 + t_54_map_10 + t_54_map_11 + t_54_map_12 + t_54_map_13 + t_54_map_14 + t_54_map_15 + t_54_map_2 + t_54_map_3 + t_54_map_4 + t_54_map_5 + t_54_map_6 + t_54_map_7 + t_54_map_8 + t_54_map_9 = 1.0\n", - "_C118693: -t54_end_ + t54_start + t_comp_54 <= 0\n", - "_C118694: t53_end_ - t54_start + t_send_53 <= 0\n", - "_C118695: t_comp_54 = 133\n", + "_C118693: -t54_end_ + t54_start + t_comp_54 + t_send_54 <= 0\n", + "_C118694: t53_end_ - t54_start <= 0\n", + "_C118695: t_comp_54 = 80\n", "_C118696: t_mem_54 = 1550\n", "_C118697: t_55_map_0 + t_55_map_1 + t_55_map_10 + t_55_map_11 + t_55_map_12 + t_55_map_13 + t_55_map_14 + t_55_map_15 + t_55_map_2 + t_55_map_3 + t_55_map_4 + t_55_map_5 + t_55_map_6 + t_55_map_7 + t_55_map_8 + t_55_map_9 = 1.0\n", - "_C118698: -t55_end_ + t55_start + t_comp_55 <= 0\n", - "_C118699: t54_end_ - t55_start + t_send_54 <= 0\n", - "_C118700: t_comp_55 = 42\n", + "_C118698: -t55_end_ + t55_start + t_comp_55 + t_send_55 <= 0\n", + "_C118699: t54_end_ - t55_start <= 0\n", + "_C118700: t_comp_55 = 25\n", "_C118701: t_mem_55 = 2067\n", "_C118702: t_56_map_0 + t_56_map_1 + t_56_map_10 + t_56_map_11 + t_56_map_12 + t_56_map_13 + t_56_map_14 + t_56_map_15 + t_56_map_2 + t_56_map_3 + t_56_map_4 + t_56_map_5 + t_56_map_6 + t_56_map_7 + t_56_map_8 + t_56_map_9 = 1.0\n", - "_C118703: -t56_end_ + t56_start + t_comp_56 <= 0\n", - "_C118704: t51_end_ - t56_start + t_send_51 <= 0\n", + "_C118703: -t56_end_ + t56_start + t_comp_56 + t_send_56 <= 0\n", + "_C118704: t51_end_ - t56_start <= 0\n", "_C118705: t_comp_56 = 1\n", "_C118706: t_mem_56 = 0\n", "_C118707: t_57_map_0 + t_57_map_1 + t_57_map_10 + t_57_map_11 + t_57_map_12 + t_57_map_13 + t_57_map_14 + t_57_map_15 + t_57_map_2 + t_57_map_3 + t_57_map_4 + t_57_map_5 + t_57_map_6 + t_57_map_7 + t_57_map_8 + t_57_map_9 = 1.0\n", - "_C118708: -t57_end_ + t57_start + t_comp_57 <= 0\n", - "_C118709: t52_end_ - t57_start + t_send_52 <= 0\n", - "_C118710: t55_end_ - t57_start + t_send_55 <= 0\n", - "_C118711: t56_end_ - t57_start + t_send_56 <= 0\n", + "_C118708: -t57_end_ + t57_start + t_comp_57 + t_send_57 <= 0\n", + "_C118709: t52_end_ - t57_start <= 0\n", + "_C118710: t55_end_ - t57_start <= 0\n", + "_C118711: t56_end_ - t57_start <= 0\n", "_C118712: t_comp_57 = 0\n", "_C118713: t_mem_57 = 0\n", "_C118714: t_58_map_0 + t_58_map_1 + t_58_map_10 + t_58_map_11 + t_58_map_12 + t_58_map_13 + t_58_map_14 + t_58_map_15 + t_58_map_2 + t_58_map_3 + t_58_map_4 + t_58_map_5 + t_58_map_6 + t_58_map_7 + t_58_map_8 + t_58_map_9 = 1.0\n", - "_C118715: -t58_end_ + t58_start + t_comp_58 <= 0\n", - "_C118716: t57_end_ - t58_start + t_send_57 <= 0\n", - "_C118717: t_comp_58 = 32\n", + "_C118715: -t58_end_ + t58_start + t_comp_58 + t_send_58 <= 0\n", + "_C118716: t57_end_ - t58_start <= 0\n", + "_C118717: t_comp_58 = 20\n", "_C118718: t_mem_58 = 1575\n", "_C118719: t_59_map_0 + t_59_map_1 + t_59_map_10 + t_59_map_11 + t_59_map_12 + t_59_map_13 + t_59_map_14 + t_59_map_15 + t_59_map_2 + t_59_map_3 + t_59_map_4 + t_59_map_5 + t_59_map_6 + t_59_map_7 + t_59_map_8 + t_59_map_9 = 1.0\n", - "_C118720: -t59_end_ + t59_start + t_comp_59 <= 0\n", - "_C118721: t57_end_ - t59_start + t_send_57 <= 0\n", - "_C118722: t_comp_59 = 16\n", + "_C118720: -t59_end_ + t59_start + t_comp_59 + t_send_59 <= 0\n", + "_C118721: t57_end_ - t59_start <= 0\n", + "_C118722: t_comp_59 = 10\n", "_C118723: t_mem_59 = 788\n", "_C118724: t_60_map_0 + t_60_map_1 + t_60_map_10 + t_60_map_11 + t_60_map_12 + t_60_map_13 + t_60_map_14 + t_60_map_15 + t_60_map_2 + t_60_map_3 + t_60_map_4 + t_60_map_5 + t_60_map_6 + t_60_map_7 + t_60_map_8 + t_60_map_9 = 1.0\n", - "_C118725: -t60_end_ + t60_start + t_comp_60 <= 0\n", - "_C118726: t59_end_ - t60_start + t_send_59 <= 0\n", - "_C118727: t_comp_60 = 25\n", + "_C118725: -t60_end_ + t60_start + t_comp_60 + t_send_60 <= 0\n", + "_C118726: t59_end_ - t60_start <= 0\n", + "_C118727: t_comp_60 = 15\n", "_C118728: t_mem_60 = 1206\n", "_C118729: t_61_map_0 + t_61_map_1 + t_61_map_10 + t_61_map_11 + t_61_map_12 + t_61_map_13 + t_61_map_14 + t_61_map_15 + t_61_map_2 + t_61_map_3 + t_61_map_4 + t_61_map_5 + t_61_map_6 + t_61_map_7 + t_61_map_8 + t_61_map_9 = 1.0\n", - "_C118730: -t61_end_ + t61_start + t_comp_61 <= 0\n", - "_C118731: t60_end_ - t61_start + t_send_60 <= 0\n", - "_C118732: t_comp_61 = 33\n", + "_C118730: -t61_end_ + t61_start + t_comp_61 + t_send_61 <= 0\n", + "_C118731: t60_end_ - t61_start <= 0\n", + "_C118732: t_comp_61 = 20\n", "_C118733: t_mem_61 = 1608\n", "_C118734: t_62_map_0 + t_62_map_1 + t_62_map_10 + t_62_map_11 + t_62_map_12 + t_62_map_13 + t_62_map_14 + t_62_map_15 + t_62_map_2 + t_62_map_3 + t_62_map_4 + t_62_map_5 + t_62_map_6 + t_62_map_7 + t_62_map_8 + t_62_map_9 = 1.0\n", - "_C118735: -t62_end_ + t62_start + t_comp_62 <= 0\n", - "_C118736: t57_end_ - t62_start + t_send_57 <= 0\n", - "_C118737: t_comp_62 = 16\n", + "_C118735: -t62_end_ + t62_start + t_comp_62 + t_send_62 <= 0\n", + "_C118736: t57_end_ - t62_start <= 0\n", + "_C118737: t_comp_62 = 10\n", "_C118738: t_mem_62 = 788\n", "_C118739: t_63_map_0 + t_63_map_1 + t_63_map_10 + t_63_map_11 + t_63_map_12 + t_63_map_13 + t_63_map_14 + t_63_map_15 + t_63_map_2 + t_63_map_3 + t_63_map_4 + t_63_map_5 + t_63_map_6 + t_63_map_7 + t_63_map_8 + t_63_map_9 = 1.0\n", - "_C118740: -t63_end_ + t63_start + t_comp_63 <= 0\n", - "_C118741: t62_end_ - t63_start + t_send_62 <= 0\n", - "_C118742: t_comp_63 = 21\n", + "_C118740: -t63_end_ + t63_start + t_comp_63 + t_send_63 <= 0\n", + "_C118741: t62_end_ - t63_start <= 0\n", + "_C118742: t_comp_63 = 13\n", "_C118743: t_mem_63 = 1034\n", "_C118744: t_64_map_0 + t_64_map_1 + t_64_map_10 + t_64_map_11 + t_64_map_12 + t_64_map_13 + t_64_map_14 + t_64_map_15 + t_64_map_2 + t_64_map_3 + t_64_map_4 + t_64_map_5 + t_64_map_6 + t_64_map_7 + t_64_map_8 + t_64_map_9 = 1.0\n", - "_C118745: -t64_end_ + t64_start + t_comp_64 <= 0\n", - "_C118746: t63_end_ - t64_start + t_send_63 <= 0\n", - "_C118747: t_comp_64 = 25\n", + "_C118745: -t64_end_ + t64_start + t_comp_64 + t_send_64 <= 0\n", + "_C118746: t63_end_ - t64_start <= 0\n", + "_C118747: t_comp_64 = 15\n", "_C118748: t_mem_64 = 1206\n", "_C118749: t_65_map_0 + t_65_map_1 + t_65_map_10 + t_65_map_11 + t_65_map_12 + t_65_map_13 + t_65_map_14 + t_65_map_15 + t_65_map_2 + t_65_map_3 + t_65_map_4 + t_65_map_5 + t_65_map_6 + t_65_map_7 + t_65_map_8 + t_65_map_9 = 1.0\n", - "_C118750: -t65_end_ + t65_start + t_comp_65 <= 0\n", - "_C118751: t64_end_ - t65_start + t_send_64 <= 0\n", - "_C118752: t_comp_65 = 29\n", + "_C118750: -t65_end_ + t65_start + t_comp_65 + t_send_65 <= 0\n", + "_C118751: t64_end_ - t65_start <= 0\n", + "_C118752: t_comp_65 = 18\n", "_C118753: t_mem_65 = 1406\n", "_C118754: t_66_map_0 + t_66_map_1 + t_66_map_10 + t_66_map_11 + t_66_map_12 + t_66_map_13 + t_66_map_14 + t_66_map_15 + t_66_map_2 + t_66_map_3 + t_66_map_4 + t_66_map_5 + t_66_map_6 + t_66_map_7 + t_66_map_8 + t_66_map_9 = 1.0\n", - "_C118755: -t66_end_ + t66_start + t_comp_66 <= 0\n", - "_C118756: t65_end_ - t66_start + t_send_65 <= 0\n", - "_C118757: t_comp_66 = 33\n", + "_C118755: -t66_end_ + t66_start + t_comp_66 + t_send_66 <= 0\n", + "_C118756: t65_end_ - t66_start <= 0\n", + "_C118757: t_comp_66 = 20\n", "_C118758: t_mem_66 = 1608\n", "_C118759: t_67_map_0 + t_67_map_1 + t_67_map_10 + t_67_map_11 + t_67_map_12 + t_67_map_13 + t_67_map_14 + t_67_map_15 + t_67_map_2 + t_67_map_3 + t_67_map_4 + t_67_map_5 + t_67_map_6 + t_67_map_7 + t_67_map_8 + t_67_map_9 = 1.0\n", - "_C118760: -t67_end_ + t67_start + t_comp_67 <= 0\n", - "_C118761: t57_end_ - t67_start + t_send_57 <= 0\n", + "_C118760: -t67_end_ + t67_start + t_comp_67 + t_send_67 <= 0\n", + "_C118761: t57_end_ - t67_start <= 0\n", "_C118762: t_comp_67 = 1\n", "_C118763: t_mem_67 = 0\n", "_C118764: t_68_map_0 + t_68_map_1 + t_68_map_10 + t_68_map_11 + t_68_map_12 + t_68_map_13 + t_68_map_14 + t_68_map_15 + t_68_map_2 + t_68_map_3 + t_68_map_4 + t_68_map_5 + t_68_map_6 + t_68_map_7 + t_68_map_8 + t_68_map_9 = 1.0\n", - "_C118765: -t68_end_ + t68_start + t_comp_68 <= 0\n", - "_C118766: t67_end_ - t68_start + t_send_67 <= 0\n", - "_C118767: t_comp_68 = 11\n", + "_C118765: -t68_end_ + t68_start + t_comp_68 + t_send_68 <= 0\n", + "_C118766: t67_end_ - t68_start <= 0\n", + "_C118767: t_comp_68 = 7\n", "_C118768: t_mem_68 = 526\n", "_C118769: t_69_map_0 + t_69_map_1 + t_69_map_10 + t_69_map_11 + t_69_map_12 + t_69_map_13 + t_69_map_14 + t_69_map_15 + t_69_map_2 + t_69_map_3 + t_69_map_4 + t_69_map_5 + t_69_map_6 + t_69_map_7 + t_69_map_8 + t_69_map_9 = 1.0\n", - "_C118770: -t69_end_ + t69_start + t_comp_69 <= 0\n", - "_C118771: t58_end_ - t69_start + t_send_58 <= 0\n", - "_C118772: t61_end_ - t69_start + t_send_61 <= 0\n", - "_C118773: t66_end_ - t69_start + t_send_66 <= 0\n", - "_C118774: t68_end_ - t69_start + t_send_68 <= 0\n", - "_C118775: t_comp_69 = 11\n", + "_C118770: -t69_end_ + t69_start + t_comp_69 + t_send_69 <= 0\n", + "_C118771: t58_end_ - t69_start <= 0\n", + "_C118772: t61_end_ - t69_start <= 0\n", + "_C118773: t66_end_ - t69_start <= 0\n", + "_C118774: t68_end_ - t69_start <= 0\n", + "_C118775: t_comp_69 = 7\n", "_C118776: t_mem_69 = 0\n", "_C118777: -t_send_0 - t_send_1 - t_send_10 - t_send_11 - t_send_12 - t_send_13 - t_send_14 - t_send_15 - t_send_16 - t_send_17 - t_send_18 - t_send_19 - t_send_2 - t_send_20 - t_send_21 - t_send_22 - t_send_23 - t_send_24 - t_send_25 - t_send_26 - t_send_27 - t_send_28 - t_send_29 - t_send_3 - t_send_30 - t_send_31 - t_send_32 - t_send_33 - t_send_34 - t_send_35 - t_send_36 - t_send_37 - t_send_38 - t_send_39 - t_send_4 - t_send_40 - t_send_41 - t_send_42 - t_send_43 - t_send_44 - t_send_45 - t_send_46 - t_send_47 - t_send_48 - t_send_49 - t_send_5 - t_send_50 - t_send_51 - t_send_52 - t_send_53 - t_send_54 - t_send_55 - t_send_56 - t_send_57 - t_send_58 - t_send_59 - t_send_6 - t_send_60 - t_send_61 - t_send_62 - t_send_63 - t_send_64 - t_send_65 - t_send_66 - t_send_67 - t_send_68 - t_send_69 - t_send_7 - t_send_8 - t_send_9 + t_send_total >= -0.0\n", "_C118778: t_send_0 >= 0\n", - "_C118779: 10000.0*same_0_1 + t_send_0 >= 285.0\n", + "_C118779: 250000.0*same_0_1 + t_send_0 >= 29.0\n", "_C118780: t_send_1 >= 0\n", - "_C118781: 10000.0*same_1_2 + t_send_1 >= 277.0\n", + "_C118781: 250000.0*same_1_2 + t_send_1 >= 28.0\n", "_C118782: t_send_2 >= 0\n", - "_C118783: 10000.0*same_2_3 + t_send_2 >= 554.0\n", + "_C118783: 250000.0*same_2_3 + t_send_2 >= 56.0\n", "_C118784: t_send_3 >= 0\n", - "_C118785: 10000.0*same_3_5 + t_send_3 >= 137.0\n", + "_C118785: 250000.0*same_3_5 + t_send_3 >= 14.0\n", "_C118786: t_send_4 >= 0\n", - "_C118787: 10000.0*same_4_5 + t_send_4 >= 205.0\n", + "_C118787: 250000.0*same_4_5 + t_send_4 >= 21.0\n", "_C118788: t_send_5 >= 0\n", - "_C118789: 10000.0*same_5_6 + t_send_5 >= 342.0\n", + "_C118789: 250000.0*same_5_6 + t_send_5 >= 35.0\n", "_C118790: t_send_6 >= 0\n", - "_C118791: 10000.0*same_6_7 + t_send_6 >= 137.0\n", + "_C118791: 250000.0*same_6_7 + t_send_6 >= 14.0\n", "_C118792: t_send_7 >= 0\n", - "_C118793: 10000.0*same_7_12 + t_send_7 >= 194.0\n", + "_C118793: 250000.0*same_7_12 + t_send_7 >= 20.0\n", "_C118794: t_send_8 >= 0\n", - "_C118795: 10000.0*same_8_9 + t_send_8 >= 137.0\n", + "_C118795: 250000.0*same_8_9 + t_send_8 >= 14.0\n", "_C118796: t_send_9 >= 0\n", - "_C118797: 10000.0*same_9_10 + t_send_9 >= 137.0\n", + "_C118797: 250000.0*same_9_10 + t_send_9 >= 14.0\n", "_C118798: t_send_10 >= 0\n", - "_C118799: 10000.0*same_10_11 + t_send_10 >= 137.0\n", + "_C118799: 250000.0*same_10_11 + t_send_10 >= 14.0\n", "_C118800: t_send_11 >= 0\n", - "_C118801: 10000.0*same_11_12 + t_send_11 >= 194.0\n", + "_C118801: 250000.0*same_11_12 + t_send_11 >= 20.0\n", "_C118802: t_send_12 >= 0\n", - "_C118803: 10000.0*same_12_13 + t_send_12 >= 388.0\n", + "_C118803: 250000.0*same_12_13 + t_send_12 >= 39.0\n", "_C118804: t_send_13 >= 0\n", - "_C118805: 10000.0*same_13_15 + t_send_13 >= 95.0\n", + "_C118805: 250000.0*same_13_15 + t_send_13 >= 10.0\n", "_C118806: t_send_14 >= 0\n", - "_C118807: 10000.0*same_14_15 + t_send_14 >= 95.0\n", + "_C118807: 250000.0*same_14_15 + t_send_14 >= 10.0\n", "_C118808: t_send_15 >= 0\n", - "_C118809: 10000.0*same_15_16 + t_send_15 >= 189.0\n", + "_C118809: 250000.0*same_15_16 + t_send_15 >= 19.0\n", "_C118810: t_send_16 >= 0\n", - "_C118811: 10000.0*same_16_24 + t_send_16 >= 48.0\n", + "_C118811: 250000.0*same_16_24 + t_send_16 >= 5.0\n", "_C118812: t_send_17 >= 0\n", - "_C118813: 10000.0*same_17_18 + t_send_17 >= 32.0\n", + "_C118813: 250000.0*same_17_18 + t_send_17 >= 4.0\n", "_C118814: t_send_18 >= 0\n", - "_C118815: 10000.0*same_18_24 + t_send_18 >= 48.0\n", + "_C118815: 250000.0*same_18_24 + t_send_18 >= 5.0\n", "_C118816: t_send_19 >= 0\n", - "_C118817: 10000.0*same_19_20 + t_send_19 >= 32.0\n", + "_C118817: 250000.0*same_19_20 + t_send_19 >= 4.0\n", "_C118818: t_send_20 >= 0\n", - "_C118819: 10000.0*same_20_21 + t_send_20 >= 48.0\n", + "_C118819: 250000.0*same_20_21 + t_send_20 >= 5.0\n", "_C118820: t_send_21 >= 0\n", - "_C118821: 10000.0*same_21_24 + t_send_21 >= 48.0\n", + "_C118821: 250000.0*same_21_24 + t_send_21 >= 5.0\n", "_C118822: t_send_22 >= 0\n", - "_C118823: 10000.0*same_22_23 + t_send_22 >= 189.0\n", + "_C118823: 250000.0*same_22_23 + t_send_22 >= 19.0\n", "_C118824: t_send_23 >= 0\n", - "_C118825: 10000.0*same_23_24 + t_send_23 >= 48.0\n", + "_C118825: 250000.0*same_23_24 + t_send_23 >= 5.0\n", "_C118826: t_send_24 >= 0\n", - "_C118827: 10000.0*same_24_25 + t_send_24 >= 189.0\n", + "_C118827: 250000.0*same_24_25 + t_send_24 >= 19.0\n", "_C118828: t_send_25 >= 0\n", - "_C118829: 10000.0*same_25_33 + t_send_25 >= 48.0\n", + "_C118829: 250000.0*same_25_33 + t_send_25 >= 5.0\n", "_C118830: t_send_26 >= 0\n", - "_C118831: 10000.0*same_26_27 + t_send_26 >= 32.0\n", + "_C118831: 250000.0*same_26_27 + t_send_26 >= 4.0\n", "_C118832: t_send_27 >= 0\n", - "_C118833: 10000.0*same_27_33 + t_send_27 >= 48.0\n", + "_C118833: 250000.0*same_27_33 + t_send_27 >= 5.0\n", "_C118834: t_send_28 >= 0\n", - "_C118835: 10000.0*same_28_29 + t_send_28 >= 32.0\n", + "_C118835: 250000.0*same_28_29 + t_send_28 >= 4.0\n", "_C118836: t_send_29 >= 0\n", - "_C118837: 10000.0*same_29_30 + t_send_29 >= 48.0\n", + "_C118837: 250000.0*same_29_30 + t_send_29 >= 5.0\n", "_C118838: t_send_30 >= 0\n", - "_C118839: 10000.0*same_30_33 + t_send_30 >= 48.0\n", + "_C118839: 250000.0*same_30_33 + t_send_30 >= 5.0\n", "_C118840: t_send_31 >= 0\n", - "_C118841: 10000.0*same_31_32 + t_send_31 >= 189.0\n", + "_C118841: 250000.0*same_31_32 + t_send_31 >= 19.0\n", "_C118842: t_send_32 >= 0\n", - "_C118843: 10000.0*same_32_33 + t_send_32 >= 48.0\n", + "_C118843: 250000.0*same_32_33 + t_send_32 >= 5.0\n", "_C118844: t_send_33 >= 0\n", - "_C118845: 10000.0*same_33_34 + t_send_33 >= 189.0\n", + "_C118845: 250000.0*same_33_34 + t_send_33 >= 19.0\n", "_C118846: t_send_34 >= 0\n", - "_C118847: 10000.0*same_34_42 + t_send_34 >= 48.0\n", + "_C118847: 250000.0*same_34_42 + t_send_34 >= 5.0\n", "_C118848: t_send_35 >= 0\n", - "_C118849: 10000.0*same_35_36 + t_send_35 >= 32.0\n", + "_C118849: 250000.0*same_35_36 + t_send_35 >= 4.0\n", "_C118850: t_send_36 >= 0\n", - "_C118851: 10000.0*same_36_42 + t_send_36 >= 48.0\n", + "_C118851: 250000.0*same_36_42 + t_send_36 >= 5.0\n", "_C118852: t_send_37 >= 0\n", - "_C118853: 10000.0*same_37_38 + t_send_37 >= 32.0\n", + "_C118853: 250000.0*same_37_38 + t_send_37 >= 4.0\n", "_C118854: t_send_38 >= 0\n", - "_C118855: 10000.0*same_38_39 + t_send_38 >= 48.0\n", + "_C118855: 250000.0*same_38_39 + t_send_38 >= 5.0\n", "_C118856: t_send_39 >= 0\n", - "_C118857: 10000.0*same_39_42 + t_send_39 >= 48.0\n", + "_C118857: 250000.0*same_39_42 + t_send_39 >= 5.0\n", "_C118858: t_send_40 >= 0\n", - "_C118859: 10000.0*same_40_41 + t_send_40 >= 189.0\n", + "_C118859: 250000.0*same_40_41 + t_send_40 >= 19.0\n", "_C118860: t_send_41 >= 0\n", - "_C118861: 10000.0*same_41_42 + t_send_41 >= 48.0\n", + "_C118861: 250000.0*same_41_42 + t_send_41 >= 5.0\n", "_C118862: t_send_42 >= 0\n", - "_C118863: 10000.0*same_42_43 + t_send_42 >= 189.0\n", + "_C118863: 250000.0*same_42_43 + t_send_42 >= 19.0\n", "_C118864: t_send_43 >= 0\n", - "_C118865: 10000.0*same_43_51 + t_send_43 >= 48.0\n", + "_C118865: 250000.0*same_43_51 + t_send_43 >= 5.0\n", "_C118866: t_send_44 >= 0\n", - "_C118867: 10000.0*same_44_45 + t_send_44 >= 32.0\n", + "_C118867: 250000.0*same_44_45 + t_send_44 >= 4.0\n", "_C118868: t_send_45 >= 0\n", - "_C118869: 10000.0*same_45_51 + t_send_45 >= 48.0\n", + "_C118869: 250000.0*same_45_51 + t_send_45 >= 5.0\n", "_C118870: t_send_46 >= 0\n", - "_C118871: 10000.0*same_46_47 + t_send_46 >= 32.0\n", + "_C118871: 250000.0*same_46_47 + t_send_46 >= 4.0\n", "_C118872: t_send_47 >= 0\n", - "_C118873: 10000.0*same_47_48 + t_send_47 >= 48.0\n", + "_C118873: 250000.0*same_47_48 + t_send_47 >= 5.0\n", "_C118874: t_send_48 >= 0\n", - "_C118875: 10000.0*same_48_51 + t_send_48 >= 48.0\n", + "_C118875: 250000.0*same_48_51 + t_send_48 >= 5.0\n", "_C118876: t_send_49 >= 0\n", - "_C118877: 10000.0*same_49_50 + t_send_49 >= 189.0\n", + "_C118877: 250000.0*same_49_50 + t_send_49 >= 19.0\n", "_C118878: t_send_50 >= 0\n", - "_C118879: 10000.0*same_50_51 + t_send_50 >= 48.0\n", + "_C118879: 250000.0*same_50_51 + t_send_50 >= 5.0\n", "_C118880: t_send_51 >= 0\n", - "_C118881: 10000.0*same_51_52 + t_send_51 >= 189.0\n", + "_C118881: 250000.0*same_51_52 + t_send_51 >= 19.0\n", "_C118882: t_send_52 >= 0\n", - "_C118883: 10000.0*same_52_57 + t_send_52 >= 45.0\n", + "_C118883: 250000.0*same_52_57 + t_send_52 >= 5.0\n", "_C118884: t_send_53 >= 0\n", - "_C118885: 10000.0*same_53_54 + t_send_53 >= 95.0\n", + "_C118885: 250000.0*same_53_54 + t_send_53 >= 10.0\n", "_C118886: t_send_54 >= 0\n", - "_C118887: 10000.0*same_54_55 + t_send_54 >= 110.0\n", + "_C118887: 250000.0*same_54_55 + t_send_54 >= 11.0\n", "_C118888: t_send_55 >= 0\n", - "_C118889: 10000.0*same_55_57 + t_send_55 >= 30.0\n", + "_C118889: 250000.0*same_55_57 + t_send_55 >= 3.0\n", "_C118890: t_send_56 >= 0\n", - "_C118891: 10000.0*same_56_57 + t_send_56 >= 45.0\n", + "_C118891: 250000.0*same_56_57 + t_send_56 >= 5.0\n", "_C118892: t_send_57 >= 0\n", - "_C118893: 10000.0*same_57_58 + t_send_57 >= 119.0\n", + "_C118893: 250000.0*same_57_58 + t_send_57 >= 12.0\n", "_C118894: t_send_58 >= 0\n", - "_C118895: 10000.0*same_58_69 + t_send_58 >= 45.0\n", + "_C118895: 250000.0*same_58_69 + t_send_58 >= 5.0\n", "_C118896: t_send_59 >= 0\n", - "_C118897: 10000.0*same_59_60 + t_send_59 >= 23.0\n", + "_C118897: 250000.0*same_59_60 + t_send_59 >= 3.0\n", "_C118898: t_send_60 >= 0\n", - "_C118899: 10000.0*same_60_61 + t_send_60 >= 26.0\n", + "_C118899: 250000.0*same_60_61 + t_send_60 >= 3.0\n", "_C118900: t_send_61 >= 0\n", - "_C118901: 10000.0*same_61_69 + t_send_61 >= 30.0\n", + "_C118901: 250000.0*same_61_69 + t_send_61 >= 3.0\n", "_C118902: t_send_62 >= 0\n", - "_C118903: 10000.0*same_62_63 + t_send_62 >= 23.0\n", + "_C118903: 250000.0*same_62_63 + t_send_62 >= 3.0\n", "_C118904: t_send_63 >= 0\n", - "_C118905: 10000.0*same_63_64 + t_send_63 >= 23.0\n", + "_C118905: 250000.0*same_63_64 + t_send_63 >= 3.0\n", "_C118906: t_send_64 >= 0\n", - "_C118907: 10000.0*same_64_65 + t_send_64 >= 26.0\n", + "_C118907: 250000.0*same_64_65 + t_send_64 >= 3.0\n", "_C118908: t_send_65 >= 0\n", - "_C118909: 10000.0*same_65_66 + t_send_65 >= 26.0\n", + "_C118909: 250000.0*same_65_66 + t_send_65 >= 3.0\n", "_C118910: t_send_66 >= 0\n", - "_C118911: 10000.0*same_66_69 + t_send_66 >= 30.0\n", + "_C118911: 250000.0*same_66_69 + t_send_66 >= 3.0\n", "_C118912: t_send_67 >= 0\n", - "_C118913: 10000.0*same_67_68 + t_send_67 >= 119.0\n", + "_C118913: 250000.0*same_67_68 + t_send_67 >= 12.0\n", "_C118914: t_send_68 >= 0\n", - "_C118915: 10000.0*same_68_69 + t_send_68 >= 15.0\n", - "_C118916: 10000.0*order_choose_3_4 + 10000.0*same_3_4 + t3_end_ - t4_start <= 20000.0\n", - "_C118917: -10000.0*order_choose_3_4 + 10000.0*same_3_4 - t3_start + t4_end_ <= 10000.0\n", - "_C118918: 10000.0*order_choose_6_8 + 10000.0*same_6_8 + t6_end_ - t8_start <= 20000.0\n", - "_C118919: -10000.0*order_choose_6_8 + 10000.0*same_6_8 - t6_start + t8_end_ <= 10000.0\n", - "_C118920: 10000.0*order_choose_6_9 + 10000.0*same_6_9 + t6_end_ - t9_start <= 20000.0\n", - "_C118921: -10000.0*order_choose_6_9 + 10000.0*same_6_9 - t6_start + t9_end_ <= 10000.0\n", - "_C118922: 10000.0*order_choose_6_10 + 10000.0*same_6_10 - t10_start + t6_end_ <= 20000.0\n", - "_C118923: -10000.0*order_choose_6_10 + 10000.0*same_6_10 + t10_end_ - t6_start <= 10000.0\n", - "_C118924: 10000.0*order_choose_6_11 + 10000.0*same_6_11 - t11_start + t6_end_ <= 20000.0\n", - "_C118925: -10000.0*order_choose_6_11 + 10000.0*same_6_11 + t11_end_ - t6_start <= 10000.0\n", - "_C118926: 10000.0*order_choose_7_8 + 10000.0*same_7_8 + t7_end_ - t8_start <= 20000.0\n", - "_C118927: -10000.0*order_choose_7_8 + 10000.0*same_7_8 - t7_start + t8_end_ <= 10000.0\n", - "_C118928: 10000.0*order_choose_7_9 + 10000.0*same_7_9 + t7_end_ - t9_start <= 20000.0\n", - "_C118929: -10000.0*order_choose_7_9 + 10000.0*same_7_9 - t7_start + t9_end_ <= 10000.0\n", - "_C118930: 10000.0*order_choose_7_10 + 10000.0*same_7_10 - t10_start + t7_end_ <= 20000.0\n", - "_C118931: -10000.0*order_choose_7_10 + 10000.0*same_7_10 + t10_end_ - t7_start <= 10000.0\n", - "_C118932: 10000.0*order_choose_7_11 + 10000.0*same_7_11 - t11_start + t7_end_ <= 20000.0\n", - "_C118933: -10000.0*order_choose_7_11 + 10000.0*same_7_11 + t11_end_ - t7_start <= 10000.0\n", - "_C118934: 10000.0*order_choose_13_14 + 10000.0*same_13_14 + t13_end_ - t14_start <= 20000.0\n", - "_C118935: -10000.0*order_choose_13_14 + 10000.0*same_13_14 - t13_start + t14_end_ <= 10000.0\n", - "_C118936: 10000.0*order_choose_16_17 + 10000.0*same_16_17 + t16_end_ - t17_start <= 20000.0\n", - "_C118937: -10000.0*order_choose_16_17 + 10000.0*same_16_17 - t16_start + t17_end_ <= 10000.0\n", - "_C118938: 10000.0*order_choose_16_18 + 10000.0*same_16_18 + t16_end_ - t18_start <= 20000.0\n", - "_C118939: -10000.0*order_choose_16_18 + 10000.0*same_16_18 - t16_start + t18_end_ <= 10000.0\n", - "_C118940: 10000.0*order_choose_16_19 + 10000.0*same_16_19 + t16_end_ - t19_start <= 20000.0\n", - "_C118941: -10000.0*order_choose_16_19 + 10000.0*same_16_19 - t16_start + t19_end_ <= 10000.0\n", - "_C118942: 10000.0*order_choose_16_20 + 10000.0*same_16_20 + t16_end_ - t20_start <= 20000.0\n", - "_C118943: -10000.0*order_choose_16_20 + 10000.0*same_16_20 - t16_start + t20_end_ <= 10000.0\n", - "_C118944: 10000.0*order_choose_16_21 + 10000.0*same_16_21 + t16_end_ - t21_start <= 20000.0\n", - "_C118945: -10000.0*order_choose_16_21 + 10000.0*same_16_21 - t16_start + t21_end_ <= 10000.0\n", - "_C118946: 10000.0*order_choose_16_22 + 10000.0*same_16_22 + t16_end_ - t22_start <= 20000.0\n", - "_C118947: -10000.0*order_choose_16_22 + 10000.0*same_16_22 - t16_start + t22_end_ <= 10000.0\n", - "_C118948: 10000.0*order_choose_16_23 + 10000.0*same_16_23 + t16_end_ - t23_start <= 20000.0\n", - "_C118949: -10000.0*order_choose_16_23 + 10000.0*same_16_23 - t16_start + t23_end_ <= 10000.0\n", - "_C118950: 10000.0*order_choose_17_19 + 10000.0*same_17_19 + t17_end_ - t19_start <= 20000.0\n", - "_C118951: -10000.0*order_choose_17_19 + 10000.0*same_17_19 - t17_start + t19_end_ <= 10000.0\n", - "_C118952: 10000.0*order_choose_17_20 + 10000.0*same_17_20 + t17_end_ - t20_start <= 20000.0\n", - "_C118953: -10000.0*order_choose_17_20 + 10000.0*same_17_20 - t17_start + t20_end_ <= 10000.0\n", - "_C118954: 10000.0*order_choose_17_21 + 10000.0*same_17_21 + t17_end_ - t21_start <= 20000.0\n", - "_C118955: -10000.0*order_choose_17_21 + 10000.0*same_17_21 - t17_start + t21_end_ <= 10000.0\n", - "_C118956: 10000.0*order_choose_17_22 + 10000.0*same_17_22 + t17_end_ - t22_start <= 20000.0\n", - "_C118957: -10000.0*order_choose_17_22 + 10000.0*same_17_22 - t17_start + t22_end_ <= 10000.0\n", - "_C118958: 10000.0*order_choose_17_23 + 10000.0*same_17_23 + t17_end_ - t23_start <= 20000.0\n", - "_C118959: -10000.0*order_choose_17_23 + 10000.0*same_17_23 - t17_start + t23_end_ <= 10000.0\n", - "_C118960: 10000.0*order_choose_18_19 + 10000.0*same_18_19 + t18_end_ - t19_start <= 20000.0\n", - "_C118961: -10000.0*order_choose_18_19 + 10000.0*same_18_19 - t18_start + t19_end_ <= 10000.0\n", - "_C118962: 10000.0*order_choose_18_20 + 10000.0*same_18_20 + t18_end_ - t20_start <= 20000.0\n", - "_C118963: -10000.0*order_choose_18_20 + 10000.0*same_18_20 - t18_start + t20_end_ <= 10000.0\n", - "_C118964: 10000.0*order_choose_18_21 + 10000.0*same_18_21 + t18_end_ - t21_start <= 20000.0\n", - "_C118965: -10000.0*order_choose_18_21 + 10000.0*same_18_21 - t18_start + t21_end_ <= 10000.0\n", - "_C118966: 10000.0*order_choose_18_22 + 10000.0*same_18_22 + t18_end_ - t22_start <= 20000.0\n", - "_C118967: -10000.0*order_choose_18_22 + 10000.0*same_18_22 - t18_start + t22_end_ <= 10000.0\n", - "_C118968: 10000.0*order_choose_18_23 + 10000.0*same_18_23 + t18_end_ - t23_start <= 20000.0\n", - "_C118969: -10000.0*order_choose_18_23 + 10000.0*same_18_23 - t18_start + t23_end_ <= 10000.0\n", - "_C118970: 10000.0*order_choose_19_22 + 10000.0*same_19_22 + t19_end_ - t22_start <= 20000.0\n", - "_C118971: -10000.0*order_choose_19_22 + 10000.0*same_19_22 - t19_start + t22_end_ <= 10000.0\n", - "_C118972: 10000.0*order_choose_19_23 + 10000.0*same_19_23 + t19_end_ - t23_start <= 20000.0\n", - "_C118973: -10000.0*order_choose_19_23 + 10000.0*same_19_23 - t19_start + t23_end_ <= 10000.0\n", - "_C118974: 10000.0*order_choose_20_22 + 10000.0*same_20_22 + t20_end_ - t22_start <= 20000.0\n", - "_C118975: -10000.0*order_choose_20_22 + 10000.0*same_20_22 - t20_start + t22_end_ <= 10000.0\n", - "_C118976: 10000.0*order_choose_20_23 + 10000.0*same_20_23 + t20_end_ - t23_start <= 20000.0\n", - "_C118977: -10000.0*order_choose_20_23 + 10000.0*same_20_23 - t20_start + t23_end_ <= 10000.0\n", - "_C118978: 10000.0*order_choose_21_22 + 10000.0*same_21_22 + t21_end_ - t22_start <= 20000.0\n", - "_C118979: -10000.0*order_choose_21_22 + 10000.0*same_21_22 - t21_start + t22_end_ <= 10000.0\n", - "_C118980: 10000.0*order_choose_21_23 + 10000.0*same_21_23 + t21_end_ - t23_start <= 20000.0\n", - "_C118981: -10000.0*order_choose_21_23 + 10000.0*same_21_23 - t21_start + t23_end_ <= 10000.0\n", - "_C118982: 10000.0*order_choose_25_26 + 10000.0*same_25_26 + t25_end_ - t26_start <= 20000.0\n", - "_C118983: -10000.0*order_choose_25_26 + 10000.0*same_25_26 - t25_start + t26_end_ <= 10000.0\n", - "_C118984: 10000.0*order_choose_25_27 + 10000.0*same_25_27 + t25_end_ - t27_start <= 20000.0\n", - "_C118985: -10000.0*order_choose_25_27 + 10000.0*same_25_27 - t25_start + t27_end_ <= 10000.0\n", - "_C118986: 10000.0*order_choose_25_28 + 10000.0*same_25_28 + t25_end_ - t28_start <= 20000.0\n", - "_C118987: -10000.0*order_choose_25_28 + 10000.0*same_25_28 - t25_start + t28_end_ <= 10000.0\n", - "_C118988: 10000.0*order_choose_25_29 + 10000.0*same_25_29 + t25_end_ - t29_start <= 20000.0\n", - "_C118989: -10000.0*order_choose_25_29 + 10000.0*same_25_29 - t25_start + t29_end_ <= 10000.0\n", - "_C118990: 10000.0*order_choose_25_30 + 10000.0*same_25_30 + t25_end_ - t30_start <= 20000.0\n", - "_C118991: -10000.0*order_choose_25_30 + 10000.0*same_25_30 - t25_start + t30_end_ <= 10000.0\n", - "_C118992: 10000.0*order_choose_25_31 + 10000.0*same_25_31 + t25_end_ - t31_start <= 20000.0\n", - "_C118993: -10000.0*order_choose_25_31 + 10000.0*same_25_31 - t25_start + t31_end_ <= 10000.0\n", - "_C118994: 10000.0*order_choose_25_32 + 10000.0*same_25_32 + t25_end_ - t32_start <= 20000.0\n", - "_C118995: -10000.0*order_choose_25_32 + 10000.0*same_25_32 - t25_start + t32_end_ <= 10000.0\n", - "_C118996: 10000.0*order_choose_26_28 + 10000.0*same_26_28 + t26_end_ - t28_start <= 20000.0\n", - "_C118997: -10000.0*order_choose_26_28 + 10000.0*same_26_28 - t26_start + t28_end_ <= 10000.0\n", - "_C118998: 10000.0*order_choose_26_29 + 10000.0*same_26_29 + t26_end_ - t29_start <= 20000.0\n", - "_C118999: -10000.0*order_choose_26_29 + 10000.0*same_26_29 - t26_start + t29_end_ <= 10000.0\n", - "_C119000: 10000.0*order_choose_26_30 + 10000.0*same_26_30 + t26_end_ - t30_start <= 20000.0\n", - "_C119001: -10000.0*order_choose_26_30 + 10000.0*same_26_30 - t26_start + t30_end_ <= 10000.0\n", - "_C119002: 10000.0*order_choose_26_31 + 10000.0*same_26_31 + t26_end_ - t31_start <= 20000.0\n", - "_C119003: -10000.0*order_choose_26_31 + 10000.0*same_26_31 - t26_start + t31_end_ <= 10000.0\n", - "_C119004: 10000.0*order_choose_26_32 + 10000.0*same_26_32 + t26_end_ - t32_start <= 20000.0\n", - "_C119005: -10000.0*order_choose_26_32 + 10000.0*same_26_32 - t26_start + t32_end_ <= 10000.0\n", - "_C119006: 10000.0*order_choose_27_28 + 10000.0*same_27_28 + t27_end_ - t28_start <= 20000.0\n", - "_C119007: -10000.0*order_choose_27_28 + 10000.0*same_27_28 - t27_start + t28_end_ <= 10000.0\n", - "_C119008: 10000.0*order_choose_27_29 + 10000.0*same_27_29 + t27_end_ - t29_start <= 20000.0\n", - "_C119009: -10000.0*order_choose_27_29 + 10000.0*same_27_29 - t27_start + t29_end_ <= 10000.0\n", - "_C119010: 10000.0*order_choose_27_30 + 10000.0*same_27_30 + t27_end_ - t30_start <= 20000.0\n", - "_C119011: -10000.0*order_choose_27_30 + 10000.0*same_27_30 - t27_start + t30_end_ <= 10000.0\n", - "_C119012: 10000.0*order_choose_27_31 + 10000.0*same_27_31 + t27_end_ - t31_start <= 20000.0\n", - "_C119013: -10000.0*order_choose_27_31 + 10000.0*same_27_31 - t27_start + t31_end_ <= 10000.0\n", - "_C119014: 10000.0*order_choose_27_32 + 10000.0*same_27_32 + t27_end_ - t32_start <= 20000.0\n", - "_C119015: -10000.0*order_choose_27_32 + 10000.0*same_27_32 - t27_start + t32_end_ <= 10000.0\n", - "_C119016: 10000.0*order_choose_28_31 + 10000.0*same_28_31 + t28_end_ - t31_start <= 20000.0\n", - "_C119017: -10000.0*order_choose_28_31 + 10000.0*same_28_31 - t28_start + t31_end_ <= 10000.0\n", - "_C119018: 10000.0*order_choose_28_32 + 10000.0*same_28_32 + t28_end_ - t32_start <= 20000.0\n", - "_C119019: -10000.0*order_choose_28_32 + 10000.0*same_28_32 - t28_start + t32_end_ <= 10000.0\n", - "_C119020: 10000.0*order_choose_29_31 + 10000.0*same_29_31 + t29_end_ - t31_start <= 20000.0\n", - "_C119021: -10000.0*order_choose_29_31 + 10000.0*same_29_31 - t29_start + t31_end_ <= 10000.0\n", - "_C119022: 10000.0*order_choose_29_32 + 10000.0*same_29_32 + t29_end_ - t32_start <= 20000.0\n", - "_C119023: -10000.0*order_choose_29_32 + 10000.0*same_29_32 - t29_start + t32_end_ <= 10000.0\n", - "_C119024: 10000.0*order_choose_30_31 + 10000.0*same_30_31 + t30_end_ - t31_start <= 20000.0\n", - "_C119025: -10000.0*order_choose_30_31 + 10000.0*same_30_31 - t30_start + t31_end_ <= 10000.0\n", - "_C119026: 10000.0*order_choose_30_32 + 10000.0*same_30_32 + t30_end_ - t32_start <= 20000.0\n", - "_C119027: -10000.0*order_choose_30_32 + 10000.0*same_30_32 - t30_start + t32_end_ <= 10000.0\n", - "_C119028: 10000.0*order_choose_34_35 + 10000.0*same_34_35 + t34_end_ - t35_start <= 20000.0\n", - "_C119029: -10000.0*order_choose_34_35 + 10000.0*same_34_35 - t34_start + t35_end_ <= 10000.0\n", - "_C119030: 10000.0*order_choose_34_36 + 10000.0*same_34_36 + t34_end_ - t36_start <= 20000.0\n", - "_C119031: -10000.0*order_choose_34_36 + 10000.0*same_34_36 - t34_start + t36_end_ <= 10000.0\n", - "_C119032: 10000.0*order_choose_34_37 + 10000.0*same_34_37 + t34_end_ - t37_start <= 20000.0\n", - "_C119033: -10000.0*order_choose_34_37 + 10000.0*same_34_37 - t34_start + t37_end_ <= 10000.0\n", - "_C119034: 10000.0*order_choose_34_38 + 10000.0*same_34_38 + t34_end_ - t38_start <= 20000.0\n", - "_C119035: -10000.0*order_choose_34_38 + 10000.0*same_34_38 - t34_start + t38_end_ <= 10000.0\n", - "_C119036: 10000.0*order_choose_34_39 + 10000.0*same_34_39 + t34_end_ - t39_start <= 20000.0\n", - "_C119037: -10000.0*order_choose_34_39 + 10000.0*same_34_39 - t34_start + t39_end_ <= 10000.0\n", - "_C119038: 10000.0*order_choose_34_40 + 10000.0*same_34_40 + t34_end_ - t40_start <= 20000.0\n", - "_C119039: -10000.0*order_choose_34_40 + 10000.0*same_34_40 - t34_start + t40_end_ <= 10000.0\n", - "_C119040: 10000.0*order_choose_34_41 + 10000.0*same_34_41 + t34_end_ - t41_start <= 20000.0\n", - "_C119041: -10000.0*order_choose_34_41 + 10000.0*same_34_41 - t34_start + t41_end_ <= 10000.0\n", - "_C119042: 10000.0*order_choose_35_37 + 10000.0*same_35_37 + t35_end_ - t37_start <= 20000.0\n", - "_C119043: -10000.0*order_choose_35_37 + 10000.0*same_35_37 - t35_start + t37_end_ <= 10000.0\n", - "_C119044: 10000.0*order_choose_35_38 + 10000.0*same_35_38 + t35_end_ - t38_start <= 20000.0\n", - "_C119045: -10000.0*order_choose_35_38 + 10000.0*same_35_38 - t35_start + t38_end_ <= 10000.0\n", - "_C119046: 10000.0*order_choose_35_39 + 10000.0*same_35_39 + t35_end_ - t39_start <= 20000.0\n", - "_C119047: -10000.0*order_choose_35_39 + 10000.0*same_35_39 - t35_start + t39_end_ <= 10000.0\n", - "_C119048: 10000.0*order_choose_35_40 + 10000.0*same_35_40 + t35_end_ - t40_start <= 20000.0\n", - "_C119049: -10000.0*order_choose_35_40 + 10000.0*same_35_40 - t35_start + t40_end_ <= 10000.0\n", - "_C119050: 10000.0*order_choose_35_41 + 10000.0*same_35_41 + t35_end_ - t41_start <= 20000.0\n", - "_C119051: -10000.0*order_choose_35_41 + 10000.0*same_35_41 - t35_start + t41_end_ <= 10000.0\n", - "_C119052: 10000.0*order_choose_36_37 + 10000.0*same_36_37 + t36_end_ - t37_start <= 20000.0\n", - "_C119053: -10000.0*order_choose_36_37 + 10000.0*same_36_37 - t36_start + t37_end_ <= 10000.0\n", - "_C119054: 10000.0*order_choose_36_38 + 10000.0*same_36_38 + t36_end_ - t38_start <= 20000.0\n", - "_C119055: -10000.0*order_choose_36_38 + 10000.0*same_36_38 - t36_start + t38_end_ <= 10000.0\n", - "_C119056: 10000.0*order_choose_36_39 + 10000.0*same_36_39 + t36_end_ - t39_start <= 20000.0\n", - "_C119057: -10000.0*order_choose_36_39 + 10000.0*same_36_39 - t36_start + t39_end_ <= 10000.0\n", - "_C119058: 10000.0*order_choose_36_40 + 10000.0*same_36_40 + t36_end_ - t40_start <= 20000.0\n", - "_C119059: -10000.0*order_choose_36_40 + 10000.0*same_36_40 - t36_start + t40_end_ <= 10000.0\n", - "_C119060: 10000.0*order_choose_36_41 + 10000.0*same_36_41 + t36_end_ - t41_start <= 20000.0\n", - "_C119061: -10000.0*order_choose_36_41 + 10000.0*same_36_41 - t36_start + t41_end_ <= 10000.0\n", - "_C119062: 10000.0*order_choose_37_40 + 10000.0*same_37_40 + t37_end_ - t40_start <= 20000.0\n", - "_C119063: -10000.0*order_choose_37_40 + 10000.0*same_37_40 - t37_start + t40_end_ <= 10000.0\n", - "_C119064: 10000.0*order_choose_37_41 + 10000.0*same_37_41 + t37_end_ - t41_start <= 20000.0\n", - "_C119065: -10000.0*order_choose_37_41 + 10000.0*same_37_41 - t37_start + t41_end_ <= 10000.0\n", - "_C119066: 10000.0*order_choose_38_40 + 10000.0*same_38_40 + t38_end_ - t40_start <= 20000.0\n", - "_C119067: -10000.0*order_choose_38_40 + 10000.0*same_38_40 - t38_start + t40_end_ <= 10000.0\n", - "_C119068: 10000.0*order_choose_38_41 + 10000.0*same_38_41 + t38_end_ - t41_start <= 20000.0\n", - "_C119069: -10000.0*order_choose_38_41 + 10000.0*same_38_41 - t38_start + t41_end_ <= 10000.0\n", - "_C119070: 10000.0*order_choose_39_40 + 10000.0*same_39_40 + t39_end_ - t40_start <= 20000.0\n", - "_C119071: -10000.0*order_choose_39_40 + 10000.0*same_39_40 - t39_start + t40_end_ <= 10000.0\n", - "_C119072: 10000.0*order_choose_39_41 + 10000.0*same_39_41 + t39_end_ - t41_start <= 20000.0\n", - "_C119073: -10000.0*order_choose_39_41 + 10000.0*same_39_41 - t39_start + t41_end_ <= 10000.0\n", - "_C119074: 10000.0*order_choose_43_44 + 10000.0*same_43_44 + t43_end_ - t44_start <= 20000.0\n", - "_C119075: -10000.0*order_choose_43_44 + 10000.0*same_43_44 - t43_start + t44_end_ <= 10000.0\n", - "_C119076: 10000.0*order_choose_43_45 + 10000.0*same_43_45 + t43_end_ - t45_start <= 20000.0\n", - "_C119077: -10000.0*order_choose_43_45 + 10000.0*same_43_45 - t43_start + t45_end_ <= 10000.0\n", - "_C119078: 10000.0*order_choose_43_46 + 10000.0*same_43_46 + t43_end_ - t46_start <= 20000.0\n", - "_C119079: -10000.0*order_choose_43_46 + 10000.0*same_43_46 - t43_start + t46_end_ <= 10000.0\n", - "_C119080: 10000.0*order_choose_43_47 + 10000.0*same_43_47 + t43_end_ - t47_start <= 20000.0\n", - "_C119081: -10000.0*order_choose_43_47 + 10000.0*same_43_47 - t43_start + t47_end_ <= 10000.0\n", - "_C119082: 10000.0*order_choose_43_48 + 10000.0*same_43_48 + t43_end_ - t48_start <= 20000.0\n", - "_C119083: -10000.0*order_choose_43_48 + 10000.0*same_43_48 - t43_start + t48_end_ <= 10000.0\n", - "_C119084: 10000.0*order_choose_43_49 + 10000.0*same_43_49 + t43_end_ - t49_start <= 20000.0\n", - "_C119085: -10000.0*order_choose_43_49 + 10000.0*same_43_49 - t43_start + t49_end_ <= 10000.0\n", - "_C119086: 10000.0*order_choose_43_50 + 10000.0*same_43_50 + t43_end_ - t50_start <= 20000.0\n", - "_C119087: -10000.0*order_choose_43_50 + 10000.0*same_43_50 - t43_start + t50_end_ <= 10000.0\n", - "_C119088: 10000.0*order_choose_44_46 + 10000.0*same_44_46 + t44_end_ - t46_start <= 20000.0\n", - "_C119089: -10000.0*order_choose_44_46 + 10000.0*same_44_46 - t44_start + t46_end_ <= 10000.0\n", - "_C119090: 10000.0*order_choose_44_47 + 10000.0*same_44_47 + t44_end_ - t47_start <= 20000.0\n", - "_C119091: -10000.0*order_choose_44_47 + 10000.0*same_44_47 - t44_start + t47_end_ <= 10000.0\n", - "_C119092: 10000.0*order_choose_44_48 + 10000.0*same_44_48 + t44_end_ - t48_start <= 20000.0\n", - "_C119093: -10000.0*order_choose_44_48 + 10000.0*same_44_48 - t44_start + t48_end_ <= 10000.0\n", - "_C119094: 10000.0*order_choose_44_49 + 10000.0*same_44_49 + t44_end_ - t49_start <= 20000.0\n", - "_C119095: -10000.0*order_choose_44_49 + 10000.0*same_44_49 - t44_start + t49_end_ <= 10000.0\n", - "_C119096: 10000.0*order_choose_44_50 + 10000.0*same_44_50 + t44_end_ - t50_start <= 20000.0\n", - "_C119097: -10000.0*order_choose_44_50 + 10000.0*same_44_50 - t44_start + t50_end_ <= 10000.0\n", - "_C119098: 10000.0*order_choose_45_46 + 10000.0*same_45_46 + t45_end_ - t46_start <= 20000.0\n", - "_C119099: -10000.0*order_choose_45_46 + 10000.0*same_45_46 - t45_start + t46_end_ <= 10000.0\n", - "_C119100: 10000.0*order_choose_45_47 + 10000.0*same_45_47 + t45_end_ - t47_start <= 20000.0\n", - "_C119101: -10000.0*order_choose_45_47 + 10000.0*same_45_47 - t45_start + t47_end_ <= 10000.0\n", - "_C119102: 10000.0*order_choose_45_48 + 10000.0*same_45_48 + t45_end_ - t48_start <= 20000.0\n", - "_C119103: -10000.0*order_choose_45_48 + 10000.0*same_45_48 - t45_start + t48_end_ <= 10000.0\n", - "_C119104: 10000.0*order_choose_45_49 + 10000.0*same_45_49 + t45_end_ - t49_start <= 20000.0\n", - "_C119105: -10000.0*order_choose_45_49 + 10000.0*same_45_49 - t45_start + t49_end_ <= 10000.0\n", - "_C119106: 10000.0*order_choose_45_50 + 10000.0*same_45_50 + t45_end_ - t50_start <= 20000.0\n", - "_C119107: -10000.0*order_choose_45_50 + 10000.0*same_45_50 - t45_start + t50_end_ <= 10000.0\n", - "_C119108: 10000.0*order_choose_46_49 + 10000.0*same_46_49 + t46_end_ - t49_start <= 20000.0\n", - "_C119109: -10000.0*order_choose_46_49 + 10000.0*same_46_49 - t46_start + t49_end_ <= 10000.0\n", - "_C119110: 10000.0*order_choose_46_50 + 10000.0*same_46_50 + t46_end_ - t50_start <= 20000.0\n", - "_C119111: -10000.0*order_choose_46_50 + 10000.0*same_46_50 - t46_start + t50_end_ <= 10000.0\n", - "_C119112: 10000.0*order_choose_47_49 + 10000.0*same_47_49 + t47_end_ - t49_start <= 20000.0\n", - "_C119113: -10000.0*order_choose_47_49 + 10000.0*same_47_49 - t47_start + t49_end_ <= 10000.0\n", - "_C119114: 10000.0*order_choose_47_50 + 10000.0*same_47_50 + t47_end_ - t50_start <= 20000.0\n", - "_C119115: -10000.0*order_choose_47_50 + 10000.0*same_47_50 - t47_start + t50_end_ <= 10000.0\n", - "_C119116: 10000.0*order_choose_48_49 + 10000.0*same_48_49 + t48_end_ - t49_start <= 20000.0\n", - "_C119117: -10000.0*order_choose_48_49 + 10000.0*same_48_49 - t48_start + t49_end_ <= 10000.0\n", - "_C119118: 10000.0*order_choose_48_50 + 10000.0*same_48_50 + t48_end_ - t50_start <= 20000.0\n", - "_C119119: -10000.0*order_choose_48_50 + 10000.0*same_48_50 - t48_start + t50_end_ <= 10000.0\n", - "_C119120: 10000.0*order_choose_52_53 + 10000.0*same_52_53 + t52_end_ - t53_start <= 20000.0\n", - "_C119121: -10000.0*order_choose_52_53 + 10000.0*same_52_53 - t52_start + t53_end_ <= 10000.0\n", - "_C119122: 10000.0*order_choose_52_54 + 10000.0*same_52_54 + t52_end_ - t54_start <= 20000.0\n", - "_C119123: -10000.0*order_choose_52_54 + 10000.0*same_52_54 - t52_start + t54_end_ <= 10000.0\n", - "_C119124: 10000.0*order_choose_52_55 + 10000.0*same_52_55 + t52_end_ - t55_start <= 20000.0\n", - "_C119125: -10000.0*order_choose_52_55 + 10000.0*same_52_55 - t52_start + t55_end_ <= 10000.0\n", - "_C119126: 10000.0*order_choose_52_56 + 10000.0*same_52_56 + t52_end_ - t56_start <= 20000.0\n", - "_C119127: -10000.0*order_choose_52_56 + 10000.0*same_52_56 - t52_start + t56_end_ <= 10000.0\n", - "_C119128: 10000.0*order_choose_53_56 + 10000.0*same_53_56 + t53_end_ - t56_start <= 20000.0\n", - "_C119129: -10000.0*order_choose_53_56 + 10000.0*same_53_56 - t53_start + t56_end_ <= 10000.0\n", - "_C119130: 10000.0*order_choose_54_56 + 10000.0*same_54_56 + t54_end_ - t56_start <= 20000.0\n", - "_C119131: -10000.0*order_choose_54_56 + 10000.0*same_54_56 - t54_start + t56_end_ <= 10000.0\n", - "_C119132: 10000.0*order_choose_55_56 + 10000.0*same_55_56 + t55_end_ - t56_start <= 20000.0\n", - "_C119133: -10000.0*order_choose_55_56 + 10000.0*same_55_56 - t55_start + t56_end_ <= 10000.0\n", - "_C119134: 10000.0*order_choose_58_59 + 10000.0*same_58_59 + t58_end_ - t59_start <= 20000.0\n", - "_C119135: -10000.0*order_choose_58_59 + 10000.0*same_58_59 - t58_start + t59_end_ <= 10000.0\n", - "_C119136: 10000.0*order_choose_58_60 + 10000.0*same_58_60 + t58_end_ - t60_start <= 20000.0\n", - "_C119137: -10000.0*order_choose_58_60 + 10000.0*same_58_60 - t58_start + t60_end_ <= 10000.0\n", - "_C119138: 10000.0*order_choose_58_61 + 10000.0*same_58_61 + t58_end_ - t61_start <= 20000.0\n", - "_C119139: -10000.0*order_choose_58_61 + 10000.0*same_58_61 - t58_start + t61_end_ <= 10000.0\n", - "_C119140: 10000.0*order_choose_58_62 + 10000.0*same_58_62 + t58_end_ - t62_start <= 20000.0\n", - "_C119141: -10000.0*order_choose_58_62 + 10000.0*same_58_62 - t58_start + t62_end_ <= 10000.0\n", - "_C119142: 10000.0*order_choose_58_63 + 10000.0*same_58_63 + t58_end_ - t63_start <= 20000.0\n", - "_C119143: -10000.0*order_choose_58_63 + 10000.0*same_58_63 - t58_start + t63_end_ <= 10000.0\n", - "_C119144: 10000.0*order_choose_58_64 + 10000.0*same_58_64 + t58_end_ - t64_start <= 20000.0\n", - "_C119145: -10000.0*order_choose_58_64 + 10000.0*same_58_64 - t58_start + t64_end_ <= 10000.0\n", - "_C119146: 10000.0*order_choose_58_65 + 10000.0*same_58_65 + t58_end_ - t65_start <= 20000.0\n", - "_C119147: -10000.0*order_choose_58_65 + 10000.0*same_58_65 - t58_start + t65_end_ <= 10000.0\n", - "_C119148: 10000.0*order_choose_58_66 + 10000.0*same_58_66 + t58_end_ - t66_start <= 20000.0\n", - "_C119149: -10000.0*order_choose_58_66 + 10000.0*same_58_66 - t58_start + t66_end_ <= 10000.0\n", - "_C119150: 10000.0*order_choose_58_67 + 10000.0*same_58_67 + t58_end_ - t67_start <= 20000.0\n", - "_C119151: -10000.0*order_choose_58_67 + 10000.0*same_58_67 - t58_start + t67_end_ <= 10000.0\n", - "_C119152: 10000.0*order_choose_58_68 + 10000.0*same_58_68 + t58_end_ - t68_start <= 20000.0\n", - "_C119153: -10000.0*order_choose_58_68 + 10000.0*same_58_68 - t58_start + t68_end_ <= 10000.0\n", - "_C119154: 10000.0*order_choose_59_62 + 10000.0*same_59_62 + t59_end_ - t62_start <= 20000.0\n", - "_C119155: -10000.0*order_choose_59_62 + 10000.0*same_59_62 - t59_start + t62_end_ <= 10000.0\n", - "_C119156: 10000.0*order_choose_59_63 + 10000.0*same_59_63 + t59_end_ - t63_start <= 20000.0\n", - "_C119157: -10000.0*order_choose_59_63 + 10000.0*same_59_63 - t59_start + t63_end_ <= 10000.0\n", - "_C119158: 10000.0*order_choose_59_64 + 10000.0*same_59_64 + t59_end_ - t64_start <= 20000.0\n", - "_C119159: -10000.0*order_choose_59_64 + 10000.0*same_59_64 - t59_start + t64_end_ <= 10000.0\n", - "_C119160: 10000.0*order_choose_59_65 + 10000.0*same_59_65 + t59_end_ - t65_start <= 20000.0\n", - "_C119161: -10000.0*order_choose_59_65 + 10000.0*same_59_65 - t59_start + t65_end_ <= 10000.0\n", - "_C119162: 10000.0*order_choose_59_66 + 10000.0*same_59_66 + t59_end_ - t66_start <= 20000.0\n", - "_C119163: -10000.0*order_choose_59_66 + 10000.0*same_59_66 - t59_start + t66_end_ <= 10000.0\n", - "_C119164: 10000.0*order_choose_59_67 + 10000.0*same_59_67 + t59_end_ - t67_start <= 20000.0\n", - "_C119165: -10000.0*order_choose_59_67 + 10000.0*same_59_67 - t59_start + t67_end_ <= 10000.0\n", - "_C119166: 10000.0*order_choose_59_68 + 10000.0*same_59_68 + t59_end_ - t68_start <= 20000.0\n", - "_C119167: -10000.0*order_choose_59_68 + 10000.0*same_59_68 - t59_start + t68_end_ <= 10000.0\n", - "_C119168: 10000.0*order_choose_60_62 + 10000.0*same_60_62 + t60_end_ - t62_start <= 20000.0\n", - "_C119169: -10000.0*order_choose_60_62 + 10000.0*same_60_62 - t60_start + t62_end_ <= 10000.0\n", - "_C119170: 10000.0*order_choose_60_63 + 10000.0*same_60_63 + t60_end_ - t63_start <= 20000.0\n", - "_C119171: -10000.0*order_choose_60_63 + 10000.0*same_60_63 - t60_start + t63_end_ <= 10000.0\n", - "_C119172: 10000.0*order_choose_60_64 + 10000.0*same_60_64 + t60_end_ - t64_start <= 20000.0\n", - "_C119173: -10000.0*order_choose_60_64 + 10000.0*same_60_64 - t60_start + t64_end_ <= 10000.0\n", - "_C119174: 10000.0*order_choose_60_65 + 10000.0*same_60_65 + t60_end_ - t65_start <= 20000.0\n", - "_C119175: -10000.0*order_choose_60_65 + 10000.0*same_60_65 - t60_start + t65_end_ <= 10000.0\n", - "_C119176: 10000.0*order_choose_60_66 + 10000.0*same_60_66 + t60_end_ - t66_start <= 20000.0\n", - "_C119177: -10000.0*order_choose_60_66 + 10000.0*same_60_66 - t60_start + t66_end_ <= 10000.0\n", - "_C119178: 10000.0*order_choose_60_67 + 10000.0*same_60_67 + t60_end_ - t67_start <= 20000.0\n", - "_C119179: -10000.0*order_choose_60_67 + 10000.0*same_60_67 - t60_start + t67_end_ <= 10000.0\n", - "_C119180: 10000.0*order_choose_60_68 + 10000.0*same_60_68 + t60_end_ - t68_start <= 20000.0\n", - "_C119181: -10000.0*order_choose_60_68 + 10000.0*same_60_68 - t60_start + t68_end_ <= 10000.0\n", - "_C119182: 10000.0*order_choose_61_62 + 10000.0*same_61_62 + t61_end_ - t62_start <= 20000.0\n", - "_C119183: -10000.0*order_choose_61_62 + 10000.0*same_61_62 - t61_start + t62_end_ <= 10000.0\n", - "_C119184: 10000.0*order_choose_61_63 + 10000.0*same_61_63 + t61_end_ - t63_start <= 20000.0\n", - "_C119185: -10000.0*order_choose_61_63 + 10000.0*same_61_63 - t61_start + t63_end_ <= 10000.0\n", - "_C119186: 10000.0*order_choose_61_64 + 10000.0*same_61_64 + t61_end_ - t64_start <= 20000.0\n", - "_C119187: -10000.0*order_choose_61_64 + 10000.0*same_61_64 - t61_start + t64_end_ <= 10000.0\n", - "_C119188: 10000.0*order_choose_61_65 + 10000.0*same_61_65 + t61_end_ - t65_start <= 20000.0\n", - "_C119189: -10000.0*order_choose_61_65 + 10000.0*same_61_65 - t61_start + t65_end_ <= 10000.0\n", - "_C119190: 10000.0*order_choose_61_66 + 10000.0*same_61_66 + t61_end_ - t66_start <= 20000.0\n", - "_C119191: -10000.0*order_choose_61_66 + 10000.0*same_61_66 - t61_start + t66_end_ <= 10000.0\n", - "_C119192: 10000.0*order_choose_61_67 + 10000.0*same_61_67 + t61_end_ - t67_start <= 20000.0\n", - "_C119193: -10000.0*order_choose_61_67 + 10000.0*same_61_67 - t61_start + t67_end_ <= 10000.0\n", - "_C119194: 10000.0*order_choose_61_68 + 10000.0*same_61_68 + t61_end_ - t68_start <= 20000.0\n", - "_C119195: -10000.0*order_choose_61_68 + 10000.0*same_61_68 - t61_start + t68_end_ <= 10000.0\n", - "_C119196: 10000.0*order_choose_62_67 + 10000.0*same_62_67 + t62_end_ - t67_start <= 20000.0\n", - "_C119197: -10000.0*order_choose_62_67 + 10000.0*same_62_67 - t62_start + t67_end_ <= 10000.0\n", - "_C119198: 10000.0*order_choose_62_68 + 10000.0*same_62_68 + t62_end_ - t68_start <= 20000.0\n", - "_C119199: -10000.0*order_choose_62_68 + 10000.0*same_62_68 - t62_start + t68_end_ <= 10000.0\n", - "_C119200: 10000.0*order_choose_63_67 + 10000.0*same_63_67 + t63_end_ - t67_start <= 20000.0\n", - "_C119201: -10000.0*order_choose_63_67 + 10000.0*same_63_67 - t63_start + t67_end_ <= 10000.0\n", - "_C119202: 10000.0*order_choose_63_68 + 10000.0*same_63_68 + t63_end_ - t68_start <= 20000.0\n", - "_C119203: -10000.0*order_choose_63_68 + 10000.0*same_63_68 - t63_start + t68_end_ <= 10000.0\n", - "_C119204: 10000.0*order_choose_64_67 + 10000.0*same_64_67 + t64_end_ - t67_start <= 20000.0\n", - "_C119205: -10000.0*order_choose_64_67 + 10000.0*same_64_67 - t64_start + t67_end_ <= 10000.0\n", - "_C119206: 10000.0*order_choose_64_68 + 10000.0*same_64_68 + t64_end_ - t68_start <= 20000.0\n", - "_C119207: -10000.0*order_choose_64_68 + 10000.0*same_64_68 - t64_start + t68_end_ <= 10000.0\n", - "_C119208: 10000.0*order_choose_65_67 + 10000.0*same_65_67 + t65_end_ - t67_start <= 20000.0\n", - "_C119209: -10000.0*order_choose_65_67 + 10000.0*same_65_67 - t65_start + t67_end_ <= 10000.0\n", - "_C119210: 10000.0*order_choose_65_68 + 10000.0*same_65_68 + t65_end_ - t68_start <= 20000.0\n", - "_C119211: -10000.0*order_choose_65_68 + 10000.0*same_65_68 - t65_start + t68_end_ <= 10000.0\n", - "_C119212: 10000.0*order_choose_66_67 + 10000.0*same_66_67 + t66_end_ - t67_start <= 20000.0\n", - "_C119213: -10000.0*order_choose_66_67 + 10000.0*same_66_67 - t66_start + t67_end_ <= 10000.0\n", - "_C119214: 10000.0*order_choose_66_68 + 10000.0*same_66_68 + t66_end_ - t68_start <= 20000.0\n", - "_C119215: -10000.0*order_choose_66_68 + 10000.0*same_66_68 - t66_start + t68_end_ <= 10000.0\n", - "_C119216: 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task_total_delay_router_router0_task57 >= -10000.0\n", - "_C119331: -10000.0*t_57_map_0 - t_mem_57 + task_total_memory_router_router0_task57 >= -10000.0\n", - "_C119332: -t58_end_ + t58_start - 10000.0*t_58_map_0 - t_send_58 + task_total_delay_router_router0_task58 >= -10000.0\n", - "_C119333: -10000.0*t_58_map_0 - t_mem_58 + task_total_memory_router_router0_task58 >= -10000.0\n", - "_C119334: -t59_end_ + t59_start - 10000.0*t_59_map_0 - t_send_59 + task_total_delay_router_router0_task59 >= -10000.0\n", - "_C119335: -10000.0*t_59_map_0 - t_mem_59 + task_total_memory_router_router0_task59 >= -10000.0\n", - "_C119336: -t60_end_ + t60_start - 10000.0*t_60_map_0 - t_send_60 + task_total_delay_router_router0_task60 >= -10000.0\n", - "_C119337: -10000.0*t_60_map_0 - t_mem_60 + task_total_memory_router_router0_task60 >= -10000.0\n", - "_C119338: -t61_end_ + t61_start - 10000.0*t_61_map_0 - t_send_61 + task_total_delay_router_router0_task61 >= -10000.0\n", - "_C119339: -10000.0*t_61_map_0 - t_mem_61 + task_total_memory_router_router0_task61 >= -10000.0\n", - "_C119340: -t62_end_ + t62_start - 10000.0*t_62_map_0 - t_send_62 + task_total_delay_router_router0_task62 >= -10000.0\n", - "_C119341: -10000.0*t_62_map_0 - t_mem_62 + task_total_memory_router_router0_task62 >= -10000.0\n", - "_C119342: -t63_end_ + t63_start - 10000.0*t_63_map_0 - t_send_63 + task_total_delay_router_router0_task63 >= -10000.0\n", - "_C119343: -10000.0*t_63_map_0 - t_mem_63 + task_total_memory_router_router0_task63 >= -10000.0\n", - "_C119344: -t64_end_ + t64_start - 10000.0*t_64_map_0 - t_send_64 + task_total_delay_router_router0_task64 >= -10000.0\n", - "_C119345: -10000.0*t_64_map_0 - t_mem_64 + task_total_memory_router_router0_task64 >= -10000.0\n", - "_C119346: -t65_end_ + t65_start - 10000.0*t_65_map_0 - t_send_65 + task_total_delay_router_router0_task65 >= -10000.0\n", - "_C119347: -10000.0*t_65_map_0 - t_mem_65 + task_total_memory_router_router0_task65 >= -10000.0\n", - "_C119348: -t66_end_ + t66_start - 10000.0*t_66_map_0 - t_send_66 + task_total_delay_router_router0_task66 >= -10000.0\n", - "_C119349: -10000.0*t_66_map_0 - t_mem_66 + task_total_memory_router_router0_task66 >= -10000.0\n", - "_C119350: -t67_end_ + t67_start - 10000.0*t_67_map_0 - t_send_67 + task_total_delay_router_router0_task67 >= -10000.0\n", - "_C119351: -10000.0*t_67_map_0 - t_mem_67 + task_total_memory_router_router0_task67 >= -10000.0\n", - "_C119352: -t68_end_ + t68_start - 10000.0*t_68_map_0 - t_send_68 + task_total_delay_router_router0_task68 >= -10000.0\n", - "_C119353: -10000.0*t_68_map_0 - t_mem_68 + task_total_memory_router_router0_task68 >= -10000.0\n", - "_C119354: -t69_end_ + t69_start - 10000.0*t_69_map_0 - t_send_69 + task_total_delay_router_router0_task69 >= -10000.0\n", - "_C119355: -10000.0*t_69_map_0 - t_mem_69 + task_total_memory_router_router0_task69 >= -10000.0\n", + "_C118915: 250000.0*same_68_69 + t_send_68 >= 2.0\n", + "_C118916: 250000.0*order_choose_3_4 + 250000.0*same_3_4 + t3_end_ - t4_start <= 500000.0\n", + "_C118917: -250000.0*order_choose_3_4 + 250000.0*same_3_4 - t3_start + t4_end_ <= 250000.0\n", + "_C118918: 250000.0*order_choose_6_8 + 250000.0*same_6_8 + t6_end_ - t8_start <= 500000.0\n", + "_C118919: -250000.0*order_choose_6_8 + 250000.0*same_6_8 - t6_start + t8_end_ <= 250000.0\n", + "_C118920: 250000.0*order_choose_6_9 + 250000.0*same_6_9 + t6_end_ - t9_start <= 500000.0\n", + "_C118921: -250000.0*order_choose_6_9 + 250000.0*same_6_9 - t6_start + t9_end_ <= 250000.0\n", + "_C118922: 250000.0*order_choose_6_10 + 250000.0*same_6_10 - t10_start + t6_end_ <= 500000.0\n", + "_C118923: -250000.0*order_choose_6_10 + 250000.0*same_6_10 + t10_end_ - t6_start <= 250000.0\n", + "_C118924: 250000.0*order_choose_6_11 + 250000.0*same_6_11 - t11_start + t6_end_ <= 500000.0\n", + "_C118925: -250000.0*order_choose_6_11 + 250000.0*same_6_11 + t11_end_ - t6_start <= 250000.0\n", + "_C118926: 250000.0*order_choose_7_8 + 250000.0*same_7_8 + t7_end_ - t8_start <= 500000.0\n", + "_C118927: -250000.0*order_choose_7_8 + 250000.0*same_7_8 - t7_start + t8_end_ <= 250000.0\n", + "_C118928: 250000.0*order_choose_7_9 + 250000.0*same_7_9 + t7_end_ - t9_start <= 500000.0\n", + "_C118929: -250000.0*order_choose_7_9 + 250000.0*same_7_9 - t7_start + t9_end_ <= 250000.0\n", + "_C118930: 250000.0*order_choose_7_10 + 250000.0*same_7_10 - t10_start + t7_end_ <= 500000.0\n", + "_C118931: -250000.0*order_choose_7_10 + 250000.0*same_7_10 + t10_end_ - t7_start <= 250000.0\n", + "_C118932: 250000.0*order_choose_7_11 + 250000.0*same_7_11 - t11_start + t7_end_ <= 500000.0\n", + "_C118933: -250000.0*order_choose_7_11 + 250000.0*same_7_11 + t11_end_ - t7_start <= 250000.0\n", + "_C118934: 250000.0*order_choose_13_14 + 250000.0*same_13_14 + t13_end_ - t14_start <= 500000.0\n", + "_C118935: -250000.0*order_choose_13_14 + 250000.0*same_13_14 - t13_start + t14_end_ <= 250000.0\n", + "_C118936: 250000.0*order_choose_16_17 + 250000.0*same_16_17 + t16_end_ - t17_start <= 500000.0\n", + "_C118937: -250000.0*order_choose_16_17 + 250000.0*same_16_17 - t16_start + t17_end_ <= 250000.0\n", + "_C118938: 250000.0*order_choose_16_18 + 250000.0*same_16_18 + t16_end_ - t18_start <= 500000.0\n", + "_C118939: -250000.0*order_choose_16_18 + 250000.0*same_16_18 - t16_start + t18_end_ <= 250000.0\n", + "_C118940: 250000.0*order_choose_16_19 + 250000.0*same_16_19 + t16_end_ - t19_start <= 500000.0\n", + "_C118941: -250000.0*order_choose_16_19 + 250000.0*same_16_19 - t16_start + t19_end_ <= 250000.0\n", + "_C118942: 250000.0*order_choose_16_20 + 250000.0*same_16_20 + t16_end_ - t20_start <= 500000.0\n", + "_C118943: -250000.0*order_choose_16_20 + 250000.0*same_16_20 - t16_start + t20_end_ <= 250000.0\n", + "_C118944: 250000.0*order_choose_16_21 + 250000.0*same_16_21 + t16_end_ - t21_start <= 500000.0\n", + "_C118945: -250000.0*order_choose_16_21 + 250000.0*same_16_21 - t16_start + t21_end_ <= 250000.0\n", + "_C118946: 250000.0*order_choose_16_22 + 250000.0*same_16_22 + t16_end_ - t22_start <= 500000.0\n", + "_C118947: -250000.0*order_choose_16_22 + 250000.0*same_16_22 - t16_start + t22_end_ <= 250000.0\n", + "_C118948: 250000.0*order_choose_16_23 + 250000.0*same_16_23 + t16_end_ - t23_start <= 500000.0\n", + "_C118949: -250000.0*order_choose_16_23 + 250000.0*same_16_23 - t16_start + t23_end_ <= 250000.0\n", + "_C118950: 250000.0*order_choose_17_19 + 250000.0*same_17_19 + t17_end_ - t19_start <= 500000.0\n", + "_C118951: -250000.0*order_choose_17_19 + 250000.0*same_17_19 - t17_start + t19_end_ <= 250000.0\n", + "_C118952: 250000.0*order_choose_17_20 + 250000.0*same_17_20 + t17_end_ - t20_start <= 500000.0\n", + "_C118953: -250000.0*order_choose_17_20 + 250000.0*same_17_20 - t17_start + t20_end_ <= 250000.0\n", + "_C118954: 250000.0*order_choose_17_21 + 250000.0*same_17_21 + t17_end_ - t21_start <= 500000.0\n", + "_C118955: -250000.0*order_choose_17_21 + 250000.0*same_17_21 - t17_start + t21_end_ <= 250000.0\n", + "_C118956: 250000.0*order_choose_17_22 + 250000.0*same_17_22 + t17_end_ - t22_start <= 500000.0\n", + "_C118957: -250000.0*order_choose_17_22 + 250000.0*same_17_22 - t17_start + t22_end_ <= 250000.0\n", + "_C118958: 250000.0*order_choose_17_23 + 250000.0*same_17_23 + t17_end_ - t23_start <= 500000.0\n", + "_C118959: -250000.0*order_choose_17_23 + 250000.0*same_17_23 - t17_start + t23_end_ <= 250000.0\n", + "_C118960: 250000.0*order_choose_18_19 + 250000.0*same_18_19 + t18_end_ - t19_start <= 500000.0\n", + "_C118961: -250000.0*order_choose_18_19 + 250000.0*same_18_19 - t18_start + t19_end_ <= 250000.0\n", + "_C118962: 250000.0*order_choose_18_20 + 250000.0*same_18_20 + t18_end_ - t20_start <= 500000.0\n", + "_C118963: -250000.0*order_choose_18_20 + 250000.0*same_18_20 - t18_start + t20_end_ <= 250000.0\n", + "_C118964: 250000.0*order_choose_18_21 + 250000.0*same_18_21 + t18_end_ - t21_start <= 500000.0\n", + "_C118965: -250000.0*order_choose_18_21 + 250000.0*same_18_21 - t18_start + t21_end_ <= 250000.0\n", + "_C118966: 250000.0*order_choose_18_22 + 250000.0*same_18_22 + t18_end_ - t22_start <= 500000.0\n", + "_C118967: -250000.0*order_choose_18_22 + 250000.0*same_18_22 - t18_start + t22_end_ <= 250000.0\n", + "_C118968: 250000.0*order_choose_18_23 + 250000.0*same_18_23 + t18_end_ - t23_start <= 500000.0\n", + "_C118969: -250000.0*order_choose_18_23 + 250000.0*same_18_23 - t18_start + t23_end_ <= 250000.0\n", + "_C118970: 250000.0*order_choose_19_22 + 250000.0*same_19_22 + t19_end_ - t22_start <= 500000.0\n", + "_C118971: -250000.0*order_choose_19_22 + 250000.0*same_19_22 - t19_start + t22_end_ <= 250000.0\n", + "_C118972: 250000.0*order_choose_19_23 + 250000.0*same_19_23 + t19_end_ - t23_start <= 500000.0\n", + "_C118973: -250000.0*order_choose_19_23 + 250000.0*same_19_23 - t19_start + t23_end_ <= 250000.0\n", + "_C118974: 250000.0*order_choose_20_22 + 250000.0*same_20_22 + t20_end_ - t22_start <= 500000.0\n", + "_C118975: -250000.0*order_choose_20_22 + 250000.0*same_20_22 - t20_start + t22_end_ <= 250000.0\n", + "_C118976: 250000.0*order_choose_20_23 + 250000.0*same_20_23 + t20_end_ - t23_start <= 500000.0\n", + "_C118977: -250000.0*order_choose_20_23 + 250000.0*same_20_23 - t20_start + t23_end_ <= 250000.0\n", + "_C118978: 250000.0*order_choose_21_22 + 250000.0*same_21_22 + t21_end_ - t22_start <= 500000.0\n", + "_C118979: -250000.0*order_choose_21_22 + 250000.0*same_21_22 - t21_start + t22_end_ <= 250000.0\n", + "_C118980: 250000.0*order_choose_21_23 + 250000.0*same_21_23 + t21_end_ - t23_start <= 500000.0\n", + "_C118981: -250000.0*order_choose_21_23 + 250000.0*same_21_23 - t21_start + t23_end_ <= 250000.0\n", + "_C118982: 250000.0*order_choose_25_26 + 250000.0*same_25_26 + t25_end_ - t26_start <= 500000.0\n", + "_C118983: -250000.0*order_choose_25_26 + 250000.0*same_25_26 - t25_start + t26_end_ <= 250000.0\n", + "_C118984: 250000.0*order_choose_25_27 + 250000.0*same_25_27 + t25_end_ - t27_start <= 500000.0\n", + "_C118985: -250000.0*order_choose_25_27 + 250000.0*same_25_27 - t25_start + t27_end_ <= 250000.0\n", + "_C118986: 250000.0*order_choose_25_28 + 250000.0*same_25_28 + t25_end_ - t28_start <= 500000.0\n", + "_C118987: -250000.0*order_choose_25_28 + 250000.0*same_25_28 - t25_start + t28_end_ <= 250000.0\n", + "_C118988: 250000.0*order_choose_25_29 + 250000.0*same_25_29 + t25_end_ - t29_start <= 500000.0\n", + "_C118989: -250000.0*order_choose_25_29 + 250000.0*same_25_29 - t25_start + t29_end_ <= 250000.0\n", + "_C118990: 250000.0*order_choose_25_30 + 250000.0*same_25_30 + t25_end_ - t30_start <= 500000.0\n", + "_C118991: -250000.0*order_choose_25_30 + 250000.0*same_25_30 - t25_start + t30_end_ <= 250000.0\n", + "_C118992: 250000.0*order_choose_25_31 + 250000.0*same_25_31 + t25_end_ - t31_start <= 500000.0\n", + "_C118993: -250000.0*order_choose_25_31 + 250000.0*same_25_31 - t25_start + t31_end_ <= 250000.0\n", + "_C118994: 250000.0*order_choose_25_32 + 250000.0*same_25_32 + t25_end_ - t32_start <= 500000.0\n", + "_C118995: -250000.0*order_choose_25_32 + 250000.0*same_25_32 - t25_start + t32_end_ <= 250000.0\n", + "_C118996: 250000.0*order_choose_26_28 + 250000.0*same_26_28 + t26_end_ - t28_start <= 500000.0\n", + "_C118997: -250000.0*order_choose_26_28 + 250000.0*same_26_28 - t26_start + t28_end_ <= 250000.0\n", + "_C118998: 250000.0*order_choose_26_29 + 250000.0*same_26_29 + t26_end_ - t29_start <= 500000.0\n", + "_C118999: -250000.0*order_choose_26_29 + 250000.0*same_26_29 - t26_start + t29_end_ <= 250000.0\n", + "_C119000: 250000.0*order_choose_26_30 + 250000.0*same_26_30 + t26_end_ - t30_start <= 500000.0\n", + "_C119001: -250000.0*order_choose_26_30 + 250000.0*same_26_30 - t26_start + t30_end_ <= 250000.0\n", + "_C119002: 250000.0*order_choose_26_31 + 250000.0*same_26_31 + t26_end_ - t31_start <= 500000.0\n", + "_C119003: -250000.0*order_choose_26_31 + 250000.0*same_26_31 - t26_start + t31_end_ <= 250000.0\n", + "_C119004: 250000.0*order_choose_26_32 + 250000.0*same_26_32 + t26_end_ - t32_start <= 500000.0\n", + "_C119005: -250000.0*order_choose_26_32 + 250000.0*same_26_32 - t26_start + t32_end_ <= 250000.0\n", + "_C119006: 250000.0*order_choose_27_28 + 250000.0*same_27_28 + t27_end_ - t28_start <= 500000.0\n", + "_C119007: -250000.0*order_choose_27_28 + 250000.0*same_27_28 - t27_start + t28_end_ <= 250000.0\n", + "_C119008: 250000.0*order_choose_27_29 + 250000.0*same_27_29 + t27_end_ - t29_start <= 500000.0\n", + "_C119009: -250000.0*order_choose_27_29 + 250000.0*same_27_29 - t27_start + t29_end_ <= 250000.0\n", + "_C119010: 250000.0*order_choose_27_30 + 250000.0*same_27_30 + t27_end_ - t30_start <= 500000.0\n", + "_C119011: -250000.0*order_choose_27_30 + 250000.0*same_27_30 - t27_start + t30_end_ <= 250000.0\n", + "_C119012: 250000.0*order_choose_27_31 + 250000.0*same_27_31 + t27_end_ - t31_start <= 500000.0\n", + "_C119013: -250000.0*order_choose_27_31 + 250000.0*same_27_31 - t27_start + t31_end_ <= 250000.0\n", + "_C119014: 250000.0*order_choose_27_32 + 250000.0*same_27_32 + t27_end_ - t32_start <= 500000.0\n", + "_C119015: -250000.0*order_choose_27_32 + 250000.0*same_27_32 - t27_start + t32_end_ <= 250000.0\n", + "_C119016: 250000.0*order_choose_28_31 + 250000.0*same_28_31 + t28_end_ - t31_start <= 500000.0\n", + "_C119017: -250000.0*order_choose_28_31 + 250000.0*same_28_31 - t28_start + t31_end_ <= 250000.0\n", + "_C119018: 250000.0*order_choose_28_32 + 250000.0*same_28_32 + t28_end_ - t32_start <= 500000.0\n", + "_C119019: -250000.0*order_choose_28_32 + 250000.0*same_28_32 - t28_start + t32_end_ <= 250000.0\n", + "_C119020: 250000.0*order_choose_29_31 + 250000.0*same_29_31 + t29_end_ - t31_start <= 500000.0\n", + "_C119021: -250000.0*order_choose_29_31 + 250000.0*same_29_31 - t29_start + t31_end_ <= 250000.0\n", + "_C119022: 250000.0*order_choose_29_32 + 250000.0*same_29_32 + t29_end_ - t32_start <= 500000.0\n", + "_C119023: -250000.0*order_choose_29_32 + 250000.0*same_29_32 - t29_start + t32_end_ <= 250000.0\n", + "_C119024: 250000.0*order_choose_30_31 + 250000.0*same_30_31 + t30_end_ - t31_start <= 500000.0\n", + "_C119025: -250000.0*order_choose_30_31 + 250000.0*same_30_31 - t30_start + t31_end_ <= 250000.0\n", + "_C119026: 250000.0*order_choose_30_32 + 250000.0*same_30_32 + t30_end_ - t32_start <= 500000.0\n", + "_C119027: -250000.0*order_choose_30_32 + 250000.0*same_30_32 - t30_start + t32_end_ <= 250000.0\n", + "_C119028: 250000.0*order_choose_34_35 + 250000.0*same_34_35 + t34_end_ - t35_start <= 500000.0\n", + "_C119029: -250000.0*order_choose_34_35 + 250000.0*same_34_35 - t34_start + t35_end_ <= 250000.0\n", + "_C119030: 250000.0*order_choose_34_36 + 250000.0*same_34_36 + t34_end_ - t36_start <= 500000.0\n", + "_C119031: -250000.0*order_choose_34_36 + 250000.0*same_34_36 - t34_start + t36_end_ <= 250000.0\n", + "_C119032: 250000.0*order_choose_34_37 + 250000.0*same_34_37 + t34_end_ - t37_start <= 500000.0\n", + "_C119033: -250000.0*order_choose_34_37 + 250000.0*same_34_37 - t34_start + t37_end_ <= 250000.0\n", + "_C119034: 250000.0*order_choose_34_38 + 250000.0*same_34_38 + t34_end_ - t38_start <= 500000.0\n", + "_C119035: -250000.0*order_choose_34_38 + 250000.0*same_34_38 - t34_start + t38_end_ <= 250000.0\n", + "_C119036: 250000.0*order_choose_34_39 + 250000.0*same_34_39 + t34_end_ - t39_start <= 500000.0\n", + "_C119037: -250000.0*order_choose_34_39 + 250000.0*same_34_39 - t34_start + t39_end_ <= 250000.0\n", + "_C119038: 250000.0*order_choose_34_40 + 250000.0*same_34_40 + t34_end_ - t40_start <= 500000.0\n", + "_C119039: -250000.0*order_choose_34_40 + 250000.0*same_34_40 - t34_start + t40_end_ <= 250000.0\n", + "_C119040: 250000.0*order_choose_34_41 + 250000.0*same_34_41 + t34_end_ - t41_start <= 500000.0\n", + "_C119041: -250000.0*order_choose_34_41 + 250000.0*same_34_41 - t34_start + t41_end_ <= 250000.0\n", + "_C119042: 250000.0*order_choose_35_37 + 250000.0*same_35_37 + t35_end_ - t37_start <= 500000.0\n", + "_C119043: -250000.0*order_choose_35_37 + 250000.0*same_35_37 - t35_start + t37_end_ <= 250000.0\n", + "_C119044: 250000.0*order_choose_35_38 + 250000.0*same_35_38 + t35_end_ - t38_start <= 500000.0\n", + "_C119045: -250000.0*order_choose_35_38 + 250000.0*same_35_38 - t35_start + t38_end_ <= 250000.0\n", + "_C119046: 250000.0*order_choose_35_39 + 250000.0*same_35_39 + t35_end_ - t39_start <= 500000.0\n", + "_C119047: -250000.0*order_choose_35_39 + 250000.0*same_35_39 - t35_start + t39_end_ <= 250000.0\n", + "_C119048: 250000.0*order_choose_35_40 + 250000.0*same_35_40 + t35_end_ - t40_start <= 500000.0\n", + "_C119049: -250000.0*order_choose_35_40 + 250000.0*same_35_40 - t35_start + t40_end_ <= 250000.0\n", + "_C119050: 250000.0*order_choose_35_41 + 250000.0*same_35_41 + t35_end_ - t41_start <= 500000.0\n", + "_C119051: -250000.0*order_choose_35_41 + 250000.0*same_35_41 - t35_start + t41_end_ <= 250000.0\n", + "_C119052: 250000.0*order_choose_36_37 + 250000.0*same_36_37 + t36_end_ - t37_start <= 500000.0\n", + "_C119053: -250000.0*order_choose_36_37 + 250000.0*same_36_37 - t36_start + t37_end_ <= 250000.0\n", + "_C119054: 250000.0*order_choose_36_38 + 250000.0*same_36_38 + t36_end_ - t38_start <= 500000.0\n", + "_C119055: -250000.0*order_choose_36_38 + 250000.0*same_36_38 - t36_start + t38_end_ <= 250000.0\n", + "_C119056: 250000.0*order_choose_36_39 + 250000.0*same_36_39 + t36_end_ - t39_start <= 500000.0\n", + "_C119057: -250000.0*order_choose_36_39 + 250000.0*same_36_39 - t36_start + t39_end_ <= 250000.0\n", + "_C119058: 250000.0*order_choose_36_40 + 250000.0*same_36_40 + t36_end_ - t40_start <= 500000.0\n", + "_C119059: -250000.0*order_choose_36_40 + 250000.0*same_36_40 - t36_start + t40_end_ <= 250000.0\n", + "_C119060: 250000.0*order_choose_36_41 + 250000.0*same_36_41 + t36_end_ - t41_start <= 500000.0\n", + "_C119061: -250000.0*order_choose_36_41 + 250000.0*same_36_41 - t36_start + t41_end_ <= 250000.0\n", + "_C119062: 250000.0*order_choose_37_40 + 250000.0*same_37_40 + t37_end_ - t40_start <= 500000.0\n", + "_C119063: -250000.0*order_choose_37_40 + 250000.0*same_37_40 - t37_start + t40_end_ <= 250000.0\n", + "_C119064: 250000.0*order_choose_37_41 + 250000.0*same_37_41 + t37_end_ - t41_start <= 500000.0\n", + "_C119065: -250000.0*order_choose_37_41 + 250000.0*same_37_41 - t37_start + t41_end_ <= 250000.0\n", + "_C119066: 250000.0*order_choose_38_40 + 250000.0*same_38_40 + t38_end_ - t40_start <= 500000.0\n", + "_C119067: -250000.0*order_choose_38_40 + 250000.0*same_38_40 - t38_start + t40_end_ <= 250000.0\n", + "_C119068: 250000.0*order_choose_38_41 + 250000.0*same_38_41 + t38_end_ - t41_start <= 500000.0\n", + "_C119069: -250000.0*order_choose_38_41 + 250000.0*same_38_41 - t38_start + t41_end_ <= 250000.0\n", + "_C119070: 250000.0*order_choose_39_40 + 250000.0*same_39_40 + t39_end_ - t40_start <= 500000.0\n", + "_C119071: -250000.0*order_choose_39_40 + 250000.0*same_39_40 - t39_start + t40_end_ <= 250000.0\n", + "_C119072: 250000.0*order_choose_39_41 + 250000.0*same_39_41 + t39_end_ - t41_start <= 500000.0\n", + "_C119073: -250000.0*order_choose_39_41 + 250000.0*same_39_41 - t39_start + t41_end_ <= 250000.0\n", + "_C119074: 250000.0*order_choose_43_44 + 250000.0*same_43_44 + t43_end_ - t44_start <= 500000.0\n", + "_C119075: -250000.0*order_choose_43_44 + 250000.0*same_43_44 - t43_start + t44_end_ <= 250000.0\n", + "_C119076: 250000.0*order_choose_43_45 + 250000.0*same_43_45 + t43_end_ - t45_start <= 500000.0\n", + "_C119077: -250000.0*order_choose_43_45 + 250000.0*same_43_45 - t43_start + t45_end_ <= 250000.0\n", + "_C119078: 250000.0*order_choose_43_46 + 250000.0*same_43_46 + t43_end_ - t46_start <= 500000.0\n", + "_C119079: -250000.0*order_choose_43_46 + 250000.0*same_43_46 - t43_start + t46_end_ <= 250000.0\n", + "_C119080: 250000.0*order_choose_43_47 + 250000.0*same_43_47 + t43_end_ - t47_start <= 500000.0\n", + "_C119081: -250000.0*order_choose_43_47 + 250000.0*same_43_47 - t43_start + t47_end_ <= 250000.0\n", + "_C119082: 250000.0*order_choose_43_48 + 250000.0*same_43_48 + t43_end_ - t48_start <= 500000.0\n", + "_C119083: -250000.0*order_choose_43_48 + 250000.0*same_43_48 - t43_start + t48_end_ <= 250000.0\n", + "_C119084: 250000.0*order_choose_43_49 + 250000.0*same_43_49 + t43_end_ - t49_start <= 500000.0\n", + "_C119085: -250000.0*order_choose_43_49 + 250000.0*same_43_49 - t43_start + t49_end_ <= 250000.0\n", + "_C119086: 250000.0*order_choose_43_50 + 250000.0*same_43_50 + t43_end_ - t50_start <= 500000.0\n", + "_C119087: -250000.0*order_choose_43_50 + 250000.0*same_43_50 - t43_start + t50_end_ <= 250000.0\n", + "_C119088: 250000.0*order_choose_44_46 + 250000.0*same_44_46 + t44_end_ - t46_start <= 500000.0\n", + "_C119089: -250000.0*order_choose_44_46 + 250000.0*same_44_46 - t44_start + t46_end_ <= 250000.0\n", + "_C119090: 250000.0*order_choose_44_47 + 250000.0*same_44_47 + t44_end_ - t47_start <= 500000.0\n", + "_C119091: -250000.0*order_choose_44_47 + 250000.0*same_44_47 - t44_start + t47_end_ <= 250000.0\n", + "_C119092: 250000.0*order_choose_44_48 + 250000.0*same_44_48 + t44_end_ - t48_start <= 500000.0\n", + "_C119093: -250000.0*order_choose_44_48 + 250000.0*same_44_48 - t44_start + t48_end_ <= 250000.0\n", + "_C119094: 250000.0*order_choose_44_49 + 250000.0*same_44_49 + t44_end_ - t49_start <= 500000.0\n", + "_C119095: -250000.0*order_choose_44_49 + 250000.0*same_44_49 - t44_start + t49_end_ <= 250000.0\n", + "_C119096: 250000.0*order_choose_44_50 + 250000.0*same_44_50 + t44_end_ - t50_start <= 500000.0\n", + "_C119097: -250000.0*order_choose_44_50 + 250000.0*same_44_50 - t44_start + t50_end_ <= 250000.0\n", + "_C119098: 250000.0*order_choose_45_46 + 250000.0*same_45_46 + t45_end_ - t46_start <= 500000.0\n", + "_C119099: -250000.0*order_choose_45_46 + 250000.0*same_45_46 - t45_start + t46_end_ <= 250000.0\n", + "_C119100: 250000.0*order_choose_45_47 + 250000.0*same_45_47 + t45_end_ - t47_start <= 500000.0\n", + "_C119101: -250000.0*order_choose_45_47 + 250000.0*same_45_47 - t45_start + t47_end_ <= 250000.0\n", + "_C119102: 250000.0*order_choose_45_48 + 250000.0*same_45_48 + t45_end_ - t48_start <= 500000.0\n", + "_C119103: -250000.0*order_choose_45_48 + 250000.0*same_45_48 - t45_start + t48_end_ <= 250000.0\n", + "_C119104: 250000.0*order_choose_45_49 + 250000.0*same_45_49 + t45_end_ - t49_start <= 500000.0\n", + "_C119105: -250000.0*order_choose_45_49 + 250000.0*same_45_49 - t45_start + t49_end_ <= 250000.0\n", + "_C119106: 250000.0*order_choose_45_50 + 250000.0*same_45_50 + t45_end_ - t50_start <= 500000.0\n", + "_C119107: -250000.0*order_choose_45_50 + 250000.0*same_45_50 - t45_start + t50_end_ <= 250000.0\n", + "_C119108: 250000.0*order_choose_46_49 + 250000.0*same_46_49 + t46_end_ - t49_start <= 500000.0\n", + "_C119109: -250000.0*order_choose_46_49 + 250000.0*same_46_49 - t46_start + t49_end_ <= 250000.0\n", + "_C119110: 250000.0*order_choose_46_50 + 250000.0*same_46_50 + t46_end_ - t50_start <= 500000.0\n", + "_C119111: -250000.0*order_choose_46_50 + 250000.0*same_46_50 - t46_start + t50_end_ <= 250000.0\n", + "_C119112: 250000.0*order_choose_47_49 + 250000.0*same_47_49 + t47_end_ - t49_start <= 500000.0\n", + "_C119113: -250000.0*order_choose_47_49 + 250000.0*same_47_49 - t47_start + t49_end_ <= 250000.0\n", + "_C119114: 250000.0*order_choose_47_50 + 250000.0*same_47_50 + t47_end_ - t50_start <= 500000.0\n", + "_C119115: -250000.0*order_choose_47_50 + 250000.0*same_47_50 - t47_start + t50_end_ <= 250000.0\n", + "_C119116: 250000.0*order_choose_48_49 + 250000.0*same_48_49 + t48_end_ - t49_start <= 500000.0\n", + "_C119117: -250000.0*order_choose_48_49 + 250000.0*same_48_49 - t48_start + t49_end_ <= 250000.0\n", + "_C119118: 250000.0*order_choose_48_50 + 250000.0*same_48_50 + t48_end_ - t50_start <= 500000.0\n", + "_C119119: -250000.0*order_choose_48_50 + 250000.0*same_48_50 - t48_start + t50_end_ <= 250000.0\n", + "_C119120: 250000.0*order_choose_52_53 + 250000.0*same_52_53 + t52_end_ - t53_start <= 500000.0\n", + "_C119121: -250000.0*order_choose_52_53 + 250000.0*same_52_53 - t52_start + t53_end_ <= 250000.0\n", + "_C119122: 250000.0*order_choose_52_54 + 250000.0*same_52_54 + t52_end_ - t54_start <= 500000.0\n", + "_C119123: -250000.0*order_choose_52_54 + 250000.0*same_52_54 - t52_start + t54_end_ <= 250000.0\n", + "_C119124: 250000.0*order_choose_52_55 + 250000.0*same_52_55 + t52_end_ - t55_start <= 500000.0\n", + "_C119125: -250000.0*order_choose_52_55 + 250000.0*same_52_55 - t52_start + t55_end_ <= 250000.0\n", + "_C119126: 250000.0*order_choose_52_56 + 250000.0*same_52_56 + t52_end_ - t56_start <= 500000.0\n", + "_C119127: -250000.0*order_choose_52_56 + 250000.0*same_52_56 - t52_start + t56_end_ <= 250000.0\n", + "_C119128: 250000.0*order_choose_53_56 + 250000.0*same_53_56 + t53_end_ - t56_start <= 500000.0\n", + "_C119129: -250000.0*order_choose_53_56 + 250000.0*same_53_56 - t53_start + t56_end_ <= 250000.0\n", + "_C119130: 250000.0*order_choose_54_56 + 250000.0*same_54_56 + t54_end_ - t56_start <= 500000.0\n", + "_C119131: -250000.0*order_choose_54_56 + 250000.0*same_54_56 - t54_start + t56_end_ <= 250000.0\n", + "_C119132: 250000.0*order_choose_55_56 + 250000.0*same_55_56 + t55_end_ - t56_start <= 500000.0\n", + "_C119133: -250000.0*order_choose_55_56 + 250000.0*same_55_56 - t55_start + t56_end_ <= 250000.0\n", + "_C119134: 250000.0*order_choose_58_59 + 250000.0*same_58_59 + t58_end_ - t59_start <= 500000.0\n", + "_C119135: -250000.0*order_choose_58_59 + 250000.0*same_58_59 - t58_start + t59_end_ <= 250000.0\n", + "_C119136: 250000.0*order_choose_58_60 + 250000.0*same_58_60 + t58_end_ - t60_start <= 500000.0\n", + "_C119137: -250000.0*order_choose_58_60 + 250000.0*same_58_60 - t58_start + t60_end_ <= 250000.0\n", + "_C119138: 250000.0*order_choose_58_61 + 250000.0*same_58_61 + t58_end_ - t61_start <= 500000.0\n", + "_C119139: -250000.0*order_choose_58_61 + 250000.0*same_58_61 - t58_start + t61_end_ <= 250000.0\n", + "_C119140: 250000.0*order_choose_58_62 + 250000.0*same_58_62 + t58_end_ - t62_start <= 500000.0\n", + "_C119141: -250000.0*order_choose_58_62 + 250000.0*same_58_62 - t58_start + t62_end_ <= 250000.0\n", + "_C119142: 250000.0*order_choose_58_63 + 250000.0*same_58_63 + t58_end_ - t63_start <= 500000.0\n", + "_C119143: -250000.0*order_choose_58_63 + 250000.0*same_58_63 - t58_start + t63_end_ <= 250000.0\n", + "_C119144: 250000.0*order_choose_58_64 + 250000.0*same_58_64 + t58_end_ - t64_start <= 500000.0\n", + "_C119145: -250000.0*order_choose_58_64 + 250000.0*same_58_64 - t58_start + t64_end_ <= 250000.0\n", + "_C119146: 250000.0*order_choose_58_65 + 250000.0*same_58_65 + t58_end_ - t65_start <= 500000.0\n", + "_C119147: -250000.0*order_choose_58_65 + 250000.0*same_58_65 - t58_start + t65_end_ <= 250000.0\n", + "_C119148: 250000.0*order_choose_58_66 + 250000.0*same_58_66 + t58_end_ - t66_start <= 500000.0\n", + "_C119149: -250000.0*order_choose_58_66 + 250000.0*same_58_66 - t58_start + t66_end_ <= 250000.0\n", + "_C119150: 250000.0*order_choose_58_67 + 250000.0*same_58_67 + t58_end_ - t67_start <= 500000.0\n", + "_C119151: -250000.0*order_choose_58_67 + 250000.0*same_58_67 - t58_start + t67_end_ <= 250000.0\n", + "_C119152: 250000.0*order_choose_58_68 + 250000.0*same_58_68 + t58_end_ - t68_start <= 500000.0\n", + "_C119153: -250000.0*order_choose_58_68 + 250000.0*same_58_68 - t58_start + t68_end_ <= 250000.0\n", + "_C119154: 250000.0*order_choose_59_62 + 250000.0*same_59_62 + t59_end_ - t62_start <= 500000.0\n", + "_C119155: -250000.0*order_choose_59_62 + 250000.0*same_59_62 - t59_start + t62_end_ <= 250000.0\n", + "_C119156: 250000.0*order_choose_59_63 + 250000.0*same_59_63 + t59_end_ - t63_start <= 500000.0\n", + "_C119157: -250000.0*order_choose_59_63 + 250000.0*same_59_63 - t59_start + t63_end_ <= 250000.0\n", + "_C119158: 250000.0*order_choose_59_64 + 250000.0*same_59_64 + t59_end_ - t64_start <= 500000.0\n", + "_C119159: -250000.0*order_choose_59_64 + 250000.0*same_59_64 - t59_start + t64_end_ <= 250000.0\n", + "_C119160: 250000.0*order_choose_59_65 + 250000.0*same_59_65 + t59_end_ - t65_start <= 500000.0\n", + "_C119161: -250000.0*order_choose_59_65 + 250000.0*same_59_65 - t59_start + t65_end_ <= 250000.0\n", + "_C119162: 250000.0*order_choose_59_66 + 250000.0*same_59_66 + t59_end_ - t66_start <= 500000.0\n", + "_C119163: -250000.0*order_choose_59_66 + 250000.0*same_59_66 - t59_start + t66_end_ <= 250000.0\n", + "_C119164: 250000.0*order_choose_59_67 + 250000.0*same_59_67 + t59_end_ - t67_start <= 500000.0\n", + "_C119165: -250000.0*order_choose_59_67 + 250000.0*same_59_67 - t59_start + t67_end_ <= 250000.0\n", + "_C119166: 250000.0*order_choose_59_68 + 250000.0*same_59_68 + t59_end_ - t68_start <= 500000.0\n", + "_C119167: -250000.0*order_choose_59_68 + 250000.0*same_59_68 - t59_start + t68_end_ <= 250000.0\n", + "_C119168: 250000.0*order_choose_60_62 + 250000.0*same_60_62 + t60_end_ - t62_start <= 500000.0\n", + "_C119169: -250000.0*order_choose_60_62 + 250000.0*same_60_62 - t60_start + t62_end_ <= 250000.0\n", + "_C119170: 250000.0*order_choose_60_63 + 250000.0*same_60_63 + t60_end_ - t63_start <= 500000.0\n", + "_C119171: -250000.0*order_choose_60_63 + 250000.0*same_60_63 - t60_start + t63_end_ <= 250000.0\n", + "_C119172: 250000.0*order_choose_60_64 + 250000.0*same_60_64 + t60_end_ - t64_start <= 500000.0\n", + "_C119173: -250000.0*order_choose_60_64 + 250000.0*same_60_64 - t60_start + t64_end_ <= 250000.0\n", + "_C119174: 250000.0*order_choose_60_65 + 250000.0*same_60_65 + t60_end_ - t65_start <= 500000.0\n", + "_C119175: -250000.0*order_choose_60_65 + 250000.0*same_60_65 - t60_start + t65_end_ <= 250000.0\n", + "_C119176: 250000.0*order_choose_60_66 + 250000.0*same_60_66 + t60_end_ - t66_start <= 500000.0\n", + "_C119177: -250000.0*order_choose_60_66 + 250000.0*same_60_66 - t60_start + t66_end_ <= 250000.0\n", + "_C119178: 250000.0*order_choose_60_67 + 250000.0*same_60_67 + t60_end_ - t67_start <= 500000.0\n", + "_C119179: -250000.0*order_choose_60_67 + 250000.0*same_60_67 - t60_start + t67_end_ <= 250000.0\n", + "_C119180: 250000.0*order_choose_60_68 + 250000.0*same_60_68 + t60_end_ - t68_start <= 500000.0\n", + "_C119181: -250000.0*order_choose_60_68 + 250000.0*same_60_68 - t60_start + t68_end_ <= 250000.0\n", + "_C119182: 250000.0*order_choose_61_62 + 250000.0*same_61_62 + t61_end_ - t62_start <= 500000.0\n", + "_C119183: -250000.0*order_choose_61_62 + 250000.0*same_61_62 - t61_start + t62_end_ <= 250000.0\n", + "_C119184: 250000.0*order_choose_61_63 + 250000.0*same_61_63 + t61_end_ - t63_start <= 500000.0\n", + "_C119185: -250000.0*order_choose_61_63 + 250000.0*same_61_63 - t61_start + t63_end_ <= 250000.0\n", + "_C119186: 250000.0*order_choose_61_64 + 250000.0*same_61_64 + t61_end_ - t64_start <= 500000.0\n", + "_C119187: -250000.0*order_choose_61_64 + 250000.0*same_61_64 - t61_start + t64_end_ <= 250000.0\n", + "_C119188: 250000.0*order_choose_61_65 + 250000.0*same_61_65 + t61_end_ - t65_start <= 500000.0\n", + "_C119189: -250000.0*order_choose_61_65 + 250000.0*same_61_65 - t61_start + t65_end_ <= 250000.0\n", + "_C119190: 250000.0*order_choose_61_66 + 250000.0*same_61_66 + t61_end_ - t66_start <= 500000.0\n", + "_C119191: -250000.0*order_choose_61_66 + 250000.0*same_61_66 - t61_start + t66_end_ <= 250000.0\n", + "_C119192: 250000.0*order_choose_61_67 + 250000.0*same_61_67 + t61_end_ - t67_start <= 500000.0\n", + "_C119193: -250000.0*order_choose_61_67 + 250000.0*same_61_67 - t61_start + t67_end_ <= 250000.0\n", + "_C119194: 250000.0*order_choose_61_68 + 250000.0*same_61_68 + t61_end_ - t68_start <= 500000.0\n", + "_C119195: -250000.0*order_choose_61_68 + 250000.0*same_61_68 - t61_start + t68_end_ <= 250000.0\n", + "_C119196: 250000.0*order_choose_62_67 + 250000.0*same_62_67 + t62_end_ - t67_start <= 500000.0\n", + "_C119197: -250000.0*order_choose_62_67 + 250000.0*same_62_67 - t62_start + t67_end_ <= 250000.0\n", + "_C119198: 250000.0*order_choose_62_68 + 250000.0*same_62_68 + t62_end_ - t68_start <= 500000.0\n", + "_C119199: -250000.0*order_choose_62_68 + 250000.0*same_62_68 - t62_start + t68_end_ <= 250000.0\n", + "_C119200: 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t_send_66 + task_total_delay_router_router0_task66 >= -250000.0\n", + "_C119349: -250000.0*t_66_map_0 - t_mem_66 + task_total_memory_router_router0_task66 >= -250000.0\n", + "_C119350: -t67_end_ + t67_start - 250000.0*t_67_map_0 - t_send_67 + task_total_delay_router_router0_task67 >= -250000.0\n", + "_C119351: -250000.0*t_67_map_0 - t_mem_67 + task_total_memory_router_router0_task67 >= -250000.0\n", + "_C119352: -t68_end_ + t68_start - 250000.0*t_68_map_0 - t_send_68 + task_total_delay_router_router0_task68 >= -250000.0\n", + "_C119353: -250000.0*t_68_map_0 - t_mem_68 + task_total_memory_router_router0_task68 >= -250000.0\n", + "_C119354: -t69_end_ + t69_start - 250000.0*t_69_map_0 - t_send_69 + task_total_delay_router_router0_task69 >= -250000.0\n", + "_C119355: -250000.0*t_69_map_0 - t_mem_69 + task_total_memory_router_router0_task69 >= -250000.0\n", "_C119356: PE_mem_overflow0 - task_total_memory_router_router0_task0 - task_total_memory_router_router0_task1 - task_total_memory_router_router0_task10 - task_total_memory_router_router0_task11 - task_total_memory_router_router0_task12 - task_total_memory_router_router0_task13 - task_total_memory_router_router0_task14 - task_total_memory_router_router0_task15 - task_total_memory_router_router0_task16 - task_total_memory_router_router0_task17 - task_total_memory_router_router0_task18 - task_total_memory_router_router0_task19 - task_total_memory_router_router0_task2 - task_total_memory_router_router0_task20 - task_total_memory_router_router0_task21 - task_total_memory_router_router0_task22 - task_total_memory_router_router0_task23 - task_total_memory_router_router0_task24 - task_total_memory_router_router0_task25 - task_total_memory_router_router0_task26 - task_total_memory_router_router0_task27 - task_total_memory_router_router0_task28 - task_total_memory_router_router0_task29 - task_total_memory_router_router0_task3 - task_total_memory_router_router0_task30 - task_total_memory_router_router0_task31 - task_total_memory_router_router0_task32 - task_total_memory_router_router0_task33 - task_total_memory_router_router0_task34 - task_total_memory_router_router0_task35 - task_total_memory_router_router0_task36 - task_total_memory_router_router0_task37 - task_total_memory_router_router0_task38 - task_total_memory_router_router0_task39 - task_total_memory_router_router0_task4 - task_total_memory_router_router0_task40 - task_total_memory_router_router0_task41 - task_total_memory_router_router0_task42 - task_total_memory_router_router0_task43 - task_total_memory_router_router0_task44 - task_total_memory_router_router0_task45 - task_total_memory_router_router0_task46 - task_total_memory_router_router0_task47 - task_total_memory_router_router0_task48 - task_total_memory_router_router0_task49 - task_total_memory_router_router0_task5 - task_total_memory_router_router0_task50 - task_total_memory_router_router0_task51 - task_total_memory_router_router0_task52 - task_total_memory_router_router0_task53 - task_total_memory_router_router0_task54 - task_total_memory_router_router0_task55 - task_total_memory_router_router0_task56 - task_total_memory_router_router0_task57 - task_total_memory_router_router0_task58 - task_total_memory_router_router0_task59 - task_total_memory_router_router0_task6 - task_total_memory_router_router0_task60 - task_total_memory_router_router0_task61 - task_total_memory_router_router0_task62 - task_total_memory_router_router0_task63 - task_total_memory_router_router0_task64 - task_total_memory_router_router0_task65 - task_total_memory_router_router0_task66 - task_total_memory_router_router0_task67 - task_total_memory_router_router0_task68 - task_total_memory_router_router0_task69 - task_total_memory_router_router0_task7 - task_total_memory_router_router0_task8 - task_total_memory_router_router0_task9 >= -0.0\n", "_C119357: PE0_total_delay - task_total_delay_router_router0_task0 - task_total_delay_router_router0_task1 - task_total_delay_router_router0_task10 - task_total_delay_router_router0_task11 - task_total_delay_router_router0_task12 - task_total_delay_router_router0_task13 - task_total_delay_router_router0_task14 - task_total_delay_router_router0_task15 - task_total_delay_router_router0_task16 - task_total_delay_router_router0_task17 - task_total_delay_router_router0_task18 - task_total_delay_router_router0_task19 - task_total_delay_router_router0_task2 - task_total_delay_router_router0_task20 - task_total_delay_router_router0_task21 - task_total_delay_router_router0_task22 - task_total_delay_router_router0_task23 - task_total_delay_router_router0_task24 - task_total_delay_router_router0_task25 - task_total_delay_router_router0_task26 - task_total_delay_router_router0_task27 - task_total_delay_router_router0_task28 - task_total_delay_router_router0_task29 - task_total_delay_router_router0_task3 - task_total_delay_router_router0_task30 - task_total_delay_router_router0_task31 - task_total_delay_router_router0_task32 - task_total_delay_router_router0_task33 - task_total_delay_router_router0_task34 - task_total_delay_router_router0_task35 - task_total_delay_router_router0_task36 - task_total_delay_router_router0_task37 - task_total_delay_router_router0_task38 - task_total_delay_router_router0_task39 - task_total_delay_router_router0_task4 - task_total_delay_router_router0_task40 - task_total_delay_router_router0_task41 - task_total_delay_router_router0_task42 - task_total_delay_router_router0_task43 - task_total_delay_router_router0_task44 - task_total_delay_router_router0_task45 - task_total_delay_router_router0_task46 - task_total_delay_router_router0_task47 - task_total_delay_router_router0_task48 - task_total_delay_router_router0_task49 - task_total_delay_router_router0_task5 - task_total_delay_router_router0_task50 - task_total_delay_router_router0_task51 - task_total_delay_router_router0_task52 - task_total_delay_router_router0_task53 - task_total_delay_router_router0_task54 - task_total_delay_router_router0_task55 - task_total_delay_router_router0_task56 - task_total_delay_router_router0_task57 - task_total_delay_router_router0_task58 - task_total_delay_router_router0_task59 - task_total_delay_router_router0_task6 - task_total_delay_router_router0_task60 - task_total_delay_router_router0_task61 - task_total_delay_router_router0_task62 - task_total_delay_router_router0_task63 - task_total_delay_router_router0_task64 - task_total_delay_router_router0_task65 - task_total_delay_router_router0_task66 - task_total_delay_router_router0_task67 - task_total_delay_router_router0_task68 - task_total_delay_router_router0_task69 - task_total_delay_router_router0_task7 - task_total_delay_router_router0_task8 - task_total_delay_router_router0_task9 >= -0.0\n", "_C119358: PE0_total_memory - task_total_memory_router_router0_task0 - task_total_memory_router_router0_task1 - task_total_memory_router_router0_task10 - task_total_memory_router_router0_task11 - task_total_memory_router_router0_task12 - task_total_memory_router_router0_task13 - task_total_memory_router_router0_task14 - task_total_memory_router_router0_task15 - task_total_memory_router_router0_task16 - task_total_memory_router_router0_task17 - task_total_memory_router_router0_task18 - task_total_memory_router_router0_task19 - task_total_memory_router_router0_task2 - task_total_memory_router_router0_task20 - task_total_memory_router_router0_task21 - task_total_memory_router_router0_task22 - task_total_memory_router_router0_task23 - task_total_memory_router_router0_task24 - task_total_memory_router_router0_task25 - task_total_memory_router_router0_task26 - task_total_memory_router_router0_task27 - task_total_memory_router_router0_task28 - task_total_memory_router_router0_task29 - task_total_memory_router_router0_task3 - task_total_memory_router_router0_task30 - task_total_memory_router_router0_task31 - task_total_memory_router_router0_task32 - task_total_memory_router_router0_task33 - task_total_memory_router_router0_task34 - task_total_memory_router_router0_task35 - task_total_memory_router_router0_task36 - task_total_memory_router_router0_task37 - task_total_memory_router_router0_task38 - task_total_memory_router_router0_task39 - task_total_memory_router_router0_task4 - task_total_memory_router_router0_task40 - task_total_memory_router_router0_task41 - task_total_memory_router_router0_task42 - task_total_memory_router_router0_task43 - task_total_memory_router_router0_task44 - task_total_memory_router_router0_task45 - task_total_memory_router_router0_task46 - task_total_memory_router_router0_task47 - task_total_memory_router_router0_task48 - task_total_memory_router_router0_task49 - task_total_memory_router_router0_task5 - task_total_memory_router_router0_task50 - task_total_memory_router_router0_task51 - task_total_memory_router_router0_task52 - task_total_memory_router_router0_task53 - task_total_memory_router_router0_task54 - task_total_memory_router_router0_task55 - task_total_memory_router_router0_task56 - task_total_memory_router_router0_task57 - task_total_memory_router_router0_task58 - task_total_memory_router_router0_task59 - task_total_memory_router_router0_task6 - task_total_memory_router_router0_task60 - task_total_memory_router_router0_task61 - task_total_memory_router_router0_task62 - task_total_memory_router_router0_task63 - task_total_memory_router_router0_task64 - task_total_memory_router_router0_task65 - task_total_memory_router_router0_task66 - task_total_memory_router_router0_task67 - task_total_memory_router_router0_task68 - task_total_memory_router_router0_task69 - task_total_memory_router_router0_task7 - task_total_memory_router_router0_task8 - task_total_memory_router_router0_task9 >= -0.0\n", "_C119359: -PE_mem_overflow0 + max_memory_overflow >= 0\n", - 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PE0_time_delay_max - t47_end_ - 250000.0*t_47_map_0 >= -250000.0\n", + "_C119455: PE0_time_delay_min - t47_start + 250000.0*t_47_map_0 <= 250000.0\n", + "_C119456: PE0_time_delay_max - t48_end_ - 250000.0*t_48_map_0 >= -250000.0\n", + "_C119457: PE0_time_delay_min - t48_start + 250000.0*t_48_map_0 <= 250000.0\n", + "_C119458: PE0_time_delay_max - t49_end_ - 250000.0*t_49_map_0 >= -250000.0\n", + "_C119459: PE0_time_delay_min - t49_start + 250000.0*t_49_map_0 <= 250000.0\n", + "_C119460: PE0_time_delay_max - t50_end_ - 250000.0*t_50_map_0 >= -250000.0\n", + "_C119461: PE0_time_delay_min - t50_start + 250000.0*t_50_map_0 <= 250000.0\n", + "_C119462: PE0_time_delay_max - t51_end_ - 250000.0*t_51_map_0 >= -250000.0\n", + "_C119463: PE0_time_delay_min - t51_start + 250000.0*t_51_map_0 <= 250000.0\n", + "_C119464: PE0_time_delay_max - t52_end_ - 250000.0*t_52_map_0 >= -250000.0\n", + "_C119465: PE0_time_delay_min - t52_start + 250000.0*t_52_map_0 <= 250000.0\n", + "_C119466: PE0_time_delay_max - t53_end_ - 250000.0*t_53_map_0 >= -250000.0\n", + "_C119467: PE0_time_delay_min - t53_start + 250000.0*t_53_map_0 <= 250000.0\n", + "_C119468: PE0_time_delay_max - t54_end_ - 250000.0*t_54_map_0 >= -250000.0\n", + "_C119469: PE0_time_delay_min - t54_start + 250000.0*t_54_map_0 <= 250000.0\n", + "_C119470: PE0_time_delay_max - t55_end_ - 250000.0*t_55_map_0 >= -250000.0\n", + "_C119471: PE0_time_delay_min - t55_start + 250000.0*t_55_map_0 <= 250000.0\n", + "_C119472: PE0_time_delay_max - t56_end_ - 250000.0*t_56_map_0 >= -250000.0\n", + "_C119473: PE0_time_delay_min - t56_start + 250000.0*t_56_map_0 <= 250000.0\n", + "_C119474: PE0_time_delay_max - t57_end_ - 250000.0*t_57_map_0 >= -250000.0\n", + "_C119475: PE0_time_delay_min - t57_start + 250000.0*t_57_map_0 <= 250000.0\n", + "_C119476: PE0_time_delay_max - t58_end_ - 250000.0*t_58_map_0 >= -250000.0\n", + "_C119477: PE0_time_delay_min - t58_start + 250000.0*t_58_map_0 <= 250000.0\n", + "_C119478: PE0_time_delay_max - t59_end_ - 250000.0*t_59_map_0 >= -250000.0\n", + "_C119479: PE0_time_delay_min - t59_start + 250000.0*t_59_map_0 <= 250000.0\n", + "_C119480: PE0_time_delay_max - t60_end_ - 250000.0*t_60_map_0 >= -250000.0\n", + "_C119481: PE0_time_delay_min - t60_start + 250000.0*t_60_map_0 <= 250000.0\n", + "_C119482: PE0_time_delay_max - t61_end_ - 250000.0*t_61_map_0 >= -250000.0\n", + "_C119483: PE0_time_delay_min - t61_start + 250000.0*t_61_map_0 <= 250000.0\n", + "_C119484: PE0_time_delay_max - t62_end_ - 250000.0*t_62_map_0 >= -250000.0\n", + "_C119485: PE0_time_delay_min - t62_start + 250000.0*t_62_map_0 <= 250000.0\n", + "_C119486: PE0_time_delay_max - t63_end_ - 250000.0*t_63_map_0 >= -250000.0\n", + "_C119487: PE0_time_delay_min - t63_start + 250000.0*t_63_map_0 <= 250000.0\n", + "_C119488: PE0_time_delay_max - t64_end_ - 250000.0*t_64_map_0 >= -250000.0\n", + "_C119489: PE0_time_delay_min - t64_start + 250000.0*t_64_map_0 <= 250000.0\n", + "_C119490: PE0_time_delay_max - t65_end_ - 250000.0*t_65_map_0 >= -250000.0\n", + "_C119491: PE0_time_delay_min - t65_start + 250000.0*t_65_map_0 <= 250000.0\n", + "_C119492: PE0_time_delay_max - t66_end_ - 250000.0*t_66_map_0 >= -250000.0\n", + "_C119493: PE0_time_delay_min - t66_start + 250000.0*t_66_map_0 <= 250000.0\n", + "_C119494: PE0_time_delay_max - t67_end_ - 250000.0*t_67_map_0 >= -250000.0\n", + "_C119495: PE0_time_delay_min - t67_start + 250000.0*t_67_map_0 <= 250000.0\n", + "_C119496: PE0_time_delay_max - t68_end_ - 250000.0*t_68_map_0 >= -250000.0\n", + "_C119497: PE0_time_delay_min - t68_start + 250000.0*t_68_map_0 <= 250000.0\n", + "_C119498: PE0_time_delay_max - t69_end_ - 250000.0*t_69_map_0 >= -250000.0\n", + "_C119499: PE0_time_delay_min - t69_start + 250000.0*t_69_map_0 <= 250000.0\n", "_C119500: -PE0_time_delay_max + PE0_time_delay_min + PE0_total_time_delay = 0\n", "_C119501: -PE0_total_time_delay + max_router_delay >= 0\n", - "_C119502: PE0_total_time_delay <= 280\n", - "_C119503: -t0_end_ + t0_start - 10000.0*t_0_map_1 - t_send_0 + task_total_delay_router_router1_task0 >= -10000.0\n", - "_C119504: -10000.0*t_0_map_1 - t_mem_0 + task_total_memory_router_router1_task0 >= -10000.0\n", - "_C119505: -t1_end_ + t1_start - 10000.0*t_1_map_1 - t_send_1 + task_total_delay_router_router1_task1 >= -10000.0\n", - "_C119506: -10000.0*t_1_map_1 - t_mem_1 + task_total_memory_router_router1_task1 >= -10000.0\n", - "_C119507: -t2_end_ + t2_start - 10000.0*t_2_map_1 - t_send_2 + task_total_delay_router_router1_task2 >= -10000.0\n", - "_C119508: -10000.0*t_2_map_1 - t_mem_2 + task_total_memory_router_router1_task2 >= -10000.0\n", - "_C119509: -t3_end_ + t3_start - 10000.0*t_3_map_1 - t_send_3 + task_total_delay_router_router1_task3 >= -10000.0\n", - "_C119510: -10000.0*t_3_map_1 - t_mem_3 + task_total_memory_router_router1_task3 >= -10000.0\n", - "_C119511: -t4_end_ + t4_start - 10000.0*t_4_map_1 - t_send_4 + task_total_delay_router_router1_task4 >= -10000.0\n", - "_C119512: -10000.0*t_4_map_1 - t_mem_4 + task_total_memory_router_router1_task4 >= -10000.0\n", - "_C119513: -t5_end_ + t5_start - 10000.0*t_5_map_1 - t_send_5 + task_total_delay_router_router1_task5 >= -10000.0\n", - "_C119514: -10000.0*t_5_map_1 - t_mem_5 + task_total_memory_router_router1_task5 >= -10000.0\n", - "_C119515: -t6_end_ + t6_start - 10000.0*t_6_map_1 - t_send_6 + task_total_delay_router_router1_task6 >= -10000.0\n", - "_C119516: -10000.0*t_6_map_1 - t_mem_6 + task_total_memory_router_router1_task6 >= -10000.0\n", - "_C119517: -t7_end_ + t7_start - 10000.0*t_7_map_1 - t_send_7 + task_total_delay_router_router1_task7 >= -10000.0\n", - "_C119518: -10000.0*t_7_map_1 - t_mem_7 + task_total_memory_router_router1_task7 >= -10000.0\n", - "_C119519: -t8_end_ + t8_start - 10000.0*t_8_map_1 - t_send_8 + task_total_delay_router_router1_task8 >= -10000.0\n", - "_C119520: -10000.0*t_8_map_1 - t_mem_8 + task_total_memory_router_router1_task8 >= -10000.0\n", - "_C119521: -t9_end_ + t9_start - 10000.0*t_9_map_1 - t_send_9 + task_total_delay_router_router1_task9 >= -10000.0\n", - "_C119522: -10000.0*t_9_map_1 - t_mem_9 + task_total_memory_router_router1_task9 >= -10000.0\n", - "_C119523: -t10_end_ + t10_start - 10000.0*t_10_map_1 - t_send_10 + task_total_delay_router_router1_task10 >= -10000.0\n", - "_C119524: -10000.0*t_10_map_1 - t_mem_10 + task_total_memory_router_router1_task10 >= -10000.0\n", - "_C119525: -t11_end_ + t11_start - 10000.0*t_11_map_1 - t_send_11 + task_total_delay_router_router1_task11 >= -10000.0\n", - "_C119526: -10000.0*t_11_map_1 - t_mem_11 + task_total_memory_router_router1_task11 >= -10000.0\n", - "_C119527: -t12_end_ + t12_start - 10000.0*t_12_map_1 - t_send_12 + task_total_delay_router_router1_task12 >= -10000.0\n", - "_C119528: -10000.0*t_12_map_1 - t_mem_12 + task_total_memory_router_router1_task12 >= -10000.0\n", - "_C119529: -t13_end_ + t13_start - 10000.0*t_13_map_1 - t_send_13 + task_total_delay_router_router1_task13 >= -10000.0\n", - "_C119530: -10000.0*t_13_map_1 - t_mem_13 + task_total_memory_router_router1_task13 >= -10000.0\n", - "_C119531: -t14_end_ + t14_start - 10000.0*t_14_map_1 - t_send_14 + task_total_delay_router_router1_task14 >= -10000.0\n", - "_C119532: -10000.0*t_14_map_1 - t_mem_14 + task_total_memory_router_router1_task14 >= -10000.0\n", - "_C119533: -t15_end_ + t15_start - 10000.0*t_15_map_1 - t_send_15 + task_total_delay_router_router1_task15 >= -10000.0\n", - "_C119534: -10000.0*t_15_map_1 - t_mem_15 + task_total_memory_router_router1_task15 >= -10000.0\n", - "_C119535: -t16_end_ + t16_start - 10000.0*t_16_map_1 - t_send_16 + task_total_delay_router_router1_task16 >= -10000.0\n", - "_C119536: -10000.0*t_16_map_1 - t_mem_16 + task_total_memory_router_router1_task16 >= -10000.0\n", - "_C119537: -t17_end_ + t17_start - 10000.0*t_17_map_1 - t_send_17 + task_total_delay_router_router1_task17 >= -10000.0\n", - "_C119538: -10000.0*t_17_map_1 - t_mem_17 + task_total_memory_router_router1_task17 >= -10000.0\n", - "_C119539: -t18_end_ + t18_start - 10000.0*t_18_map_1 - t_send_18 + task_total_delay_router_router1_task18 >= -10000.0\n", - "_C119540: -10000.0*t_18_map_1 - t_mem_18 + task_total_memory_router_router1_task18 >= -10000.0\n", - "_C119541: -t19_end_ + t19_start - 10000.0*t_19_map_1 - t_send_19 + task_total_delay_router_router1_task19 >= -10000.0\n", - "_C119542: -10000.0*t_19_map_1 - t_mem_19 + task_total_memory_router_router1_task19 >= -10000.0\n", - "_C119543: -t20_end_ + t20_start - 10000.0*t_20_map_1 - t_send_20 + task_total_delay_router_router1_task20 >= -10000.0\n", - "_C119544: -10000.0*t_20_map_1 - t_mem_20 + task_total_memory_router_router1_task20 >= -10000.0\n", - "_C119545: -t21_end_ + t21_start - 10000.0*t_21_map_1 - t_send_21 + task_total_delay_router_router1_task21 >= -10000.0\n", - "_C119546: -10000.0*t_21_map_1 - t_mem_21 + task_total_memory_router_router1_task21 >= -10000.0\n", - "_C119547: -t22_end_ + t22_start - 10000.0*t_22_map_1 - t_send_22 + task_total_delay_router_router1_task22 >= -10000.0\n", - "_C119548: -10000.0*t_22_map_1 - t_mem_22 + task_total_memory_router_router1_task22 >= -10000.0\n", - "_C119549: -t23_end_ + t23_start - 10000.0*t_23_map_1 - t_send_23 + task_total_delay_router_router1_task23 >= -10000.0\n", - "_C119550: -10000.0*t_23_map_1 - t_mem_23 + task_total_memory_router_router1_task23 >= -10000.0\n", - "_C119551: -t24_end_ + t24_start - 10000.0*t_24_map_1 - t_send_24 + task_total_delay_router_router1_task24 >= -10000.0\n", - "_C119552: -10000.0*t_24_map_1 - t_mem_24 + task_total_memory_router_router1_task24 >= -10000.0\n", - "_C119553: -t25_end_ + t25_start - 10000.0*t_25_map_1 - t_send_25 + task_total_delay_router_router1_task25 >= -10000.0\n", - "_C119554: -10000.0*t_25_map_1 - t_mem_25 + task_total_memory_router_router1_task25 >= -10000.0\n", - "_C119555: -t26_end_ + t26_start - 10000.0*t_26_map_1 - t_send_26 + task_total_delay_router_router1_task26 >= -10000.0\n", - "_C119556: -10000.0*t_26_map_1 - t_mem_26 + task_total_memory_router_router1_task26 >= -10000.0\n", - "_C119557: -t27_end_ + t27_start - 10000.0*t_27_map_1 - t_send_27 + task_total_delay_router_router1_task27 >= -10000.0\n", - "_C119558: -10000.0*t_27_map_1 - t_mem_27 + task_total_memory_router_router1_task27 >= -10000.0\n", - "_C119559: -t28_end_ + t28_start - 10000.0*t_28_map_1 - t_send_28 + task_total_delay_router_router1_task28 >= -10000.0\n", - "_C119560: -10000.0*t_28_map_1 - t_mem_28 + task_total_memory_router_router1_task28 >= -10000.0\n", - "_C119561: -t29_end_ + t29_start - 10000.0*t_29_map_1 - t_send_29 + task_total_delay_router_router1_task29 >= -10000.0\n", - "_C119562: -10000.0*t_29_map_1 - t_mem_29 + task_total_memory_router_router1_task29 >= -10000.0\n", - "_C119563: -t30_end_ + t30_start - 10000.0*t_30_map_1 - t_send_30 + task_total_delay_router_router1_task30 >= -10000.0\n", - "_C119564: -10000.0*t_30_map_1 - t_mem_30 + task_total_memory_router_router1_task30 >= -10000.0\n", - "_C119565: -t31_end_ + t31_start - 10000.0*t_31_map_1 - t_send_31 + task_total_delay_router_router1_task31 >= -10000.0\n", - "_C119566: -10000.0*t_31_map_1 - t_mem_31 + task_total_memory_router_router1_task31 >= -10000.0\n", - "_C119567: -t32_end_ + t32_start - 10000.0*t_32_map_1 - t_send_32 + task_total_delay_router_router1_task32 >= -10000.0\n", - "_C119568: -10000.0*t_32_map_1 - t_mem_32 + task_total_memory_router_router1_task32 >= -10000.0\n", - "_C119569: -t33_end_ + t33_start - 10000.0*t_33_map_1 - t_send_33 + task_total_delay_router_router1_task33 >= -10000.0\n", - "_C119570: -10000.0*t_33_map_1 - t_mem_33 + task_total_memory_router_router1_task33 >= -10000.0\n", - "_C119571: -t34_end_ + t34_start - 10000.0*t_34_map_1 - t_send_34 + task_total_delay_router_router1_task34 >= -10000.0\n", - "_C119572: -10000.0*t_34_map_1 - t_mem_34 + task_total_memory_router_router1_task34 >= -10000.0\n", - "_C119573: -t35_end_ + t35_start - 10000.0*t_35_map_1 - t_send_35 + task_total_delay_router_router1_task35 >= 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task_total_memory_router_router1_task39 >= -10000.0\n", - "_C119583: -t40_end_ + t40_start - 10000.0*t_40_map_1 - t_send_40 + task_total_delay_router_router1_task40 >= -10000.0\n", - "_C119584: -10000.0*t_40_map_1 - t_mem_40 + task_total_memory_router_router1_task40 >= -10000.0\n", - "_C119585: -t41_end_ + t41_start - 10000.0*t_41_map_1 - t_send_41 + task_total_delay_router_router1_task41 >= -10000.0\n", - "_C119586: -10000.0*t_41_map_1 - t_mem_41 + task_total_memory_router_router1_task41 >= -10000.0\n", - "_C119587: -t42_end_ + t42_start - 10000.0*t_42_map_1 - t_send_42 + task_total_delay_router_router1_task42 >= -10000.0\n", - "_C119588: -10000.0*t_42_map_1 - t_mem_42 + task_total_memory_router_router1_task42 >= -10000.0\n", - "_C119589: -t43_end_ + t43_start - 10000.0*t_43_map_1 - t_send_43 + task_total_delay_router_router1_task43 >= -10000.0\n", - "_C119590: -10000.0*t_43_map_1 - t_mem_43 + task_total_memory_router_router1_task43 >= -10000.0\n", - "_C119591: -t44_end_ + t44_start - 10000.0*t_44_map_1 - t_send_44 + task_total_delay_router_router1_task44 >= -10000.0\n", - "_C119592: -10000.0*t_44_map_1 - t_mem_44 + task_total_memory_router_router1_task44 >= -10000.0\n", - "_C119593: -t45_end_ + t45_start - 10000.0*t_45_map_1 - t_send_45 + task_total_delay_router_router1_task45 >= -10000.0\n", - "_C119594: -10000.0*t_45_map_1 - t_mem_45 + task_total_memory_router_router1_task45 >= -10000.0\n", - "_C119595: -t46_end_ + t46_start - 10000.0*t_46_map_1 - t_send_46 + task_total_delay_router_router1_task46 >= -10000.0\n", - "_C119596: -10000.0*t_46_map_1 - t_mem_46 + task_total_memory_router_router1_task46 >= -10000.0\n", - "_C119597: -t47_end_ + t47_start - 10000.0*t_47_map_1 - t_send_47 + task_total_delay_router_router1_task47 >= -10000.0\n", - "_C119598: -10000.0*t_47_map_1 - t_mem_47 + task_total_memory_router_router1_task47 >= -10000.0\n", - "_C119599: -t48_end_ + t48_start - 10000.0*t_48_map_1 - t_send_48 + task_total_delay_router_router1_task48 >= -10000.0\n", - 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task_total_delay_router_router1_task57 >= -10000.0\n", - "_C119618: -10000.0*t_57_map_1 - t_mem_57 + task_total_memory_router_router1_task57 >= -10000.0\n", - "_C119619: -t58_end_ + t58_start - 10000.0*t_58_map_1 - t_send_58 + task_total_delay_router_router1_task58 >= -10000.0\n", - "_C119620: -10000.0*t_58_map_1 - t_mem_58 + task_total_memory_router_router1_task58 >= -10000.0\n", - "_C119621: -t59_end_ + t59_start - 10000.0*t_59_map_1 - t_send_59 + task_total_delay_router_router1_task59 >= -10000.0\n", - "_C119622: -10000.0*t_59_map_1 - t_mem_59 + task_total_memory_router_router1_task59 >= -10000.0\n", - "_C119623: -t60_end_ + t60_start - 10000.0*t_60_map_1 - t_send_60 + task_total_delay_router_router1_task60 >= -10000.0\n", - "_C119624: -10000.0*t_60_map_1 - t_mem_60 + task_total_memory_router_router1_task60 >= -10000.0\n", - "_C119625: -t61_end_ + t61_start - 10000.0*t_61_map_1 - t_send_61 + task_total_delay_router_router1_task61 >= -10000.0\n", - "_C119626: -10000.0*t_61_map_1 - t_mem_61 + task_total_memory_router_router1_task61 >= -10000.0\n", - "_C119627: -t62_end_ + t62_start - 10000.0*t_62_map_1 - t_send_62 + task_total_delay_router_router1_task62 >= -10000.0\n", - "_C119628: -10000.0*t_62_map_1 - t_mem_62 + task_total_memory_router_router1_task62 >= -10000.0\n", - "_C119629: -t63_end_ + t63_start - 10000.0*t_63_map_1 - t_send_63 + task_total_delay_router_router1_task63 >= -10000.0\n", - "_C119630: -10000.0*t_63_map_1 - t_mem_63 + task_total_memory_router_router1_task63 >= -10000.0\n", - "_C119631: -t64_end_ + t64_start - 10000.0*t_64_map_1 - t_send_64 + task_total_delay_router_router1_task64 >= -10000.0\n", - "_C119632: -10000.0*t_64_map_1 - t_mem_64 + task_total_memory_router_router1_task64 >= -10000.0\n", - "_C119633: -t65_end_ + t65_start - 10000.0*t_65_map_1 - t_send_65 + task_total_delay_router_router1_task65 >= -10000.0\n", - "_C119634: -10000.0*t_65_map_1 - t_mem_65 + task_total_memory_router_router1_task65 >= -10000.0\n", - "_C119635: -t66_end_ + t66_start - 10000.0*t_66_map_1 - t_send_66 + task_total_delay_router_router1_task66 >= -10000.0\n", - "_C119636: -10000.0*t_66_map_1 - t_mem_66 + task_total_memory_router_router1_task66 >= -10000.0\n", - "_C119637: -t67_end_ + t67_start - 10000.0*t_67_map_1 - t_send_67 + task_total_delay_router_router1_task67 >= -10000.0\n", - "_C119638: -10000.0*t_67_map_1 - t_mem_67 + task_total_memory_router_router1_task67 >= -10000.0\n", - "_C119639: -t68_end_ + t68_start - 10000.0*t_68_map_1 - t_send_68 + task_total_delay_router_router1_task68 >= -10000.0\n", - "_C119640: -10000.0*t_68_map_1 - t_mem_68 + task_total_memory_router_router1_task68 >= -10000.0\n", - "_C119641: -t69_end_ + t69_start - 10000.0*t_69_map_1 - t_send_69 + task_total_delay_router_router1_task69 >= -10000.0\n", - "_C119642: -10000.0*t_69_map_1 - t_mem_69 + task_total_memory_router_router1_task69 >= -10000.0\n", - "_C119643: PE_mem_overflow1 - task_total_memory_router_router1_task0 - task_total_memory_router_router1_task1 - task_total_memory_router_router1_task10 - task_total_memory_router_router1_task11 - task_total_memory_router_router1_task12 - task_total_memory_router_router1_task13 - task_total_memory_router_router1_task14 - task_total_memory_router_router1_task15 - task_total_memory_router_router1_task16 - task_total_memory_router_router1_task17 - task_total_memory_router_router1_task18 - task_total_memory_router_router1_task19 - task_total_memory_router_router1_task2 - task_total_memory_router_router1_task20 - task_total_memory_router_router1_task21 - task_total_memory_router_router1_task22 - task_total_memory_router_router1_task23 - task_total_memory_router_router1_task24 - task_total_memory_router_router1_task25 - task_total_memory_router_router1_task26 - task_total_memory_router_router1_task27 - task_total_memory_router_router1_task28 - task_total_memory_router_router1_task29 - task_total_memory_router_router1_task3 - task_total_memory_router_router1_task30 - task_total_memory_router_router1_task31 - task_total_memory_router_router1_task32 - task_total_memory_router_router1_task33 - task_total_memory_router_router1_task34 - task_total_memory_router_router1_task35 - task_total_memory_router_router1_task36 - task_total_memory_router_router1_task37 - task_total_memory_router_router1_task38 - task_total_memory_router_router1_task39 - task_total_memory_router_router1_task4 - task_total_memory_router_router1_task40 - task_total_memory_router_router1_task41 - task_total_memory_router_router1_task42 - task_total_memory_router_router1_task43 - task_total_memory_router_router1_task44 - task_total_memory_router_router1_task45 - task_total_memory_router_router1_task46 - task_total_memory_router_router1_task47 - task_total_memory_router_router1_task48 - task_total_memory_router_router1_task49 - task_total_memory_router_router1_task5 - task_total_memory_router_router1_task50 - task_total_memory_router_router1_task51 - task_total_memory_router_router1_task52 - task_total_memory_router_router1_task53 - task_total_memory_router_router1_task54 - task_total_memory_router_router1_task55 - task_total_memory_router_router1_task56 - task_total_memory_router_router1_task57 - task_total_memory_router_router1_task58 - task_total_memory_router_router1_task59 - task_total_memory_router_router1_task6 - task_total_memory_router_router1_task60 - task_total_memory_router_router1_task61 - task_total_memory_router_router1_task62 - task_total_memory_router_router1_task63 - task_total_memory_router_router1_task64 - task_total_memory_router_router1_task65 - task_total_memory_router_router1_task66 - task_total_memory_router_router1_task67 - task_total_memory_router_router1_task68 - task_total_memory_router_router1_task69 - task_total_memory_router_router1_task7 - task_total_memory_router_router1_task8 - task_total_memory_router_router1_task9 >= -0.0\n", - "_C119644: PE1_total_delay - task_total_delay_router_router1_task0 - task_total_delay_router_router1_task1 - task_total_delay_router_router1_task10 - task_total_delay_router_router1_task11 - task_total_delay_router_router1_task12 - task_total_delay_router_router1_task13 - task_total_delay_router_router1_task14 - task_total_delay_router_router1_task15 - task_total_delay_router_router1_task16 - task_total_delay_router_router1_task17 - task_total_delay_router_router1_task18 - task_total_delay_router_router1_task19 - task_total_delay_router_router1_task2 - task_total_delay_router_router1_task20 - task_total_delay_router_router1_task21 - task_total_delay_router_router1_task22 - task_total_delay_router_router1_task23 - task_total_delay_router_router1_task24 - task_total_delay_router_router1_task25 - task_total_delay_router_router1_task26 - task_total_delay_router_router1_task27 - task_total_delay_router_router1_task28 - task_total_delay_router_router1_task29 - task_total_delay_router_router1_task3 - task_total_delay_router_router1_task30 - task_total_delay_router_router1_task31 - task_total_delay_router_router1_task32 - task_total_delay_router_router1_task33 - task_total_delay_router_router1_task34 - task_total_delay_router_router1_task35 - task_total_delay_router_router1_task36 - task_total_delay_router_router1_task37 - task_total_delay_router_router1_task38 - task_total_delay_router_router1_task39 - task_total_delay_router_router1_task4 - task_total_delay_router_router1_task40 - task_total_delay_router_router1_task41 - task_total_delay_router_router1_task42 - task_total_delay_router_router1_task43 - task_total_delay_router_router1_task44 - task_total_delay_router_router1_task45 - task_total_delay_router_router1_task46 - task_total_delay_router_router1_task47 - task_total_delay_router_router1_task48 - task_total_delay_router_router1_task49 - task_total_delay_router_router1_task5 - task_total_delay_router_router1_task50 - task_total_delay_router_router1_task51 - task_total_delay_router_router1_task52 - task_total_delay_router_router1_task53 - task_total_delay_router_router1_task54 - task_total_delay_router_router1_task55 - task_total_delay_router_router1_task56 - task_total_delay_router_router1_task57 - task_total_delay_router_router1_task58 - task_total_delay_router_router1_task59 - task_total_delay_router_router1_task6 - task_total_delay_router_router1_task60 - task_total_delay_router_router1_task61 - task_total_delay_router_router1_task62 - task_total_delay_router_router1_task63 - task_total_delay_router_router1_task64 - task_total_delay_router_router1_task65 - task_total_delay_router_router1_task66 - task_total_delay_router_router1_task67 - task_total_delay_router_router1_task68 - task_total_delay_router_router1_task69 - task_total_delay_router_router1_task7 - task_total_delay_router_router1_task8 - task_total_delay_router_router1_task9 >= -0.0\n", - "_C119645: PE1_total_memory - task_total_memory_router_router1_task0 - task_total_memory_router_router1_task1 - task_total_memory_router_router1_task10 - task_total_memory_router_router1_task11 - task_total_memory_router_router1_task12 - task_total_memory_router_router1_task13 - task_total_memory_router_router1_task14 - task_total_memory_router_router1_task15 - task_total_memory_router_router1_task16 - task_total_memory_router_router1_task17 - task_total_memory_router_router1_task18 - task_total_memory_router_router1_task19 - task_total_memory_router_router1_task2 - task_total_memory_router_router1_task20 - task_total_memory_router_router1_task21 - task_total_memory_router_router1_task22 - task_total_memory_router_router1_task23 - task_total_memory_router_router1_task24 - task_total_memory_router_router1_task25 - task_total_memory_router_router1_task26 - task_total_memory_router_router1_task27 - task_total_memory_router_router1_task28 - task_total_memory_router_router1_task29 - task_total_memory_router_router1_task3 - task_total_memory_router_router1_task30 - task_total_memory_router_router1_task31 - task_total_memory_router_router1_task32 - task_total_memory_router_router1_task33 - task_total_memory_router_router1_task34 - task_total_memory_router_router1_task35 - task_total_memory_router_router1_task36 - task_total_memory_router_router1_task37 - task_total_memory_router_router1_task38 - task_total_memory_router_router1_task39 - task_total_memory_router_router1_task4 - task_total_memory_router_router1_task40 - task_total_memory_router_router1_task41 - task_total_memory_router_router1_task42 - task_total_memory_router_router1_task43 - task_total_memory_router_router1_task44 - task_total_memory_router_router1_task45 - task_total_memory_router_router1_task46 - task_total_memory_router_router1_task47 - task_total_memory_router_router1_task48 - task_total_memory_router_router1_task49 - task_total_memory_router_router1_task5 - task_total_memory_router_router1_task50 - task_total_memory_router_router1_task51 - task_total_memory_router_router1_task52 - task_total_memory_router_router1_task53 - task_total_memory_router_router1_task54 - task_total_memory_router_router1_task55 - task_total_memory_router_router1_task56 - task_total_memory_router_router1_task57 - task_total_memory_router_router1_task58 - task_total_memory_router_router1_task59 - task_total_memory_router_router1_task6 - task_total_memory_router_router1_task60 - task_total_memory_router_router1_task61 - task_total_memory_router_router1_task62 - task_total_memory_router_router1_task63 - task_total_memory_router_router1_task64 - task_total_memory_router_router1_task65 - task_total_memory_router_router1_task66 - task_total_memory_router_router1_task67 - task_total_memory_router_router1_task68 - task_total_memory_router_router1_task69 - task_total_memory_router_router1_task7 - task_total_memory_router_router1_task8 - task_total_memory_router_router1_task9 >= -0.0\n", - "_C119646: -PE_mem_overflow1 + max_memory_overflow >= 0\n", - 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t12_start + 10000.0*t_12_map_1 <= 10000.0\n", - "_C119673: PE1_time_delay_max - t13_end_ - 10000.0*t_13_map_1 >= -10000.0\n", - "_C119674: PE1_time_delay_min - t13_start + 10000.0*t_13_map_1 <= 10000.0\n", - "_C119675: PE1_time_delay_max - t14_end_ - 10000.0*t_14_map_1 >= -10000.0\n", - "_C119676: PE1_time_delay_min - t14_start + 10000.0*t_14_map_1 <= 10000.0\n", - "_C119677: PE1_time_delay_max - t15_end_ - 10000.0*t_15_map_1 >= -10000.0\n", - "_C119678: PE1_time_delay_min - t15_start + 10000.0*t_15_map_1 <= 10000.0\n", - "_C119679: PE1_time_delay_max - t16_end_ - 10000.0*t_16_map_1 >= -10000.0\n", - "_C119680: PE1_time_delay_min - t16_start + 10000.0*t_16_map_1 <= 10000.0\n", - "_C119681: PE1_time_delay_max - t17_end_ - 10000.0*t_17_map_1 >= -10000.0\n", - "_C119682: PE1_time_delay_min - t17_start + 10000.0*t_17_map_1 <= 10000.0\n", - "_C119683: PE1_time_delay_max - t18_end_ - 10000.0*t_18_map_1 >= -10000.0\n", - "_C119684: PE1_time_delay_min - t18_start + 10000.0*t_18_map_1 <= 10000.0\n", - "_C119685: PE1_time_delay_max - t19_end_ - 10000.0*t_19_map_1 >= -10000.0\n", - "_C119686: PE1_time_delay_min - t19_start + 10000.0*t_19_map_1 <= 10000.0\n", - "_C119687: PE1_time_delay_max - t20_end_ - 10000.0*t_20_map_1 >= -10000.0\n", - "_C119688: PE1_time_delay_min - t20_start + 10000.0*t_20_map_1 <= 10000.0\n", - "_C119689: PE1_time_delay_max - t21_end_ - 10000.0*t_21_map_1 >= -10000.0\n", - "_C119690: PE1_time_delay_min - t21_start + 10000.0*t_21_map_1 <= 10000.0\n", - "_C119691: PE1_time_delay_max - t22_end_ - 10000.0*t_22_map_1 >= -10000.0\n", - "_C119692: PE1_time_delay_min - t22_start + 10000.0*t_22_map_1 <= 10000.0\n", - "_C119693: PE1_time_delay_max - t23_end_ - 10000.0*t_23_map_1 >= -10000.0\n", - "_C119694: PE1_time_delay_min - t23_start + 10000.0*t_23_map_1 <= 10000.0\n", - "_C119695: PE1_time_delay_max - t24_end_ - 10000.0*t_24_map_1 >= -10000.0\n", - "_C119696: PE1_time_delay_min - t24_start + 10000.0*t_24_map_1 <= 10000.0\n", - "_C119697: PE1_time_delay_max - t25_end_ - 10000.0*t_25_map_1 >= -10000.0\n", - "_C119698: PE1_time_delay_min - t25_start + 10000.0*t_25_map_1 <= 10000.0\n", - "_C119699: PE1_time_delay_max - t26_end_ - 10000.0*t_26_map_1 >= -10000.0\n", - "_C119700: PE1_time_delay_min - t26_start + 10000.0*t_26_map_1 <= 10000.0\n", - "_C119701: PE1_time_delay_max - t27_end_ - 10000.0*t_27_map_1 >= -10000.0\n", - "_C119702: PE1_time_delay_min - t27_start + 10000.0*t_27_map_1 <= 10000.0\n", - "_C119703: PE1_time_delay_max - t28_end_ - 10000.0*t_28_map_1 >= -10000.0\n", - "_C119704: PE1_time_delay_min - t28_start + 10000.0*t_28_map_1 <= 10000.0\n", - "_C119705: PE1_time_delay_max - t29_end_ - 10000.0*t_29_map_1 >= -10000.0\n", - "_C119706: PE1_time_delay_min - t29_start + 10000.0*t_29_map_1 <= 10000.0\n", - "_C119707: PE1_time_delay_max - t30_end_ - 10000.0*t_30_map_1 >= -10000.0\n", - "_C119708: PE1_time_delay_min - t30_start + 10000.0*t_30_map_1 <= 10000.0\n", - "_C119709: PE1_time_delay_max - t31_end_ - 10000.0*t_31_map_1 >= -10000.0\n", - "_C119710: PE1_time_delay_min - t31_start + 10000.0*t_31_map_1 <= 10000.0\n", - "_C119711: PE1_time_delay_max - t32_end_ - 10000.0*t_32_map_1 >= -10000.0\n", - "_C119712: PE1_time_delay_min - t32_start + 10000.0*t_32_map_1 <= 10000.0\n", - "_C119713: PE1_time_delay_max - t33_end_ - 10000.0*t_33_map_1 >= -10000.0\n", - "_C119714: PE1_time_delay_min - t33_start + 10000.0*t_33_map_1 <= 10000.0\n", - "_C119715: PE1_time_delay_max - t34_end_ - 10000.0*t_34_map_1 >= -10000.0\n", - "_C119716: PE1_time_delay_min - t34_start + 10000.0*t_34_map_1 <= 10000.0\n", - "_C119717: PE1_time_delay_max - t35_end_ - 10000.0*t_35_map_1 >= -10000.0\n", - "_C119718: PE1_time_delay_min - t35_start + 10000.0*t_35_map_1 <= 10000.0\n", - "_C119719: PE1_time_delay_max - t36_end_ - 10000.0*t_36_map_1 >= -10000.0\n", - "_C119720: PE1_time_delay_min - t36_start + 10000.0*t_36_map_1 <= 10000.0\n", - "_C119721: PE1_time_delay_max - t37_end_ - 10000.0*t_37_map_1 >= -10000.0\n", - "_C119722: PE1_time_delay_min - t37_start + 10000.0*t_37_map_1 <= 10000.0\n", - "_C119723: PE1_time_delay_max - t38_end_ - 10000.0*t_38_map_1 >= -10000.0\n", - "_C119724: PE1_time_delay_min - t38_start + 10000.0*t_38_map_1 <= 10000.0\n", - "_C119725: PE1_time_delay_max - t39_end_ - 10000.0*t_39_map_1 >= -10000.0\n", - "_C119726: PE1_time_delay_min - t39_start + 10000.0*t_39_map_1 <= 10000.0\n", - "_C119727: PE1_time_delay_max - t40_end_ - 10000.0*t_40_map_1 >= -10000.0\n", - "_C119728: PE1_time_delay_min - t40_start + 10000.0*t_40_map_1 <= 10000.0\n", - "_C119729: PE1_time_delay_max - t41_end_ - 10000.0*t_41_map_1 >= -10000.0\n", - "_C119730: PE1_time_delay_min - t41_start + 10000.0*t_41_map_1 <= 10000.0\n", - "_C119731: PE1_time_delay_max - t42_end_ - 10000.0*t_42_map_1 >= -10000.0\n", - "_C119732: PE1_time_delay_min - t42_start + 10000.0*t_42_map_1 <= 10000.0\n", - "_C119733: PE1_time_delay_max - t43_end_ - 10000.0*t_43_map_1 >= -10000.0\n", - "_C119734: PE1_time_delay_min - t43_start + 10000.0*t_43_map_1 <= 10000.0\n", - "_C119735: PE1_time_delay_max - t44_end_ - 10000.0*t_44_map_1 >= -10000.0\n", - "_C119736: PE1_time_delay_min - t44_start + 10000.0*t_44_map_1 <= 10000.0\n", - "_C119737: PE1_time_delay_max - t45_end_ - 10000.0*t_45_map_1 >= -10000.0\n", - "_C119738: PE1_time_delay_min - t45_start + 10000.0*t_45_map_1 <= 10000.0\n", - "_C119739: PE1_time_delay_max - t46_end_ - 10000.0*t_46_map_1 >= -10000.0\n", - "_C119740: PE1_time_delay_min - t46_start + 10000.0*t_46_map_1 <= 10000.0\n", - "_C119741: PE1_time_delay_max - t47_end_ - 10000.0*t_47_map_1 >= -10000.0\n", - "_C119742: PE1_time_delay_min - t47_start + 10000.0*t_47_map_1 <= 10000.0\n", - "_C119743: PE1_time_delay_max - t48_end_ - 10000.0*t_48_map_1 >= -10000.0\n", - "_C119744: PE1_time_delay_min - t48_start + 10000.0*t_48_map_1 <= 10000.0\n", - "_C119745: PE1_time_delay_max - t49_end_ - 10000.0*t_49_map_1 >= -10000.0\n", - "_C119746: PE1_time_delay_min - t49_start + 10000.0*t_49_map_1 <= 10000.0\n", - "_C119747: PE1_time_delay_max - t50_end_ - 10000.0*t_50_map_1 >= -10000.0\n", - "_C119748: PE1_time_delay_min - t50_start + 10000.0*t_50_map_1 <= 10000.0\n", - "_C119749: PE1_time_delay_max - t51_end_ - 10000.0*t_51_map_1 >= -10000.0\n", - "_C119750: PE1_time_delay_min - t51_start + 10000.0*t_51_map_1 <= 10000.0\n", - "_C119751: PE1_time_delay_max - t52_end_ - 10000.0*t_52_map_1 >= -10000.0\n", - "_C119752: PE1_time_delay_min - t52_start + 10000.0*t_52_map_1 <= 10000.0\n", - "_C119753: PE1_time_delay_max - t53_end_ - 10000.0*t_53_map_1 >= -10000.0\n", - "_C119754: PE1_time_delay_min - t53_start + 10000.0*t_53_map_1 <= 10000.0\n", - "_C119755: PE1_time_delay_max - t54_end_ - 10000.0*t_54_map_1 >= -10000.0\n", - "_C119756: PE1_time_delay_min - t54_start + 10000.0*t_54_map_1 <= 10000.0\n", - "_C119757: PE1_time_delay_max - t55_end_ - 10000.0*t_55_map_1 >= -10000.0\n", - "_C119758: PE1_time_delay_min - t55_start + 10000.0*t_55_map_1 <= 10000.0\n", - "_C119759: PE1_time_delay_max - t56_end_ - 10000.0*t_56_map_1 >= -10000.0\n", - "_C119760: PE1_time_delay_min - t56_start + 10000.0*t_56_map_1 <= 10000.0\n", - "_C119761: PE1_time_delay_max - t57_end_ - 10000.0*t_57_map_1 >= -10000.0\n", - "_C119762: PE1_time_delay_min - t57_start + 10000.0*t_57_map_1 <= 10000.0\n", - "_C119763: PE1_time_delay_max - t58_end_ - 10000.0*t_58_map_1 >= -10000.0\n", - "_C119764: PE1_time_delay_min - t58_start + 10000.0*t_58_map_1 <= 10000.0\n", - "_C119765: PE1_time_delay_max - t59_end_ - 10000.0*t_59_map_1 >= -10000.0\n", - "_C119766: PE1_time_delay_min - t59_start + 10000.0*t_59_map_1 <= 10000.0\n", - "_C119767: PE1_time_delay_max - t60_end_ - 10000.0*t_60_map_1 >= -10000.0\n", - "_C119768: PE1_time_delay_min - t60_start + 10000.0*t_60_map_1 <= 10000.0\n", - "_C119769: PE1_time_delay_max - t61_end_ - 10000.0*t_61_map_1 >= -10000.0\n", - "_C119770: PE1_time_delay_min - t61_start + 10000.0*t_61_map_1 <= 10000.0\n", - "_C119771: PE1_time_delay_max - t62_end_ - 10000.0*t_62_map_1 >= -10000.0\n", - "_C119772: PE1_time_delay_min - t62_start + 10000.0*t_62_map_1 <= 10000.0\n", - "_C119773: PE1_time_delay_max - t63_end_ - 10000.0*t_63_map_1 >= -10000.0\n", - "_C119774: PE1_time_delay_min - t63_start + 10000.0*t_63_map_1 <= 10000.0\n", - "_C119775: PE1_time_delay_max - t64_end_ - 10000.0*t_64_map_1 >= -10000.0\n", - "_C119776: PE1_time_delay_min - t64_start + 10000.0*t_64_map_1 <= 10000.0\n", - "_C119777: PE1_time_delay_max - t65_end_ - 10000.0*t_65_map_1 >= -10000.0\n", - "_C119778: PE1_time_delay_min - t65_start + 10000.0*t_65_map_1 <= 10000.0\n", - "_C119779: PE1_time_delay_max - t66_end_ - 10000.0*t_66_map_1 >= -10000.0\n", - "_C119780: PE1_time_delay_min - t66_start + 10000.0*t_66_map_1 <= 10000.0\n", - "_C119781: PE1_time_delay_max - t67_end_ - 10000.0*t_67_map_1 >= -10000.0\n", - "_C119782: PE1_time_delay_min - t67_start + 10000.0*t_67_map_1 <= 10000.0\n", - "_C119783: PE1_time_delay_max - t68_end_ - 10000.0*t_68_map_1 >= -10000.0\n", - "_C119784: PE1_time_delay_min - t68_start + 10000.0*t_68_map_1 <= 10000.0\n", - "_C119785: PE1_time_delay_max - t69_end_ - 10000.0*t_69_map_1 >= -10000.0\n", - "_C119786: PE1_time_delay_min - t69_start + 10000.0*t_69_map_1 <= 10000.0\n", - "_C119787: -PE1_time_delay_max + PE1_time_delay_min + PE1_total_time_delay = 0\n", - "_C119788: -PE1_total_time_delay + max_router_delay >= 0\n", - "_C119789: PE1_total_time_delay <= 280\n", - "_C119790: -t0_end_ + t0_start - 10000.0*t_0_map_2 - t_send_0 + task_total_delay_router_router2_task0 >= -10000.0\n", - "_C119791: -10000.0*t_0_map_2 - t_mem_0 + task_total_memory_router_router2_task0 >= -10000.0\n", - "_C119792: -t1_end_ + t1_start - 10000.0*t_1_map_2 - t_send_1 + task_total_delay_router_router2_task1 >= -10000.0\n", - "_C119793: -10000.0*t_1_map_2 - t_mem_1 + task_total_memory_router_router2_task1 >= -10000.0\n", - "_C119794: -t2_end_ + t2_start - 10000.0*t_2_map_2 - t_send_2 + task_total_delay_router_router2_task2 >= -10000.0\n", - "_C119795: -10000.0*t_2_map_2 - t_mem_2 + task_total_memory_router_router2_task2 >= -10000.0\n", - "_C119796: -t3_end_ + t3_start - 10000.0*t_3_map_2 - t_send_3 + task_total_delay_router_router2_task3 >= -10000.0\n", - "_C119797: -10000.0*t_3_map_2 - t_mem_3 + task_total_memory_router_router2_task3 >= -10000.0\n", - "_C119798: -t4_end_ + t4_start - 10000.0*t_4_map_2 - t_send_4 + task_total_delay_router_router2_task4 >= -10000.0\n", - "_C119799: -10000.0*t_4_map_2 - t_mem_4 + task_total_memory_router_router2_task4 >= -10000.0\n", - "_C119800: -t5_end_ + t5_start - 10000.0*t_5_map_2 - t_send_5 + task_total_delay_router_router2_task5 >= -10000.0\n", - "_C119801: -10000.0*t_5_map_2 - t_mem_5 + task_total_memory_router_router2_task5 >= -10000.0\n", - "_C119802: -t6_end_ + t6_start - 10000.0*t_6_map_2 - t_send_6 + task_total_delay_router_router2_task6 >= -10000.0\n", - "_C119803: -10000.0*t_6_map_2 - t_mem_6 + task_total_memory_router_router2_task6 >= -10000.0\n", - "_C119804: -t7_end_ + t7_start - 10000.0*t_7_map_2 - t_send_7 + task_total_delay_router_router2_task7 >= -10000.0\n", - "_C119805: -10000.0*t_7_map_2 - t_mem_7 + task_total_memory_router_router2_task7 >= -10000.0\n", - "_C119806: -t8_end_ + t8_start - 10000.0*t_8_map_2 - t_send_8 + task_total_delay_router_router2_task8 >= -10000.0\n", - "_C119807: -10000.0*t_8_map_2 - t_mem_8 + task_total_memory_router_router2_task8 >= -10000.0\n", - "_C119808: -t9_end_ + t9_start - 10000.0*t_9_map_2 - t_send_9 + task_total_delay_router_router2_task9 >= -10000.0\n", - "_C119809: -10000.0*t_9_map_2 - t_mem_9 + task_total_memory_router_router2_task9 >= -10000.0\n", - "_C119810: -t10_end_ + t10_start - 10000.0*t_10_map_2 - t_send_10 + task_total_delay_router_router2_task10 >= -10000.0\n", - "_C119811: -10000.0*t_10_map_2 - t_mem_10 + task_total_memory_router_router2_task10 >= -10000.0\n", - "_C119812: -t11_end_ + t11_start - 10000.0*t_11_map_2 - t_send_11 + task_total_delay_router_router2_task11 >= -10000.0\n", - "_C119813: -10000.0*t_11_map_2 - t_mem_11 + task_total_memory_router_router2_task11 >= -10000.0\n", - "_C119814: -t12_end_ + t12_start - 10000.0*t_12_map_2 - t_send_12 + task_total_delay_router_router2_task12 >= -10000.0\n", - "_C119815: -10000.0*t_12_map_2 - t_mem_12 + task_total_memory_router_router2_task12 >= -10000.0\n", - "_C119816: -t13_end_ + t13_start - 10000.0*t_13_map_2 - t_send_13 + task_total_delay_router_router2_task13 >= -10000.0\n", - "_C119817: -10000.0*t_13_map_2 - t_mem_13 + task_total_memory_router_router2_task13 >= -10000.0\n", - "_C119818: -t14_end_ + t14_start - 10000.0*t_14_map_2 - t_send_14 + task_total_delay_router_router2_task14 >= -10000.0\n", - "_C119819: -10000.0*t_14_map_2 - t_mem_14 + task_total_memory_router_router2_task14 >= -10000.0\n", - "_C119820: -t15_end_ + t15_start - 10000.0*t_15_map_2 - t_send_15 + task_total_delay_router_router2_task15 >= -10000.0\n", - "_C119821: -10000.0*t_15_map_2 - t_mem_15 + task_total_memory_router_router2_task15 >= -10000.0\n", - "_C119822: -t16_end_ + t16_start - 10000.0*t_16_map_2 - t_send_16 + task_total_delay_router_router2_task16 >= -10000.0\n", - "_C119823: -10000.0*t_16_map_2 - t_mem_16 + task_total_memory_router_router2_task16 >= -10000.0\n", - "_C119824: -t17_end_ + t17_start - 10000.0*t_17_map_2 - t_send_17 + task_total_delay_router_router2_task17 >= -10000.0\n", - "_C119825: -10000.0*t_17_map_2 - t_mem_17 + task_total_memory_router_router2_task17 >= -10000.0\n", - "_C119826: -t18_end_ + t18_start - 10000.0*t_18_map_2 - t_send_18 + task_total_delay_router_router2_task18 >= -10000.0\n", - "_C119827: -10000.0*t_18_map_2 - t_mem_18 + task_total_memory_router_router2_task18 >= -10000.0\n", - "_C119828: -t19_end_ + t19_start - 10000.0*t_19_map_2 - t_send_19 + task_total_delay_router_router2_task19 >= -10000.0\n", - "_C119829: -10000.0*t_19_map_2 - t_mem_19 + task_total_memory_router_router2_task19 >= -10000.0\n", - "_C119830: -t20_end_ + t20_start - 10000.0*t_20_map_2 - t_send_20 + task_total_delay_router_router2_task20 >= -10000.0\n", - "_C119831: -10000.0*t_20_map_2 - t_mem_20 + task_total_memory_router_router2_task20 >= -10000.0\n", - "_C119832: -t21_end_ + t21_start - 10000.0*t_21_map_2 - t_send_21 + task_total_delay_router_router2_task21 >= -10000.0\n", - "_C119833: -10000.0*t_21_map_2 - t_mem_21 + task_total_memory_router_router2_task21 >= -10000.0\n", - "_C119834: -t22_end_ + t22_start - 10000.0*t_22_map_2 - t_send_22 + task_total_delay_router_router2_task22 >= -10000.0\n", - "_C119835: -10000.0*t_22_map_2 - t_mem_22 + task_total_memory_router_router2_task22 >= -10000.0\n", - "_C119836: -t23_end_ + t23_start - 10000.0*t_23_map_2 - t_send_23 + task_total_delay_router_router2_task23 >= -10000.0\n", - "_C119837: -10000.0*t_23_map_2 - t_mem_23 + task_total_memory_router_router2_task23 >= -10000.0\n", - "_C119838: -t24_end_ + t24_start - 10000.0*t_24_map_2 - t_send_24 + task_total_delay_router_router2_task24 >= -10000.0\n", - "_C119839: -10000.0*t_24_map_2 - t_mem_24 + task_total_memory_router_router2_task24 >= -10000.0\n", - "_C119840: -t25_end_ + t25_start - 10000.0*t_25_map_2 - t_send_25 + task_total_delay_router_router2_task25 >= -10000.0\n", - "_C119841: -10000.0*t_25_map_2 - t_mem_25 + task_total_memory_router_router2_task25 >= -10000.0\n", - "_C119842: -t26_end_ + t26_start - 10000.0*t_26_map_2 - t_send_26 + task_total_delay_router_router2_task26 >= -10000.0\n", - "_C119843: -10000.0*t_26_map_2 - t_mem_26 + task_total_memory_router_router2_task26 >= -10000.0\n", - "_C119844: -t27_end_ + t27_start - 10000.0*t_27_map_2 - t_send_27 + task_total_delay_router_router2_task27 >= -10000.0\n", - "_C119845: -10000.0*t_27_map_2 - t_mem_27 + task_total_memory_router_router2_task27 >= -10000.0\n", - "_C119846: -t28_end_ + t28_start - 10000.0*t_28_map_2 - t_send_28 + task_total_delay_router_router2_task28 >= -10000.0\n", - "_C119847: -10000.0*t_28_map_2 - t_mem_28 + task_total_memory_router_router2_task28 >= -10000.0\n", - "_C119848: -t29_end_ + t29_start - 10000.0*t_29_map_2 - t_send_29 + task_total_delay_router_router2_task29 >= -10000.0\n", - "_C119849: -10000.0*t_29_map_2 - t_mem_29 + task_total_memory_router_router2_task29 >= -10000.0\n", - "_C119850: -t30_end_ + t30_start - 10000.0*t_30_map_2 - t_send_30 + task_total_delay_router_router2_task30 >= -10000.0\n", - "_C119851: -10000.0*t_30_map_2 - t_mem_30 + task_total_memory_router_router2_task30 >= -10000.0\n", - "_C119852: -t31_end_ + t31_start - 10000.0*t_31_map_2 - t_send_31 + task_total_delay_router_router2_task31 >= -10000.0\n", - "_C119853: -10000.0*t_31_map_2 - t_mem_31 + task_total_memory_router_router2_task31 >= -10000.0\n", - "_C119854: -t32_end_ + t32_start - 10000.0*t_32_map_2 - t_send_32 + task_total_delay_router_router2_task32 >= -10000.0\n", - "_C119855: -10000.0*t_32_map_2 - t_mem_32 + task_total_memory_router_router2_task32 >= -10000.0\n", - "_C119856: -t33_end_ + t33_start - 10000.0*t_33_map_2 - t_send_33 + task_total_delay_router_router2_task33 >= 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task_total_memory_router_router2_task22 - task_total_memory_router_router2_task23 - task_total_memory_router_router2_task24 - task_total_memory_router_router2_task25 - task_total_memory_router_router2_task26 - task_total_memory_router_router2_task27 - task_total_memory_router_router2_task28 - task_total_memory_router_router2_task29 - task_total_memory_router_router2_task3 - task_total_memory_router_router2_task30 - task_total_memory_router_router2_task31 - task_total_memory_router_router2_task32 - task_total_memory_router_router2_task33 - task_total_memory_router_router2_task34 - task_total_memory_router_router2_task35 - task_total_memory_router_router2_task36 - task_total_memory_router_router2_task37 - task_total_memory_router_router2_task38 - task_total_memory_router_router2_task39 - task_total_memory_router_router2_task4 - task_total_memory_router_router2_task40 - task_total_memory_router_router2_task41 - task_total_memory_router_router2_task42 - task_total_memory_router_router2_task43 - task_total_memory_router_router2_task44 - task_total_memory_router_router2_task45 - task_total_memory_router_router2_task46 - task_total_memory_router_router2_task47 - task_total_memory_router_router2_task48 - task_total_memory_router_router2_task49 - task_total_memory_router_router2_task5 - task_total_memory_router_router2_task50 - task_total_memory_router_router2_task51 - task_total_memory_router_router2_task52 - task_total_memory_router_router2_task53 - task_total_memory_router_router2_task54 - task_total_memory_router_router2_task55 - task_total_memory_router_router2_task56 - task_total_memory_router_router2_task57 - task_total_memory_router_router2_task58 - task_total_memory_router_router2_task59 - task_total_memory_router_router2_task6 - task_total_memory_router_router2_task60 - task_total_memory_router_router2_task61 - task_total_memory_router_router2_task62 - task_total_memory_router_router2_task63 - task_total_memory_router_router2_task64 - task_total_memory_router_router2_task65 - task_total_memory_router_router2_task66 - task_total_memory_router_router2_task67 - task_total_memory_router_router2_task68 - task_total_memory_router_router2_task69 - task_total_memory_router_router2_task7 - task_total_memory_router_router2_task8 - task_total_memory_router_router2_task9 >= -0.0\n", - "_C119931: PE2_total_delay - task_total_delay_router_router2_task0 - task_total_delay_router_router2_task1 - task_total_delay_router_router2_task10 - task_total_delay_router_router2_task11 - task_total_delay_router_router2_task12 - task_total_delay_router_router2_task13 - task_total_delay_router_router2_task14 - task_total_delay_router_router2_task15 - task_total_delay_router_router2_task16 - task_total_delay_router_router2_task17 - task_total_delay_router_router2_task18 - task_total_delay_router_router2_task19 - task_total_delay_router_router2_task2 - task_total_delay_router_router2_task20 - task_total_delay_router_router2_task21 - task_total_delay_router_router2_task22 - task_total_delay_router_router2_task23 - task_total_delay_router_router2_task24 - task_total_delay_router_router2_task25 - task_total_delay_router_router2_task26 - task_total_delay_router_router2_task27 - task_total_delay_router_router2_task28 - task_total_delay_router_router2_task29 - task_total_delay_router_router2_task3 - task_total_delay_router_router2_task30 - task_total_delay_router_router2_task31 - task_total_delay_router_router2_task32 - task_total_delay_router_router2_task33 - task_total_delay_router_router2_task34 - task_total_delay_router_router2_task35 - task_total_delay_router_router2_task36 - task_total_delay_router_router2_task37 - task_total_delay_router_router2_task38 - task_total_delay_router_router2_task39 - task_total_delay_router_router2_task4 - task_total_delay_router_router2_task40 - task_total_delay_router_router2_task41 - task_total_delay_router_router2_task42 - task_total_delay_router_router2_task43 - task_total_delay_router_router2_task44 - task_total_delay_router_router2_task45 - task_total_delay_router_router2_task46 - task_total_delay_router_router2_task47 - task_total_delay_router_router2_task48 - task_total_delay_router_router2_task49 - task_total_delay_router_router2_task5 - task_total_delay_router_router2_task50 - task_total_delay_router_router2_task51 - task_total_delay_router_router2_task52 - task_total_delay_router_router2_task53 - task_total_delay_router_router2_task54 - task_total_delay_router_router2_task55 - task_total_delay_router_router2_task56 - task_total_delay_router_router2_task57 - task_total_delay_router_router2_task58 - task_total_delay_router_router2_task59 - task_total_delay_router_router2_task6 - task_total_delay_router_router2_task60 - task_total_delay_router_router2_task61 - task_total_delay_router_router2_task62 - task_total_delay_router_router2_task63 - task_total_delay_router_router2_task64 - task_total_delay_router_router2_task65 - task_total_delay_router_router2_task66 - task_total_delay_router_router2_task67 - task_total_delay_router_router2_task68 - task_total_delay_router_router2_task69 - task_total_delay_router_router2_task7 - task_total_delay_router_router2_task8 - task_total_delay_router_router2_task9 >= -0.0\n", - "_C119932: PE2_total_memory - task_total_memory_router_router2_task0 - task_total_memory_router_router2_task1 - task_total_memory_router_router2_task10 - task_total_memory_router_router2_task11 - task_total_memory_router_router2_task12 - task_total_memory_router_router2_task13 - task_total_memory_router_router2_task14 - task_total_memory_router_router2_task15 - task_total_memory_router_router2_task16 - task_total_memory_router_router2_task17 - task_total_memory_router_router2_task18 - task_total_memory_router_router2_task19 - task_total_memory_router_router2_task2 - task_total_memory_router_router2_task20 - task_total_memory_router_router2_task21 - task_total_memory_router_router2_task22 - task_total_memory_router_router2_task23 - task_total_memory_router_router2_task24 - task_total_memory_router_router2_task25 - task_total_memory_router_router2_task26 - task_total_memory_router_router2_task27 - task_total_memory_router_router2_task28 - task_total_memory_router_router2_task29 - task_total_memory_router_router2_task3 - task_total_memory_router_router2_task30 - task_total_memory_router_router2_task31 - task_total_memory_router_router2_task32 - task_total_memory_router_router2_task33 - task_total_memory_router_router2_task34 - task_total_memory_router_router2_task35 - task_total_memory_router_router2_task36 - task_total_memory_router_router2_task37 - task_total_memory_router_router2_task38 - task_total_memory_router_router2_task39 - task_total_memory_router_router2_task4 - task_total_memory_router_router2_task40 - task_total_memory_router_router2_task41 - task_total_memory_router_router2_task42 - task_total_memory_router_router2_task43 - task_total_memory_router_router2_task44 - task_total_memory_router_router2_task45 - task_total_memory_router_router2_task46 - task_total_memory_router_router2_task47 - task_total_memory_router_router2_task48 - task_total_memory_router_router2_task49 - task_total_memory_router_router2_task5 - task_total_memory_router_router2_task50 - task_total_memory_router_router2_task51 - task_total_memory_router_router2_task52 - task_total_memory_router_router2_task53 - task_total_memory_router_router2_task54 - task_total_memory_router_router2_task55 - task_total_memory_router_router2_task56 - task_total_memory_router_router2_task57 - task_total_memory_router_router2_task58 - task_total_memory_router_router2_task59 - task_total_memory_router_router2_task6 - task_total_memory_router_router2_task60 - task_total_memory_router_router2_task61 - task_total_memory_router_router2_task62 - task_total_memory_router_router2_task63 - task_total_memory_router_router2_task64 - task_total_memory_router_router2_task65 - task_total_memory_router_router2_task66 - task_total_memory_router_router2_task67 - task_total_memory_router_router2_task68 - task_total_memory_router_router2_task69 - task_total_memory_router_router2_task7 - task_total_memory_router_router2_task8 - task_total_memory_router_router2_task9 >= -0.0\n", - "_C119933: -PE_mem_overflow2 + max_memory_overflow >= 0\n", - "_C119934: PE2_time_delay_max - t0_end_ - 10000.0*t_0_map_2 >= -10000.0\n", - "_C119935: PE2_time_delay_min - t0_start + 10000.0*t_0_map_2 <= 10000.0\n", - "_C119936: PE2_time_delay_max - t1_end_ - 10000.0*t_1_map_2 >= -10000.0\n", - "_C119937: PE2_time_delay_min - t1_start + 10000.0*t_1_map_2 <= 10000.0\n", - "_C119938: PE2_time_delay_max - t2_end_ - 10000.0*t_2_map_2 >= -10000.0\n", - "_C119939: PE2_time_delay_min - t2_start + 10000.0*t_2_map_2 <= 10000.0\n", - "_C119940: PE2_time_delay_max - t3_end_ - 10000.0*t_3_map_2 >= -10000.0\n", - "_C119941: PE2_time_delay_min - t3_start + 10000.0*t_3_map_2 <= 10000.0\n", - "_C119942: PE2_time_delay_max - t4_end_ - 10000.0*t_4_map_2 >= -10000.0\n", - "_C119943: PE2_time_delay_min - t4_start + 10000.0*t_4_map_2 <= 10000.0\n", - "_C119944: PE2_time_delay_max - t5_end_ - 10000.0*t_5_map_2 >= -10000.0\n", - "_C119945: PE2_time_delay_min - t5_start + 10000.0*t_5_map_2 <= 10000.0\n", - "_C119946: PE2_time_delay_max - t6_end_ - 10000.0*t_6_map_2 >= -10000.0\n", - "_C119947: PE2_time_delay_min - t6_start + 10000.0*t_6_map_2 <= 10000.0\n", - "_C119948: PE2_time_delay_max - t7_end_ - 10000.0*t_7_map_2 >= -10000.0\n", - "_C119949: PE2_time_delay_min - t7_start + 10000.0*t_7_map_2 <= 10000.0\n", - "_C119950: PE2_time_delay_max - t8_end_ - 10000.0*t_8_map_2 >= -10000.0\n", - "_C119951: PE2_time_delay_min - t8_start + 10000.0*t_8_map_2 <= 10000.0\n", - "_C119952: PE2_time_delay_max - t9_end_ - 10000.0*t_9_map_2 >= -10000.0\n", - "_C119953: PE2_time_delay_min - t9_start + 10000.0*t_9_map_2 <= 10000.0\n", - "_C119954: PE2_time_delay_max - t10_end_ - 10000.0*t_10_map_2 >= -10000.0\n", - "_C119955: PE2_time_delay_min - t10_start + 10000.0*t_10_map_2 <= 10000.0\n", - "_C119956: PE2_time_delay_max - t11_end_ - 10000.0*t_11_map_2 >= -10000.0\n", - "_C119957: PE2_time_delay_min - t11_start + 10000.0*t_11_map_2 <= 10000.0\n", - "_C119958: PE2_time_delay_max - t12_end_ - 10000.0*t_12_map_2 >= -10000.0\n", - "_C119959: PE2_time_delay_min - t12_start + 10000.0*t_12_map_2 <= 10000.0\n", - "_C119960: PE2_time_delay_max - t13_end_ - 10000.0*t_13_map_2 >= -10000.0\n", - "_C119961: PE2_time_delay_min - t13_start + 10000.0*t_13_map_2 <= 10000.0\n", - "_C119962: PE2_time_delay_max - t14_end_ - 10000.0*t_14_map_2 >= -10000.0\n", - "_C119963: PE2_time_delay_min - t14_start + 10000.0*t_14_map_2 <= 10000.0\n", - "_C119964: PE2_time_delay_max - t15_end_ - 10000.0*t_15_map_2 >= -10000.0\n", - "_C119965: PE2_time_delay_min - t15_start + 10000.0*t_15_map_2 <= 10000.0\n", - "_C119966: PE2_time_delay_max - t16_end_ - 10000.0*t_16_map_2 >= -10000.0\n", - "_C119967: PE2_time_delay_min - t16_start + 10000.0*t_16_map_2 <= 10000.0\n", - "_C119968: PE2_time_delay_max - t17_end_ - 10000.0*t_17_map_2 >= -10000.0\n", - "_C119969: PE2_time_delay_min - t17_start + 10000.0*t_17_map_2 <= 10000.0\n", - "_C119970: PE2_time_delay_max - t18_end_ - 10000.0*t_18_map_2 >= -10000.0\n", - "_C119971: PE2_time_delay_min - t18_start + 10000.0*t_18_map_2 <= 10000.0\n", - "_C119972: PE2_time_delay_max - t19_end_ - 10000.0*t_19_map_2 >= -10000.0\n", - "_C119973: PE2_time_delay_min - t19_start + 10000.0*t_19_map_2 <= 10000.0\n", - "_C119974: PE2_time_delay_max - t20_end_ - 10000.0*t_20_map_2 >= -10000.0\n", - "_C119975: PE2_time_delay_min - t20_start + 10000.0*t_20_map_2 <= 10000.0\n", - "_C119976: PE2_time_delay_max - t21_end_ - 10000.0*t_21_map_2 >= -10000.0\n", - "_C119977: PE2_time_delay_min - t21_start + 10000.0*t_21_map_2 <= 10000.0\n", - "_C119978: PE2_time_delay_max - t22_end_ - 10000.0*t_22_map_2 >= -10000.0\n", - "_C119979: PE2_time_delay_min - t22_start + 10000.0*t_22_map_2 <= 10000.0\n", - "_C119980: PE2_time_delay_max - t23_end_ - 10000.0*t_23_map_2 >= -10000.0\n", - "_C119981: PE2_time_delay_min - t23_start + 10000.0*t_23_map_2 <= 10000.0\n", - "_C119982: PE2_time_delay_max - t24_end_ - 10000.0*t_24_map_2 >= -10000.0\n", - "_C119983: PE2_time_delay_min - t24_start + 10000.0*t_24_map_2 <= 10000.0\n", - "_C119984: PE2_time_delay_max - t25_end_ - 10000.0*t_25_map_2 >= -10000.0\n", - "_C119985: PE2_time_delay_min - t25_start + 10000.0*t_25_map_2 <= 10000.0\n", - "_C119986: PE2_time_delay_max - t26_end_ - 10000.0*t_26_map_2 >= -10000.0\n", - "_C119987: PE2_time_delay_min - t26_start + 10000.0*t_26_map_2 <= 10000.0\n", - "_C119988: PE2_time_delay_max - t27_end_ - 10000.0*t_27_map_2 >= -10000.0\n", - "_C119989: PE2_time_delay_min - t27_start + 10000.0*t_27_map_2 <= 10000.0\n", - "_C119990: PE2_time_delay_max - t28_end_ - 10000.0*t_28_map_2 >= -10000.0\n", - "_C119991: PE2_time_delay_min - t28_start + 10000.0*t_28_map_2 <= 10000.0\n", - "_C119992: PE2_time_delay_max - t29_end_ - 10000.0*t_29_map_2 >= -10000.0\n", - "_C119993: PE2_time_delay_min - t29_start + 10000.0*t_29_map_2 <= 10000.0\n", - "_C119994: PE2_time_delay_max - t30_end_ - 10000.0*t_30_map_2 >= -10000.0\n", - "_C119995: PE2_time_delay_min - t30_start + 10000.0*t_30_map_2 <= 10000.0\n", - "_C119996: PE2_time_delay_max - t31_end_ - 10000.0*t_31_map_2 >= -10000.0\n", - "_C119997: PE2_time_delay_min - t31_start + 10000.0*t_31_map_2 <= 10000.0\n", - "_C119998: PE2_time_delay_max - t32_end_ - 10000.0*t_32_map_2 >= -10000.0\n", - "_C119999: PE2_time_delay_min - t32_start + 10000.0*t_32_map_2 <= 10000.0\n", - "_C120000: PE2_time_delay_max - t33_end_ - 10000.0*t_33_map_2 >= -10000.0\n", - "_C120001: PE2_time_delay_min - t33_start + 10000.0*t_33_map_2 <= 10000.0\n", - "_C120002: PE2_time_delay_max - t34_end_ - 10000.0*t_34_map_2 >= -10000.0\n", - "_C120003: PE2_time_delay_min - t34_start + 10000.0*t_34_map_2 <= 10000.0\n", - "_C120004: PE2_time_delay_max - t35_end_ - 10000.0*t_35_map_2 >= -10000.0\n", - "_C120005: PE2_time_delay_min - t35_start + 10000.0*t_35_map_2 <= 10000.0\n", - "_C120006: PE2_time_delay_max - t36_end_ - 10000.0*t_36_map_2 >= -10000.0\n", - "_C120007: PE2_time_delay_min - t36_start + 10000.0*t_36_map_2 <= 10000.0\n", - "_C120008: PE2_time_delay_max - t37_end_ - 10000.0*t_37_map_2 >= -10000.0\n", - "_C120009: PE2_time_delay_min - t37_start + 10000.0*t_37_map_2 <= 10000.0\n", - "_C120010: PE2_time_delay_max - t38_end_ - 10000.0*t_38_map_2 >= -10000.0\n", - "_C120011: PE2_time_delay_min - t38_start + 10000.0*t_38_map_2 <= 10000.0\n", - "_C120012: PE2_time_delay_max - t39_end_ - 10000.0*t_39_map_2 >= -10000.0\n", - "_C120013: PE2_time_delay_min - t39_start + 10000.0*t_39_map_2 <= 10000.0\n", - "_C120014: PE2_time_delay_max - t40_end_ - 10000.0*t_40_map_2 >= -10000.0\n", - "_C120015: PE2_time_delay_min - t40_start + 10000.0*t_40_map_2 <= 10000.0\n", - "_C120016: PE2_time_delay_max - t41_end_ - 10000.0*t_41_map_2 >= -10000.0\n", - "_C120017: PE2_time_delay_min - t41_start + 10000.0*t_41_map_2 <= 10000.0\n", - "_C120018: PE2_time_delay_max - t42_end_ - 10000.0*t_42_map_2 >= -10000.0\n", - "_C120019: PE2_time_delay_min - t42_start + 10000.0*t_42_map_2 <= 10000.0\n", - "_C120020: PE2_time_delay_max - t43_end_ - 10000.0*t_43_map_2 >= -10000.0\n", - "_C120021: PE2_time_delay_min - t43_start + 10000.0*t_43_map_2 <= 10000.0\n", - "_C120022: PE2_time_delay_max - t44_end_ - 10000.0*t_44_map_2 >= -10000.0\n", - "_C120023: PE2_time_delay_min - t44_start + 10000.0*t_44_map_2 <= 10000.0\n", - "_C120024: PE2_time_delay_max - t45_end_ - 10000.0*t_45_map_2 >= -10000.0\n", - "_C120025: PE2_time_delay_min - t45_start + 10000.0*t_45_map_2 <= 10000.0\n", - "_C120026: PE2_time_delay_max - t46_end_ - 10000.0*t_46_map_2 >= -10000.0\n", - "_C120027: PE2_time_delay_min - t46_start + 10000.0*t_46_map_2 <= 10000.0\n", - "_C120028: PE2_time_delay_max - t47_end_ - 10000.0*t_47_map_2 >= -10000.0\n", - "_C120029: PE2_time_delay_min - t47_start + 10000.0*t_47_map_2 <= 10000.0\n", - "_C120030: PE2_time_delay_max - t48_end_ - 10000.0*t_48_map_2 >= -10000.0\n", - "_C120031: PE2_time_delay_min - t48_start + 10000.0*t_48_map_2 <= 10000.0\n", - "_C120032: PE2_time_delay_max - t49_end_ - 10000.0*t_49_map_2 >= -10000.0\n", - "_C120033: PE2_time_delay_min - t49_start + 10000.0*t_49_map_2 <= 10000.0\n", - "_C120034: PE2_time_delay_max - t50_end_ - 10000.0*t_50_map_2 >= -10000.0\n", - "_C120035: PE2_time_delay_min - t50_start + 10000.0*t_50_map_2 <= 10000.0\n", - "_C120036: PE2_time_delay_max - t51_end_ - 10000.0*t_51_map_2 >= -10000.0\n", - "_C120037: PE2_time_delay_min - t51_start + 10000.0*t_51_map_2 <= 10000.0\n", - "_C120038: PE2_time_delay_max - t52_end_ - 10000.0*t_52_map_2 >= -10000.0\n", - "_C120039: PE2_time_delay_min - t52_start + 10000.0*t_52_map_2 <= 10000.0\n", - "_C120040: PE2_time_delay_max - t53_end_ - 10000.0*t_53_map_2 >= -10000.0\n", - "_C120041: PE2_time_delay_min - t53_start + 10000.0*t_53_map_2 <= 10000.0\n", - "_C120042: PE2_time_delay_max - t54_end_ - 10000.0*t_54_map_2 >= -10000.0\n", - "_C120043: PE2_time_delay_min - t54_start + 10000.0*t_54_map_2 <= 10000.0\n", - "_C120044: PE2_time_delay_max - t55_end_ - 10000.0*t_55_map_2 >= -10000.0\n", - "_C120045: PE2_time_delay_min - t55_start + 10000.0*t_55_map_2 <= 10000.0\n", - "_C120046: PE2_time_delay_max - t56_end_ - 10000.0*t_56_map_2 >= -10000.0\n", - "_C120047: PE2_time_delay_min - t56_start + 10000.0*t_56_map_2 <= 10000.0\n", - "_C120048: PE2_time_delay_max - t57_end_ - 10000.0*t_57_map_2 >= -10000.0\n", - "_C120049: PE2_time_delay_min - t57_start + 10000.0*t_57_map_2 <= 10000.0\n", - "_C120050: PE2_time_delay_max - t58_end_ - 10000.0*t_58_map_2 >= -10000.0\n", - "_C120051: PE2_time_delay_min - t58_start + 10000.0*t_58_map_2 <= 10000.0\n", - "_C120052: PE2_time_delay_max - t59_end_ - 10000.0*t_59_map_2 >= -10000.0\n", - "_C120053: PE2_time_delay_min - t59_start + 10000.0*t_59_map_2 <= 10000.0\n", - "_C120054: PE2_time_delay_max - t60_end_ - 10000.0*t_60_map_2 >= -10000.0\n", - "_C120055: PE2_time_delay_min - t60_start + 10000.0*t_60_map_2 <= 10000.0\n", - "_C120056: PE2_time_delay_max - t61_end_ - 10000.0*t_61_map_2 >= -10000.0\n", - "_C120057: PE2_time_delay_min - t61_start + 10000.0*t_61_map_2 <= 10000.0\n", - "_C120058: PE2_time_delay_max - t62_end_ - 10000.0*t_62_map_2 >= -10000.0\n", - "_C120059: PE2_time_delay_min - t62_start + 10000.0*t_62_map_2 <= 10000.0\n", - "_C120060: PE2_time_delay_max - t63_end_ - 10000.0*t_63_map_2 >= -10000.0\n", - "_C120061: PE2_time_delay_min - t63_start + 10000.0*t_63_map_2 <= 10000.0\n", - "_C120062: PE2_time_delay_max - t64_end_ - 10000.0*t_64_map_2 >= -10000.0\n", - "_C120063: PE2_time_delay_min - t64_start + 10000.0*t_64_map_2 <= 10000.0\n", - "_C120064: PE2_time_delay_max - t65_end_ - 10000.0*t_65_map_2 >= -10000.0\n", - "_C120065: PE2_time_delay_min - t65_start + 10000.0*t_65_map_2 <= 10000.0\n", - "_C120066: PE2_time_delay_max - t66_end_ - 10000.0*t_66_map_2 >= -10000.0\n", - "_C120067: PE2_time_delay_min - t66_start + 10000.0*t_66_map_2 <= 10000.0\n", - "_C120068: PE2_time_delay_max - t67_end_ - 10000.0*t_67_map_2 >= -10000.0\n", - "_C120069: PE2_time_delay_min - t67_start + 10000.0*t_67_map_2 <= 10000.0\n", - "_C120070: PE2_time_delay_max - t68_end_ - 10000.0*t_68_map_2 >= -10000.0\n", - "_C120071: PE2_time_delay_min - t68_start + 10000.0*t_68_map_2 <= 10000.0\n", - "_C120072: PE2_time_delay_max - t69_end_ - 10000.0*t_69_map_2 >= -10000.0\n", - "_C120073: PE2_time_delay_min - t69_start + 10000.0*t_69_map_2 <= 10000.0\n", - "_C120074: -PE2_time_delay_max + PE2_time_delay_min + PE2_total_time_delay = 0\n", - "_C120075: -PE2_total_time_delay + max_router_delay >= 0\n", - "_C120076: PE2_total_time_delay <= 280\n", - "_C120077: -t0_end_ + t0_start - 10000.0*t_0_map_3 - t_send_0 + task_total_delay_router_router3_task0 >= -10000.0\n", - "_C120078: -10000.0*t_0_map_3 - t_mem_0 + task_total_memory_router_router3_task0 >= -10000.0\n", - "_C120079: -t1_end_ + t1_start - 10000.0*t_1_map_3 - t_send_1 + task_total_delay_router_router3_task1 >= -10000.0\n", - "_C120080: -10000.0*t_1_map_3 - t_mem_1 + task_total_memory_router_router3_task1 >= -10000.0\n", - "_C120081: -t2_end_ + t2_start - 10000.0*t_2_map_3 - t_send_2 + task_total_delay_router_router3_task2 >= -10000.0\n", - "_C120082: -10000.0*t_2_map_3 - t_mem_2 + task_total_memory_router_router3_task2 >= -10000.0\n", - "_C120083: -t3_end_ + t3_start - 10000.0*t_3_map_3 - t_send_3 + task_total_delay_router_router3_task3 >= -10000.0\n", - "_C120084: -10000.0*t_3_map_3 - t_mem_3 + task_total_memory_router_router3_task3 >= -10000.0\n", - "_C120085: -t4_end_ + t4_start - 10000.0*t_4_map_3 - t_send_4 + task_total_delay_router_router3_task4 >= -10000.0\n", - "_C120086: -10000.0*t_4_map_3 - t_mem_4 + task_total_memory_router_router3_task4 >= -10000.0\n", - "_C120087: -t5_end_ + t5_start - 10000.0*t_5_map_3 - t_send_5 + task_total_delay_router_router3_task5 >= -10000.0\n", - "_C120088: -10000.0*t_5_map_3 - t_mem_5 + task_total_memory_router_router3_task5 >= -10000.0\n", - "_C120089: -t6_end_ + t6_start - 10000.0*t_6_map_3 - t_send_6 + task_total_delay_router_router3_task6 >= -10000.0\n", - "_C120090: -10000.0*t_6_map_3 - t_mem_6 + task_total_memory_router_router3_task6 >= -10000.0\n", - "_C120091: -t7_end_ + t7_start - 10000.0*t_7_map_3 - t_send_7 + task_total_delay_router_router3_task7 >= -10000.0\n", - "_C120092: -10000.0*t_7_map_3 - t_mem_7 + task_total_memory_router_router3_task7 >= -10000.0\n", - "_C120093: -t8_end_ + t8_start - 10000.0*t_8_map_3 - t_send_8 + task_total_delay_router_router3_task8 >= -10000.0\n", - "_C120094: -10000.0*t_8_map_3 - t_mem_8 + task_total_memory_router_router3_task8 >= -10000.0\n", - "_C120095: -t9_end_ + t9_start - 10000.0*t_9_map_3 - t_send_9 + task_total_delay_router_router3_task9 >= -10000.0\n", - "_C120096: 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"_C120105: -t14_end_ + t14_start - 10000.0*t_14_map_3 - t_send_14 + task_total_delay_router_router3_task14 >= -10000.0\n", - "_C120106: -10000.0*t_14_map_3 - t_mem_14 + task_total_memory_router_router3_task14 >= -10000.0\n", - "_C120107: -t15_end_ + t15_start - 10000.0*t_15_map_3 - t_send_15 + task_total_delay_router_router3_task15 >= -10000.0\n", - "_C120108: -10000.0*t_15_map_3 - t_mem_15 + task_total_memory_router_router3_task15 >= -10000.0\n", - "_C120109: -t16_end_ + t16_start - 10000.0*t_16_map_3 - t_send_16 + task_total_delay_router_router3_task16 >= -10000.0\n", - "_C120110: -10000.0*t_16_map_3 - t_mem_16 + task_total_memory_router_router3_task16 >= -10000.0\n", - "_C120111: -t17_end_ + t17_start - 10000.0*t_17_map_3 - t_send_17 + task_total_delay_router_router3_task17 >= -10000.0\n", - "_C120112: -10000.0*t_17_map_3 - t_mem_17 + task_total_memory_router_router3_task17 >= -10000.0\n", - "_C120113: -t18_end_ + t18_start - 10000.0*t_18_map_3 - t_send_18 + 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task_total_memory_router_router3_task12 - task_total_memory_router_router3_task13 - task_total_memory_router_router3_task14 - task_total_memory_router_router3_task15 - task_total_memory_router_router3_task16 - task_total_memory_router_router3_task17 - task_total_memory_router_router3_task18 - task_total_memory_router_router3_task19 - task_total_memory_router_router3_task2 - task_total_memory_router_router3_task20 - task_total_memory_router_router3_task21 - task_total_memory_router_router3_task22 - task_total_memory_router_router3_task23 - task_total_memory_router_router3_task24 - task_total_memory_router_router3_task25 - task_total_memory_router_router3_task26 - task_total_memory_router_router3_task27 - task_total_memory_router_router3_task28 - task_total_memory_router_router3_task29 - task_total_memory_router_router3_task3 - task_total_memory_router_router3_task30 - task_total_memory_router_router3_task31 - task_total_memory_router_router3_task32 - task_total_memory_router_router3_task33 - task_total_memory_router_router3_task34 - task_total_memory_router_router3_task35 - task_total_memory_router_router3_task36 - task_total_memory_router_router3_task37 - task_total_memory_router_router3_task38 - task_total_memory_router_router3_task39 - task_total_memory_router_router3_task4 - task_total_memory_router_router3_task40 - task_total_memory_router_router3_task41 - task_total_memory_router_router3_task42 - task_total_memory_router_router3_task43 - task_total_memory_router_router3_task44 - task_total_memory_router_router3_task45 - task_total_memory_router_router3_task46 - task_total_memory_router_router3_task47 - task_total_memory_router_router3_task48 - task_total_memory_router_router3_task49 - task_total_memory_router_router3_task5 - task_total_memory_router_router3_task50 - task_total_memory_router_router3_task51 - task_total_memory_router_router3_task52 - task_total_memory_router_router3_task53 - task_total_memory_router_router3_task54 - task_total_memory_router_router3_task55 - task_total_memory_router_router3_task56 - task_total_memory_router_router3_task57 - task_total_memory_router_router3_task58 - task_total_memory_router_router3_task59 - task_total_memory_router_router3_task6 - task_total_memory_router_router3_task60 - task_total_memory_router_router3_task61 - task_total_memory_router_router3_task62 - task_total_memory_router_router3_task63 - task_total_memory_router_router3_task64 - task_total_memory_router_router3_task65 - task_total_memory_router_router3_task66 - task_total_memory_router_router3_task67 - task_total_memory_router_router3_task68 - task_total_memory_router_router3_task69 - task_total_memory_router_router3_task7 - task_total_memory_router_router3_task8 - task_total_memory_router_router3_task9 >= -0.0\n", - "_C120218: PE3_total_delay - task_total_delay_router_router3_task0 - task_total_delay_router_router3_task1 - task_total_delay_router_router3_task10 - task_total_delay_router_router3_task11 - task_total_delay_router_router3_task12 - task_total_delay_router_router3_task13 - task_total_delay_router_router3_task14 - task_total_delay_router_router3_task15 - task_total_delay_router_router3_task16 - task_total_delay_router_router3_task17 - task_total_delay_router_router3_task18 - task_total_delay_router_router3_task19 - task_total_delay_router_router3_task2 - task_total_delay_router_router3_task20 - task_total_delay_router_router3_task21 - task_total_delay_router_router3_task22 - task_total_delay_router_router3_task23 - task_total_delay_router_router3_task24 - task_total_delay_router_router3_task25 - task_total_delay_router_router3_task26 - task_total_delay_router_router3_task27 - task_total_delay_router_router3_task28 - task_total_delay_router_router3_task29 - task_total_delay_router_router3_task3 - task_total_delay_router_router3_task30 - task_total_delay_router_router3_task31 - task_total_delay_router_router3_task32 - task_total_delay_router_router3_task33 - task_total_delay_router_router3_task34 - task_total_delay_router_router3_task35 - task_total_delay_router_router3_task36 - task_total_delay_router_router3_task37 - task_total_delay_router_router3_task38 - task_total_delay_router_router3_task39 - task_total_delay_router_router3_task4 - task_total_delay_router_router3_task40 - task_total_delay_router_router3_task41 - task_total_delay_router_router3_task42 - task_total_delay_router_router3_task43 - task_total_delay_router_router3_task44 - task_total_delay_router_router3_task45 - task_total_delay_router_router3_task46 - task_total_delay_router_router3_task47 - task_total_delay_router_router3_task48 - task_total_delay_router_router3_task49 - task_total_delay_router_router3_task5 - task_total_delay_router_router3_task50 - task_total_delay_router_router3_task51 - task_total_delay_router_router3_task52 - task_total_delay_router_router3_task53 - task_total_delay_router_router3_task54 - task_total_delay_router_router3_task55 - task_total_delay_router_router3_task56 - task_total_delay_router_router3_task57 - task_total_delay_router_router3_task58 - task_total_delay_router_router3_task59 - task_total_delay_router_router3_task6 - task_total_delay_router_router3_task60 - task_total_delay_router_router3_task61 - task_total_delay_router_router3_task62 - task_total_delay_router_router3_task63 - task_total_delay_router_router3_task64 - task_total_delay_router_router3_task65 - task_total_delay_router_router3_task66 - task_total_delay_router_router3_task67 - task_total_delay_router_router3_task68 - task_total_delay_router_router3_task69 - task_total_delay_router_router3_task7 - task_total_delay_router_router3_task8 - task_total_delay_router_router3_task9 >= -0.0\n", - "_C120219: PE3_total_memory - task_total_memory_router_router3_task0 - task_total_memory_router_router3_task1 - task_total_memory_router_router3_task10 - task_total_memory_router_router3_task11 - task_total_memory_router_router3_task12 - task_total_memory_router_router3_task13 - task_total_memory_router_router3_task14 - task_total_memory_router_router3_task15 - task_total_memory_router_router3_task16 - task_total_memory_router_router3_task17 - task_total_memory_router_router3_task18 - task_total_memory_router_router3_task19 - task_total_memory_router_router3_task2 - task_total_memory_router_router3_task20 - task_total_memory_router_router3_task21 - task_total_memory_router_router3_task22 - task_total_memory_router_router3_task23 - task_total_memory_router_router3_task24 - task_total_memory_router_router3_task25 - task_total_memory_router_router3_task26 - task_total_memory_router_router3_task27 - task_total_memory_router_router3_task28 - task_total_memory_router_router3_task29 - task_total_memory_router_router3_task3 - task_total_memory_router_router3_task30 - task_total_memory_router_router3_task31 - task_total_memory_router_router3_task32 - task_total_memory_router_router3_task33 - task_total_memory_router_router3_task34 - task_total_memory_router_router3_task35 - task_total_memory_router_router3_task36 - task_total_memory_router_router3_task37 - task_total_memory_router_router3_task38 - task_total_memory_router_router3_task39 - task_total_memory_router_router3_task4 - task_total_memory_router_router3_task40 - task_total_memory_router_router3_task41 - task_total_memory_router_router3_task42 - task_total_memory_router_router3_task43 - task_total_memory_router_router3_task44 - task_total_memory_router_router3_task45 - task_total_memory_router_router3_task46 - task_total_memory_router_router3_task47 - task_total_memory_router_router3_task48 - task_total_memory_router_router3_task49 - task_total_memory_router_router3_task5 - task_total_memory_router_router3_task50 - task_total_memory_router_router3_task51 - task_total_memory_router_router3_task52 - task_total_memory_router_router3_task53 - task_total_memory_router_router3_task54 - task_total_memory_router_router3_task55 - task_total_memory_router_router3_task56 - task_total_memory_router_router3_task57 - task_total_memory_router_router3_task58 - task_total_memory_router_router3_task59 - task_total_memory_router_router3_task6 - task_total_memory_router_router3_task60 - task_total_memory_router_router3_task61 - task_total_memory_router_router3_task62 - task_total_memory_router_router3_task63 - task_total_memory_router_router3_task64 - task_total_memory_router_router3_task65 - task_total_memory_router_router3_task66 - task_total_memory_router_router3_task67 - task_total_memory_router_router3_task68 - task_total_memory_router_router3_task69 - task_total_memory_router_router3_task7 - task_total_memory_router_router3_task8 - task_total_memory_router_router3_task9 >= -0.0\n", - "_C120220: -PE_mem_overflow3 + max_memory_overflow >= 0\n", - "_C120221: PE3_time_delay_max - t0_end_ - 10000.0*t_0_map_3 >= -10000.0\n", - "_C120222: PE3_time_delay_min - t0_start + 10000.0*t_0_map_3 <= 10000.0\n", - "_C120223: PE3_time_delay_max - t1_end_ - 10000.0*t_1_map_3 >= -10000.0\n", - "_C120224: PE3_time_delay_min - t1_start + 10000.0*t_1_map_3 <= 10000.0\n", - "_C120225: PE3_time_delay_max - t2_end_ - 10000.0*t_2_map_3 >= -10000.0\n", - "_C120226: PE3_time_delay_min - t2_start + 10000.0*t_2_map_3 <= 10000.0\n", - "_C120227: PE3_time_delay_max - t3_end_ - 10000.0*t_3_map_3 >= -10000.0\n", - "_C120228: PE3_time_delay_min - t3_start + 10000.0*t_3_map_3 <= 10000.0\n", - "_C120229: PE3_time_delay_max - t4_end_ - 10000.0*t_4_map_3 >= -10000.0\n", - "_C120230: PE3_time_delay_min - t4_start + 10000.0*t_4_map_3 <= 10000.0\n", - "_C120231: PE3_time_delay_max - t5_end_ - 10000.0*t_5_map_3 >= -10000.0\n", - "_C120232: PE3_time_delay_min - t5_start + 10000.0*t_5_map_3 <= 10000.0\n", - "_C120233: PE3_time_delay_max - t6_end_ - 10000.0*t_6_map_3 >= -10000.0\n", - "_C120234: PE3_time_delay_min - t6_start + 10000.0*t_6_map_3 <= 10000.0\n", - "_C120235: PE3_time_delay_max - t7_end_ - 10000.0*t_7_map_3 >= -10000.0\n", - "_C120236: PE3_time_delay_min - t7_start + 10000.0*t_7_map_3 <= 10000.0\n", - "_C120237: PE3_time_delay_max - t8_end_ - 10000.0*t_8_map_3 >= -10000.0\n", - "_C120238: PE3_time_delay_min - t8_start + 10000.0*t_8_map_3 <= 10000.0\n", - "_C120239: PE3_time_delay_max - t9_end_ - 10000.0*t_9_map_3 >= -10000.0\n", - "_C120240: PE3_time_delay_min - t9_start + 10000.0*t_9_map_3 <= 10000.0\n", - "_C120241: PE3_time_delay_max - t10_end_ - 10000.0*t_10_map_3 >= -10000.0\n", - "_C120242: PE3_time_delay_min - t10_start + 10000.0*t_10_map_3 <= 10000.0\n", - "_C120243: PE3_time_delay_max - t11_end_ - 10000.0*t_11_map_3 >= -10000.0\n", - "_C120244: PE3_time_delay_min - t11_start + 10000.0*t_11_map_3 <= 10000.0\n", - "_C120245: PE3_time_delay_max - t12_end_ - 10000.0*t_12_map_3 >= -10000.0\n", - "_C120246: PE3_time_delay_min - t12_start + 10000.0*t_12_map_3 <= 10000.0\n", - "_C120247: PE3_time_delay_max - t13_end_ - 10000.0*t_13_map_3 >= -10000.0\n", - "_C120248: PE3_time_delay_min - t13_start + 10000.0*t_13_map_3 <= 10000.0\n", - "_C120249: PE3_time_delay_max - t14_end_ - 10000.0*t_14_map_3 >= -10000.0\n", - "_C120250: PE3_time_delay_min - t14_start + 10000.0*t_14_map_3 <= 10000.0\n", - "_C120251: PE3_time_delay_max - t15_end_ - 10000.0*t_15_map_3 >= -10000.0\n", - "_C120252: PE3_time_delay_min - t15_start + 10000.0*t_15_map_3 <= 10000.0\n", - "_C120253: PE3_time_delay_max - t16_end_ - 10000.0*t_16_map_3 >= -10000.0\n", - "_C120254: PE3_time_delay_min - t16_start + 10000.0*t_16_map_3 <= 10000.0\n", - "_C120255: PE3_time_delay_max - t17_end_ - 10000.0*t_17_map_3 >= -10000.0\n", - "_C120256: PE3_time_delay_min - t17_start + 10000.0*t_17_map_3 <= 10000.0\n", - "_C120257: PE3_time_delay_max - t18_end_ - 10000.0*t_18_map_3 >= -10000.0\n", - "_C120258: PE3_time_delay_min - t18_start + 10000.0*t_18_map_3 <= 10000.0\n", - "_C120259: PE3_time_delay_max - t19_end_ - 10000.0*t_19_map_3 >= -10000.0\n", - "_C120260: PE3_time_delay_min - t19_start + 10000.0*t_19_map_3 <= 10000.0\n", - "_C120261: PE3_time_delay_max - t20_end_ - 10000.0*t_20_map_3 >= -10000.0\n", - "_C120262: PE3_time_delay_min - t20_start + 10000.0*t_20_map_3 <= 10000.0\n", - "_C120263: PE3_time_delay_max - t21_end_ - 10000.0*t_21_map_3 >= -10000.0\n", - "_C120264: PE3_time_delay_min - t21_start + 10000.0*t_21_map_3 <= 10000.0\n", - "_C120265: PE3_time_delay_max - t22_end_ - 10000.0*t_22_map_3 >= -10000.0\n", - "_C120266: PE3_time_delay_min - t22_start + 10000.0*t_22_map_3 <= 10000.0\n", - "_C120267: PE3_time_delay_max - t23_end_ - 10000.0*t_23_map_3 >= -10000.0\n", - "_C120268: PE3_time_delay_min - t23_start + 10000.0*t_23_map_3 <= 10000.0\n", - "_C120269: PE3_time_delay_max - t24_end_ - 10000.0*t_24_map_3 >= -10000.0\n", - "_C120270: PE3_time_delay_min - t24_start + 10000.0*t_24_map_3 <= 10000.0\n", - "_C120271: PE3_time_delay_max - t25_end_ - 10000.0*t_25_map_3 >= -10000.0\n", - "_C120272: PE3_time_delay_min - t25_start + 10000.0*t_25_map_3 <= 10000.0\n", - "_C120273: PE3_time_delay_max - t26_end_ - 10000.0*t_26_map_3 >= -10000.0\n", - "_C120274: PE3_time_delay_min - t26_start + 10000.0*t_26_map_3 <= 10000.0\n", - "_C120275: PE3_time_delay_max - t27_end_ - 10000.0*t_27_map_3 >= -10000.0\n", - "_C120276: PE3_time_delay_min - t27_start + 10000.0*t_27_map_3 <= 10000.0\n", - "_C120277: PE3_time_delay_max - t28_end_ - 10000.0*t_28_map_3 >= -10000.0\n", - "_C120278: PE3_time_delay_min - t28_start + 10000.0*t_28_map_3 <= 10000.0\n", - "_C120279: PE3_time_delay_max - t29_end_ - 10000.0*t_29_map_3 >= -10000.0\n", - "_C120280: PE3_time_delay_min - t29_start + 10000.0*t_29_map_3 <= 10000.0\n", - "_C120281: PE3_time_delay_max - t30_end_ - 10000.0*t_30_map_3 >= -10000.0\n", - "_C120282: PE3_time_delay_min - t30_start + 10000.0*t_30_map_3 <= 10000.0\n", - "_C120283: PE3_time_delay_max - t31_end_ - 10000.0*t_31_map_3 >= -10000.0\n", - "_C120284: PE3_time_delay_min - t31_start + 10000.0*t_31_map_3 <= 10000.0\n", - "_C120285: PE3_time_delay_max - t32_end_ - 10000.0*t_32_map_3 >= -10000.0\n", - "_C120286: PE3_time_delay_min - t32_start + 10000.0*t_32_map_3 <= 10000.0\n", - "_C120287: PE3_time_delay_max - t33_end_ - 10000.0*t_33_map_3 >= -10000.0\n", - "_C120288: PE3_time_delay_min - t33_start + 10000.0*t_33_map_3 <= 10000.0\n", - "_C120289: PE3_time_delay_max - t34_end_ - 10000.0*t_34_map_3 >= -10000.0\n", - "_C120290: PE3_time_delay_min - t34_start + 10000.0*t_34_map_3 <= 10000.0\n", - "_C120291: PE3_time_delay_max - t35_end_ - 10000.0*t_35_map_3 >= -10000.0\n", - "_C120292: PE3_time_delay_min - t35_start + 10000.0*t_35_map_3 <= 10000.0\n", - "_C120293: PE3_time_delay_max - t36_end_ - 10000.0*t_36_map_3 >= -10000.0\n", - "_C120294: PE3_time_delay_min - t36_start + 10000.0*t_36_map_3 <= 10000.0\n", - "_C120295: PE3_time_delay_max - t37_end_ - 10000.0*t_37_map_3 >= -10000.0\n", - "_C120296: PE3_time_delay_min - t37_start + 10000.0*t_37_map_3 <= 10000.0\n", - "_C120297: PE3_time_delay_max - t38_end_ - 10000.0*t_38_map_3 >= -10000.0\n", - "_C120298: PE3_time_delay_min - t38_start + 10000.0*t_38_map_3 <= 10000.0\n", - "_C120299: PE3_time_delay_max - t39_end_ - 10000.0*t_39_map_3 >= -10000.0\n", - "_C120300: PE3_time_delay_min - t39_start + 10000.0*t_39_map_3 <= 10000.0\n", - "_C120301: PE3_time_delay_max - t40_end_ - 10000.0*t_40_map_3 >= -10000.0\n", - "_C120302: PE3_time_delay_min - t40_start + 10000.0*t_40_map_3 <= 10000.0\n", - "_C120303: PE3_time_delay_max - t41_end_ - 10000.0*t_41_map_3 >= -10000.0\n", - "_C120304: PE3_time_delay_min - t41_start + 10000.0*t_41_map_3 <= 10000.0\n", - "_C120305: PE3_time_delay_max - t42_end_ - 10000.0*t_42_map_3 >= -10000.0\n", - "_C120306: PE3_time_delay_min - t42_start + 10000.0*t_42_map_3 <= 10000.0\n", - "_C120307: PE3_time_delay_max - t43_end_ - 10000.0*t_43_map_3 >= -10000.0\n", - "_C120308: PE3_time_delay_min - t43_start + 10000.0*t_43_map_3 <= 10000.0\n", - "_C120309: PE3_time_delay_max - t44_end_ - 10000.0*t_44_map_3 >= -10000.0\n", - "_C120310: PE3_time_delay_min - t44_start + 10000.0*t_44_map_3 <= 10000.0\n", - "_C120311: PE3_time_delay_max - t45_end_ - 10000.0*t_45_map_3 >= -10000.0\n", - "_C120312: PE3_time_delay_min - t45_start + 10000.0*t_45_map_3 <= 10000.0\n", - "_C120313: PE3_time_delay_max - t46_end_ - 10000.0*t_46_map_3 >= -10000.0\n", - "_C120314: PE3_time_delay_min - t46_start + 10000.0*t_46_map_3 <= 10000.0\n", - "_C120315: PE3_time_delay_max - t47_end_ - 10000.0*t_47_map_3 >= -10000.0\n", - "_C120316: PE3_time_delay_min - t47_start + 10000.0*t_47_map_3 <= 10000.0\n", - "_C120317: PE3_time_delay_max - t48_end_ - 10000.0*t_48_map_3 >= -10000.0\n", - "_C120318: PE3_time_delay_min - t48_start + 10000.0*t_48_map_3 <= 10000.0\n", - "_C120319: PE3_time_delay_max - t49_end_ - 10000.0*t_49_map_3 >= -10000.0\n", - "_C120320: PE3_time_delay_min - t49_start + 10000.0*t_49_map_3 <= 10000.0\n", - "_C120321: PE3_time_delay_max - t50_end_ - 10000.0*t_50_map_3 >= -10000.0\n", - "_C120322: PE3_time_delay_min - t50_start + 10000.0*t_50_map_3 <= 10000.0\n", - "_C120323: PE3_time_delay_max - t51_end_ - 10000.0*t_51_map_3 >= -10000.0\n", - "_C120324: PE3_time_delay_min - t51_start + 10000.0*t_51_map_3 <= 10000.0\n", - "_C120325: PE3_time_delay_max - t52_end_ - 10000.0*t_52_map_3 >= -10000.0\n", - "_C120326: PE3_time_delay_min - t52_start + 10000.0*t_52_map_3 <= 10000.0\n", - "_C120327: PE3_time_delay_max - t53_end_ - 10000.0*t_53_map_3 >= -10000.0\n", - "_C120328: PE3_time_delay_min - t53_start + 10000.0*t_53_map_3 <= 10000.0\n", - "_C120329: PE3_time_delay_max - t54_end_ - 10000.0*t_54_map_3 >= -10000.0\n", - "_C120330: PE3_time_delay_min - t54_start + 10000.0*t_54_map_3 <= 10000.0\n", - "_C120331: PE3_time_delay_max - t55_end_ - 10000.0*t_55_map_3 >= -10000.0\n", - "_C120332: PE3_time_delay_min - t55_start + 10000.0*t_55_map_3 <= 10000.0\n", - "_C120333: PE3_time_delay_max - t56_end_ - 10000.0*t_56_map_3 >= -10000.0\n", - "_C120334: PE3_time_delay_min - t56_start + 10000.0*t_56_map_3 <= 10000.0\n", - "_C120335: PE3_time_delay_max - t57_end_ - 10000.0*t_57_map_3 >= -10000.0\n", - "_C120336: PE3_time_delay_min - t57_start + 10000.0*t_57_map_3 <= 10000.0\n", - "_C120337: PE3_time_delay_max - t58_end_ - 10000.0*t_58_map_3 >= -10000.0\n", - "_C120338: PE3_time_delay_min - t58_start + 10000.0*t_58_map_3 <= 10000.0\n", - "_C120339: PE3_time_delay_max - t59_end_ - 10000.0*t_59_map_3 >= -10000.0\n", - "_C120340: PE3_time_delay_min - t59_start + 10000.0*t_59_map_3 <= 10000.0\n", - "_C120341: PE3_time_delay_max - t60_end_ - 10000.0*t_60_map_3 >= -10000.0\n", - "_C120342: PE3_time_delay_min - t60_start + 10000.0*t_60_map_3 <= 10000.0\n", - "_C120343: PE3_time_delay_max - t61_end_ - 10000.0*t_61_map_3 >= -10000.0\n", - "_C120344: PE3_time_delay_min - t61_start + 10000.0*t_61_map_3 <= 10000.0\n", - "_C120345: PE3_time_delay_max - t62_end_ - 10000.0*t_62_map_3 >= -10000.0\n", - "_C120346: PE3_time_delay_min - t62_start + 10000.0*t_62_map_3 <= 10000.0\n", - "_C120347: PE3_time_delay_max - t63_end_ - 10000.0*t_63_map_3 >= -10000.0\n", - "_C120348: PE3_time_delay_min - t63_start + 10000.0*t_63_map_3 <= 10000.0\n", - "_C120349: PE3_time_delay_max - t64_end_ - 10000.0*t_64_map_3 >= -10000.0\n", - "_C120350: PE3_time_delay_min - t64_start + 10000.0*t_64_map_3 <= 10000.0\n", - "_C120351: PE3_time_delay_max - t65_end_ - 10000.0*t_65_map_3 >= -10000.0\n", - "_C120352: PE3_time_delay_min - t65_start + 10000.0*t_65_map_3 <= 10000.0\n", - "_C120353: PE3_time_delay_max - t66_end_ - 10000.0*t_66_map_3 >= -10000.0\n", - "_C120354: PE3_time_delay_min - t66_start + 10000.0*t_66_map_3 <= 10000.0\n", - "_C120355: PE3_time_delay_max - t67_end_ - 10000.0*t_67_map_3 >= -10000.0\n", - "_C120356: PE3_time_delay_min - t67_start + 10000.0*t_67_map_3 <= 10000.0\n", - "_C120357: PE3_time_delay_max - t68_end_ - 10000.0*t_68_map_3 >= -10000.0\n", - "_C120358: PE3_time_delay_min - t68_start + 10000.0*t_68_map_3 <= 10000.0\n", - "_C120359: PE3_time_delay_max - t69_end_ - 10000.0*t_69_map_3 >= -10000.0\n", - "_C120360: PE3_time_delay_min - t69_start + 10000.0*t_69_map_3 <= 10000.0\n", - "_C120361: -PE3_time_delay_max + PE3_time_delay_min + PE3_total_time_delay = 0\n", - "_C120362: -PE3_total_time_delay + max_router_delay >= 0\n", - "_C120363: PE3_total_time_delay <= 280\n", - "_C120364: -t0_end_ + t0_start - 10000.0*t_0_map_4 - t_send_0 + task_total_delay_router_router4_task0 >= -10000.0\n", - "_C120365: -10000.0*t_0_map_4 - t_mem_0 + task_total_memory_router_router4_task0 >= -10000.0\n", - "_C120366: -t1_end_ + t1_start - 10000.0*t_1_map_4 - t_send_1 + task_total_delay_router_router4_task1 >= -10000.0\n", - "_C120367: -10000.0*t_1_map_4 - t_mem_1 + task_total_memory_router_router4_task1 >= -10000.0\n", - "_C120368: -t2_end_ + t2_start - 10000.0*t_2_map_4 - t_send_2 + task_total_delay_router_router4_task2 >= -10000.0\n", - "_C120369: -10000.0*t_2_map_4 - t_mem_2 + task_total_memory_router_router4_task2 >= -10000.0\n", - 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task_total_memory_router_router4_task68 >= -10000.0\n", - "_C120502: -t69_end_ + t69_start - 10000.0*t_69_map_4 - t_send_69 + task_total_delay_router_router4_task69 >= -10000.0\n", - "_C120503: -10000.0*t_69_map_4 - t_mem_69 + task_total_memory_router_router4_task69 >= -10000.0\n", - "_C120504: PE_mem_overflow4 - task_total_memory_router_router4_task0 - task_total_memory_router_router4_task1 - task_total_memory_router_router4_task10 - task_total_memory_router_router4_task11 - task_total_memory_router_router4_task12 - task_total_memory_router_router4_task13 - task_total_memory_router_router4_task14 - task_total_memory_router_router4_task15 - task_total_memory_router_router4_task16 - task_total_memory_router_router4_task17 - task_total_memory_router_router4_task18 - task_total_memory_router_router4_task19 - task_total_memory_router_router4_task2 - task_total_memory_router_router4_task20 - task_total_memory_router_router4_task21 - task_total_memory_router_router4_task22 - task_total_memory_router_router4_task23 - task_total_memory_router_router4_task24 - task_total_memory_router_router4_task25 - task_total_memory_router_router4_task26 - task_total_memory_router_router4_task27 - task_total_memory_router_router4_task28 - task_total_memory_router_router4_task29 - task_total_memory_router_router4_task3 - task_total_memory_router_router4_task30 - task_total_memory_router_router4_task31 - task_total_memory_router_router4_task32 - task_total_memory_router_router4_task33 - task_total_memory_router_router4_task34 - task_total_memory_router_router4_task35 - task_total_memory_router_router4_task36 - task_total_memory_router_router4_task37 - task_total_memory_router_router4_task38 - task_total_memory_router_router4_task39 - task_total_memory_router_router4_task4 - task_total_memory_router_router4_task40 - task_total_memory_router_router4_task41 - task_total_memory_router_router4_task42 - task_total_memory_router_router4_task43 - task_total_memory_router_router4_task44 - task_total_memory_router_router4_task45 - task_total_memory_router_router4_task46 - task_total_memory_router_router4_task47 - task_total_memory_router_router4_task48 - task_total_memory_router_router4_task49 - task_total_memory_router_router4_task5 - task_total_memory_router_router4_task50 - task_total_memory_router_router4_task51 - task_total_memory_router_router4_task52 - task_total_memory_router_router4_task53 - task_total_memory_router_router4_task54 - task_total_memory_router_router4_task55 - task_total_memory_router_router4_task56 - task_total_memory_router_router4_task57 - task_total_memory_router_router4_task58 - task_total_memory_router_router4_task59 - task_total_memory_router_router4_task6 - task_total_memory_router_router4_task60 - task_total_memory_router_router4_task61 - task_total_memory_router_router4_task62 - task_total_memory_router_router4_task63 - task_total_memory_router_router4_task64 - task_total_memory_router_router4_task65 - task_total_memory_router_router4_task66 - task_total_memory_router_router4_task67 - task_total_memory_router_router4_task68 - task_total_memory_router_router4_task69 - task_total_memory_router_router4_task7 - task_total_memory_router_router4_task8 - task_total_memory_router_router4_task9 >= -0.0\n", - "_C120505: PE4_total_delay - task_total_delay_router_router4_task0 - task_total_delay_router_router4_task1 - task_total_delay_router_router4_task10 - task_total_delay_router_router4_task11 - task_total_delay_router_router4_task12 - task_total_delay_router_router4_task13 - task_total_delay_router_router4_task14 - task_total_delay_router_router4_task15 - task_total_delay_router_router4_task16 - task_total_delay_router_router4_task17 - task_total_delay_router_router4_task18 - task_total_delay_router_router4_task19 - task_total_delay_router_router4_task2 - task_total_delay_router_router4_task20 - task_total_delay_router_router4_task21 - task_total_delay_router_router4_task22 - task_total_delay_router_router4_task23 - task_total_delay_router_router4_task24 - task_total_delay_router_router4_task25 - task_total_delay_router_router4_task26 - task_total_delay_router_router4_task27 - task_total_delay_router_router4_task28 - task_total_delay_router_router4_task29 - task_total_delay_router_router4_task3 - task_total_delay_router_router4_task30 - task_total_delay_router_router4_task31 - task_total_delay_router_router4_task32 - task_total_delay_router_router4_task33 - task_total_delay_router_router4_task34 - task_total_delay_router_router4_task35 - task_total_delay_router_router4_task36 - task_total_delay_router_router4_task37 - task_total_delay_router_router4_task38 - task_total_delay_router_router4_task39 - task_total_delay_router_router4_task4 - task_total_delay_router_router4_task40 - task_total_delay_router_router4_task41 - task_total_delay_router_router4_task42 - task_total_delay_router_router4_task43 - task_total_delay_router_router4_task44 - task_total_delay_router_router4_task45 - task_total_delay_router_router4_task46 - task_total_delay_router_router4_task47 - task_total_delay_router_router4_task48 - task_total_delay_router_router4_task49 - task_total_delay_router_router4_task5 - task_total_delay_router_router4_task50 - task_total_delay_router_router4_task51 - task_total_delay_router_router4_task52 - task_total_delay_router_router4_task53 - task_total_delay_router_router4_task54 - task_total_delay_router_router4_task55 - task_total_delay_router_router4_task56 - task_total_delay_router_router4_task57 - task_total_delay_router_router4_task58 - task_total_delay_router_router4_task59 - task_total_delay_router_router4_task6 - task_total_delay_router_router4_task60 - task_total_delay_router_router4_task61 - task_total_delay_router_router4_task62 - task_total_delay_router_router4_task63 - task_total_delay_router_router4_task64 - task_total_delay_router_router4_task65 - task_total_delay_router_router4_task66 - task_total_delay_router_router4_task67 - task_total_delay_router_router4_task68 - task_total_delay_router_router4_task69 - task_total_delay_router_router4_task7 - task_total_delay_router_router4_task8 - task_total_delay_router_router4_task9 >= -0.0\n", - "_C120506: PE4_total_memory - task_total_memory_router_router4_task0 - task_total_memory_router_router4_task1 - task_total_memory_router_router4_task10 - task_total_memory_router_router4_task11 - task_total_memory_router_router4_task12 - task_total_memory_router_router4_task13 - task_total_memory_router_router4_task14 - task_total_memory_router_router4_task15 - task_total_memory_router_router4_task16 - task_total_memory_router_router4_task17 - task_total_memory_router_router4_task18 - task_total_memory_router_router4_task19 - task_total_memory_router_router4_task2 - task_total_memory_router_router4_task20 - task_total_memory_router_router4_task21 - task_total_memory_router_router4_task22 - task_total_memory_router_router4_task23 - task_total_memory_router_router4_task24 - task_total_memory_router_router4_task25 - task_total_memory_router_router4_task26 - task_total_memory_router_router4_task27 - task_total_memory_router_router4_task28 - task_total_memory_router_router4_task29 - task_total_memory_router_router4_task3 - task_total_memory_router_router4_task30 - task_total_memory_router_router4_task31 - task_total_memory_router_router4_task32 - task_total_memory_router_router4_task33 - task_total_memory_router_router4_task34 - task_total_memory_router_router4_task35 - task_total_memory_router_router4_task36 - task_total_memory_router_router4_task37 - task_total_memory_router_router4_task38 - task_total_memory_router_router4_task39 - task_total_memory_router_router4_task4 - task_total_memory_router_router4_task40 - task_total_memory_router_router4_task41 - task_total_memory_router_router4_task42 - task_total_memory_router_router4_task43 - task_total_memory_router_router4_task44 - task_total_memory_router_router4_task45 - task_total_memory_router_router4_task46 - task_total_memory_router_router4_task47 - task_total_memory_router_router4_task48 - task_total_memory_router_router4_task49 - task_total_memory_router_router4_task5 - task_total_memory_router_router4_task50 - task_total_memory_router_router4_task51 - task_total_memory_router_router4_task52 - task_total_memory_router_router4_task53 - task_total_memory_router_router4_task54 - task_total_memory_router_router4_task55 - task_total_memory_router_router4_task56 - task_total_memory_router_router4_task57 - task_total_memory_router_router4_task58 - task_total_memory_router_router4_task59 - task_total_memory_router_router4_task6 - task_total_memory_router_router4_task60 - task_total_memory_router_router4_task61 - task_total_memory_router_router4_task62 - task_total_memory_router_router4_task63 - task_total_memory_router_router4_task64 - task_total_memory_router_router4_task65 - task_total_memory_router_router4_task66 - task_total_memory_router_router4_task67 - task_total_memory_router_router4_task68 - task_total_memory_router_router4_task69 - task_total_memory_router_router4_task7 - task_total_memory_router_router4_task8 - task_total_memory_router_router4_task9 >= -0.0\n", - "_C120507: -PE_mem_overflow4 + max_memory_overflow >= 0\n", - "_C120508: PE4_time_delay_max - t0_end_ - 10000.0*t_0_map_4 >= -10000.0\n", - "_C120509: PE4_time_delay_min - t0_start + 10000.0*t_0_map_4 <= 10000.0\n", - "_C120510: PE4_time_delay_max - t1_end_ - 10000.0*t_1_map_4 >= -10000.0\n", - "_C120511: PE4_time_delay_min - t1_start + 10000.0*t_1_map_4 <= 10000.0\n", - "_C120512: PE4_time_delay_max - t2_end_ - 10000.0*t_2_map_4 >= -10000.0\n", - "_C120513: PE4_time_delay_min - t2_start + 10000.0*t_2_map_4 <= 10000.0\n", - "_C120514: PE4_time_delay_max - t3_end_ - 10000.0*t_3_map_4 >= -10000.0\n", - "_C120515: PE4_time_delay_min - t3_start + 10000.0*t_3_map_4 <= 10000.0\n", - "_C120516: PE4_time_delay_max - t4_end_ - 10000.0*t_4_map_4 >= -10000.0\n", - "_C120517: PE4_time_delay_min - t4_start + 10000.0*t_4_map_4 <= 10000.0\n", - "_C120518: PE4_time_delay_max - t5_end_ - 10000.0*t_5_map_4 >= -10000.0\n", - "_C120519: PE4_time_delay_min - t5_start + 10000.0*t_5_map_4 <= 10000.0\n", - "_C120520: PE4_time_delay_max - t6_end_ - 10000.0*t_6_map_4 >= -10000.0\n", - "_C120521: PE4_time_delay_min - t6_start + 10000.0*t_6_map_4 <= 10000.0\n", - "_C120522: PE4_time_delay_max - t7_end_ - 10000.0*t_7_map_4 >= -10000.0\n", - "_C120523: PE4_time_delay_min - t7_start + 10000.0*t_7_map_4 <= 10000.0\n", - "_C120524: PE4_time_delay_max - t8_end_ - 10000.0*t_8_map_4 >= -10000.0\n", - "_C120525: PE4_time_delay_min - t8_start + 10000.0*t_8_map_4 <= 10000.0\n", - "_C120526: PE4_time_delay_max - t9_end_ - 10000.0*t_9_map_4 >= -10000.0\n", - "_C120527: PE4_time_delay_min - t9_start + 10000.0*t_9_map_4 <= 10000.0\n", - "_C120528: PE4_time_delay_max - t10_end_ - 10000.0*t_10_map_4 >= -10000.0\n", - "_C120529: PE4_time_delay_min - t10_start + 10000.0*t_10_map_4 <= 10000.0\n", - "_C120530: PE4_time_delay_max - t11_end_ - 10000.0*t_11_map_4 >= -10000.0\n", - "_C120531: PE4_time_delay_min - t11_start + 10000.0*t_11_map_4 <= 10000.0\n", - "_C120532: PE4_time_delay_max - t12_end_ - 10000.0*t_12_map_4 >= -10000.0\n", - "_C120533: PE4_time_delay_min - t12_start + 10000.0*t_12_map_4 <= 10000.0\n", - "_C120534: PE4_time_delay_max - t13_end_ - 10000.0*t_13_map_4 >= -10000.0\n", - "_C120535: PE4_time_delay_min - t13_start + 10000.0*t_13_map_4 <= 10000.0\n", - "_C120536: PE4_time_delay_max - t14_end_ - 10000.0*t_14_map_4 >= -10000.0\n", - "_C120537: PE4_time_delay_min - t14_start + 10000.0*t_14_map_4 <= 10000.0\n", - "_C120538: PE4_time_delay_max - t15_end_ - 10000.0*t_15_map_4 >= -10000.0\n", - "_C120539: PE4_time_delay_min - t15_start + 10000.0*t_15_map_4 <= 10000.0\n", - "_C120540: PE4_time_delay_max - t16_end_ - 10000.0*t_16_map_4 >= -10000.0\n", - "_C120541: PE4_time_delay_min - t16_start + 10000.0*t_16_map_4 <= 10000.0\n", - "_C120542: PE4_time_delay_max - t17_end_ - 10000.0*t_17_map_4 >= -10000.0\n", - "_C120543: PE4_time_delay_min - t17_start + 10000.0*t_17_map_4 <= 10000.0\n", - "_C120544: PE4_time_delay_max - t18_end_ - 10000.0*t_18_map_4 >= -10000.0\n", - "_C120545: PE4_time_delay_min - t18_start + 10000.0*t_18_map_4 <= 10000.0\n", - "_C120546: PE4_time_delay_max - t19_end_ - 10000.0*t_19_map_4 >= -10000.0\n", - "_C120547: PE4_time_delay_min - t19_start + 10000.0*t_19_map_4 <= 10000.0\n", - "_C120548: PE4_time_delay_max - t20_end_ - 10000.0*t_20_map_4 >= -10000.0\n", - "_C120549: PE4_time_delay_min - t20_start + 10000.0*t_20_map_4 <= 10000.0\n", - "_C120550: PE4_time_delay_max - t21_end_ - 10000.0*t_21_map_4 >= -10000.0\n", - "_C120551: PE4_time_delay_min - t21_start + 10000.0*t_21_map_4 <= 10000.0\n", - "_C120552: PE4_time_delay_max - t22_end_ - 10000.0*t_22_map_4 >= -10000.0\n", - "_C120553: PE4_time_delay_min - t22_start + 10000.0*t_22_map_4 <= 10000.0\n", - "_C120554: PE4_time_delay_max - t23_end_ - 10000.0*t_23_map_4 >= -10000.0\n", - "_C120555: PE4_time_delay_min - t23_start + 10000.0*t_23_map_4 <= 10000.0\n", - "_C120556: PE4_time_delay_max - t24_end_ - 10000.0*t_24_map_4 >= -10000.0\n", - "_C120557: PE4_time_delay_min - t24_start + 10000.0*t_24_map_4 <= 10000.0\n", - "_C120558: PE4_time_delay_max - t25_end_ - 10000.0*t_25_map_4 >= -10000.0\n", - "_C120559: PE4_time_delay_min - t25_start + 10000.0*t_25_map_4 <= 10000.0\n", - "_C120560: PE4_time_delay_max - t26_end_ - 10000.0*t_26_map_4 >= -10000.0\n", - "_C120561: PE4_time_delay_min - t26_start + 10000.0*t_26_map_4 <= 10000.0\n", - "_C120562: PE4_time_delay_max - t27_end_ - 10000.0*t_27_map_4 >= -10000.0\n", - "_C120563: PE4_time_delay_min - t27_start + 10000.0*t_27_map_4 <= 10000.0\n", - "_C120564: PE4_time_delay_max - t28_end_ - 10000.0*t_28_map_4 >= -10000.0\n", - "_C120565: PE4_time_delay_min - t28_start + 10000.0*t_28_map_4 <= 10000.0\n", - "_C120566: PE4_time_delay_max - t29_end_ - 10000.0*t_29_map_4 >= -10000.0\n", - "_C120567: PE4_time_delay_min - t29_start + 10000.0*t_29_map_4 <= 10000.0\n", - "_C120568: PE4_time_delay_max - t30_end_ - 10000.0*t_30_map_4 >= -10000.0\n", - "_C120569: PE4_time_delay_min - t30_start + 10000.0*t_30_map_4 <= 10000.0\n", - "_C120570: PE4_time_delay_max - t31_end_ - 10000.0*t_31_map_4 >= -10000.0\n", - "_C120571: PE4_time_delay_min - t31_start + 10000.0*t_31_map_4 <= 10000.0\n", - "_C120572: PE4_time_delay_max - t32_end_ - 10000.0*t_32_map_4 >= -10000.0\n", - "_C120573: PE4_time_delay_min - t32_start + 10000.0*t_32_map_4 <= 10000.0\n", - "_C120574: PE4_time_delay_max - t33_end_ - 10000.0*t_33_map_4 >= -10000.0\n", - "_C120575: PE4_time_delay_min - t33_start + 10000.0*t_33_map_4 <= 10000.0\n", - "_C120576: PE4_time_delay_max - t34_end_ - 10000.0*t_34_map_4 >= -10000.0\n", - "_C120577: PE4_time_delay_min - t34_start + 10000.0*t_34_map_4 <= 10000.0\n", - "_C120578: PE4_time_delay_max - t35_end_ - 10000.0*t_35_map_4 >= -10000.0\n", - "_C120579: PE4_time_delay_min - t35_start + 10000.0*t_35_map_4 <= 10000.0\n", - "_C120580: PE4_time_delay_max - t36_end_ - 10000.0*t_36_map_4 >= -10000.0\n", - "_C120581: PE4_time_delay_min - t36_start + 10000.0*t_36_map_4 <= 10000.0\n", - "_C120582: PE4_time_delay_max - t37_end_ - 10000.0*t_37_map_4 >= -10000.0\n", - "_C120583: PE4_time_delay_min - t37_start + 10000.0*t_37_map_4 <= 10000.0\n", - "_C120584: PE4_time_delay_max - t38_end_ - 10000.0*t_38_map_4 >= -10000.0\n", - "_C120585: PE4_time_delay_min - t38_start + 10000.0*t_38_map_4 <= 10000.0\n", - "_C120586: PE4_time_delay_max - t39_end_ - 10000.0*t_39_map_4 >= -10000.0\n", - "_C120587: PE4_time_delay_min - t39_start + 10000.0*t_39_map_4 <= 10000.0\n", - "_C120588: PE4_time_delay_max - t40_end_ - 10000.0*t_40_map_4 >= -10000.0\n", - "_C120589: PE4_time_delay_min - t40_start + 10000.0*t_40_map_4 <= 10000.0\n", - "_C120590: PE4_time_delay_max - t41_end_ - 10000.0*t_41_map_4 >= -10000.0\n", - "_C120591: PE4_time_delay_min - t41_start + 10000.0*t_41_map_4 <= 10000.0\n", - "_C120592: PE4_time_delay_max - t42_end_ - 10000.0*t_42_map_4 >= -10000.0\n", - "_C120593: PE4_time_delay_min - t42_start + 10000.0*t_42_map_4 <= 10000.0\n", - "_C120594: PE4_time_delay_max - t43_end_ - 10000.0*t_43_map_4 >= -10000.0\n", - "_C120595: PE4_time_delay_min - t43_start + 10000.0*t_43_map_4 <= 10000.0\n", - "_C120596: PE4_time_delay_max - t44_end_ - 10000.0*t_44_map_4 >= -10000.0\n", - "_C120597: PE4_time_delay_min - t44_start + 10000.0*t_44_map_4 <= 10000.0\n", - "_C120598: PE4_time_delay_max - t45_end_ - 10000.0*t_45_map_4 >= -10000.0\n", - "_C120599: PE4_time_delay_min - t45_start + 10000.0*t_45_map_4 <= 10000.0\n", - "_C120600: PE4_time_delay_max - t46_end_ - 10000.0*t_46_map_4 >= -10000.0\n", - "_C120601: PE4_time_delay_min - t46_start + 10000.0*t_46_map_4 <= 10000.0\n", - "_C120602: PE4_time_delay_max - t47_end_ - 10000.0*t_47_map_4 >= -10000.0\n", - "_C120603: PE4_time_delay_min - t47_start + 10000.0*t_47_map_4 <= 10000.0\n", - "_C120604: PE4_time_delay_max - t48_end_ - 10000.0*t_48_map_4 >= -10000.0\n", - "_C120605: PE4_time_delay_min - t48_start + 10000.0*t_48_map_4 <= 10000.0\n", - "_C120606: PE4_time_delay_max - t49_end_ - 10000.0*t_49_map_4 >= -10000.0\n", - "_C120607: PE4_time_delay_min - t49_start + 10000.0*t_49_map_4 <= 10000.0\n", - "_C120608: PE4_time_delay_max - t50_end_ - 10000.0*t_50_map_4 >= -10000.0\n", - "_C120609: PE4_time_delay_min - t50_start + 10000.0*t_50_map_4 <= 10000.0\n", - "_C120610: PE4_time_delay_max - t51_end_ - 10000.0*t_51_map_4 >= -10000.0\n", - "_C120611: PE4_time_delay_min - t51_start + 10000.0*t_51_map_4 <= 10000.0\n", - "_C120612: PE4_time_delay_max - t52_end_ - 10000.0*t_52_map_4 >= -10000.0\n", - "_C120613: PE4_time_delay_min - t52_start + 10000.0*t_52_map_4 <= 10000.0\n", - "_C120614: PE4_time_delay_max - t53_end_ - 10000.0*t_53_map_4 >= -10000.0\n", - "_C120615: PE4_time_delay_min - t53_start + 10000.0*t_53_map_4 <= 10000.0\n", - "_C120616: PE4_time_delay_max - t54_end_ - 10000.0*t_54_map_4 >= -10000.0\n", - "_C120617: PE4_time_delay_min - t54_start + 10000.0*t_54_map_4 <= 10000.0\n", - "_C120618: PE4_time_delay_max - t55_end_ - 10000.0*t_55_map_4 >= -10000.0\n", - "_C120619: PE4_time_delay_min - t55_start + 10000.0*t_55_map_4 <= 10000.0\n", - "_C120620: PE4_time_delay_max - t56_end_ - 10000.0*t_56_map_4 >= -10000.0\n", - "_C120621: PE4_time_delay_min - t56_start + 10000.0*t_56_map_4 <= 10000.0\n", - "_C120622: PE4_time_delay_max - t57_end_ - 10000.0*t_57_map_4 >= -10000.0\n", - "_C120623: PE4_time_delay_min - t57_start + 10000.0*t_57_map_4 <= 10000.0\n", - "_C120624: PE4_time_delay_max - t58_end_ - 10000.0*t_58_map_4 >= -10000.0\n", - "_C120625: PE4_time_delay_min - t58_start + 10000.0*t_58_map_4 <= 10000.0\n", - "_C120626: PE4_time_delay_max - t59_end_ - 10000.0*t_59_map_4 >= -10000.0\n", - "_C120627: PE4_time_delay_min - t59_start + 10000.0*t_59_map_4 <= 10000.0\n", - "_C120628: PE4_time_delay_max - t60_end_ - 10000.0*t_60_map_4 >= -10000.0\n", - "_C120629: PE4_time_delay_min - t60_start + 10000.0*t_60_map_4 <= 10000.0\n", - "_C120630: PE4_time_delay_max - t61_end_ - 10000.0*t_61_map_4 >= -10000.0\n", - "_C120631: PE4_time_delay_min - t61_start + 10000.0*t_61_map_4 <= 10000.0\n", - "_C120632: PE4_time_delay_max - t62_end_ - 10000.0*t_62_map_4 >= -10000.0\n", - "_C120633: PE4_time_delay_min - t62_start + 10000.0*t_62_map_4 <= 10000.0\n", - "_C120634: PE4_time_delay_max - t63_end_ - 10000.0*t_63_map_4 >= -10000.0\n", - "_C120635: PE4_time_delay_min - t63_start + 10000.0*t_63_map_4 <= 10000.0\n", - "_C120636: PE4_time_delay_max - t64_end_ - 10000.0*t_64_map_4 >= -10000.0\n", - "_C120637: PE4_time_delay_min - t64_start + 10000.0*t_64_map_4 <= 10000.0\n", - "_C120638: PE4_time_delay_max - t65_end_ - 10000.0*t_65_map_4 >= -10000.0\n", - "_C120639: PE4_time_delay_min - t65_start + 10000.0*t_65_map_4 <= 10000.0\n", - "_C120640: PE4_time_delay_max - t66_end_ - 10000.0*t_66_map_4 >= -10000.0\n", - "_C120641: PE4_time_delay_min - t66_start + 10000.0*t_66_map_4 <= 10000.0\n", - "_C120642: PE4_time_delay_max - t67_end_ - 10000.0*t_67_map_4 >= -10000.0\n", - "_C120643: PE4_time_delay_min - t67_start + 10000.0*t_67_map_4 <= 10000.0\n", - "_C120644: PE4_time_delay_max - t68_end_ - 10000.0*t_68_map_4 >= -10000.0\n", - "_C120645: PE4_time_delay_min - t68_start + 10000.0*t_68_map_4 <= 10000.0\n", - "_C120646: PE4_time_delay_max - t69_end_ - 10000.0*t_69_map_4 >= -10000.0\n", - "_C120647: PE4_time_delay_min - t69_start + 10000.0*t_69_map_4 <= 10000.0\n", - "_C120648: -PE4_time_delay_max + PE4_time_delay_min + PE4_total_time_delay = 0\n", - "_C120649: -PE4_total_time_delay + max_router_delay >= 0\n", - "_C120650: PE4_total_time_delay <= 280\n", - "_C120651: -t0_end_ + t0_start - 10000.0*t_0_map_5 - t_send_0 + task_total_delay_router_router5_task0 >= -10000.0\n", - "_C120652: -10000.0*t_0_map_5 - t_mem_0 + task_total_memory_router_router5_task0 >= -10000.0\n", - "_C120653: -t1_end_ + t1_start - 10000.0*t_1_map_5 - t_send_1 + task_total_delay_router_router5_task1 >= -10000.0\n", - "_C120654: -10000.0*t_1_map_5 - t_mem_1 + task_total_memory_router_router5_task1 >= -10000.0\n", - "_C120655: -t2_end_ + t2_start - 10000.0*t_2_map_5 - t_send_2 + task_total_delay_router_router5_task2 >= -10000.0\n", - "_C120656: -10000.0*t_2_map_5 - t_mem_2 + task_total_memory_router_router5_task2 >= -10000.0\n", - "_C120657: -t3_end_ + t3_start - 10000.0*t_3_map_5 - t_send_3 + task_total_delay_router_router5_task3 >= -10000.0\n", - "_C120658: -10000.0*t_3_map_5 - t_mem_3 + task_total_memory_router_router5_task3 >= -10000.0\n", - "_C120659: -t4_end_ + t4_start - 10000.0*t_4_map_5 - t_send_4 + task_total_delay_router_router5_task4 >= -10000.0\n", - "_C120660: -10000.0*t_4_map_5 - t_mem_4 + task_total_memory_router_router5_task4 >= -10000.0\n", - "_C120661: -t5_end_ + t5_start - 10000.0*t_5_map_5 - t_send_5 + task_total_delay_router_router5_task5 >= -10000.0\n", - "_C120662: -10000.0*t_5_map_5 - t_mem_5 + task_total_memory_router_router5_task5 >= -10000.0\n", - "_C120663: -t6_end_ + t6_start - 10000.0*t_6_map_5 - t_send_6 + task_total_delay_router_router5_task6 >= -10000.0\n", - "_C120664: -10000.0*t_6_map_5 - t_mem_6 + task_total_memory_router_router5_task6 >= -10000.0\n", - "_C120665: -t7_end_ + t7_start - 10000.0*t_7_map_5 - t_send_7 + task_total_delay_router_router5_task7 >= -10000.0\n", - "_C120666: -10000.0*t_7_map_5 - t_mem_7 + task_total_memory_router_router5_task7 >= -10000.0\n", - "_C120667: -t8_end_ + t8_start - 10000.0*t_8_map_5 - t_send_8 + task_total_delay_router_router5_task8 >= -10000.0\n", - "_C120668: -10000.0*t_8_map_5 - t_mem_8 + task_total_memory_router_router5_task8 >= -10000.0\n", - "_C120669: -t9_end_ + t9_start - 10000.0*t_9_map_5 - t_send_9 + task_total_delay_router_router5_task9 >= -10000.0\n", - "_C120670: -10000.0*t_9_map_5 - t_mem_9 + task_total_memory_router_router5_task9 >= -10000.0\n", - "_C120671: -t10_end_ + t10_start - 10000.0*t_10_map_5 - t_send_10 + task_total_delay_router_router5_task10 >= -10000.0\n", - "_C120672: -10000.0*t_10_map_5 - t_mem_10 + task_total_memory_router_router5_task10 >= -10000.0\n", - "_C120673: -t11_end_ + t11_start - 10000.0*t_11_map_5 - t_send_11 + task_total_delay_router_router5_task11 >= -10000.0\n", - "_C120674: -10000.0*t_11_map_5 - t_mem_11 + task_total_memory_router_router5_task11 >= -10000.0\n", - "_C120675: -t12_end_ + t12_start - 10000.0*t_12_map_5 - t_send_12 + task_total_delay_router_router5_task12 >= -10000.0\n", - "_C120676: -10000.0*t_12_map_5 - t_mem_12 + task_total_memory_router_router5_task12 >= -10000.0\n", - "_C120677: -t13_end_ + t13_start - 10000.0*t_13_map_5 - t_send_13 + task_total_delay_router_router5_task13 >= -10000.0\n", - "_C120678: -10000.0*t_13_map_5 - t_mem_13 + task_total_memory_router_router5_task13 >= -10000.0\n", - "_C120679: -t14_end_ + t14_start - 10000.0*t_14_map_5 - t_send_14 + task_total_delay_router_router5_task14 >= -10000.0\n", - "_C120680: -10000.0*t_14_map_5 - t_mem_14 + task_total_memory_router_router5_task14 >= -10000.0\n", - "_C120681: -t15_end_ + t15_start - 10000.0*t_15_map_5 - t_send_15 + task_total_delay_router_router5_task15 >= -10000.0\n", - "_C120682: -10000.0*t_15_map_5 - t_mem_15 + task_total_memory_router_router5_task15 >= -10000.0\n", - "_C120683: -t16_end_ + t16_start - 10000.0*t_16_map_5 - t_send_16 + task_total_delay_router_router5_task16 >= -10000.0\n", - "_C120684: -10000.0*t_16_map_5 - t_mem_16 + task_total_memory_router_router5_task16 >= -10000.0\n", - "_C120685: -t17_end_ + t17_start - 10000.0*t_17_map_5 - t_send_17 + task_total_delay_router_router5_task17 >= -10000.0\n", - "_C120686: -10000.0*t_17_map_5 - t_mem_17 + task_total_memory_router_router5_task17 >= -10000.0\n", - "_C120687: -t18_end_ + t18_start - 10000.0*t_18_map_5 - t_send_18 + task_total_delay_router_router5_task18 >= -10000.0\n", - 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task_total_delay_router_router5_task27 >= -10000.0\n", - "_C120706: -10000.0*t_27_map_5 - t_mem_27 + task_total_memory_router_router5_task27 >= -10000.0\n", - "_C120707: -t28_end_ + t28_start - 10000.0*t_28_map_5 - t_send_28 + task_total_delay_router_router5_task28 >= -10000.0\n", - "_C120708: -10000.0*t_28_map_5 - t_mem_28 + task_total_memory_router_router5_task28 >= -10000.0\n", - "_C120709: -t29_end_ + t29_start - 10000.0*t_29_map_5 - t_send_29 + task_total_delay_router_router5_task29 >= -10000.0\n", - "_C120710: -10000.0*t_29_map_5 - t_mem_29 + task_total_memory_router_router5_task29 >= -10000.0\n", - "_C120711: -t30_end_ + t30_start - 10000.0*t_30_map_5 - t_send_30 + task_total_delay_router_router5_task30 >= -10000.0\n", - "_C120712: -10000.0*t_30_map_5 - t_mem_30 + task_total_memory_router_router5_task30 >= -10000.0\n", - "_C120713: -t31_end_ + t31_start - 10000.0*t_31_map_5 - t_send_31 + task_total_delay_router_router5_task31 >= -10000.0\n", - "_C120714: -10000.0*t_31_map_5 - t_mem_31 + task_total_memory_router_router5_task31 >= -10000.0\n", - "_C120715: -t32_end_ + t32_start - 10000.0*t_32_map_5 - t_send_32 + task_total_delay_router_router5_task32 >= -10000.0\n", - "_C120716: -10000.0*t_32_map_5 - t_mem_32 + task_total_memory_router_router5_task32 >= -10000.0\n", - "_C120717: -t33_end_ + t33_start - 10000.0*t_33_map_5 - t_send_33 + task_total_delay_router_router5_task33 >= -10000.0\n", - "_C120718: -10000.0*t_33_map_5 - t_mem_33 + task_total_memory_router_router5_task33 >= -10000.0\n", - "_C120719: -t34_end_ + t34_start - 10000.0*t_34_map_5 - t_send_34 + task_total_delay_router_router5_task34 >= -10000.0\n", - "_C120720: -10000.0*t_34_map_5 - t_mem_34 + task_total_memory_router_router5_task34 >= -10000.0\n", - "_C120721: -t35_end_ + t35_start - 10000.0*t_35_map_5 - t_send_35 + task_total_delay_router_router5_task35 >= -10000.0\n", - "_C120722: -10000.0*t_35_map_5 - t_mem_35 + task_total_memory_router_router5_task35 >= -10000.0\n", - "_C120723: -t36_end_ + 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task_total_memory_router_router5_task44 >= -10000.0\n", - "_C120741: -t45_end_ + t45_start - 10000.0*t_45_map_5 - t_send_45 + task_total_delay_router_router5_task45 >= -10000.0\n", - "_C120742: -10000.0*t_45_map_5 - t_mem_45 + task_total_memory_router_router5_task45 >= -10000.0\n", - "_C120743: -t46_end_ + t46_start - 10000.0*t_46_map_5 - t_send_46 + task_total_delay_router_router5_task46 >= -10000.0\n", - "_C120744: -10000.0*t_46_map_5 - t_mem_46 + task_total_memory_router_router5_task46 >= -10000.0\n", - "_C120745: -t47_end_ + t47_start - 10000.0*t_47_map_5 - t_send_47 + task_total_delay_router_router5_task47 >= -10000.0\n", - "_C120746: -10000.0*t_47_map_5 - t_mem_47 + task_total_memory_router_router5_task47 >= -10000.0\n", - "_C120747: -t48_end_ + t48_start - 10000.0*t_48_map_5 - t_send_48 + task_total_delay_router_router5_task48 >= -10000.0\n", - "_C120748: -10000.0*t_48_map_5 - t_mem_48 + task_total_memory_router_router5_task48 >= -10000.0\n", - "_C120749: -t49_end_ + t49_start - 10000.0*t_49_map_5 - t_send_49 + task_total_delay_router_router5_task49 >= -10000.0\n", - "_C120750: -10000.0*t_49_map_5 - t_mem_49 + task_total_memory_router_router5_task49 >= -10000.0\n", - "_C120751: -t50_end_ + t50_start - 10000.0*t_50_map_5 - t_send_50 + task_total_delay_router_router5_task50 >= -10000.0\n", - "_C120752: -10000.0*t_50_map_5 - t_mem_50 + task_total_memory_router_router5_task50 >= -10000.0\n", - "_C120753: -t51_end_ + t51_start - 10000.0*t_51_map_5 - t_send_51 + task_total_delay_router_router5_task51 >= -10000.0\n", - "_C120754: -10000.0*t_51_map_5 - t_mem_51 + task_total_memory_router_router5_task51 >= -10000.0\n", - "_C120755: -t52_end_ + t52_start - 10000.0*t_52_map_5 - t_send_52 + task_total_delay_router_router5_task52 >= -10000.0\n", - "_C120756: -10000.0*t_52_map_5 - t_mem_52 + task_total_memory_router_router5_task52 >= -10000.0\n", - "_C120757: -t53_end_ + t53_start - 10000.0*t_53_map_5 - t_send_53 + task_total_delay_router_router5_task53 >= -10000.0\n", - "_C120758: -10000.0*t_53_map_5 - t_mem_53 + task_total_memory_router_router5_task53 >= -10000.0\n", - "_C120759: -t54_end_ + t54_start - 10000.0*t_54_map_5 - t_send_54 + task_total_delay_router_router5_task54 >= -10000.0\n", - "_C120760: -10000.0*t_54_map_5 - t_mem_54 + task_total_memory_router_router5_task54 >= -10000.0\n", - "_C120761: -t55_end_ + t55_start - 10000.0*t_55_map_5 - t_send_55 + task_total_delay_router_router5_task55 >= -10000.0\n", - "_C120762: -10000.0*t_55_map_5 - t_mem_55 + task_total_memory_router_router5_task55 >= -10000.0\n", - "_C120763: -t56_end_ + t56_start - 10000.0*t_56_map_5 - t_send_56 + task_total_delay_router_router5_task56 >= -10000.0\n", - "_C120764: -10000.0*t_56_map_5 - t_mem_56 + task_total_memory_router_router5_task56 >= -10000.0\n", - "_C120765: -t57_end_ + t57_start - 10000.0*t_57_map_5 - t_send_57 + task_total_delay_router_router5_task57 >= -10000.0\n", - "_C120766: -10000.0*t_57_map_5 - t_mem_57 + task_total_memory_router_router5_task57 >= -10000.0\n", - "_C120767: -t58_end_ + t58_start - 10000.0*t_58_map_5 - t_send_58 + task_total_delay_router_router5_task58 >= -10000.0\n", - "_C120768: -10000.0*t_58_map_5 - t_mem_58 + task_total_memory_router_router5_task58 >= -10000.0\n", - "_C120769: -t59_end_ + t59_start - 10000.0*t_59_map_5 - t_send_59 + task_total_delay_router_router5_task59 >= -10000.0\n", - "_C120770: -10000.0*t_59_map_5 - t_mem_59 + task_total_memory_router_router5_task59 >= -10000.0\n", - "_C120771: -t60_end_ + t60_start - 10000.0*t_60_map_5 - t_send_60 + task_total_delay_router_router5_task60 >= -10000.0\n", - "_C120772: -10000.0*t_60_map_5 - t_mem_60 + task_total_memory_router_router5_task60 >= -10000.0\n", - "_C120773: -t61_end_ + t61_start - 10000.0*t_61_map_5 - t_send_61 + task_total_delay_router_router5_task61 >= -10000.0\n", - "_C120774: -10000.0*t_61_map_5 - t_mem_61 + task_total_memory_router_router5_task61 >= -10000.0\n", - "_C120775: -t62_end_ + t62_start - 10000.0*t_62_map_5 - t_send_62 + task_total_delay_router_router5_task62 >= -10000.0\n", - "_C120776: -10000.0*t_62_map_5 - t_mem_62 + task_total_memory_router_router5_task62 >= -10000.0\n", - "_C120777: -t63_end_ + t63_start - 10000.0*t_63_map_5 - t_send_63 + task_total_delay_router_router5_task63 >= -10000.0\n", - "_C120778: -10000.0*t_63_map_5 - t_mem_63 + task_total_memory_router_router5_task63 >= -10000.0\n", - "_C120779: -t64_end_ + t64_start - 10000.0*t_64_map_5 - t_send_64 + task_total_delay_router_router5_task64 >= -10000.0\n", - "_C120780: -10000.0*t_64_map_5 - t_mem_64 + task_total_memory_router_router5_task64 >= -10000.0\n", - "_C120781: -t65_end_ + t65_start - 10000.0*t_65_map_5 - t_send_65 + task_total_delay_router_router5_task65 >= -10000.0\n", - "_C120782: -10000.0*t_65_map_5 - t_mem_65 + task_total_memory_router_router5_task65 >= -10000.0\n", - "_C120783: -t66_end_ + t66_start - 10000.0*t_66_map_5 - t_send_66 + task_total_delay_router_router5_task66 >= -10000.0\n", - "_C120784: -10000.0*t_66_map_5 - t_mem_66 + task_total_memory_router_router5_task66 >= -10000.0\n", - "_C120785: -t67_end_ + t67_start - 10000.0*t_67_map_5 - t_send_67 + task_total_delay_router_router5_task67 >= -10000.0\n", - "_C120786: -10000.0*t_67_map_5 - t_mem_67 + task_total_memory_router_router5_task67 >= -10000.0\n", - "_C120787: -t68_end_ + t68_start - 10000.0*t_68_map_5 - t_send_68 + task_total_delay_router_router5_task68 >= -10000.0\n", - "_C120788: -10000.0*t_68_map_5 - t_mem_68 + task_total_memory_router_router5_task68 >= -10000.0\n", - "_C120789: -t69_end_ + t69_start - 10000.0*t_69_map_5 - t_send_69 + task_total_delay_router_router5_task69 >= -10000.0\n", - "_C120790: -10000.0*t_69_map_5 - t_mem_69 + task_total_memory_router_router5_task69 >= -10000.0\n", - "_C120791: PE_mem_overflow5 - task_total_memory_router_router5_task0 - task_total_memory_router_router5_task1 - task_total_memory_router_router5_task10 - task_total_memory_router_router5_task11 - task_total_memory_router_router5_task12 - task_total_memory_router_router5_task13 - task_total_memory_router_router5_task14 - task_total_memory_router_router5_task15 - task_total_memory_router_router5_task16 - task_total_memory_router_router5_task17 - task_total_memory_router_router5_task18 - task_total_memory_router_router5_task19 - task_total_memory_router_router5_task2 - task_total_memory_router_router5_task20 - task_total_memory_router_router5_task21 - task_total_memory_router_router5_task22 - task_total_memory_router_router5_task23 - task_total_memory_router_router5_task24 - task_total_memory_router_router5_task25 - task_total_memory_router_router5_task26 - task_total_memory_router_router5_task27 - task_total_memory_router_router5_task28 - task_total_memory_router_router5_task29 - task_total_memory_router_router5_task3 - task_total_memory_router_router5_task30 - task_total_memory_router_router5_task31 - task_total_memory_router_router5_task32 - task_total_memory_router_router5_task33 - task_total_memory_router_router5_task34 - task_total_memory_router_router5_task35 - task_total_memory_router_router5_task36 - task_total_memory_router_router5_task37 - task_total_memory_router_router5_task38 - task_total_memory_router_router5_task39 - task_total_memory_router_router5_task4 - task_total_memory_router_router5_task40 - task_total_memory_router_router5_task41 - task_total_memory_router_router5_task42 - task_total_memory_router_router5_task43 - task_total_memory_router_router5_task44 - task_total_memory_router_router5_task45 - task_total_memory_router_router5_task46 - task_total_memory_router_router5_task47 - task_total_memory_router_router5_task48 - task_total_memory_router_router5_task49 - task_total_memory_router_router5_task5 - task_total_memory_router_router5_task50 - task_total_memory_router_router5_task51 - task_total_memory_router_router5_task52 - task_total_memory_router_router5_task53 - task_total_memory_router_router5_task54 - task_total_memory_router_router5_task55 - task_total_memory_router_router5_task56 - task_total_memory_router_router5_task57 - task_total_memory_router_router5_task58 - task_total_memory_router_router5_task59 - task_total_memory_router_router5_task6 - task_total_memory_router_router5_task60 - task_total_memory_router_router5_task61 - task_total_memory_router_router5_task62 - task_total_memory_router_router5_task63 - task_total_memory_router_router5_task64 - task_total_memory_router_router5_task65 - task_total_memory_router_router5_task66 - task_total_memory_router_router5_task67 - task_total_memory_router_router5_task68 - task_total_memory_router_router5_task69 - task_total_memory_router_router5_task7 - task_total_memory_router_router5_task8 - task_total_memory_router_router5_task9 >= -0.0\n", - "_C120792: PE5_total_delay - task_total_delay_router_router5_task0 - task_total_delay_router_router5_task1 - task_total_delay_router_router5_task10 - task_total_delay_router_router5_task11 - task_total_delay_router_router5_task12 - task_total_delay_router_router5_task13 - task_total_delay_router_router5_task14 - task_total_delay_router_router5_task15 - task_total_delay_router_router5_task16 - task_total_delay_router_router5_task17 - task_total_delay_router_router5_task18 - task_total_delay_router_router5_task19 - task_total_delay_router_router5_task2 - task_total_delay_router_router5_task20 - task_total_delay_router_router5_task21 - task_total_delay_router_router5_task22 - task_total_delay_router_router5_task23 - task_total_delay_router_router5_task24 - task_total_delay_router_router5_task25 - task_total_delay_router_router5_task26 - task_total_delay_router_router5_task27 - task_total_delay_router_router5_task28 - task_total_delay_router_router5_task29 - task_total_delay_router_router5_task3 - task_total_delay_router_router5_task30 - task_total_delay_router_router5_task31 - task_total_delay_router_router5_task32 - task_total_delay_router_router5_task33 - task_total_delay_router_router5_task34 - task_total_delay_router_router5_task35 - task_total_delay_router_router5_task36 - task_total_delay_router_router5_task37 - task_total_delay_router_router5_task38 - task_total_delay_router_router5_task39 - task_total_delay_router_router5_task4 - task_total_delay_router_router5_task40 - task_total_delay_router_router5_task41 - task_total_delay_router_router5_task42 - task_total_delay_router_router5_task43 - task_total_delay_router_router5_task44 - task_total_delay_router_router5_task45 - task_total_delay_router_router5_task46 - task_total_delay_router_router5_task47 - task_total_delay_router_router5_task48 - task_total_delay_router_router5_task49 - task_total_delay_router_router5_task5 - task_total_delay_router_router5_task50 - task_total_delay_router_router5_task51 - task_total_delay_router_router5_task52 - task_total_delay_router_router5_task53 - task_total_delay_router_router5_task54 - task_total_delay_router_router5_task55 - task_total_delay_router_router5_task56 - task_total_delay_router_router5_task57 - task_total_delay_router_router5_task58 - task_total_delay_router_router5_task59 - task_total_delay_router_router5_task6 - task_total_delay_router_router5_task60 - task_total_delay_router_router5_task61 - task_total_delay_router_router5_task62 - task_total_delay_router_router5_task63 - task_total_delay_router_router5_task64 - task_total_delay_router_router5_task65 - task_total_delay_router_router5_task66 - task_total_delay_router_router5_task67 - task_total_delay_router_router5_task68 - task_total_delay_router_router5_task69 - task_total_delay_router_router5_task7 - task_total_delay_router_router5_task8 - task_total_delay_router_router5_task9 >= -0.0\n", - "_C120793: PE5_total_memory - task_total_memory_router_router5_task0 - task_total_memory_router_router5_task1 - task_total_memory_router_router5_task10 - task_total_memory_router_router5_task11 - task_total_memory_router_router5_task12 - task_total_memory_router_router5_task13 - task_total_memory_router_router5_task14 - task_total_memory_router_router5_task15 - task_total_memory_router_router5_task16 - task_total_memory_router_router5_task17 - task_total_memory_router_router5_task18 - task_total_memory_router_router5_task19 - task_total_memory_router_router5_task2 - task_total_memory_router_router5_task20 - task_total_memory_router_router5_task21 - task_total_memory_router_router5_task22 - task_total_memory_router_router5_task23 - task_total_memory_router_router5_task24 - task_total_memory_router_router5_task25 - task_total_memory_router_router5_task26 - task_total_memory_router_router5_task27 - task_total_memory_router_router5_task28 - task_total_memory_router_router5_task29 - task_total_memory_router_router5_task3 - task_total_memory_router_router5_task30 - task_total_memory_router_router5_task31 - task_total_memory_router_router5_task32 - task_total_memory_router_router5_task33 - task_total_memory_router_router5_task34 - task_total_memory_router_router5_task35 - task_total_memory_router_router5_task36 - task_total_memory_router_router5_task37 - task_total_memory_router_router5_task38 - task_total_memory_router_router5_task39 - task_total_memory_router_router5_task4 - task_total_memory_router_router5_task40 - task_total_memory_router_router5_task41 - task_total_memory_router_router5_task42 - task_total_memory_router_router5_task43 - task_total_memory_router_router5_task44 - task_total_memory_router_router5_task45 - task_total_memory_router_router5_task46 - task_total_memory_router_router5_task47 - task_total_memory_router_router5_task48 - task_total_memory_router_router5_task49 - task_total_memory_router_router5_task5 - task_total_memory_router_router5_task50 - task_total_memory_router_router5_task51 - task_total_memory_router_router5_task52 - task_total_memory_router_router5_task53 - task_total_memory_router_router5_task54 - task_total_memory_router_router5_task55 - task_total_memory_router_router5_task56 - task_total_memory_router_router5_task57 - task_total_memory_router_router5_task58 - task_total_memory_router_router5_task59 - task_total_memory_router_router5_task6 - task_total_memory_router_router5_task60 - task_total_memory_router_router5_task61 - task_total_memory_router_router5_task62 - task_total_memory_router_router5_task63 - task_total_memory_router_router5_task64 - task_total_memory_router_router5_task65 - task_total_memory_router_router5_task66 - task_total_memory_router_router5_task67 - task_total_memory_router_router5_task68 - task_total_memory_router_router5_task69 - task_total_memory_router_router5_task7 - task_total_memory_router_router5_task8 - task_total_memory_router_router5_task9 >= -0.0\n", - "_C120794: -PE_mem_overflow5 + max_memory_overflow >= 0\n", - "_C120795: PE5_time_delay_max - t0_end_ - 10000.0*t_0_map_5 >= -10000.0\n", - "_C120796: PE5_time_delay_min - t0_start + 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- t7_end_ - 10000.0*t_7_map_5 >= -10000.0\n", - "_C120810: PE5_time_delay_min - t7_start + 10000.0*t_7_map_5 <= 10000.0\n", - "_C120811: PE5_time_delay_max - t8_end_ - 10000.0*t_8_map_5 >= -10000.0\n", - "_C120812: PE5_time_delay_min - t8_start + 10000.0*t_8_map_5 <= 10000.0\n", - "_C120813: PE5_time_delay_max - t9_end_ - 10000.0*t_9_map_5 >= -10000.0\n", - "_C120814: PE5_time_delay_min - t9_start + 10000.0*t_9_map_5 <= 10000.0\n", - "_C120815: PE5_time_delay_max - t10_end_ - 10000.0*t_10_map_5 >= -10000.0\n", - "_C120816: PE5_time_delay_min - t10_start + 10000.0*t_10_map_5 <= 10000.0\n", - "_C120817: PE5_time_delay_max - t11_end_ - 10000.0*t_11_map_5 >= -10000.0\n", - "_C120818: PE5_time_delay_min - t11_start + 10000.0*t_11_map_5 <= 10000.0\n", - "_C120819: PE5_time_delay_max - t12_end_ - 10000.0*t_12_map_5 >= -10000.0\n", - "_C120820: PE5_time_delay_min - t12_start + 10000.0*t_12_map_5 <= 10000.0\n", - "_C120821: PE5_time_delay_max - t13_end_ - 10000.0*t_13_map_5 >= -10000.0\n", - "_C120822: PE5_time_delay_min - t13_start + 10000.0*t_13_map_5 <= 10000.0\n", - "_C120823: PE5_time_delay_max - t14_end_ - 10000.0*t_14_map_5 >= -10000.0\n", - "_C120824: PE5_time_delay_min - t14_start + 10000.0*t_14_map_5 <= 10000.0\n", - "_C120825: PE5_time_delay_max - t15_end_ - 10000.0*t_15_map_5 >= -10000.0\n", - "_C120826: PE5_time_delay_min - t15_start + 10000.0*t_15_map_5 <= 10000.0\n", - "_C120827: PE5_time_delay_max - t16_end_ - 10000.0*t_16_map_5 >= -10000.0\n", - "_C120828: PE5_time_delay_min - t16_start + 10000.0*t_16_map_5 <= 10000.0\n", - "_C120829: PE5_time_delay_max - t17_end_ - 10000.0*t_17_map_5 >= -10000.0\n", - "_C120830: PE5_time_delay_min - t17_start + 10000.0*t_17_map_5 <= 10000.0\n", - "_C120831: PE5_time_delay_max - t18_end_ - 10000.0*t_18_map_5 >= -10000.0\n", - "_C120832: PE5_time_delay_min - t18_start + 10000.0*t_18_map_5 <= 10000.0\n", - "_C120833: PE5_time_delay_max - t19_end_ - 10000.0*t_19_map_5 >= -10000.0\n", - "_C120834: PE5_time_delay_min - t19_start + 10000.0*t_19_map_5 <= 10000.0\n", - "_C120835: PE5_time_delay_max - t20_end_ - 10000.0*t_20_map_5 >= -10000.0\n", - "_C120836: PE5_time_delay_min - t20_start + 10000.0*t_20_map_5 <= 10000.0\n", - "_C120837: PE5_time_delay_max - t21_end_ - 10000.0*t_21_map_5 >= -10000.0\n", - "_C120838: PE5_time_delay_min - t21_start + 10000.0*t_21_map_5 <= 10000.0\n", - "_C120839: PE5_time_delay_max - t22_end_ - 10000.0*t_22_map_5 >= -10000.0\n", - "_C120840: PE5_time_delay_min - t22_start + 10000.0*t_22_map_5 <= 10000.0\n", - "_C120841: PE5_time_delay_max - t23_end_ - 10000.0*t_23_map_5 >= -10000.0\n", - "_C120842: PE5_time_delay_min - t23_start + 10000.0*t_23_map_5 <= 10000.0\n", - "_C120843: PE5_time_delay_max - t24_end_ - 10000.0*t_24_map_5 >= -10000.0\n", - "_C120844: PE5_time_delay_min - t24_start + 10000.0*t_24_map_5 <= 10000.0\n", - "_C120845: PE5_time_delay_max - t25_end_ - 10000.0*t_25_map_5 >= -10000.0\n", - "_C120846: PE5_time_delay_min - t25_start + 10000.0*t_25_map_5 <= 10000.0\n", - "_C120847: PE5_time_delay_max - t26_end_ - 10000.0*t_26_map_5 >= -10000.0\n", - "_C120848: PE5_time_delay_min - t26_start + 10000.0*t_26_map_5 <= 10000.0\n", - "_C120849: PE5_time_delay_max - t27_end_ - 10000.0*t_27_map_5 >= -10000.0\n", - "_C120850: PE5_time_delay_min - t27_start + 10000.0*t_27_map_5 <= 10000.0\n", - "_C120851: PE5_time_delay_max - t28_end_ - 10000.0*t_28_map_5 >= -10000.0\n", - "_C120852: PE5_time_delay_min - t28_start + 10000.0*t_28_map_5 <= 10000.0\n", - "_C120853: PE5_time_delay_max - t29_end_ - 10000.0*t_29_map_5 >= -10000.0\n", - "_C120854: PE5_time_delay_min - t29_start + 10000.0*t_29_map_5 <= 10000.0\n", - "_C120855: PE5_time_delay_max - t30_end_ - 10000.0*t_30_map_5 >= -10000.0\n", - "_C120856: PE5_time_delay_min - t30_start + 10000.0*t_30_map_5 <= 10000.0\n", - "_C120857: PE5_time_delay_max - t31_end_ - 10000.0*t_31_map_5 >= -10000.0\n", - "_C120858: PE5_time_delay_min - t31_start + 10000.0*t_31_map_5 <= 10000.0\n", - "_C120859: PE5_time_delay_max - t32_end_ - 10000.0*t_32_map_5 >= -10000.0\n", - "_C120860: PE5_time_delay_min - t32_start + 10000.0*t_32_map_5 <= 10000.0\n", - "_C120861: PE5_time_delay_max - t33_end_ - 10000.0*t_33_map_5 >= -10000.0\n", - "_C120862: PE5_time_delay_min - t33_start + 10000.0*t_33_map_5 <= 10000.0\n", - "_C120863: PE5_time_delay_max - t34_end_ - 10000.0*t_34_map_5 >= -10000.0\n", - "_C120864: PE5_time_delay_min - t34_start + 10000.0*t_34_map_5 <= 10000.0\n", - "_C120865: PE5_time_delay_max - t35_end_ - 10000.0*t_35_map_5 >= -10000.0\n", - "_C120866: PE5_time_delay_min - t35_start + 10000.0*t_35_map_5 <= 10000.0\n", - "_C120867: PE5_time_delay_max - t36_end_ - 10000.0*t_36_map_5 >= -10000.0\n", - "_C120868: PE5_time_delay_min - t36_start + 10000.0*t_36_map_5 <= 10000.0\n", - "_C120869: PE5_time_delay_max - t37_end_ - 10000.0*t_37_map_5 >= -10000.0\n", - "_C120870: PE5_time_delay_min - t37_start + 10000.0*t_37_map_5 <= 10000.0\n", - "_C120871: PE5_time_delay_max - t38_end_ - 10000.0*t_38_map_5 >= -10000.0\n", - "_C120872: PE5_time_delay_min - t38_start + 10000.0*t_38_map_5 <= 10000.0\n", - "_C120873: PE5_time_delay_max - t39_end_ - 10000.0*t_39_map_5 >= -10000.0\n", - "_C120874: PE5_time_delay_min - t39_start + 10000.0*t_39_map_5 <= 10000.0\n", - "_C120875: PE5_time_delay_max - t40_end_ - 10000.0*t_40_map_5 >= -10000.0\n", - "_C120876: PE5_time_delay_min - t40_start + 10000.0*t_40_map_5 <= 10000.0\n", - "_C120877: PE5_time_delay_max - t41_end_ - 10000.0*t_41_map_5 >= -10000.0\n", - "_C120878: PE5_time_delay_min - t41_start + 10000.0*t_41_map_5 <= 10000.0\n", - "_C120879: PE5_time_delay_max - t42_end_ - 10000.0*t_42_map_5 >= -10000.0\n", - "_C120880: PE5_time_delay_min - t42_start + 10000.0*t_42_map_5 <= 10000.0\n", - "_C120881: PE5_time_delay_max - t43_end_ - 10000.0*t_43_map_5 >= -10000.0\n", - "_C120882: PE5_time_delay_min - t43_start + 10000.0*t_43_map_5 <= 10000.0\n", - "_C120883: PE5_time_delay_max - t44_end_ - 10000.0*t_44_map_5 >= -10000.0\n", - "_C120884: PE5_time_delay_min - t44_start + 10000.0*t_44_map_5 <= 10000.0\n", - "_C120885: PE5_time_delay_max - t45_end_ - 10000.0*t_45_map_5 >= -10000.0\n", - "_C120886: PE5_time_delay_min - t45_start + 10000.0*t_45_map_5 <= 10000.0\n", - "_C120887: PE5_time_delay_max - t46_end_ - 10000.0*t_46_map_5 >= -10000.0\n", - "_C120888: PE5_time_delay_min - t46_start + 10000.0*t_46_map_5 <= 10000.0\n", - "_C120889: PE5_time_delay_max - t47_end_ - 10000.0*t_47_map_5 >= -10000.0\n", - "_C120890: PE5_time_delay_min - t47_start + 10000.0*t_47_map_5 <= 10000.0\n", - "_C120891: PE5_time_delay_max - t48_end_ - 10000.0*t_48_map_5 >= -10000.0\n", - "_C120892: PE5_time_delay_min - t48_start + 10000.0*t_48_map_5 <= 10000.0\n", - "_C120893: PE5_time_delay_max - t49_end_ - 10000.0*t_49_map_5 >= -10000.0\n", - "_C120894: PE5_time_delay_min - t49_start + 10000.0*t_49_map_5 <= 10000.0\n", - "_C120895: PE5_time_delay_max - t50_end_ - 10000.0*t_50_map_5 >= -10000.0\n", - "_C120896: PE5_time_delay_min - t50_start + 10000.0*t_50_map_5 <= 10000.0\n", - "_C120897: PE5_time_delay_max - t51_end_ - 10000.0*t_51_map_5 >= -10000.0\n", - "_C120898: PE5_time_delay_min - t51_start + 10000.0*t_51_map_5 <= 10000.0\n", - "_C120899: PE5_time_delay_max - t52_end_ - 10000.0*t_52_map_5 >= -10000.0\n", - "_C120900: PE5_time_delay_min - t52_start + 10000.0*t_52_map_5 <= 10000.0\n", - "_C120901: PE5_time_delay_max - t53_end_ - 10000.0*t_53_map_5 >= -10000.0\n", - "_C120902: PE5_time_delay_min - t53_start + 10000.0*t_53_map_5 <= 10000.0\n", - "_C120903: PE5_time_delay_max - t54_end_ - 10000.0*t_54_map_5 >= -10000.0\n", - "_C120904: PE5_time_delay_min - t54_start + 10000.0*t_54_map_5 <= 10000.0\n", - "_C120905: PE5_time_delay_max - t55_end_ - 10000.0*t_55_map_5 >= -10000.0\n", - "_C120906: PE5_time_delay_min - t55_start + 10000.0*t_55_map_5 <= 10000.0\n", - "_C120907: PE5_time_delay_max - t56_end_ - 10000.0*t_56_map_5 >= -10000.0\n", - "_C120908: PE5_time_delay_min - t56_start + 10000.0*t_56_map_5 <= 10000.0\n", - "_C120909: PE5_time_delay_max - t57_end_ - 10000.0*t_57_map_5 >= -10000.0\n", - "_C120910: PE5_time_delay_min - t57_start + 10000.0*t_57_map_5 <= 10000.0\n", - "_C120911: PE5_time_delay_max - t58_end_ - 10000.0*t_58_map_5 >= -10000.0\n", - "_C120912: PE5_time_delay_min - t58_start + 10000.0*t_58_map_5 <= 10000.0\n", - "_C120913: PE5_time_delay_max - t59_end_ - 10000.0*t_59_map_5 >= -10000.0\n", - "_C120914: PE5_time_delay_min - t59_start + 10000.0*t_59_map_5 <= 10000.0\n", - "_C120915: PE5_time_delay_max - t60_end_ - 10000.0*t_60_map_5 >= -10000.0\n", - "_C120916: PE5_time_delay_min - t60_start + 10000.0*t_60_map_5 <= 10000.0\n", - "_C120917: PE5_time_delay_max - t61_end_ - 10000.0*t_61_map_5 >= -10000.0\n", - "_C120918: PE5_time_delay_min - t61_start + 10000.0*t_61_map_5 <= 10000.0\n", - "_C120919: PE5_time_delay_max - t62_end_ - 10000.0*t_62_map_5 >= -10000.0\n", - "_C120920: PE5_time_delay_min - t62_start + 10000.0*t_62_map_5 <= 10000.0\n", - "_C120921: PE5_time_delay_max - t63_end_ - 10000.0*t_63_map_5 >= -10000.0\n", - "_C120922: PE5_time_delay_min - t63_start + 10000.0*t_63_map_5 <= 10000.0\n", - "_C120923: PE5_time_delay_max - t64_end_ - 10000.0*t_64_map_5 >= -10000.0\n", - "_C120924: PE5_time_delay_min - t64_start + 10000.0*t_64_map_5 <= 10000.0\n", - "_C120925: PE5_time_delay_max - t65_end_ - 10000.0*t_65_map_5 >= -10000.0\n", - "_C120926: PE5_time_delay_min - t65_start + 10000.0*t_65_map_5 <= 10000.0\n", - "_C120927: PE5_time_delay_max - t66_end_ - 10000.0*t_66_map_5 >= -10000.0\n", - "_C120928: PE5_time_delay_min - t66_start + 10000.0*t_66_map_5 <= 10000.0\n", - "_C120929: PE5_time_delay_max - t67_end_ - 10000.0*t_67_map_5 >= -10000.0\n", - "_C120930: PE5_time_delay_min - t67_start + 10000.0*t_67_map_5 <= 10000.0\n", - "_C120931: PE5_time_delay_max - t68_end_ - 10000.0*t_68_map_5 >= -10000.0\n", - "_C120932: PE5_time_delay_min - t68_start + 10000.0*t_68_map_5 <= 10000.0\n", - "_C120933: PE5_time_delay_max - t69_end_ - 10000.0*t_69_map_5 >= -10000.0\n", - "_C120934: PE5_time_delay_min - t69_start + 10000.0*t_69_map_5 <= 10000.0\n", - "_C120935: -PE5_time_delay_max + PE5_time_delay_min + PE5_total_time_delay = 0\n", - "_C120936: -PE5_total_time_delay + max_router_delay >= 0\n", - "_C120937: PE5_total_time_delay <= 280\n", - "_C120938: -t0_end_ + t0_start - 10000.0*t_0_map_6 - t_send_0 + task_total_delay_router_router6_task0 >= -10000.0\n", - "_C120939: -10000.0*t_0_map_6 - t_mem_0 + task_total_memory_router_router6_task0 >= -10000.0\n", - "_C120940: -t1_end_ + t1_start - 10000.0*t_1_map_6 - t_send_1 + task_total_delay_router_router6_task1 >= -10000.0\n", - "_C120941: -10000.0*t_1_map_6 - t_mem_1 + task_total_memory_router_router6_task1 >= -10000.0\n", - "_C120942: -t2_end_ + t2_start - 10000.0*t_2_map_6 - t_send_2 + task_total_delay_router_router6_task2 >= -10000.0\n", - "_C120943: -10000.0*t_2_map_6 - t_mem_2 + task_total_memory_router_router6_task2 >= -10000.0\n", - "_C120944: -t3_end_ + t3_start - 10000.0*t_3_map_6 - t_send_3 + task_total_delay_router_router6_task3 >= -10000.0\n", - "_C120945: -10000.0*t_3_map_6 - t_mem_3 + task_total_memory_router_router6_task3 >= -10000.0\n", - "_C120946: -t4_end_ + t4_start - 10000.0*t_4_map_6 - t_send_4 + task_total_delay_router_router6_task4 >= -10000.0\n", - "_C120947: -10000.0*t_4_map_6 - t_mem_4 + task_total_memory_router_router6_task4 >= -10000.0\n", - "_C120948: -t5_end_ + t5_start - 10000.0*t_5_map_6 - t_send_5 + task_total_delay_router_router6_task5 >= -10000.0\n", - "_C120949: -10000.0*t_5_map_6 - t_mem_5 + task_total_memory_router_router6_task5 >= -10000.0\n", - "_C120950: -t6_end_ + t6_start - 10000.0*t_6_map_6 - t_send_6 + task_total_delay_router_router6_task6 >= -10000.0\n", - "_C120951: -10000.0*t_6_map_6 - t_mem_6 + task_total_memory_router_router6_task6 >= -10000.0\n", - "_C120952: -t7_end_ + t7_start - 10000.0*t_7_map_6 - t_send_7 + task_total_delay_router_router6_task7 >= -10000.0\n", - "_C120953: -10000.0*t_7_map_6 - t_mem_7 + task_total_memory_router_router6_task7 >= -10000.0\n", - "_C120954: -t8_end_ + t8_start - 10000.0*t_8_map_6 - t_send_8 + task_total_delay_router_router6_task8 >= -10000.0\n", - "_C120955: -10000.0*t_8_map_6 - t_mem_8 + task_total_memory_router_router6_task8 >= -10000.0\n", - "_C120956: -t9_end_ + t9_start - 10000.0*t_9_map_6 - t_send_9 + task_total_delay_router_router6_task9 >= -10000.0\n", - "_C120957: -10000.0*t_9_map_6 - t_mem_9 + task_total_memory_router_router6_task9 >= -10000.0\n", - "_C120958: -t10_end_ + t10_start - 10000.0*t_10_map_6 - t_send_10 + task_total_delay_router_router6_task10 >= -10000.0\n", - "_C120959: -10000.0*t_10_map_6 - t_mem_10 + task_total_memory_router_router6_task10 >= -10000.0\n", - "_C120960: -t11_end_ + t11_start - 10000.0*t_11_map_6 - t_send_11 + task_total_delay_router_router6_task11 >= -10000.0\n", - "_C120961: -10000.0*t_11_map_6 - t_mem_11 + task_total_memory_router_router6_task11 >= -10000.0\n", - "_C120962: -t12_end_ + t12_start - 10000.0*t_12_map_6 - t_send_12 + task_total_delay_router_router6_task12 >= -10000.0\n", - "_C120963: -10000.0*t_12_map_6 - t_mem_12 + task_total_memory_router_router6_task12 >= -10000.0\n", - "_C120964: -t13_end_ + t13_start - 10000.0*t_13_map_6 - t_send_13 + task_total_delay_router_router6_task13 >= -10000.0\n", - "_C120965: -10000.0*t_13_map_6 - t_mem_13 + task_total_memory_router_router6_task13 >= -10000.0\n", - "_C120966: -t14_end_ + t14_start - 10000.0*t_14_map_6 - t_send_14 + task_total_delay_router_router6_task14 >= -10000.0\n", - "_C120967: -10000.0*t_14_map_6 - t_mem_14 + task_total_memory_router_router6_task14 >= -10000.0\n", - "_C120968: -t15_end_ + t15_start - 10000.0*t_15_map_6 - t_send_15 + task_total_delay_router_router6_task15 >= -10000.0\n", - "_C120969: -10000.0*t_15_map_6 - t_mem_15 + task_total_memory_router_router6_task15 >= -10000.0\n", - "_C120970: -t16_end_ + t16_start - 10000.0*t_16_map_6 - t_send_16 + task_total_delay_router_router6_task16 >= -10000.0\n", - 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task_total_memory_router_router6_task25 - task_total_memory_router_router6_task26 - task_total_memory_router_router6_task27 - task_total_memory_router_router6_task28 - task_total_memory_router_router6_task29 - task_total_memory_router_router6_task3 - task_total_memory_router_router6_task30 - task_total_memory_router_router6_task31 - task_total_memory_router_router6_task32 - task_total_memory_router_router6_task33 - task_total_memory_router_router6_task34 - task_total_memory_router_router6_task35 - task_total_memory_router_router6_task36 - task_total_memory_router_router6_task37 - task_total_memory_router_router6_task38 - task_total_memory_router_router6_task39 - task_total_memory_router_router6_task4 - task_total_memory_router_router6_task40 - task_total_memory_router_router6_task41 - task_total_memory_router_router6_task42 - task_total_memory_router_router6_task43 - task_total_memory_router_router6_task44 - task_total_memory_router_router6_task45 - task_total_memory_router_router6_task46 - task_total_memory_router_router6_task47 - task_total_memory_router_router6_task48 - task_total_memory_router_router6_task49 - task_total_memory_router_router6_task5 - task_total_memory_router_router6_task50 - task_total_memory_router_router6_task51 - task_total_memory_router_router6_task52 - task_total_memory_router_router6_task53 - task_total_memory_router_router6_task54 - task_total_memory_router_router6_task55 - task_total_memory_router_router6_task56 - task_total_memory_router_router6_task57 - task_total_memory_router_router6_task58 - task_total_memory_router_router6_task59 - task_total_memory_router_router6_task6 - task_total_memory_router_router6_task60 - task_total_memory_router_router6_task61 - task_total_memory_router_router6_task62 - task_total_memory_router_router6_task63 - task_total_memory_router_router6_task64 - task_total_memory_router_router6_task65 - task_total_memory_router_router6_task66 - task_total_memory_router_router6_task67 - task_total_memory_router_router6_task68 - task_total_memory_router_router6_task69 - task_total_memory_router_router6_task7 - task_total_memory_router_router6_task8 - task_total_memory_router_router6_task9 >= -0.0\n", - "_C121079: PE6_total_delay - task_total_delay_router_router6_task0 - task_total_delay_router_router6_task1 - task_total_delay_router_router6_task10 - task_total_delay_router_router6_task11 - task_total_delay_router_router6_task12 - task_total_delay_router_router6_task13 - task_total_delay_router_router6_task14 - task_total_delay_router_router6_task15 - task_total_delay_router_router6_task16 - task_total_delay_router_router6_task17 - task_total_delay_router_router6_task18 - task_total_delay_router_router6_task19 - task_total_delay_router_router6_task2 - task_total_delay_router_router6_task20 - task_total_delay_router_router6_task21 - task_total_delay_router_router6_task22 - task_total_delay_router_router6_task23 - task_total_delay_router_router6_task24 - task_total_delay_router_router6_task25 - task_total_delay_router_router6_task26 - task_total_delay_router_router6_task27 - task_total_delay_router_router6_task28 - task_total_delay_router_router6_task29 - task_total_delay_router_router6_task3 - task_total_delay_router_router6_task30 - task_total_delay_router_router6_task31 - task_total_delay_router_router6_task32 - task_total_delay_router_router6_task33 - task_total_delay_router_router6_task34 - task_total_delay_router_router6_task35 - task_total_delay_router_router6_task36 - task_total_delay_router_router6_task37 - task_total_delay_router_router6_task38 - task_total_delay_router_router6_task39 - task_total_delay_router_router6_task4 - task_total_delay_router_router6_task40 - task_total_delay_router_router6_task41 - task_total_delay_router_router6_task42 - task_total_delay_router_router6_task43 - task_total_delay_router_router6_task44 - task_total_delay_router_router6_task45 - task_total_delay_router_router6_task46 - task_total_delay_router_router6_task47 - task_total_delay_router_router6_task48 - task_total_delay_router_router6_task49 - task_total_delay_router_router6_task5 - task_total_delay_router_router6_task50 - task_total_delay_router_router6_task51 - task_total_delay_router_router6_task52 - task_total_delay_router_router6_task53 - task_total_delay_router_router6_task54 - task_total_delay_router_router6_task55 - task_total_delay_router_router6_task56 - task_total_delay_router_router6_task57 - task_total_delay_router_router6_task58 - task_total_delay_router_router6_task59 - task_total_delay_router_router6_task6 - task_total_delay_router_router6_task60 - task_total_delay_router_router6_task61 - task_total_delay_router_router6_task62 - task_total_delay_router_router6_task63 - task_total_delay_router_router6_task64 - task_total_delay_router_router6_task65 - task_total_delay_router_router6_task66 - task_total_delay_router_router6_task67 - task_total_delay_router_router6_task68 - task_total_delay_router_router6_task69 - task_total_delay_router_router6_task7 - task_total_delay_router_router6_task8 - task_total_delay_router_router6_task9 >= -0.0\n", - "_C121080: PE6_total_memory - task_total_memory_router_router6_task0 - task_total_memory_router_router6_task1 - task_total_memory_router_router6_task10 - task_total_memory_router_router6_task11 - task_total_memory_router_router6_task12 - task_total_memory_router_router6_task13 - task_total_memory_router_router6_task14 - task_total_memory_router_router6_task15 - task_total_memory_router_router6_task16 - task_total_memory_router_router6_task17 - task_total_memory_router_router6_task18 - task_total_memory_router_router6_task19 - task_total_memory_router_router6_task2 - task_total_memory_router_router6_task20 - task_total_memory_router_router6_task21 - task_total_memory_router_router6_task22 - task_total_memory_router_router6_task23 - task_total_memory_router_router6_task24 - task_total_memory_router_router6_task25 - task_total_memory_router_router6_task26 - task_total_memory_router_router6_task27 - task_total_memory_router_router6_task28 - task_total_memory_router_router6_task29 - task_total_memory_router_router6_task3 - task_total_memory_router_router6_task30 - task_total_memory_router_router6_task31 - task_total_memory_router_router6_task32 - task_total_memory_router_router6_task33 - task_total_memory_router_router6_task34 - task_total_memory_router_router6_task35 - task_total_memory_router_router6_task36 - task_total_memory_router_router6_task37 - task_total_memory_router_router6_task38 - task_total_memory_router_router6_task39 - task_total_memory_router_router6_task4 - task_total_memory_router_router6_task40 - task_total_memory_router_router6_task41 - task_total_memory_router_router6_task42 - task_total_memory_router_router6_task43 - task_total_memory_router_router6_task44 - task_total_memory_router_router6_task45 - task_total_memory_router_router6_task46 - task_total_memory_router_router6_task47 - task_total_memory_router_router6_task48 - task_total_memory_router_router6_task49 - task_total_memory_router_router6_task5 - task_total_memory_router_router6_task50 - task_total_memory_router_router6_task51 - task_total_memory_router_router6_task52 - task_total_memory_router_router6_task53 - task_total_memory_router_router6_task54 - task_total_memory_router_router6_task55 - task_total_memory_router_router6_task56 - task_total_memory_router_router6_task57 - task_total_memory_router_router6_task58 - task_total_memory_router_router6_task59 - task_total_memory_router_router6_task6 - task_total_memory_router_router6_task60 - task_total_memory_router_router6_task61 - task_total_memory_router_router6_task62 - task_total_memory_router_router6_task63 - task_total_memory_router_router6_task64 - task_total_memory_router_router6_task65 - task_total_memory_router_router6_task66 - task_total_memory_router_router6_task67 - task_total_memory_router_router6_task68 - task_total_memory_router_router6_task69 - task_total_memory_router_router6_task7 - task_total_memory_router_router6_task8 - task_total_memory_router_router6_task9 >= -0.0\n", - "_C121081: -PE_mem_overflow6 + max_memory_overflow >= 0\n", - "_C121082: PE6_time_delay_max - t0_end_ - 10000.0*t_0_map_6 >= -10000.0\n", - "_C121083: PE6_time_delay_min - t0_start + 10000.0*t_0_map_6 <= 10000.0\n", - "_C121084: PE6_time_delay_max - t1_end_ - 10000.0*t_1_map_6 >= -10000.0\n", - "_C121085: PE6_time_delay_min - t1_start + 10000.0*t_1_map_6 <= 10000.0\n", - "_C121086: PE6_time_delay_max - t2_end_ - 10000.0*t_2_map_6 >= -10000.0\n", - "_C121087: PE6_time_delay_min - t2_start + 10000.0*t_2_map_6 <= 10000.0\n", - "_C121088: PE6_time_delay_max - t3_end_ - 10000.0*t_3_map_6 >= -10000.0\n", - "_C121089: PE6_time_delay_min - t3_start + 10000.0*t_3_map_6 <= 10000.0\n", - "_C121090: PE6_time_delay_max - t4_end_ - 10000.0*t_4_map_6 >= -10000.0\n", - "_C121091: PE6_time_delay_min - t4_start + 10000.0*t_4_map_6 <= 10000.0\n", - "_C121092: PE6_time_delay_max - t5_end_ - 10000.0*t_5_map_6 >= -10000.0\n", - "_C121093: PE6_time_delay_min - t5_start + 10000.0*t_5_map_6 <= 10000.0\n", - "_C121094: PE6_time_delay_max - t6_end_ - 10000.0*t_6_map_6 >= -10000.0\n", - "_C121095: PE6_time_delay_min - t6_start + 10000.0*t_6_map_6 <= 10000.0\n", - "_C121096: PE6_time_delay_max - t7_end_ - 10000.0*t_7_map_6 >= -10000.0\n", - "_C121097: PE6_time_delay_min - t7_start + 10000.0*t_7_map_6 <= 10000.0\n", - "_C121098: PE6_time_delay_max - t8_end_ - 10000.0*t_8_map_6 >= -10000.0\n", - "_C121099: PE6_time_delay_min - t8_start + 10000.0*t_8_map_6 <= 10000.0\n", - "_C121100: PE6_time_delay_max - t9_end_ - 10000.0*t_9_map_6 >= -10000.0\n", - "_C121101: PE6_time_delay_min - t9_start + 10000.0*t_9_map_6 <= 10000.0\n", - "_C121102: PE6_time_delay_max - t10_end_ - 10000.0*t_10_map_6 >= -10000.0\n", - "_C121103: PE6_time_delay_min - t10_start + 10000.0*t_10_map_6 <= 10000.0\n", - "_C121104: PE6_time_delay_max - t11_end_ - 10000.0*t_11_map_6 >= -10000.0\n", - "_C121105: PE6_time_delay_min - t11_start + 10000.0*t_11_map_6 <= 10000.0\n", - "_C121106: PE6_time_delay_max - t12_end_ - 10000.0*t_12_map_6 >= -10000.0\n", - "_C121107: PE6_time_delay_min - t12_start + 10000.0*t_12_map_6 <= 10000.0\n", - "_C121108: PE6_time_delay_max - t13_end_ - 10000.0*t_13_map_6 >= -10000.0\n", - "_C121109: PE6_time_delay_min - t13_start + 10000.0*t_13_map_6 <= 10000.0\n", - "_C121110: PE6_time_delay_max - t14_end_ - 10000.0*t_14_map_6 >= -10000.0\n", - "_C121111: PE6_time_delay_min - t14_start + 10000.0*t_14_map_6 <= 10000.0\n", - "_C121112: PE6_time_delay_max - t15_end_ - 10000.0*t_15_map_6 >= -10000.0\n", - "_C121113: PE6_time_delay_min - t15_start + 10000.0*t_15_map_6 <= 10000.0\n", - "_C121114: PE6_time_delay_max - t16_end_ - 10000.0*t_16_map_6 >= -10000.0\n", - "_C121115: PE6_time_delay_min - t16_start + 10000.0*t_16_map_6 <= 10000.0\n", - "_C121116: PE6_time_delay_max - t17_end_ - 10000.0*t_17_map_6 >= -10000.0\n", - "_C121117: PE6_time_delay_min - t17_start + 10000.0*t_17_map_6 <= 10000.0\n", - "_C121118: PE6_time_delay_max - t18_end_ - 10000.0*t_18_map_6 >= -10000.0\n", - "_C121119: PE6_time_delay_min - t18_start + 10000.0*t_18_map_6 <= 10000.0\n", - "_C121120: PE6_time_delay_max - t19_end_ - 10000.0*t_19_map_6 >= -10000.0\n", - "_C121121: PE6_time_delay_min - t19_start + 10000.0*t_19_map_6 <= 10000.0\n", - "_C121122: PE6_time_delay_max - t20_end_ - 10000.0*t_20_map_6 >= -10000.0\n", - "_C121123: PE6_time_delay_min - t20_start + 10000.0*t_20_map_6 <= 10000.0\n", - "_C121124: PE6_time_delay_max - t21_end_ - 10000.0*t_21_map_6 >= -10000.0\n", - "_C121125: PE6_time_delay_min - t21_start + 10000.0*t_21_map_6 <= 10000.0\n", - "_C121126: PE6_time_delay_max - t22_end_ - 10000.0*t_22_map_6 >= -10000.0\n", - "_C121127: PE6_time_delay_min - t22_start + 10000.0*t_22_map_6 <= 10000.0\n", - "_C121128: PE6_time_delay_max - t23_end_ - 10000.0*t_23_map_6 >= -10000.0\n", - "_C121129: PE6_time_delay_min - t23_start + 10000.0*t_23_map_6 <= 10000.0\n", - "_C121130: PE6_time_delay_max - t24_end_ - 10000.0*t_24_map_6 >= -10000.0\n", - "_C121131: PE6_time_delay_min - t24_start + 10000.0*t_24_map_6 <= 10000.0\n", - "_C121132: PE6_time_delay_max - t25_end_ - 10000.0*t_25_map_6 >= -10000.0\n", - "_C121133: PE6_time_delay_min - t25_start + 10000.0*t_25_map_6 <= 10000.0\n", - "_C121134: PE6_time_delay_max - t26_end_ - 10000.0*t_26_map_6 >= -10000.0\n", - "_C121135: PE6_time_delay_min - t26_start + 10000.0*t_26_map_6 <= 10000.0\n", - "_C121136: PE6_time_delay_max - t27_end_ - 10000.0*t_27_map_6 >= -10000.0\n", - "_C121137: PE6_time_delay_min - t27_start + 10000.0*t_27_map_6 <= 10000.0\n", - "_C121138: PE6_time_delay_max - t28_end_ - 10000.0*t_28_map_6 >= -10000.0\n", - "_C121139: PE6_time_delay_min - t28_start + 10000.0*t_28_map_6 <= 10000.0\n", - "_C121140: PE6_time_delay_max - t29_end_ - 10000.0*t_29_map_6 >= -10000.0\n", - "_C121141: PE6_time_delay_min - t29_start + 10000.0*t_29_map_6 <= 10000.0\n", - "_C121142: PE6_time_delay_max - t30_end_ - 10000.0*t_30_map_6 >= -10000.0\n", - "_C121143: PE6_time_delay_min - t30_start + 10000.0*t_30_map_6 <= 10000.0\n", - "_C121144: PE6_time_delay_max - t31_end_ - 10000.0*t_31_map_6 >= -10000.0\n", - "_C121145: PE6_time_delay_min - t31_start + 10000.0*t_31_map_6 <= 10000.0\n", - "_C121146: PE6_time_delay_max - t32_end_ - 10000.0*t_32_map_6 >= -10000.0\n", - "_C121147: PE6_time_delay_min - t32_start + 10000.0*t_32_map_6 <= 10000.0\n", - "_C121148: PE6_time_delay_max - t33_end_ - 10000.0*t_33_map_6 >= -10000.0\n", - "_C121149: PE6_time_delay_min - t33_start + 10000.0*t_33_map_6 <= 10000.0\n", - "_C121150: PE6_time_delay_max - t34_end_ - 10000.0*t_34_map_6 >= -10000.0\n", - "_C121151: PE6_time_delay_min - t34_start + 10000.0*t_34_map_6 <= 10000.0\n", - "_C121152: PE6_time_delay_max - t35_end_ - 10000.0*t_35_map_6 >= -10000.0\n", - "_C121153: PE6_time_delay_min - t35_start + 10000.0*t_35_map_6 <= 10000.0\n", - "_C121154: PE6_time_delay_max - t36_end_ - 10000.0*t_36_map_6 >= -10000.0\n", - "_C121155: PE6_time_delay_min - t36_start + 10000.0*t_36_map_6 <= 10000.0\n", - "_C121156: PE6_time_delay_max - t37_end_ - 10000.0*t_37_map_6 >= -10000.0\n", - "_C121157: PE6_time_delay_min - t37_start + 10000.0*t_37_map_6 <= 10000.0\n", - "_C121158: PE6_time_delay_max - t38_end_ - 10000.0*t_38_map_6 >= -10000.0\n", - "_C121159: PE6_time_delay_min - t38_start + 10000.0*t_38_map_6 <= 10000.0\n", - "_C121160: PE6_time_delay_max - t39_end_ - 10000.0*t_39_map_6 >= -10000.0\n", - "_C121161: PE6_time_delay_min - t39_start + 10000.0*t_39_map_6 <= 10000.0\n", - "_C121162: PE6_time_delay_max - t40_end_ - 10000.0*t_40_map_6 >= -10000.0\n", - "_C121163: PE6_time_delay_min - t40_start + 10000.0*t_40_map_6 <= 10000.0\n", - "_C121164: PE6_time_delay_max - t41_end_ - 10000.0*t_41_map_6 >= -10000.0\n", - "_C121165: PE6_time_delay_min - t41_start + 10000.0*t_41_map_6 <= 10000.0\n", - "_C121166: PE6_time_delay_max - t42_end_ - 10000.0*t_42_map_6 >= -10000.0\n", - "_C121167: PE6_time_delay_min - t42_start + 10000.0*t_42_map_6 <= 10000.0\n", - "_C121168: PE6_time_delay_max - t43_end_ - 10000.0*t_43_map_6 >= -10000.0\n", - "_C121169: PE6_time_delay_min - t43_start + 10000.0*t_43_map_6 <= 10000.0\n", - "_C121170: PE6_time_delay_max - t44_end_ - 10000.0*t_44_map_6 >= -10000.0\n", - "_C121171: PE6_time_delay_min - t44_start + 10000.0*t_44_map_6 <= 10000.0\n", - "_C121172: PE6_time_delay_max - t45_end_ - 10000.0*t_45_map_6 >= -10000.0\n", - "_C121173: PE6_time_delay_min - t45_start + 10000.0*t_45_map_6 <= 10000.0\n", - "_C121174: PE6_time_delay_max - t46_end_ - 10000.0*t_46_map_6 >= -10000.0\n", - "_C121175: PE6_time_delay_min - t46_start + 10000.0*t_46_map_6 <= 10000.0\n", - "_C121176: PE6_time_delay_max - t47_end_ - 10000.0*t_47_map_6 >= -10000.0\n", - "_C121177: PE6_time_delay_min - t47_start + 10000.0*t_47_map_6 <= 10000.0\n", - "_C121178: PE6_time_delay_max - t48_end_ - 10000.0*t_48_map_6 >= -10000.0\n", - "_C121179: PE6_time_delay_min - t48_start + 10000.0*t_48_map_6 <= 10000.0\n", - "_C121180: PE6_time_delay_max - t49_end_ - 10000.0*t_49_map_6 >= -10000.0\n", - "_C121181: PE6_time_delay_min - t49_start + 10000.0*t_49_map_6 <= 10000.0\n", - "_C121182: PE6_time_delay_max - t50_end_ - 10000.0*t_50_map_6 >= -10000.0\n", - "_C121183: PE6_time_delay_min - t50_start + 10000.0*t_50_map_6 <= 10000.0\n", - "_C121184: PE6_time_delay_max - t51_end_ - 10000.0*t_51_map_6 >= -10000.0\n", - "_C121185: PE6_time_delay_min - t51_start + 10000.0*t_51_map_6 <= 10000.0\n", - "_C121186: PE6_time_delay_max - t52_end_ - 10000.0*t_52_map_6 >= -10000.0\n", - "_C121187: PE6_time_delay_min - t52_start + 10000.0*t_52_map_6 <= 10000.0\n", - "_C121188: PE6_time_delay_max - t53_end_ - 10000.0*t_53_map_6 >= -10000.0\n", - "_C121189: PE6_time_delay_min - t53_start + 10000.0*t_53_map_6 <= 10000.0\n", - "_C121190: PE6_time_delay_max - t54_end_ - 10000.0*t_54_map_6 >= -10000.0\n", - "_C121191: PE6_time_delay_min - t54_start + 10000.0*t_54_map_6 <= 10000.0\n", - "_C121192: PE6_time_delay_max - t55_end_ - 10000.0*t_55_map_6 >= -10000.0\n", - "_C121193: PE6_time_delay_min - t55_start + 10000.0*t_55_map_6 <= 10000.0\n", - "_C121194: PE6_time_delay_max - t56_end_ - 10000.0*t_56_map_6 >= -10000.0\n", - "_C121195: PE6_time_delay_min - t56_start + 10000.0*t_56_map_6 <= 10000.0\n", - "_C121196: PE6_time_delay_max - t57_end_ - 10000.0*t_57_map_6 >= -10000.0\n", - "_C121197: PE6_time_delay_min - t57_start + 10000.0*t_57_map_6 <= 10000.0\n", - "_C121198: PE6_time_delay_max - t58_end_ - 10000.0*t_58_map_6 >= -10000.0\n", - "_C121199: PE6_time_delay_min - t58_start + 10000.0*t_58_map_6 <= 10000.0\n", - "_C121200: PE6_time_delay_max - t59_end_ - 10000.0*t_59_map_6 >= -10000.0\n", - "_C121201: PE6_time_delay_min - t59_start + 10000.0*t_59_map_6 <= 10000.0\n", - "_C121202: PE6_time_delay_max - t60_end_ - 10000.0*t_60_map_6 >= -10000.0\n", - "_C121203: PE6_time_delay_min - t60_start + 10000.0*t_60_map_6 <= 10000.0\n", - "_C121204: PE6_time_delay_max - t61_end_ - 10000.0*t_61_map_6 >= -10000.0\n", - "_C121205: PE6_time_delay_min - t61_start + 10000.0*t_61_map_6 <= 10000.0\n", - "_C121206: PE6_time_delay_max - t62_end_ - 10000.0*t_62_map_6 >= -10000.0\n", - "_C121207: PE6_time_delay_min - t62_start + 10000.0*t_62_map_6 <= 10000.0\n", - "_C121208: PE6_time_delay_max - t63_end_ - 10000.0*t_63_map_6 >= -10000.0\n", - "_C121209: PE6_time_delay_min - t63_start + 10000.0*t_63_map_6 <= 10000.0\n", - "_C121210: PE6_time_delay_max - t64_end_ - 10000.0*t_64_map_6 >= -10000.0\n", - "_C121211: PE6_time_delay_min - t64_start + 10000.0*t_64_map_6 <= 10000.0\n", - "_C121212: PE6_time_delay_max - t65_end_ - 10000.0*t_65_map_6 >= -10000.0\n", - "_C121213: PE6_time_delay_min - t65_start + 10000.0*t_65_map_6 <= 10000.0\n", - "_C121214: PE6_time_delay_max - t66_end_ - 10000.0*t_66_map_6 >= -10000.0\n", - "_C121215: PE6_time_delay_min - t66_start + 10000.0*t_66_map_6 <= 10000.0\n", - "_C121216: PE6_time_delay_max - t67_end_ - 10000.0*t_67_map_6 >= -10000.0\n", - "_C121217: PE6_time_delay_min - t67_start + 10000.0*t_67_map_6 <= 10000.0\n", - "_C121218: PE6_time_delay_max - t68_end_ - 10000.0*t_68_map_6 >= -10000.0\n", - "_C121219: PE6_time_delay_min - t68_start + 10000.0*t_68_map_6 <= 10000.0\n", - "_C121220: PE6_time_delay_max - t69_end_ - 10000.0*t_69_map_6 >= -10000.0\n", - "_C121221: PE6_time_delay_min - t69_start + 10000.0*t_69_map_6 <= 10000.0\n", - "_C121222: -PE6_time_delay_max + PE6_time_delay_min + PE6_total_time_delay = 0\n", - "_C121223: -PE6_total_time_delay + max_router_delay >= 0\n", - "_C121224: PE6_total_time_delay <= 280\n", - "_C121225: -t0_end_ + t0_start - 10000.0*t_0_map_7 - t_send_0 + task_total_delay_router_router7_task0 >= -10000.0\n", - "_C121226: -10000.0*t_0_map_7 - t_mem_0 + task_total_memory_router_router7_task0 >= -10000.0\n", - "_C121227: -t1_end_ + 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task_total_memory_router_router7_task15 - task_total_memory_router_router7_task16 - task_total_memory_router_router7_task17 - task_total_memory_router_router7_task18 - task_total_memory_router_router7_task19 - task_total_memory_router_router7_task2 - task_total_memory_router_router7_task20 - task_total_memory_router_router7_task21 - task_total_memory_router_router7_task22 - task_total_memory_router_router7_task23 - task_total_memory_router_router7_task24 - task_total_memory_router_router7_task25 - task_total_memory_router_router7_task26 - task_total_memory_router_router7_task27 - task_total_memory_router_router7_task28 - task_total_memory_router_router7_task29 - task_total_memory_router_router7_task3 - task_total_memory_router_router7_task30 - task_total_memory_router_router7_task31 - task_total_memory_router_router7_task32 - task_total_memory_router_router7_task33 - task_total_memory_router_router7_task34 - task_total_memory_router_router7_task35 - task_total_memory_router_router7_task36 - task_total_memory_router_router7_task37 - task_total_memory_router_router7_task38 - task_total_memory_router_router7_task39 - task_total_memory_router_router7_task4 - task_total_memory_router_router7_task40 - task_total_memory_router_router7_task41 - task_total_memory_router_router7_task42 - task_total_memory_router_router7_task43 - task_total_memory_router_router7_task44 - task_total_memory_router_router7_task45 - task_total_memory_router_router7_task46 - task_total_memory_router_router7_task47 - task_total_memory_router_router7_task48 - task_total_memory_router_router7_task49 - task_total_memory_router_router7_task5 - task_total_memory_router_router7_task50 - task_total_memory_router_router7_task51 - task_total_memory_router_router7_task52 - task_total_memory_router_router7_task53 - task_total_memory_router_router7_task54 - task_total_memory_router_router7_task55 - task_total_memory_router_router7_task56 - task_total_memory_router_router7_task57 - task_total_memory_router_router7_task58 - task_total_memory_router_router7_task59 - task_total_memory_router_router7_task6 - task_total_memory_router_router7_task60 - task_total_memory_router_router7_task61 - task_total_memory_router_router7_task62 - task_total_memory_router_router7_task63 - task_total_memory_router_router7_task64 - task_total_memory_router_router7_task65 - task_total_memory_router_router7_task66 - task_total_memory_router_router7_task67 - task_total_memory_router_router7_task68 - task_total_memory_router_router7_task69 - task_total_memory_router_router7_task7 - task_total_memory_router_router7_task8 - task_total_memory_router_router7_task9 >= -0.0\n", - "_C121366: PE7_total_delay - task_total_delay_router_router7_task0 - task_total_delay_router_router7_task1 - task_total_delay_router_router7_task10 - task_total_delay_router_router7_task11 - task_total_delay_router_router7_task12 - task_total_delay_router_router7_task13 - task_total_delay_router_router7_task14 - task_total_delay_router_router7_task15 - task_total_delay_router_router7_task16 - task_total_delay_router_router7_task17 - task_total_delay_router_router7_task18 - task_total_delay_router_router7_task19 - task_total_delay_router_router7_task2 - task_total_delay_router_router7_task20 - task_total_delay_router_router7_task21 - task_total_delay_router_router7_task22 - task_total_delay_router_router7_task23 - task_total_delay_router_router7_task24 - task_total_delay_router_router7_task25 - task_total_delay_router_router7_task26 - task_total_delay_router_router7_task27 - task_total_delay_router_router7_task28 - task_total_delay_router_router7_task29 - task_total_delay_router_router7_task3 - task_total_delay_router_router7_task30 - task_total_delay_router_router7_task31 - task_total_delay_router_router7_task32 - task_total_delay_router_router7_task33 - task_total_delay_router_router7_task34 - task_total_delay_router_router7_task35 - task_total_delay_router_router7_task36 - task_total_delay_router_router7_task37 - task_total_delay_router_router7_task38 - task_total_delay_router_router7_task39 - task_total_delay_router_router7_task4 - task_total_delay_router_router7_task40 - task_total_delay_router_router7_task41 - task_total_delay_router_router7_task42 - task_total_delay_router_router7_task43 - task_total_delay_router_router7_task44 - task_total_delay_router_router7_task45 - task_total_delay_router_router7_task46 - task_total_delay_router_router7_task47 - task_total_delay_router_router7_task48 - task_total_delay_router_router7_task49 - task_total_delay_router_router7_task5 - task_total_delay_router_router7_task50 - task_total_delay_router_router7_task51 - task_total_delay_router_router7_task52 - task_total_delay_router_router7_task53 - task_total_delay_router_router7_task54 - task_total_delay_router_router7_task55 - task_total_delay_router_router7_task56 - task_total_delay_router_router7_task57 - task_total_delay_router_router7_task58 - task_total_delay_router_router7_task59 - task_total_delay_router_router7_task6 - task_total_delay_router_router7_task60 - task_total_delay_router_router7_task61 - task_total_delay_router_router7_task62 - task_total_delay_router_router7_task63 - task_total_delay_router_router7_task64 - task_total_delay_router_router7_task65 - task_total_delay_router_router7_task66 - task_total_delay_router_router7_task67 - task_total_delay_router_router7_task68 - task_total_delay_router_router7_task69 - task_total_delay_router_router7_task7 - task_total_delay_router_router7_task8 - task_total_delay_router_router7_task9 >= -0.0\n", - "_C121367: PE7_total_memory - task_total_memory_router_router7_task0 - task_total_memory_router_router7_task1 - task_total_memory_router_router7_task10 - task_total_memory_router_router7_task11 - task_total_memory_router_router7_task12 - task_total_memory_router_router7_task13 - task_total_memory_router_router7_task14 - task_total_memory_router_router7_task15 - task_total_memory_router_router7_task16 - task_total_memory_router_router7_task17 - task_total_memory_router_router7_task18 - task_total_memory_router_router7_task19 - task_total_memory_router_router7_task2 - task_total_memory_router_router7_task20 - task_total_memory_router_router7_task21 - task_total_memory_router_router7_task22 - task_total_memory_router_router7_task23 - task_total_memory_router_router7_task24 - task_total_memory_router_router7_task25 - task_total_memory_router_router7_task26 - task_total_memory_router_router7_task27 - task_total_memory_router_router7_task28 - task_total_memory_router_router7_task29 - task_total_memory_router_router7_task3 - task_total_memory_router_router7_task30 - task_total_memory_router_router7_task31 - task_total_memory_router_router7_task32 - task_total_memory_router_router7_task33 - task_total_memory_router_router7_task34 - task_total_memory_router_router7_task35 - task_total_memory_router_router7_task36 - task_total_memory_router_router7_task37 - task_total_memory_router_router7_task38 - task_total_memory_router_router7_task39 - task_total_memory_router_router7_task4 - task_total_memory_router_router7_task40 - task_total_memory_router_router7_task41 - task_total_memory_router_router7_task42 - task_total_memory_router_router7_task43 - task_total_memory_router_router7_task44 - task_total_memory_router_router7_task45 - task_total_memory_router_router7_task46 - task_total_memory_router_router7_task47 - task_total_memory_router_router7_task48 - task_total_memory_router_router7_task49 - task_total_memory_router_router7_task5 - task_total_memory_router_router7_task50 - task_total_memory_router_router7_task51 - task_total_memory_router_router7_task52 - task_total_memory_router_router7_task53 - task_total_memory_router_router7_task54 - task_total_memory_router_router7_task55 - task_total_memory_router_router7_task56 - task_total_memory_router_router7_task57 - task_total_memory_router_router7_task58 - task_total_memory_router_router7_task59 - task_total_memory_router_router7_task6 - task_total_memory_router_router7_task60 - task_total_memory_router_router7_task61 - task_total_memory_router_router7_task62 - task_total_memory_router_router7_task63 - task_total_memory_router_router7_task64 - task_total_memory_router_router7_task65 - task_total_memory_router_router7_task66 - task_total_memory_router_router7_task67 - task_total_memory_router_router7_task68 - task_total_memory_router_router7_task69 - task_total_memory_router_router7_task7 - task_total_memory_router_router7_task8 - task_total_memory_router_router7_task9 >= -0.0\n", - "_C121368: -PE_mem_overflow7 + max_memory_overflow >= 0\n", - "_C121369: PE7_time_delay_max - t0_end_ - 10000.0*t_0_map_7 >= -10000.0\n", - "_C121370: PE7_time_delay_min - t0_start + 10000.0*t_0_map_7 <= 10000.0\n", - "_C121371: PE7_time_delay_max - t1_end_ - 10000.0*t_1_map_7 >= -10000.0\n", - "_C121372: PE7_time_delay_min - t1_start + 10000.0*t_1_map_7 <= 10000.0\n", - "_C121373: PE7_time_delay_max - t2_end_ - 10000.0*t_2_map_7 >= -10000.0\n", - "_C121374: PE7_time_delay_min - t2_start + 10000.0*t_2_map_7 <= 10000.0\n", - "_C121375: PE7_time_delay_max - t3_end_ - 10000.0*t_3_map_7 >= -10000.0\n", - "_C121376: PE7_time_delay_min - t3_start + 10000.0*t_3_map_7 <= 10000.0\n", - "_C121377: PE7_time_delay_max - t4_end_ - 10000.0*t_4_map_7 >= -10000.0\n", - "_C121378: PE7_time_delay_min - t4_start + 10000.0*t_4_map_7 <= 10000.0\n", - "_C121379: PE7_time_delay_max - t5_end_ - 10000.0*t_5_map_7 >= -10000.0\n", - "_C121380: PE7_time_delay_min - t5_start + 10000.0*t_5_map_7 <= 10000.0\n", - "_C121381: PE7_time_delay_max - t6_end_ - 10000.0*t_6_map_7 >= -10000.0\n", - "_C121382: PE7_time_delay_min - t6_start + 10000.0*t_6_map_7 <= 10000.0\n", - "_C121383: PE7_time_delay_max - t7_end_ - 10000.0*t_7_map_7 >= -10000.0\n", - "_C121384: PE7_time_delay_min - t7_start + 10000.0*t_7_map_7 <= 10000.0\n", - "_C121385: PE7_time_delay_max - t8_end_ - 10000.0*t_8_map_7 >= -10000.0\n", - "_C121386: PE7_time_delay_min - t8_start + 10000.0*t_8_map_7 <= 10000.0\n", - "_C121387: PE7_time_delay_max - t9_end_ - 10000.0*t_9_map_7 >= -10000.0\n", - "_C121388: PE7_time_delay_min - t9_start + 10000.0*t_9_map_7 <= 10000.0\n", - "_C121389: PE7_time_delay_max - t10_end_ - 10000.0*t_10_map_7 >= -10000.0\n", - "_C121390: PE7_time_delay_min - t10_start + 10000.0*t_10_map_7 <= 10000.0\n", - "_C121391: PE7_time_delay_max - t11_end_ - 10000.0*t_11_map_7 >= -10000.0\n", - "_C121392: PE7_time_delay_min - t11_start + 10000.0*t_11_map_7 <= 10000.0\n", - "_C121393: PE7_time_delay_max - t12_end_ - 10000.0*t_12_map_7 >= -10000.0\n", - "_C121394: PE7_time_delay_min - t12_start + 10000.0*t_12_map_7 <= 10000.0\n", - "_C121395: PE7_time_delay_max - t13_end_ - 10000.0*t_13_map_7 >= -10000.0\n", - "_C121396: PE7_time_delay_min - t13_start + 10000.0*t_13_map_7 <= 10000.0\n", - "_C121397: PE7_time_delay_max - t14_end_ - 10000.0*t_14_map_7 >= -10000.0\n", - "_C121398: PE7_time_delay_min - t14_start + 10000.0*t_14_map_7 <= 10000.0\n", - "_C121399: PE7_time_delay_max - t15_end_ - 10000.0*t_15_map_7 >= -10000.0\n", - "_C121400: PE7_time_delay_min - t15_start + 10000.0*t_15_map_7 <= 10000.0\n", - "_C121401: PE7_time_delay_max - t16_end_ - 10000.0*t_16_map_7 >= -10000.0\n", - "_C121402: PE7_time_delay_min - t16_start + 10000.0*t_16_map_7 <= 10000.0\n", - "_C121403: PE7_time_delay_max - t17_end_ - 10000.0*t_17_map_7 >= -10000.0\n", - "_C121404: PE7_time_delay_min - t17_start + 10000.0*t_17_map_7 <= 10000.0\n", - "_C121405: PE7_time_delay_max - t18_end_ - 10000.0*t_18_map_7 >= -10000.0\n", - "_C121406: PE7_time_delay_min - t18_start + 10000.0*t_18_map_7 <= 10000.0\n", - "_C121407: PE7_time_delay_max - t19_end_ - 10000.0*t_19_map_7 >= -10000.0\n", - "_C121408: PE7_time_delay_min - t19_start + 10000.0*t_19_map_7 <= 10000.0\n", - "_C121409: PE7_time_delay_max - t20_end_ - 10000.0*t_20_map_7 >= -10000.0\n", - "_C121410: PE7_time_delay_min - t20_start + 10000.0*t_20_map_7 <= 10000.0\n", - "_C121411: PE7_time_delay_max - t21_end_ - 10000.0*t_21_map_7 >= -10000.0\n", - "_C121412: PE7_time_delay_min - t21_start + 10000.0*t_21_map_7 <= 10000.0\n", - "_C121413: PE7_time_delay_max - t22_end_ - 10000.0*t_22_map_7 >= -10000.0\n", - "_C121414: PE7_time_delay_min - t22_start + 10000.0*t_22_map_7 <= 10000.0\n", - "_C121415: PE7_time_delay_max - t23_end_ - 10000.0*t_23_map_7 >= -10000.0\n", - "_C121416: PE7_time_delay_min - t23_start + 10000.0*t_23_map_7 <= 10000.0\n", - "_C121417: PE7_time_delay_max - t24_end_ - 10000.0*t_24_map_7 >= -10000.0\n", - "_C121418: PE7_time_delay_min - t24_start + 10000.0*t_24_map_7 <= 10000.0\n", - "_C121419: PE7_time_delay_max - t25_end_ - 10000.0*t_25_map_7 >= -10000.0\n", - "_C121420: PE7_time_delay_min - t25_start + 10000.0*t_25_map_7 <= 10000.0\n", - "_C121421: PE7_time_delay_max - t26_end_ - 10000.0*t_26_map_7 >= -10000.0\n", - "_C121422: PE7_time_delay_min - t26_start + 10000.0*t_26_map_7 <= 10000.0\n", - "_C121423: PE7_time_delay_max - t27_end_ - 10000.0*t_27_map_7 >= -10000.0\n", - "_C121424: PE7_time_delay_min - t27_start + 10000.0*t_27_map_7 <= 10000.0\n", - "_C121425: PE7_time_delay_max - t28_end_ - 10000.0*t_28_map_7 >= -10000.0\n", - "_C121426: PE7_time_delay_min - t28_start + 10000.0*t_28_map_7 <= 10000.0\n", - "_C121427: PE7_time_delay_max - t29_end_ - 10000.0*t_29_map_7 >= -10000.0\n", - "_C121428: PE7_time_delay_min - t29_start + 10000.0*t_29_map_7 <= 10000.0\n", - "_C121429: PE7_time_delay_max - t30_end_ - 10000.0*t_30_map_7 >= -10000.0\n", - "_C121430: PE7_time_delay_min - t30_start + 10000.0*t_30_map_7 <= 10000.0\n", - "_C121431: PE7_time_delay_max - t31_end_ - 10000.0*t_31_map_7 >= -10000.0\n", - "_C121432: PE7_time_delay_min - t31_start + 10000.0*t_31_map_7 <= 10000.0\n", - "_C121433: PE7_time_delay_max - t32_end_ - 10000.0*t_32_map_7 >= -10000.0\n", - "_C121434: PE7_time_delay_min - t32_start + 10000.0*t_32_map_7 <= 10000.0\n", - "_C121435: PE7_time_delay_max - t33_end_ - 10000.0*t_33_map_7 >= -10000.0\n", - "_C121436: PE7_time_delay_min - t33_start + 10000.0*t_33_map_7 <= 10000.0\n", - "_C121437: PE7_time_delay_max - t34_end_ - 10000.0*t_34_map_7 >= -10000.0\n", - "_C121438: PE7_time_delay_min - t34_start + 10000.0*t_34_map_7 <= 10000.0\n", - "_C121439: PE7_time_delay_max - t35_end_ - 10000.0*t_35_map_7 >= -10000.0\n", - "_C121440: PE7_time_delay_min - t35_start + 10000.0*t_35_map_7 <= 10000.0\n", - "_C121441: PE7_time_delay_max - t36_end_ - 10000.0*t_36_map_7 >= -10000.0\n", - "_C121442: PE7_time_delay_min - t36_start + 10000.0*t_36_map_7 <= 10000.0\n", - "_C121443: PE7_time_delay_max - t37_end_ - 10000.0*t_37_map_7 >= -10000.0\n", - "_C121444: PE7_time_delay_min - t37_start + 10000.0*t_37_map_7 <= 10000.0\n", - "_C121445: PE7_time_delay_max - t38_end_ - 10000.0*t_38_map_7 >= -10000.0\n", - "_C121446: PE7_time_delay_min - t38_start + 10000.0*t_38_map_7 <= 10000.0\n", - "_C121447: PE7_time_delay_max - t39_end_ - 10000.0*t_39_map_7 >= -10000.0\n", - "_C121448: PE7_time_delay_min - t39_start + 10000.0*t_39_map_7 <= 10000.0\n", - "_C121449: PE7_time_delay_max - t40_end_ - 10000.0*t_40_map_7 >= -10000.0\n", - "_C121450: PE7_time_delay_min - t40_start + 10000.0*t_40_map_7 <= 10000.0\n", - "_C121451: PE7_time_delay_max - t41_end_ - 10000.0*t_41_map_7 >= -10000.0\n", - "_C121452: PE7_time_delay_min - t41_start + 10000.0*t_41_map_7 <= 10000.0\n", - "_C121453: PE7_time_delay_max - t42_end_ - 10000.0*t_42_map_7 >= -10000.0\n", - "_C121454: PE7_time_delay_min - t42_start + 10000.0*t_42_map_7 <= 10000.0\n", - "_C121455: PE7_time_delay_max - t43_end_ - 10000.0*t_43_map_7 >= -10000.0\n", - "_C121456: PE7_time_delay_min - t43_start + 10000.0*t_43_map_7 <= 10000.0\n", - "_C121457: PE7_time_delay_max - t44_end_ - 10000.0*t_44_map_7 >= -10000.0\n", - "_C121458: PE7_time_delay_min - t44_start + 10000.0*t_44_map_7 <= 10000.0\n", - "_C121459: PE7_time_delay_max - t45_end_ - 10000.0*t_45_map_7 >= -10000.0\n", - "_C121460: PE7_time_delay_min - t45_start + 10000.0*t_45_map_7 <= 10000.0\n", - "_C121461: PE7_time_delay_max - t46_end_ - 10000.0*t_46_map_7 >= -10000.0\n", - "_C121462: PE7_time_delay_min - t46_start + 10000.0*t_46_map_7 <= 10000.0\n", - "_C121463: PE7_time_delay_max - t47_end_ - 10000.0*t_47_map_7 >= -10000.0\n", - "_C121464: PE7_time_delay_min - t47_start + 10000.0*t_47_map_7 <= 10000.0\n", - "_C121465: PE7_time_delay_max - t48_end_ - 10000.0*t_48_map_7 >= -10000.0\n", - "_C121466: PE7_time_delay_min - t48_start + 10000.0*t_48_map_7 <= 10000.0\n", - "_C121467: PE7_time_delay_max - t49_end_ - 10000.0*t_49_map_7 >= -10000.0\n", - "_C121468: PE7_time_delay_min - t49_start + 10000.0*t_49_map_7 <= 10000.0\n", - "_C121469: PE7_time_delay_max - t50_end_ - 10000.0*t_50_map_7 >= -10000.0\n", - "_C121470: PE7_time_delay_min - t50_start + 10000.0*t_50_map_7 <= 10000.0\n", - "_C121471: PE7_time_delay_max - t51_end_ - 10000.0*t_51_map_7 >= -10000.0\n", - "_C121472: PE7_time_delay_min - t51_start + 10000.0*t_51_map_7 <= 10000.0\n", - "_C121473: PE7_time_delay_max - t52_end_ - 10000.0*t_52_map_7 >= -10000.0\n", - "_C121474: PE7_time_delay_min - t52_start + 10000.0*t_52_map_7 <= 10000.0\n", - "_C121475: PE7_time_delay_max - t53_end_ - 10000.0*t_53_map_7 >= -10000.0\n", - "_C121476: PE7_time_delay_min - t53_start + 10000.0*t_53_map_7 <= 10000.0\n", - "_C121477: PE7_time_delay_max - t54_end_ - 10000.0*t_54_map_7 >= -10000.0\n", - "_C121478: PE7_time_delay_min - t54_start + 10000.0*t_54_map_7 <= 10000.0\n", - "_C121479: PE7_time_delay_max - t55_end_ - 10000.0*t_55_map_7 >= -10000.0\n", - "_C121480: PE7_time_delay_min - t55_start + 10000.0*t_55_map_7 <= 10000.0\n", - "_C121481: PE7_time_delay_max - t56_end_ - 10000.0*t_56_map_7 >= -10000.0\n", - "_C121482: PE7_time_delay_min - t56_start + 10000.0*t_56_map_7 <= 10000.0\n", - "_C121483: PE7_time_delay_max - t57_end_ - 10000.0*t_57_map_7 >= -10000.0\n", - "_C121484: PE7_time_delay_min - t57_start + 10000.0*t_57_map_7 <= 10000.0\n", - "_C121485: PE7_time_delay_max - t58_end_ - 10000.0*t_58_map_7 >= -10000.0\n", - "_C121486: PE7_time_delay_min - t58_start + 10000.0*t_58_map_7 <= 10000.0\n", - "_C121487: PE7_time_delay_max - t59_end_ - 10000.0*t_59_map_7 >= -10000.0\n", - "_C121488: PE7_time_delay_min - t59_start + 10000.0*t_59_map_7 <= 10000.0\n", - "_C121489: PE7_time_delay_max - t60_end_ - 10000.0*t_60_map_7 >= -10000.0\n", - "_C121490: PE7_time_delay_min - t60_start + 10000.0*t_60_map_7 <= 10000.0\n", - "_C121491: PE7_time_delay_max - t61_end_ - 10000.0*t_61_map_7 >= -10000.0\n", - "_C121492: PE7_time_delay_min - t61_start + 10000.0*t_61_map_7 <= 10000.0\n", - "_C121493: PE7_time_delay_max - t62_end_ - 10000.0*t_62_map_7 >= -10000.0\n", - "_C121494: PE7_time_delay_min - t62_start + 10000.0*t_62_map_7 <= 10000.0\n", - "_C121495: PE7_time_delay_max - t63_end_ - 10000.0*t_63_map_7 >= -10000.0\n", - "_C121496: PE7_time_delay_min - t63_start + 10000.0*t_63_map_7 <= 10000.0\n", - "_C121497: PE7_time_delay_max - t64_end_ - 10000.0*t_64_map_7 >= -10000.0\n", - "_C121498: PE7_time_delay_min - t64_start + 10000.0*t_64_map_7 <= 10000.0\n", - "_C121499: PE7_time_delay_max - t65_end_ - 10000.0*t_65_map_7 >= -10000.0\n", - "_C121500: PE7_time_delay_min - t65_start + 10000.0*t_65_map_7 <= 10000.0\n", - "_C121501: PE7_time_delay_max - t66_end_ - 10000.0*t_66_map_7 >= -10000.0\n", - "_C121502: PE7_time_delay_min - t66_start + 10000.0*t_66_map_7 <= 10000.0\n", - "_C121503: PE7_time_delay_max - t67_end_ - 10000.0*t_67_map_7 >= -10000.0\n", - "_C121504: PE7_time_delay_min - t67_start + 10000.0*t_67_map_7 <= 10000.0\n", - "_C121505: PE7_time_delay_max - t68_end_ - 10000.0*t_68_map_7 >= -10000.0\n", - "_C121506: PE7_time_delay_min - t68_start + 10000.0*t_68_map_7 <= 10000.0\n", - "_C121507: PE7_time_delay_max - t69_end_ - 10000.0*t_69_map_7 >= -10000.0\n", - "_C121508: PE7_time_delay_min - t69_start + 10000.0*t_69_map_7 <= 10000.0\n", - "_C121509: -PE7_time_delay_max + PE7_time_delay_min + PE7_total_time_delay = 0\n", - "_C121510: -PE7_total_time_delay + max_router_delay >= 0\n", - "_C121511: PE7_total_time_delay <= 280\n", - "_C121512: -t0_end_ + t0_start - 10000.0*t_0_map_8 - t_send_0 + task_total_delay_router_router8_task0 >= -10000.0\n", - "_C121513: -10000.0*t_0_map_8 - t_mem_0 + task_total_memory_router_router8_task0 >= -10000.0\n", - "_C121514: -t1_end_ + t1_start - 10000.0*t_1_map_8 - t_send_1 + task_total_delay_router_router8_task1 >= -10000.0\n", - "_C121515: -10000.0*t_1_map_8 - t_mem_1 + task_total_memory_router_router8_task1 >= -10000.0\n", - "_C121516: -t2_end_ + t2_start - 10000.0*t_2_map_8 - t_send_2 + task_total_delay_router_router8_task2 >= -10000.0\n", - "_C121517: -10000.0*t_2_map_8 - t_mem_2 + task_total_memory_router_router8_task2 >= -10000.0\n", - "_C121518: -t3_end_ + t3_start - 10000.0*t_3_map_8 - t_send_3 + task_total_delay_router_router8_task3 >= -10000.0\n", - "_C121519: -10000.0*t_3_map_8 - t_mem_3 + task_total_memory_router_router8_task3 >= -10000.0\n", - "_C121520: -t4_end_ + t4_start - 10000.0*t_4_map_8 - t_send_4 + task_total_delay_router_router8_task4 >= -10000.0\n", - "_C121521: -10000.0*t_4_map_8 - t_mem_4 + task_total_memory_router_router8_task4 >= -10000.0\n", - "_C121522: -t5_end_ + t5_start - 10000.0*t_5_map_8 - t_send_5 + task_total_delay_router_router8_task5 >= -10000.0\n", - "_C121523: -10000.0*t_5_map_8 - t_mem_5 + task_total_memory_router_router8_task5 >= -10000.0\n", - "_C121524: -t6_end_ + t6_start - 10000.0*t_6_map_8 - t_send_6 + task_total_delay_router_router8_task6 >= -10000.0\n", - "_C121525: -10000.0*t_6_map_8 - t_mem_6 + task_total_memory_router_router8_task6 >= -10000.0\n", - "_C121526: -t7_end_ + t7_start - 10000.0*t_7_map_8 - t_send_7 + task_total_delay_router_router8_task7 >= -10000.0\n", - "_C121527: -10000.0*t_7_map_8 - t_mem_7 + task_total_memory_router_router8_task7 >= -10000.0\n", - "_C121528: -t8_end_ + t8_start - 10000.0*t_8_map_8 - t_send_8 + task_total_delay_router_router8_task8 >= -10000.0\n", - "_C121529: -10000.0*t_8_map_8 - t_mem_8 + task_total_memory_router_router8_task8 >= -10000.0\n", - "_C121530: -t9_end_ + t9_start - 10000.0*t_9_map_8 - t_send_9 + task_total_delay_router_router8_task9 >= -10000.0\n", - "_C121531: -10000.0*t_9_map_8 - t_mem_9 + task_total_memory_router_router8_task9 >= -10000.0\n", - "_C121532: -t10_end_ + t10_start - 10000.0*t_10_map_8 - t_send_10 + task_total_delay_router_router8_task10 >= -10000.0\n", - "_C121533: -10000.0*t_10_map_8 - t_mem_10 + task_total_memory_router_router8_task10 >= -10000.0\n", - "_C121534: -t11_end_ + t11_start - 10000.0*t_11_map_8 - t_send_11 + task_total_delay_router_router8_task11 >= -10000.0\n", - "_C121535: -10000.0*t_11_map_8 - t_mem_11 + task_total_memory_router_router8_task11 >= -10000.0\n", - "_C121536: -t12_end_ + t12_start - 10000.0*t_12_map_8 - t_send_12 + task_total_delay_router_router8_task12 >= -10000.0\n", - "_C121537: -10000.0*t_12_map_8 - t_mem_12 + task_total_memory_router_router8_task12 >= -10000.0\n", - "_C121538: -t13_end_ + t13_start - 10000.0*t_13_map_8 - t_send_13 + task_total_delay_router_router8_task13 >= -10000.0\n", - "_C121539: -10000.0*t_13_map_8 - t_mem_13 + task_total_memory_router_router8_task13 >= -10000.0\n", - "_C121540: -t14_end_ + t14_start - 10000.0*t_14_map_8 - t_send_14 + task_total_delay_router_router8_task14 >= -10000.0\n", - "_C121541: -10000.0*t_14_map_8 - t_mem_14 + task_total_memory_router_router8_task14 >= -10000.0\n", - "_C121542: -t15_end_ + t15_start - 10000.0*t_15_map_8 - t_send_15 + task_total_delay_router_router8_task15 >= -10000.0\n", - "_C121543: -10000.0*t_15_map_8 - t_mem_15 + task_total_memory_router_router8_task15 >= -10000.0\n", - "_C121544: -t16_end_ + t16_start - 10000.0*t_16_map_8 - t_send_16 + task_total_delay_router_router8_task16 >= -10000.0\n", - "_C121545: -10000.0*t_16_map_8 - t_mem_16 + task_total_memory_router_router8_task16 >= -10000.0\n", - "_C121546: -t17_end_ + t17_start - 10000.0*t_17_map_8 - t_send_17 + task_total_delay_router_router8_task17 >= -10000.0\n", - "_C121547: -10000.0*t_17_map_8 - t_mem_17 + task_total_memory_router_router8_task17 >= -10000.0\n", - "_C121548: -t18_end_ + t18_start - 10000.0*t_18_map_8 - t_send_18 + task_total_delay_router_router8_task18 >= -10000.0\n", - "_C121549: -10000.0*t_18_map_8 - t_mem_18 + task_total_memory_router_router8_task18 >= -10000.0\n", - "_C121550: -t19_end_ + t19_start - 10000.0*t_19_map_8 - t_send_19 + task_total_delay_router_router8_task19 >= -10000.0\n", - "_C121551: -10000.0*t_19_map_8 - t_mem_19 + task_total_memory_router_router8_task19 >= -10000.0\n", - "_C121552: -t20_end_ + t20_start - 10000.0*t_20_map_8 - t_send_20 + task_total_delay_router_router8_task20 >= -10000.0\n", - "_C121553: -10000.0*t_20_map_8 - t_mem_20 + task_total_memory_router_router8_task20 >= -10000.0\n", - "_C121554: -t21_end_ + t21_start - 10000.0*t_21_map_8 - t_send_21 + task_total_delay_router_router8_task21 >= -10000.0\n", - "_C121555: -10000.0*t_21_map_8 - t_mem_21 + task_total_memory_router_router8_task21 >= -10000.0\n", - "_C121556: -t22_end_ + t22_start - 10000.0*t_22_map_8 - t_send_22 + task_total_delay_router_router8_task22 >= -10000.0\n", - "_C121557: -10000.0*t_22_map_8 - t_mem_22 + task_total_memory_router_router8_task22 >= -10000.0\n", - "_C121558: -t23_end_ + t23_start - 10000.0*t_23_map_8 - t_send_23 + task_total_delay_router_router8_task23 >= -10000.0\n", - "_C121559: -10000.0*t_23_map_8 - t_mem_23 + task_total_memory_router_router8_task23 >= -10000.0\n", - "_C121560: -t24_end_ + t24_start - 10000.0*t_24_map_8 - t_send_24 + task_total_delay_router_router8_task24 >= -10000.0\n", - "_C121561: -10000.0*t_24_map_8 - t_mem_24 + task_total_memory_router_router8_task24 >= -10000.0\n", - "_C121562: -t25_end_ + t25_start - 10000.0*t_25_map_8 - t_send_25 + task_total_delay_router_router8_task25 >= -10000.0\n", - "_C121563: -10000.0*t_25_map_8 - t_mem_25 + task_total_memory_router_router8_task25 >= -10000.0\n", - "_C121564: -t26_end_ + t26_start - 10000.0*t_26_map_8 - t_send_26 + task_total_delay_router_router8_task26 >= -10000.0\n", - "_C121565: -10000.0*t_26_map_8 - t_mem_26 + task_total_memory_router_router8_task26 >= -10000.0\n", - "_C121566: -t27_end_ + t27_start - 10000.0*t_27_map_8 - t_send_27 + task_total_delay_router_router8_task27 >= -10000.0\n", - "_C121567: -10000.0*t_27_map_8 - t_mem_27 + task_total_memory_router_router8_task27 >= -10000.0\n", - "_C121568: -t28_end_ + t28_start - 10000.0*t_28_map_8 - t_send_28 + task_total_delay_router_router8_task28 >= -10000.0\n", - "_C121569: -10000.0*t_28_map_8 - t_mem_28 + task_total_memory_router_router8_task28 >= -10000.0\n", - "_C121570: -t29_end_ + t29_start - 10000.0*t_29_map_8 - t_send_29 + task_total_delay_router_router8_task29 >= -10000.0\n", - "_C121571: -10000.0*t_29_map_8 - t_mem_29 + task_total_memory_router_router8_task29 >= -10000.0\n", - "_C121572: -t30_end_ + 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task_total_memory_router_router8_task38 >= -10000.0\n", - "_C121590: -t39_end_ + t39_start - 10000.0*t_39_map_8 - t_send_39 + task_total_delay_router_router8_task39 >= -10000.0\n", - "_C121591: -10000.0*t_39_map_8 - t_mem_39 + task_total_memory_router_router8_task39 >= -10000.0\n", - "_C121592: -t40_end_ + t40_start - 10000.0*t_40_map_8 - t_send_40 + task_total_delay_router_router8_task40 >= -10000.0\n", - "_C121593: -10000.0*t_40_map_8 - t_mem_40 + task_total_memory_router_router8_task40 >= -10000.0\n", - "_C121594: -t41_end_ + t41_start - 10000.0*t_41_map_8 - t_send_41 + task_total_delay_router_router8_task41 >= -10000.0\n", - "_C121595: -10000.0*t_41_map_8 - t_mem_41 + task_total_memory_router_router8_task41 >= -10000.0\n", - "_C121596: -t42_end_ + t42_start - 10000.0*t_42_map_8 - t_send_42 + task_total_delay_router_router8_task42 >= -10000.0\n", - "_C121597: -10000.0*t_42_map_8 - t_mem_42 + task_total_memory_router_router8_task42 >= -10000.0\n", - "_C121598: -t43_end_ + t43_start - 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task_total_delay_router_router8_task56 >= -10000.0\n", - "_C121625: -10000.0*t_56_map_8 - t_mem_56 + task_total_memory_router_router8_task56 >= -10000.0\n", - "_C121626: -t57_end_ + t57_start - 10000.0*t_57_map_8 - t_send_57 + task_total_delay_router_router8_task57 >= -10000.0\n", - "_C121627: -10000.0*t_57_map_8 - t_mem_57 + task_total_memory_router_router8_task57 >= -10000.0\n", - "_C121628: -t58_end_ + t58_start - 10000.0*t_58_map_8 - t_send_58 + task_total_delay_router_router8_task58 >= -10000.0\n", - "_C121629: -10000.0*t_58_map_8 - t_mem_58 + task_total_memory_router_router8_task58 >= -10000.0\n", - "_C121630: -t59_end_ + t59_start - 10000.0*t_59_map_8 - t_send_59 + task_total_delay_router_router8_task59 >= -10000.0\n", - "_C121631: -10000.0*t_59_map_8 - t_mem_59 + task_total_memory_router_router8_task59 >= -10000.0\n", - "_C121632: -t60_end_ + t60_start - 10000.0*t_60_map_8 - t_send_60 + task_total_delay_router_router8_task60 >= -10000.0\n", - "_C121633: -10000.0*t_60_map_8 - t_mem_60 + task_total_memory_router_router8_task60 >= -10000.0\n", - "_C121634: -t61_end_ + t61_start - 10000.0*t_61_map_8 - t_send_61 + task_total_delay_router_router8_task61 >= -10000.0\n", - "_C121635: -10000.0*t_61_map_8 - t_mem_61 + task_total_memory_router_router8_task61 >= -10000.0\n", - "_C121636: -t62_end_ + t62_start - 10000.0*t_62_map_8 - t_send_62 + task_total_delay_router_router8_task62 >= -10000.0\n", - "_C121637: -10000.0*t_62_map_8 - t_mem_62 + task_total_memory_router_router8_task62 >= -10000.0\n", - "_C121638: -t63_end_ + t63_start - 10000.0*t_63_map_8 - t_send_63 + task_total_delay_router_router8_task63 >= -10000.0\n", - "_C121639: -10000.0*t_63_map_8 - t_mem_63 + task_total_memory_router_router8_task63 >= -10000.0\n", - "_C121640: -t64_end_ + t64_start - 10000.0*t_64_map_8 - t_send_64 + task_total_delay_router_router8_task64 >= -10000.0\n", - "_C121641: -10000.0*t_64_map_8 - t_mem_64 + task_total_memory_router_router8_task64 >= -10000.0\n", - "_C121642: -t65_end_ + t65_start - 10000.0*t_65_map_8 - t_send_65 + task_total_delay_router_router8_task65 >= -10000.0\n", - "_C121643: -10000.0*t_65_map_8 - t_mem_65 + task_total_memory_router_router8_task65 >= -10000.0\n", - "_C121644: -t66_end_ + t66_start - 10000.0*t_66_map_8 - t_send_66 + task_total_delay_router_router8_task66 >= -10000.0\n", - "_C121645: -10000.0*t_66_map_8 - t_mem_66 + task_total_memory_router_router8_task66 >= -10000.0\n", - "_C121646: -t67_end_ + t67_start - 10000.0*t_67_map_8 - t_send_67 + task_total_delay_router_router8_task67 >= -10000.0\n", - "_C121647: -10000.0*t_67_map_8 - t_mem_67 + task_total_memory_router_router8_task67 >= -10000.0\n", - "_C121648: -t68_end_ + t68_start - 10000.0*t_68_map_8 - t_send_68 + task_total_delay_router_router8_task68 >= -10000.0\n", - "_C121649: -10000.0*t_68_map_8 - t_mem_68 + task_total_memory_router_router8_task68 >= -10000.0\n", - "_C121650: -t69_end_ + t69_start - 10000.0*t_69_map_8 - t_send_69 + task_total_delay_router_router8_task69 >= 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task_total_memory_router_router8_task27 - task_total_memory_router_router8_task28 - task_total_memory_router_router8_task29 - task_total_memory_router_router8_task3 - task_total_memory_router_router8_task30 - task_total_memory_router_router8_task31 - task_total_memory_router_router8_task32 - task_total_memory_router_router8_task33 - task_total_memory_router_router8_task34 - task_total_memory_router_router8_task35 - task_total_memory_router_router8_task36 - task_total_memory_router_router8_task37 - task_total_memory_router_router8_task38 - task_total_memory_router_router8_task39 - task_total_memory_router_router8_task4 - task_total_memory_router_router8_task40 - task_total_memory_router_router8_task41 - task_total_memory_router_router8_task42 - task_total_memory_router_router8_task43 - task_total_memory_router_router8_task44 - task_total_memory_router_router8_task45 - task_total_memory_router_router8_task46 - task_total_memory_router_router8_task47 - task_total_memory_router_router8_task48 - task_total_memory_router_router8_task49 - task_total_memory_router_router8_task5 - task_total_memory_router_router8_task50 - task_total_memory_router_router8_task51 - task_total_memory_router_router8_task52 - task_total_memory_router_router8_task53 - task_total_memory_router_router8_task54 - task_total_memory_router_router8_task55 - task_total_memory_router_router8_task56 - task_total_memory_router_router8_task57 - task_total_memory_router_router8_task58 - task_total_memory_router_router8_task59 - task_total_memory_router_router8_task6 - task_total_memory_router_router8_task60 - task_total_memory_router_router8_task61 - task_total_memory_router_router8_task62 - task_total_memory_router_router8_task63 - task_total_memory_router_router8_task64 - task_total_memory_router_router8_task65 - task_total_memory_router_router8_task66 - task_total_memory_router_router8_task67 - task_total_memory_router_router8_task68 - task_total_memory_router_router8_task69 - task_total_memory_router_router8_task7 - task_total_memory_router_router8_task8 - task_total_memory_router_router8_task9 >= -0.0\n", - "_C121653: PE8_total_delay - task_total_delay_router_router8_task0 - task_total_delay_router_router8_task1 - task_total_delay_router_router8_task10 - task_total_delay_router_router8_task11 - task_total_delay_router_router8_task12 - task_total_delay_router_router8_task13 - task_total_delay_router_router8_task14 - task_total_delay_router_router8_task15 - task_total_delay_router_router8_task16 - task_total_delay_router_router8_task17 - task_total_delay_router_router8_task18 - task_total_delay_router_router8_task19 - task_total_delay_router_router8_task2 - task_total_delay_router_router8_task20 - task_total_delay_router_router8_task21 - task_total_delay_router_router8_task22 - task_total_delay_router_router8_task23 - task_total_delay_router_router8_task24 - task_total_delay_router_router8_task25 - task_total_delay_router_router8_task26 - task_total_delay_router_router8_task27 - task_total_delay_router_router8_task28 - task_total_delay_router_router8_task29 - task_total_delay_router_router8_task3 - task_total_delay_router_router8_task30 - task_total_delay_router_router8_task31 - task_total_delay_router_router8_task32 - task_total_delay_router_router8_task33 - task_total_delay_router_router8_task34 - task_total_delay_router_router8_task35 - task_total_delay_router_router8_task36 - task_total_delay_router_router8_task37 - task_total_delay_router_router8_task38 - task_total_delay_router_router8_task39 - task_total_delay_router_router8_task4 - task_total_delay_router_router8_task40 - task_total_delay_router_router8_task41 - task_total_delay_router_router8_task42 - task_total_delay_router_router8_task43 - task_total_delay_router_router8_task44 - task_total_delay_router_router8_task45 - task_total_delay_router_router8_task46 - task_total_delay_router_router8_task47 - task_total_delay_router_router8_task48 - task_total_delay_router_router8_task49 - task_total_delay_router_router8_task5 - task_total_delay_router_router8_task50 - task_total_delay_router_router8_task51 - task_total_delay_router_router8_task52 - task_total_delay_router_router8_task53 - task_total_delay_router_router8_task54 - task_total_delay_router_router8_task55 - task_total_delay_router_router8_task56 - task_total_delay_router_router8_task57 - task_total_delay_router_router8_task58 - task_total_delay_router_router8_task59 - task_total_delay_router_router8_task6 - task_total_delay_router_router8_task60 - task_total_delay_router_router8_task61 - task_total_delay_router_router8_task62 - task_total_delay_router_router8_task63 - task_total_delay_router_router8_task64 - task_total_delay_router_router8_task65 - task_total_delay_router_router8_task66 - task_total_delay_router_router8_task67 - task_total_delay_router_router8_task68 - task_total_delay_router_router8_task69 - task_total_delay_router_router8_task7 - task_total_delay_router_router8_task8 - task_total_delay_router_router8_task9 >= -0.0\n", - "_C121654: PE8_total_memory - task_total_memory_router_router8_task0 - task_total_memory_router_router8_task1 - task_total_memory_router_router8_task10 - task_total_memory_router_router8_task11 - task_total_memory_router_router8_task12 - task_total_memory_router_router8_task13 - task_total_memory_router_router8_task14 - task_total_memory_router_router8_task15 - task_total_memory_router_router8_task16 - task_total_memory_router_router8_task17 - task_total_memory_router_router8_task18 - task_total_memory_router_router8_task19 - task_total_memory_router_router8_task2 - task_total_memory_router_router8_task20 - task_total_memory_router_router8_task21 - task_total_memory_router_router8_task22 - task_total_memory_router_router8_task23 - task_total_memory_router_router8_task24 - task_total_memory_router_router8_task25 - task_total_memory_router_router8_task26 - task_total_memory_router_router8_task27 - task_total_memory_router_router8_task28 - task_total_memory_router_router8_task29 - task_total_memory_router_router8_task3 - task_total_memory_router_router8_task30 - task_total_memory_router_router8_task31 - task_total_memory_router_router8_task32 - task_total_memory_router_router8_task33 - task_total_memory_router_router8_task34 - task_total_memory_router_router8_task35 - task_total_memory_router_router8_task36 - task_total_memory_router_router8_task37 - task_total_memory_router_router8_task38 - task_total_memory_router_router8_task39 - task_total_memory_router_router8_task4 - task_total_memory_router_router8_task40 - task_total_memory_router_router8_task41 - task_total_memory_router_router8_task42 - task_total_memory_router_router8_task43 - task_total_memory_router_router8_task44 - task_total_memory_router_router8_task45 - task_total_memory_router_router8_task46 - task_total_memory_router_router8_task47 - task_total_memory_router_router8_task48 - task_total_memory_router_router8_task49 - task_total_memory_router_router8_task5 - task_total_memory_router_router8_task50 - task_total_memory_router_router8_task51 - task_total_memory_router_router8_task52 - task_total_memory_router_router8_task53 - task_total_memory_router_router8_task54 - task_total_memory_router_router8_task55 - task_total_memory_router_router8_task56 - task_total_memory_router_router8_task57 - task_total_memory_router_router8_task58 - task_total_memory_router_router8_task59 - task_total_memory_router_router8_task6 - task_total_memory_router_router8_task60 - task_total_memory_router_router8_task61 - task_total_memory_router_router8_task62 - task_total_memory_router_router8_task63 - task_total_memory_router_router8_task64 - task_total_memory_router_router8_task65 - task_total_memory_router_router8_task66 - task_total_memory_router_router8_task67 - task_total_memory_router_router8_task68 - task_total_memory_router_router8_task69 - task_total_memory_router_router8_task7 - task_total_memory_router_router8_task8 - task_total_memory_router_router8_task9 >= -0.0\n", - "_C121655: -PE_mem_overflow8 + max_memory_overflow >= 0\n", - "_C121656: PE8_time_delay_max - t0_end_ - 10000.0*t_0_map_8 >= -10000.0\n", - "_C121657: PE8_time_delay_min - t0_start + 10000.0*t_0_map_8 <= 10000.0\n", - "_C121658: PE8_time_delay_max - t1_end_ - 10000.0*t_1_map_8 >= -10000.0\n", - "_C121659: PE8_time_delay_min - t1_start + 10000.0*t_1_map_8 <= 10000.0\n", - "_C121660: PE8_time_delay_max - t2_end_ - 10000.0*t_2_map_8 >= -10000.0\n", - "_C121661: PE8_time_delay_min - t2_start + 10000.0*t_2_map_8 <= 10000.0\n", - "_C121662: PE8_time_delay_max - t3_end_ - 10000.0*t_3_map_8 >= -10000.0\n", - "_C121663: PE8_time_delay_min - t3_start + 10000.0*t_3_map_8 <= 10000.0\n", - "_C121664: PE8_time_delay_max - t4_end_ - 10000.0*t_4_map_8 >= -10000.0\n", - "_C121665: PE8_time_delay_min - t4_start + 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PE8_time_delay_max - t11_end_ - 10000.0*t_11_map_8 >= -10000.0\n", - "_C121679: PE8_time_delay_min - t11_start + 10000.0*t_11_map_8 <= 10000.0\n", - "_C121680: PE8_time_delay_max - t12_end_ - 10000.0*t_12_map_8 >= -10000.0\n", - "_C121681: PE8_time_delay_min - t12_start + 10000.0*t_12_map_8 <= 10000.0\n", - "_C121682: PE8_time_delay_max - t13_end_ - 10000.0*t_13_map_8 >= -10000.0\n", - "_C121683: PE8_time_delay_min - t13_start + 10000.0*t_13_map_8 <= 10000.0\n", - "_C121684: PE8_time_delay_max - t14_end_ - 10000.0*t_14_map_8 >= -10000.0\n", - "_C121685: PE8_time_delay_min - t14_start + 10000.0*t_14_map_8 <= 10000.0\n", - "_C121686: PE8_time_delay_max - t15_end_ - 10000.0*t_15_map_8 >= -10000.0\n", - "_C121687: PE8_time_delay_min - t15_start + 10000.0*t_15_map_8 <= 10000.0\n", - "_C121688: PE8_time_delay_max - t16_end_ - 10000.0*t_16_map_8 >= -10000.0\n", - "_C121689: PE8_time_delay_min - t16_start + 10000.0*t_16_map_8 <= 10000.0\n", - "_C121690: PE8_time_delay_max - t17_end_ - 10000.0*t_17_map_8 >= -10000.0\n", - "_C121691: PE8_time_delay_min - t17_start + 10000.0*t_17_map_8 <= 10000.0\n", - "_C121692: PE8_time_delay_max - t18_end_ - 10000.0*t_18_map_8 >= -10000.0\n", - "_C121693: PE8_time_delay_min - t18_start + 10000.0*t_18_map_8 <= 10000.0\n", - "_C121694: PE8_time_delay_max - t19_end_ - 10000.0*t_19_map_8 >= -10000.0\n", - "_C121695: PE8_time_delay_min - t19_start + 10000.0*t_19_map_8 <= 10000.0\n", - "_C121696: PE8_time_delay_max - t20_end_ - 10000.0*t_20_map_8 >= -10000.0\n", - "_C121697: PE8_time_delay_min - t20_start + 10000.0*t_20_map_8 <= 10000.0\n", - "_C121698: PE8_time_delay_max - t21_end_ - 10000.0*t_21_map_8 >= -10000.0\n", - "_C121699: PE8_time_delay_min - t21_start + 10000.0*t_21_map_8 <= 10000.0\n", - "_C121700: PE8_time_delay_max - t22_end_ - 10000.0*t_22_map_8 >= -10000.0\n", - "_C121701: PE8_time_delay_min - t22_start + 10000.0*t_22_map_8 <= 10000.0\n", - "_C121702: PE8_time_delay_max - t23_end_ - 10000.0*t_23_map_8 >= -10000.0\n", - "_C121703: PE8_time_delay_min - t23_start + 10000.0*t_23_map_8 <= 10000.0\n", - "_C121704: PE8_time_delay_max - t24_end_ - 10000.0*t_24_map_8 >= -10000.0\n", - "_C121705: PE8_time_delay_min - t24_start + 10000.0*t_24_map_8 <= 10000.0\n", - "_C121706: PE8_time_delay_max - t25_end_ - 10000.0*t_25_map_8 >= -10000.0\n", - "_C121707: PE8_time_delay_min - t25_start + 10000.0*t_25_map_8 <= 10000.0\n", - "_C121708: PE8_time_delay_max - t26_end_ - 10000.0*t_26_map_8 >= -10000.0\n", - "_C121709: PE8_time_delay_min - t26_start + 10000.0*t_26_map_8 <= 10000.0\n", - "_C121710: PE8_time_delay_max - t27_end_ - 10000.0*t_27_map_8 >= -10000.0\n", - "_C121711: PE8_time_delay_min - t27_start + 10000.0*t_27_map_8 <= 10000.0\n", - "_C121712: PE8_time_delay_max - t28_end_ - 10000.0*t_28_map_8 >= -10000.0\n", - "_C121713: PE8_time_delay_min - t28_start + 10000.0*t_28_map_8 <= 10000.0\n", - "_C121714: PE8_time_delay_max - t29_end_ - 10000.0*t_29_map_8 >= -10000.0\n", - "_C121715: PE8_time_delay_min - t29_start + 10000.0*t_29_map_8 <= 10000.0\n", - "_C121716: PE8_time_delay_max - t30_end_ - 10000.0*t_30_map_8 >= -10000.0\n", - "_C121717: PE8_time_delay_min - t30_start + 10000.0*t_30_map_8 <= 10000.0\n", - "_C121718: PE8_time_delay_max - t31_end_ - 10000.0*t_31_map_8 >= -10000.0\n", - "_C121719: PE8_time_delay_min - t31_start + 10000.0*t_31_map_8 <= 10000.0\n", - "_C121720: PE8_time_delay_max - t32_end_ - 10000.0*t_32_map_8 >= -10000.0\n", - "_C121721: PE8_time_delay_min - t32_start + 10000.0*t_32_map_8 <= 10000.0\n", - "_C121722: PE8_time_delay_max - t33_end_ - 10000.0*t_33_map_8 >= -10000.0\n", - "_C121723: PE8_time_delay_min - t33_start + 10000.0*t_33_map_8 <= 10000.0\n", - "_C121724: PE8_time_delay_max - t34_end_ - 10000.0*t_34_map_8 >= -10000.0\n", - "_C121725: PE8_time_delay_min - t34_start + 10000.0*t_34_map_8 <= 10000.0\n", - "_C121726: PE8_time_delay_max - t35_end_ - 10000.0*t_35_map_8 >= -10000.0\n", - "_C121727: PE8_time_delay_min - t35_start + 10000.0*t_35_map_8 <= 10000.0\n", - "_C121728: PE8_time_delay_max - t36_end_ - 10000.0*t_36_map_8 >= -10000.0\n", - "_C121729: PE8_time_delay_min - t36_start + 10000.0*t_36_map_8 <= 10000.0\n", - "_C121730: PE8_time_delay_max - t37_end_ - 10000.0*t_37_map_8 >= -10000.0\n", - "_C121731: PE8_time_delay_min - t37_start + 10000.0*t_37_map_8 <= 10000.0\n", - "_C121732: PE8_time_delay_max - t38_end_ - 10000.0*t_38_map_8 >= -10000.0\n", - "_C121733: PE8_time_delay_min - t38_start + 10000.0*t_38_map_8 <= 10000.0\n", - "_C121734: PE8_time_delay_max - t39_end_ - 10000.0*t_39_map_8 >= -10000.0\n", - "_C121735: PE8_time_delay_min - t39_start + 10000.0*t_39_map_8 <= 10000.0\n", - "_C121736: PE8_time_delay_max - t40_end_ - 10000.0*t_40_map_8 >= -10000.0\n", - "_C121737: PE8_time_delay_min - t40_start + 10000.0*t_40_map_8 <= 10000.0\n", - "_C121738: PE8_time_delay_max - t41_end_ - 10000.0*t_41_map_8 >= -10000.0\n", - "_C121739: PE8_time_delay_min - t41_start + 10000.0*t_41_map_8 <= 10000.0\n", - "_C121740: PE8_time_delay_max - t42_end_ - 10000.0*t_42_map_8 >= -10000.0\n", - "_C121741: PE8_time_delay_min - t42_start + 10000.0*t_42_map_8 <= 10000.0\n", - "_C121742: PE8_time_delay_max - t43_end_ - 10000.0*t_43_map_8 >= -10000.0\n", - "_C121743: PE8_time_delay_min - t43_start + 10000.0*t_43_map_8 <= 10000.0\n", - "_C121744: PE8_time_delay_max - t44_end_ - 10000.0*t_44_map_8 >= -10000.0\n", - "_C121745: PE8_time_delay_min - t44_start + 10000.0*t_44_map_8 <= 10000.0\n", - "_C121746: PE8_time_delay_max - t45_end_ - 10000.0*t_45_map_8 >= -10000.0\n", - "_C121747: PE8_time_delay_min - t45_start + 10000.0*t_45_map_8 <= 10000.0\n", - "_C121748: PE8_time_delay_max - t46_end_ - 10000.0*t_46_map_8 >= -10000.0\n", - "_C121749: PE8_time_delay_min - t46_start + 10000.0*t_46_map_8 <= 10000.0\n", - "_C121750: PE8_time_delay_max - t47_end_ - 10000.0*t_47_map_8 >= -10000.0\n", - "_C121751: PE8_time_delay_min - t47_start + 10000.0*t_47_map_8 <= 10000.0\n", - "_C121752: PE8_time_delay_max - t48_end_ - 10000.0*t_48_map_8 >= -10000.0\n", - "_C121753: PE8_time_delay_min - t48_start + 10000.0*t_48_map_8 <= 10000.0\n", - "_C121754: PE8_time_delay_max - t49_end_ - 10000.0*t_49_map_8 >= -10000.0\n", - "_C121755: PE8_time_delay_min - t49_start + 10000.0*t_49_map_8 <= 10000.0\n", - "_C121756: PE8_time_delay_max - t50_end_ - 10000.0*t_50_map_8 >= -10000.0\n", - "_C121757: PE8_time_delay_min - t50_start + 10000.0*t_50_map_8 <= 10000.0\n", - "_C121758: PE8_time_delay_max - t51_end_ - 10000.0*t_51_map_8 >= -10000.0\n", - "_C121759: PE8_time_delay_min - t51_start + 10000.0*t_51_map_8 <= 10000.0\n", - "_C121760: PE8_time_delay_max - t52_end_ - 10000.0*t_52_map_8 >= -10000.0\n", - "_C121761: PE8_time_delay_min - t52_start + 10000.0*t_52_map_8 <= 10000.0\n", - "_C121762: PE8_time_delay_max - t53_end_ - 10000.0*t_53_map_8 >= -10000.0\n", - "_C121763: PE8_time_delay_min - t53_start + 10000.0*t_53_map_8 <= 10000.0\n", - "_C121764: PE8_time_delay_max - t54_end_ - 10000.0*t_54_map_8 >= -10000.0\n", - "_C121765: PE8_time_delay_min - t54_start + 10000.0*t_54_map_8 <= 10000.0\n", - "_C121766: PE8_time_delay_max - t55_end_ - 10000.0*t_55_map_8 >= -10000.0\n", - "_C121767: PE8_time_delay_min - t55_start + 10000.0*t_55_map_8 <= 10000.0\n", - "_C121768: PE8_time_delay_max - t56_end_ - 10000.0*t_56_map_8 >= -10000.0\n", - "_C121769: PE8_time_delay_min - t56_start + 10000.0*t_56_map_8 <= 10000.0\n", - "_C121770: PE8_time_delay_max - t57_end_ - 10000.0*t_57_map_8 >= -10000.0\n", - "_C121771: PE8_time_delay_min - t57_start + 10000.0*t_57_map_8 <= 10000.0\n", - "_C121772: PE8_time_delay_max - t58_end_ - 10000.0*t_58_map_8 >= -10000.0\n", - "_C121773: PE8_time_delay_min - t58_start + 10000.0*t_58_map_8 <= 10000.0\n", - "_C121774: PE8_time_delay_max - t59_end_ - 10000.0*t_59_map_8 >= -10000.0\n", - "_C121775: PE8_time_delay_min - t59_start + 10000.0*t_59_map_8 <= 10000.0\n", - "_C121776: PE8_time_delay_max - t60_end_ - 10000.0*t_60_map_8 >= -10000.0\n", - "_C121777: PE8_time_delay_min - t60_start + 10000.0*t_60_map_8 <= 10000.0\n", - "_C121778: PE8_time_delay_max - t61_end_ - 10000.0*t_61_map_8 >= -10000.0\n", - "_C121779: PE8_time_delay_min - t61_start + 10000.0*t_61_map_8 <= 10000.0\n", - "_C121780: PE8_time_delay_max - t62_end_ - 10000.0*t_62_map_8 >= -10000.0\n", - "_C121781: PE8_time_delay_min - t62_start + 10000.0*t_62_map_8 <= 10000.0\n", - "_C121782: PE8_time_delay_max - t63_end_ - 10000.0*t_63_map_8 >= -10000.0\n", - "_C121783: PE8_time_delay_min - t63_start + 10000.0*t_63_map_8 <= 10000.0\n", - "_C121784: PE8_time_delay_max - t64_end_ - 10000.0*t_64_map_8 >= -10000.0\n", - "_C121785: PE8_time_delay_min - t64_start + 10000.0*t_64_map_8 <= 10000.0\n", - "_C121786: PE8_time_delay_max - t65_end_ - 10000.0*t_65_map_8 >= -10000.0\n", - "_C121787: PE8_time_delay_min - t65_start + 10000.0*t_65_map_8 <= 10000.0\n", - "_C121788: PE8_time_delay_max - t66_end_ - 10000.0*t_66_map_8 >= -10000.0\n", - "_C121789: PE8_time_delay_min - t66_start + 10000.0*t_66_map_8 <= 10000.0\n", - "_C121790: PE8_time_delay_max - t67_end_ - 10000.0*t_67_map_8 >= -10000.0\n", - "_C121791: PE8_time_delay_min - t67_start + 10000.0*t_67_map_8 <= 10000.0\n", - "_C121792: PE8_time_delay_max - t68_end_ - 10000.0*t_68_map_8 >= -10000.0\n", - "_C121793: PE8_time_delay_min - t68_start + 10000.0*t_68_map_8 <= 10000.0\n", - "_C121794: PE8_time_delay_max - t69_end_ - 10000.0*t_69_map_8 >= -10000.0\n", - "_C121795: PE8_time_delay_min - t69_start + 10000.0*t_69_map_8 <= 10000.0\n", - "_C121796: -PE8_time_delay_max + PE8_time_delay_min + PE8_total_time_delay = 0\n", - "_C121797: -PE8_total_time_delay + max_router_delay >= 0\n", - "_C121798: PE8_total_time_delay <= 280\n", - "_C121799: -t0_end_ + t0_start - 10000.0*t_0_map_9 - t_send_0 + task_total_delay_router_router9_task0 >= -10000.0\n", - "_C121800: -10000.0*t_0_map_9 - t_mem_0 + task_total_memory_router_router9_task0 >= -10000.0\n", - "_C121801: -t1_end_ + t1_start - 10000.0*t_1_map_9 - t_send_1 + task_total_delay_router_router9_task1 >= -10000.0\n", - "_C121802: -10000.0*t_1_map_9 - t_mem_1 + task_total_memory_router_router9_task1 >= -10000.0\n", - "_C121803: -t2_end_ + t2_start - 10000.0*t_2_map_9 - t_send_2 + task_total_delay_router_router9_task2 >= -10000.0\n", - "_C121804: -10000.0*t_2_map_9 - t_mem_2 + task_total_memory_router_router9_task2 >= -10000.0\n", - "_C121805: -t3_end_ + t3_start - 10000.0*t_3_map_9 - t_send_3 + task_total_delay_router_router9_task3 >= -10000.0\n", - "_C121806: -10000.0*t_3_map_9 - t_mem_3 + task_total_memory_router_router9_task3 >= -10000.0\n", - "_C121807: -t4_end_ + t4_start - 10000.0*t_4_map_9 - t_send_4 + task_total_delay_router_router9_task4 >= -10000.0\n", - "_C121808: -10000.0*t_4_map_9 - t_mem_4 + task_total_memory_router_router9_task4 >= -10000.0\n", - "_C121809: -t5_end_ + t5_start - 10000.0*t_5_map_9 - t_send_5 + task_total_delay_router_router9_task5 >= -10000.0\n", - "_C121810: -10000.0*t_5_map_9 - t_mem_5 + task_total_memory_router_router9_task5 >= -10000.0\n", - "_C121811: -t6_end_ + t6_start - 10000.0*t_6_map_9 - t_send_6 + task_total_delay_router_router9_task6 >= -10000.0\n", - "_C121812: -10000.0*t_6_map_9 - t_mem_6 + task_total_memory_router_router9_task6 >= -10000.0\n", - "_C121813: -t7_end_ + t7_start - 10000.0*t_7_map_9 - t_send_7 + task_total_delay_router_router9_task7 >= -10000.0\n", - "_C121814: -10000.0*t_7_map_9 - t_mem_7 + task_total_memory_router_router9_task7 >= -10000.0\n", - "_C121815: -t8_end_ + t8_start - 10000.0*t_8_map_9 - t_send_8 + task_total_delay_router_router9_task8 >= -10000.0\n", - "_C121816: -10000.0*t_8_map_9 - t_mem_8 + task_total_memory_router_router9_task8 >= -10000.0\n", - "_C121817: -t9_end_ + t9_start - 10000.0*t_9_map_9 - t_send_9 + task_total_delay_router_router9_task9 >= -10000.0\n", - "_C121818: -10000.0*t_9_map_9 - t_mem_9 + task_total_memory_router_router9_task9 >= -10000.0\n", - "_C121819: -t10_end_ + t10_start - 10000.0*t_10_map_9 - t_send_10 + task_total_delay_router_router9_task10 >= -10000.0\n", - "_C121820: -10000.0*t_10_map_9 - t_mem_10 + task_total_memory_router_router9_task10 >= -10000.0\n", - "_C121821: -t11_end_ + t11_start - 10000.0*t_11_map_9 - t_send_11 + task_total_delay_router_router9_task11 >= -10000.0\n", - "_C121822: -10000.0*t_11_map_9 - t_mem_11 + task_total_memory_router_router9_task11 >= -10000.0\n", - "_C121823: -t12_end_ + t12_start - 10000.0*t_12_map_9 - t_send_12 + task_total_delay_router_router9_task12 >= -10000.0\n", - "_C121824: -10000.0*t_12_map_9 - t_mem_12 + task_total_memory_router_router9_task12 >= -10000.0\n", - "_C121825: -t13_end_ + t13_start - 10000.0*t_13_map_9 - t_send_13 + task_total_delay_router_router9_task13 >= -10000.0\n", - "_C121826: -10000.0*t_13_map_9 - t_mem_13 + task_total_memory_router_router9_task13 >= -10000.0\n", - "_C121827: -t14_end_ + t14_start - 10000.0*t_14_map_9 - t_send_14 + task_total_delay_router_router9_task14 >= -10000.0\n", - "_C121828: -10000.0*t_14_map_9 - t_mem_14 + task_total_memory_router_router9_task14 >= -10000.0\n", - "_C121829: -t15_end_ + t15_start - 10000.0*t_15_map_9 - t_send_15 + task_total_delay_router_router9_task15 >= -10000.0\n", - "_C121830: -10000.0*t_15_map_9 - t_mem_15 + task_total_memory_router_router9_task15 >= -10000.0\n", - "_C121831: -t16_end_ + t16_start - 10000.0*t_16_map_9 - t_send_16 + task_total_delay_router_router9_task16 >= -10000.0\n", - "_C121832: -10000.0*t_16_map_9 - t_mem_16 + task_total_memory_router_router9_task16 >= -10000.0\n", - "_C121833: -t17_end_ + t17_start - 10000.0*t_17_map_9 - t_send_17 + task_total_delay_router_router9_task17 >= -10000.0\n", - "_C121834: -10000.0*t_17_map_9 - t_mem_17 + task_total_memory_router_router9_task17 >= -10000.0\n", - "_C121835: -t18_end_ + t18_start - 10000.0*t_18_map_9 - t_send_18 + task_total_delay_router_router9_task18 >= -10000.0\n", - "_C121836: -10000.0*t_18_map_9 - t_mem_18 + task_total_memory_router_router9_task18 >= -10000.0\n", - "_C121837: -t19_end_ + t19_start - 10000.0*t_19_map_9 - t_send_19 + task_total_delay_router_router9_task19 >= -10000.0\n", - "_C121838: -10000.0*t_19_map_9 - t_mem_19 + task_total_memory_router_router9_task19 >= -10000.0\n", - "_C121839: -t20_end_ + t20_start - 10000.0*t_20_map_9 - t_send_20 + task_total_delay_router_router9_task20 >= -10000.0\n", - "_C121840: -10000.0*t_20_map_9 - t_mem_20 + task_total_memory_router_router9_task20 >= -10000.0\n", - "_C121841: -t21_end_ + t21_start - 10000.0*t_21_map_9 - t_send_21 + task_total_delay_router_router9_task21 >= -10000.0\n", - "_C121842: -10000.0*t_21_map_9 - t_mem_21 + task_total_memory_router_router9_task21 >= -10000.0\n", - "_C121843: -t22_end_ + t22_start - 10000.0*t_22_map_9 - t_send_22 + task_total_delay_router_router9_task22 >= -10000.0\n", - "_C121844: -10000.0*t_22_map_9 - t_mem_22 + task_total_memory_router_router9_task22 >= -10000.0\n", - "_C121845: -t23_end_ + t23_start - 10000.0*t_23_map_9 - t_send_23 + task_total_delay_router_router9_task23 >= -10000.0\n", - "_C121846: -10000.0*t_23_map_9 - t_mem_23 + task_total_memory_router_router9_task23 >= -10000.0\n", - "_C121847: -t24_end_ + t24_start - 10000.0*t_24_map_9 - t_send_24 + task_total_delay_router_router9_task24 >= -10000.0\n", - "_C121848: -10000.0*t_24_map_9 - t_mem_24 + task_total_memory_router_router9_task24 >= -10000.0\n", - "_C121849: -t25_end_ + t25_start - 10000.0*t_25_map_9 - t_send_25 + task_total_delay_router_router9_task25 >= -10000.0\n", - "_C121850: -10000.0*t_25_map_9 - t_mem_25 + task_total_memory_router_router9_task25 >= -10000.0\n", - "_C121851: -t26_end_ + t26_start - 10000.0*t_26_map_9 - t_send_26 + task_total_delay_router_router9_task26 >= -10000.0\n", - "_C121852: -10000.0*t_26_map_9 - t_mem_26 + task_total_memory_router_router9_task26 >= -10000.0\n", - "_C121853: -t27_end_ + t27_start - 10000.0*t_27_map_9 - t_send_27 + task_total_delay_router_router9_task27 >= -10000.0\n", - "_C121854: -10000.0*t_27_map_9 - t_mem_27 + 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task_total_memory_router_router9_task15 - task_total_memory_router_router9_task16 - task_total_memory_router_router9_task17 - task_total_memory_router_router9_task18 - task_total_memory_router_router9_task19 - task_total_memory_router_router9_task2 - task_total_memory_router_router9_task20 - task_total_memory_router_router9_task21 - task_total_memory_router_router9_task22 - task_total_memory_router_router9_task23 - task_total_memory_router_router9_task24 - task_total_memory_router_router9_task25 - task_total_memory_router_router9_task26 - task_total_memory_router_router9_task27 - task_total_memory_router_router9_task28 - task_total_memory_router_router9_task29 - task_total_memory_router_router9_task3 - task_total_memory_router_router9_task30 - task_total_memory_router_router9_task31 - task_total_memory_router_router9_task32 - task_total_memory_router_router9_task33 - task_total_memory_router_router9_task34 - task_total_memory_router_router9_task35 - task_total_memory_router_router9_task36 - task_total_memory_router_router9_task37 - task_total_memory_router_router9_task38 - task_total_memory_router_router9_task39 - task_total_memory_router_router9_task4 - task_total_memory_router_router9_task40 - task_total_memory_router_router9_task41 - task_total_memory_router_router9_task42 - task_total_memory_router_router9_task43 - task_total_memory_router_router9_task44 - task_total_memory_router_router9_task45 - task_total_memory_router_router9_task46 - task_total_memory_router_router9_task47 - task_total_memory_router_router9_task48 - task_total_memory_router_router9_task49 - task_total_memory_router_router9_task5 - task_total_memory_router_router9_task50 - task_total_memory_router_router9_task51 - task_total_memory_router_router9_task52 - task_total_memory_router_router9_task53 - task_total_memory_router_router9_task54 - task_total_memory_router_router9_task55 - task_total_memory_router_router9_task56 - task_total_memory_router_router9_task57 - task_total_memory_router_router9_task58 - task_total_memory_router_router9_task59 - task_total_memory_router_router9_task6 - task_total_memory_router_router9_task60 - task_total_memory_router_router9_task61 - task_total_memory_router_router9_task62 - task_total_memory_router_router9_task63 - task_total_memory_router_router9_task64 - task_total_memory_router_router9_task65 - task_total_memory_router_router9_task66 - task_total_memory_router_router9_task67 - task_total_memory_router_router9_task68 - task_total_memory_router_router9_task69 - task_total_memory_router_router9_task7 - task_total_memory_router_router9_task8 - task_total_memory_router_router9_task9 >= -0.0\n", - "_C121940: PE9_total_delay - task_total_delay_router_router9_task0 - task_total_delay_router_router9_task1 - task_total_delay_router_router9_task10 - task_total_delay_router_router9_task11 - task_total_delay_router_router9_task12 - task_total_delay_router_router9_task13 - task_total_delay_router_router9_task14 - task_total_delay_router_router9_task15 - task_total_delay_router_router9_task16 - task_total_delay_router_router9_task17 - task_total_delay_router_router9_task18 - task_total_delay_router_router9_task19 - task_total_delay_router_router9_task2 - task_total_delay_router_router9_task20 - task_total_delay_router_router9_task21 - task_total_delay_router_router9_task22 - task_total_delay_router_router9_task23 - task_total_delay_router_router9_task24 - task_total_delay_router_router9_task25 - task_total_delay_router_router9_task26 - task_total_delay_router_router9_task27 - task_total_delay_router_router9_task28 - task_total_delay_router_router9_task29 - task_total_delay_router_router9_task3 - task_total_delay_router_router9_task30 - task_total_delay_router_router9_task31 - task_total_delay_router_router9_task32 - task_total_delay_router_router9_task33 - task_total_delay_router_router9_task34 - task_total_delay_router_router9_task35 - task_total_delay_router_router9_task36 - task_total_delay_router_router9_task37 - task_total_delay_router_router9_task38 - task_total_delay_router_router9_task39 - task_total_delay_router_router9_task4 - task_total_delay_router_router9_task40 - task_total_delay_router_router9_task41 - task_total_delay_router_router9_task42 - task_total_delay_router_router9_task43 - task_total_delay_router_router9_task44 - task_total_delay_router_router9_task45 - task_total_delay_router_router9_task46 - task_total_delay_router_router9_task47 - task_total_delay_router_router9_task48 - task_total_delay_router_router9_task49 - task_total_delay_router_router9_task5 - task_total_delay_router_router9_task50 - task_total_delay_router_router9_task51 - task_total_delay_router_router9_task52 - task_total_delay_router_router9_task53 - task_total_delay_router_router9_task54 - task_total_delay_router_router9_task55 - task_total_delay_router_router9_task56 - task_total_delay_router_router9_task57 - task_total_delay_router_router9_task58 - task_total_delay_router_router9_task59 - task_total_delay_router_router9_task6 - task_total_delay_router_router9_task60 - task_total_delay_router_router9_task61 - task_total_delay_router_router9_task62 - task_total_delay_router_router9_task63 - task_total_delay_router_router9_task64 - task_total_delay_router_router9_task65 - task_total_delay_router_router9_task66 - task_total_delay_router_router9_task67 - task_total_delay_router_router9_task68 - task_total_delay_router_router9_task69 - task_total_delay_router_router9_task7 - task_total_delay_router_router9_task8 - task_total_delay_router_router9_task9 >= -0.0\n", - "_C121941: PE9_total_memory - task_total_memory_router_router9_task0 - task_total_memory_router_router9_task1 - task_total_memory_router_router9_task10 - task_total_memory_router_router9_task11 - task_total_memory_router_router9_task12 - task_total_memory_router_router9_task13 - task_total_memory_router_router9_task14 - task_total_memory_router_router9_task15 - task_total_memory_router_router9_task16 - task_total_memory_router_router9_task17 - task_total_memory_router_router9_task18 - task_total_memory_router_router9_task19 - task_total_memory_router_router9_task2 - task_total_memory_router_router9_task20 - task_total_memory_router_router9_task21 - task_total_memory_router_router9_task22 - task_total_memory_router_router9_task23 - task_total_memory_router_router9_task24 - task_total_memory_router_router9_task25 - task_total_memory_router_router9_task26 - task_total_memory_router_router9_task27 - task_total_memory_router_router9_task28 - task_total_memory_router_router9_task29 - task_total_memory_router_router9_task3 - task_total_memory_router_router9_task30 - task_total_memory_router_router9_task31 - task_total_memory_router_router9_task32 - task_total_memory_router_router9_task33 - task_total_memory_router_router9_task34 - task_total_memory_router_router9_task35 - task_total_memory_router_router9_task36 - task_total_memory_router_router9_task37 - task_total_memory_router_router9_task38 - task_total_memory_router_router9_task39 - task_total_memory_router_router9_task4 - task_total_memory_router_router9_task40 - task_total_memory_router_router9_task41 - task_total_memory_router_router9_task42 - task_total_memory_router_router9_task43 - task_total_memory_router_router9_task44 - task_total_memory_router_router9_task45 - task_total_memory_router_router9_task46 - task_total_memory_router_router9_task47 - task_total_memory_router_router9_task48 - task_total_memory_router_router9_task49 - task_total_memory_router_router9_task5 - task_total_memory_router_router9_task50 - task_total_memory_router_router9_task51 - task_total_memory_router_router9_task52 - task_total_memory_router_router9_task53 - task_total_memory_router_router9_task54 - task_total_memory_router_router9_task55 - task_total_memory_router_router9_task56 - task_total_memory_router_router9_task57 - task_total_memory_router_router9_task58 - task_total_memory_router_router9_task59 - task_total_memory_router_router9_task6 - task_total_memory_router_router9_task60 - task_total_memory_router_router9_task61 - task_total_memory_router_router9_task62 - task_total_memory_router_router9_task63 - task_total_memory_router_router9_task64 - task_total_memory_router_router9_task65 - task_total_memory_router_router9_task66 - task_total_memory_router_router9_task67 - task_total_memory_router_router9_task68 - task_total_memory_router_router9_task69 - task_total_memory_router_router9_task7 - task_total_memory_router_router9_task8 - task_total_memory_router_router9_task9 >= -0.0\n", - "_C121942: -PE_mem_overflow9 + max_memory_overflow >= 0\n", - "_C121943: PE9_time_delay_max - t0_end_ - 10000.0*t_0_map_9 >= -10000.0\n", - "_C121944: PE9_time_delay_min - t0_start + 10000.0*t_0_map_9 <= 10000.0\n", - "_C121945: PE9_time_delay_max - t1_end_ - 10000.0*t_1_map_9 >= -10000.0\n", - "_C121946: PE9_time_delay_min - t1_start + 10000.0*t_1_map_9 <= 10000.0\n", - "_C121947: PE9_time_delay_max - t2_end_ - 10000.0*t_2_map_9 >= -10000.0\n", - "_C121948: PE9_time_delay_min - t2_start + 10000.0*t_2_map_9 <= 10000.0\n", - "_C121949: PE9_time_delay_max - t3_end_ - 10000.0*t_3_map_9 >= -10000.0\n", - "_C121950: PE9_time_delay_min - t3_start + 10000.0*t_3_map_9 <= 10000.0\n", - "_C121951: PE9_time_delay_max - t4_end_ - 10000.0*t_4_map_9 >= -10000.0\n", - "_C121952: PE9_time_delay_min - t4_start + 10000.0*t_4_map_9 <= 10000.0\n", - "_C121953: PE9_time_delay_max - t5_end_ - 10000.0*t_5_map_9 >= -10000.0\n", - "_C121954: PE9_time_delay_min - t5_start + 10000.0*t_5_map_9 <= 10000.0\n", - "_C121955: PE9_time_delay_max - t6_end_ - 10000.0*t_6_map_9 >= -10000.0\n", - "_C121956: PE9_time_delay_min - t6_start + 10000.0*t_6_map_9 <= 10000.0\n", - "_C121957: PE9_time_delay_max - t7_end_ - 10000.0*t_7_map_9 >= -10000.0\n", - "_C121958: PE9_time_delay_min - t7_start + 10000.0*t_7_map_9 <= 10000.0\n", - "_C121959: PE9_time_delay_max - t8_end_ - 10000.0*t_8_map_9 >= -10000.0\n", - "_C121960: PE9_time_delay_min - t8_start + 10000.0*t_8_map_9 <= 10000.0\n", - "_C121961: PE9_time_delay_max - t9_end_ - 10000.0*t_9_map_9 >= -10000.0\n", - "_C121962: PE9_time_delay_min - t9_start + 10000.0*t_9_map_9 <= 10000.0\n", - "_C121963: PE9_time_delay_max - t10_end_ - 10000.0*t_10_map_9 >= -10000.0\n", - "_C121964: PE9_time_delay_min - t10_start + 10000.0*t_10_map_9 <= 10000.0\n", - "_C121965: PE9_time_delay_max - t11_end_ - 10000.0*t_11_map_9 >= -10000.0\n", - "_C121966: PE9_time_delay_min - t11_start + 10000.0*t_11_map_9 <= 10000.0\n", - "_C121967: PE9_time_delay_max - t12_end_ - 10000.0*t_12_map_9 >= -10000.0\n", - "_C121968: PE9_time_delay_min - t12_start + 10000.0*t_12_map_9 <= 10000.0\n", - "_C121969: PE9_time_delay_max - t13_end_ - 10000.0*t_13_map_9 >= -10000.0\n", - "_C121970: PE9_time_delay_min - t13_start + 10000.0*t_13_map_9 <= 10000.0\n", - "_C121971: PE9_time_delay_max - t14_end_ - 10000.0*t_14_map_9 >= -10000.0\n", - "_C121972: PE9_time_delay_min - t14_start + 10000.0*t_14_map_9 <= 10000.0\n", - "_C121973: PE9_time_delay_max - t15_end_ - 10000.0*t_15_map_9 >= -10000.0\n", - "_C121974: PE9_time_delay_min - t15_start + 10000.0*t_15_map_9 <= 10000.0\n", - "_C121975: PE9_time_delay_max - t16_end_ - 10000.0*t_16_map_9 >= -10000.0\n", - "_C121976: PE9_time_delay_min - t16_start + 10000.0*t_16_map_9 <= 10000.0\n", - "_C121977: PE9_time_delay_max - t17_end_ - 10000.0*t_17_map_9 >= -10000.0\n", - "_C121978: PE9_time_delay_min - t17_start + 10000.0*t_17_map_9 <= 10000.0\n", - "_C121979: PE9_time_delay_max - t18_end_ - 10000.0*t_18_map_9 >= -10000.0\n", - "_C121980: PE9_time_delay_min - t18_start + 10000.0*t_18_map_9 <= 10000.0\n", - "_C121981: PE9_time_delay_max - t19_end_ - 10000.0*t_19_map_9 >= -10000.0\n", - "_C121982: PE9_time_delay_min - t19_start + 10000.0*t_19_map_9 <= 10000.0\n", - "_C121983: PE9_time_delay_max - t20_end_ - 10000.0*t_20_map_9 >= -10000.0\n", - "_C121984: PE9_time_delay_min - t20_start + 10000.0*t_20_map_9 <= 10000.0\n", - "_C121985: PE9_time_delay_max - t21_end_ - 10000.0*t_21_map_9 >= -10000.0\n", - "_C121986: PE9_time_delay_min - t21_start + 10000.0*t_21_map_9 <= 10000.0\n", - "_C121987: PE9_time_delay_max - t22_end_ - 10000.0*t_22_map_9 >= -10000.0\n", - "_C121988: PE9_time_delay_min - t22_start + 10000.0*t_22_map_9 <= 10000.0\n", - "_C121989: PE9_time_delay_max - t23_end_ - 10000.0*t_23_map_9 >= -10000.0\n", - "_C121990: PE9_time_delay_min - t23_start + 10000.0*t_23_map_9 <= 10000.0\n", - "_C121991: PE9_time_delay_max - t24_end_ - 10000.0*t_24_map_9 >= -10000.0\n", - "_C121992: PE9_time_delay_min - t24_start + 10000.0*t_24_map_9 <= 10000.0\n", - "_C121993: PE9_time_delay_max - t25_end_ - 10000.0*t_25_map_9 >= -10000.0\n", - "_C121994: PE9_time_delay_min - t25_start + 10000.0*t_25_map_9 <= 10000.0\n", - "_C121995: PE9_time_delay_max - t26_end_ - 10000.0*t_26_map_9 >= -10000.0\n", - "_C121996: PE9_time_delay_min - t26_start + 10000.0*t_26_map_9 <= 10000.0\n", - "_C121997: PE9_time_delay_max - t27_end_ - 10000.0*t_27_map_9 >= -10000.0\n", - "_C121998: PE9_time_delay_min - t27_start + 10000.0*t_27_map_9 <= 10000.0\n", - "_C121999: PE9_time_delay_max - t28_end_ - 10000.0*t_28_map_9 >= -10000.0\n", - "_C122000: PE9_time_delay_min - t28_start + 10000.0*t_28_map_9 <= 10000.0\n", - "_C122001: PE9_time_delay_max - t29_end_ - 10000.0*t_29_map_9 >= -10000.0\n", - "_C122002: PE9_time_delay_min - t29_start + 10000.0*t_29_map_9 <= 10000.0\n", - "_C122003: PE9_time_delay_max - t30_end_ - 10000.0*t_30_map_9 >= -10000.0\n", - "_C122004: PE9_time_delay_min - t30_start + 10000.0*t_30_map_9 <= 10000.0\n", - "_C122005: PE9_time_delay_max - t31_end_ - 10000.0*t_31_map_9 >= -10000.0\n", - "_C122006: PE9_time_delay_min - t31_start + 10000.0*t_31_map_9 <= 10000.0\n", - "_C122007: PE9_time_delay_max - t32_end_ - 10000.0*t_32_map_9 >= -10000.0\n", - "_C122008: PE9_time_delay_min - t32_start + 10000.0*t_32_map_9 <= 10000.0\n", - "_C122009: PE9_time_delay_max - t33_end_ - 10000.0*t_33_map_9 >= -10000.0\n", - "_C122010: PE9_time_delay_min - t33_start + 10000.0*t_33_map_9 <= 10000.0\n", - "_C122011: PE9_time_delay_max - t34_end_ - 10000.0*t_34_map_9 >= -10000.0\n", - "_C122012: PE9_time_delay_min - t34_start + 10000.0*t_34_map_9 <= 10000.0\n", - "_C122013: PE9_time_delay_max - t35_end_ - 10000.0*t_35_map_9 >= -10000.0\n", - "_C122014: PE9_time_delay_min - t35_start + 10000.0*t_35_map_9 <= 10000.0\n", - "_C122015: PE9_time_delay_max - t36_end_ - 10000.0*t_36_map_9 >= -10000.0\n", - "_C122016: PE9_time_delay_min - t36_start + 10000.0*t_36_map_9 <= 10000.0\n", - "_C122017: PE9_time_delay_max - t37_end_ - 10000.0*t_37_map_9 >= -10000.0\n", - "_C122018: PE9_time_delay_min - t37_start + 10000.0*t_37_map_9 <= 10000.0\n", - "_C122019: PE9_time_delay_max - t38_end_ - 10000.0*t_38_map_9 >= -10000.0\n", - "_C122020: PE9_time_delay_min - t38_start + 10000.0*t_38_map_9 <= 10000.0\n", - "_C122021: PE9_time_delay_max - t39_end_ - 10000.0*t_39_map_9 >= -10000.0\n", - "_C122022: PE9_time_delay_min - t39_start + 10000.0*t_39_map_9 <= 10000.0\n", - "_C122023: PE9_time_delay_max - t40_end_ - 10000.0*t_40_map_9 >= -10000.0\n", - "_C122024: PE9_time_delay_min - t40_start + 10000.0*t_40_map_9 <= 10000.0\n", - "_C122025: PE9_time_delay_max - t41_end_ - 10000.0*t_41_map_9 >= -10000.0\n", - "_C122026: PE9_time_delay_min - t41_start + 10000.0*t_41_map_9 <= 10000.0\n", - "_C122027: PE9_time_delay_max - t42_end_ - 10000.0*t_42_map_9 >= -10000.0\n", - "_C122028: PE9_time_delay_min - t42_start + 10000.0*t_42_map_9 <= 10000.0\n", - "_C122029: PE9_time_delay_max - t43_end_ - 10000.0*t_43_map_9 >= -10000.0\n", - "_C122030: PE9_time_delay_min - t43_start + 10000.0*t_43_map_9 <= 10000.0\n", - "_C122031: PE9_time_delay_max - t44_end_ - 10000.0*t_44_map_9 >= -10000.0\n", - "_C122032: PE9_time_delay_min - t44_start + 10000.0*t_44_map_9 <= 10000.0\n", - "_C122033: PE9_time_delay_max - t45_end_ - 10000.0*t_45_map_9 >= -10000.0\n", - "_C122034: PE9_time_delay_min - t45_start + 10000.0*t_45_map_9 <= 10000.0\n", - "_C122035: PE9_time_delay_max - t46_end_ - 10000.0*t_46_map_9 >= -10000.0\n", - "_C122036: PE9_time_delay_min - t46_start + 10000.0*t_46_map_9 <= 10000.0\n", - "_C122037: PE9_time_delay_max - t47_end_ - 10000.0*t_47_map_9 >= -10000.0\n", - "_C122038: PE9_time_delay_min - t47_start + 10000.0*t_47_map_9 <= 10000.0\n", - "_C122039: PE9_time_delay_max - t48_end_ - 10000.0*t_48_map_9 >= -10000.0\n", - "_C122040: PE9_time_delay_min - t48_start + 10000.0*t_48_map_9 <= 10000.0\n", - "_C122041: PE9_time_delay_max - t49_end_ - 10000.0*t_49_map_9 >= -10000.0\n", - "_C122042: PE9_time_delay_min - t49_start + 10000.0*t_49_map_9 <= 10000.0\n", - "_C122043: PE9_time_delay_max - t50_end_ - 10000.0*t_50_map_9 >= -10000.0\n", - "_C122044: PE9_time_delay_min - t50_start + 10000.0*t_50_map_9 <= 10000.0\n", - "_C122045: PE9_time_delay_max - t51_end_ - 10000.0*t_51_map_9 >= -10000.0\n", - "_C122046: PE9_time_delay_min - t51_start + 10000.0*t_51_map_9 <= 10000.0\n", - "_C122047: PE9_time_delay_max - t52_end_ - 10000.0*t_52_map_9 >= -10000.0\n", - "_C122048: PE9_time_delay_min - t52_start + 10000.0*t_52_map_9 <= 10000.0\n", - "_C122049: PE9_time_delay_max - t53_end_ - 10000.0*t_53_map_9 >= -10000.0\n", - "_C122050: PE9_time_delay_min - t53_start + 10000.0*t_53_map_9 <= 10000.0\n", - "_C122051: PE9_time_delay_max - t54_end_ - 10000.0*t_54_map_9 >= -10000.0\n", - "_C122052: PE9_time_delay_min - t54_start + 10000.0*t_54_map_9 <= 10000.0\n", - "_C122053: PE9_time_delay_max - t55_end_ - 10000.0*t_55_map_9 >= -10000.0\n", - "_C122054: PE9_time_delay_min - t55_start + 10000.0*t_55_map_9 <= 10000.0\n", - "_C122055: PE9_time_delay_max - t56_end_ - 10000.0*t_56_map_9 >= -10000.0\n", - "_C122056: PE9_time_delay_min - t56_start + 10000.0*t_56_map_9 <= 10000.0\n", - "_C122057: PE9_time_delay_max - t57_end_ - 10000.0*t_57_map_9 >= -10000.0\n", - "_C122058: PE9_time_delay_min - t57_start + 10000.0*t_57_map_9 <= 10000.0\n", - "_C122059: PE9_time_delay_max - t58_end_ - 10000.0*t_58_map_9 >= -10000.0\n", - "_C122060: PE9_time_delay_min - t58_start + 10000.0*t_58_map_9 <= 10000.0\n", - "_C122061: PE9_time_delay_max - t59_end_ - 10000.0*t_59_map_9 >= -10000.0\n", - "_C122062: PE9_time_delay_min - t59_start + 10000.0*t_59_map_9 <= 10000.0\n", - "_C122063: PE9_time_delay_max - t60_end_ - 10000.0*t_60_map_9 >= -10000.0\n", - "_C122064: PE9_time_delay_min - t60_start + 10000.0*t_60_map_9 <= 10000.0\n", - "_C122065: PE9_time_delay_max - t61_end_ - 10000.0*t_61_map_9 >= -10000.0\n", - "_C122066: PE9_time_delay_min - t61_start + 10000.0*t_61_map_9 <= 10000.0\n", - "_C122067: PE9_time_delay_max - t62_end_ - 10000.0*t_62_map_9 >= -10000.0\n", - "_C122068: PE9_time_delay_min - t62_start + 10000.0*t_62_map_9 <= 10000.0\n", - "_C122069: PE9_time_delay_max - t63_end_ - 10000.0*t_63_map_9 >= -10000.0\n", - "_C122070: PE9_time_delay_min - t63_start + 10000.0*t_63_map_9 <= 10000.0\n", - "_C122071: PE9_time_delay_max - t64_end_ - 10000.0*t_64_map_9 >= -10000.0\n", - "_C122072: PE9_time_delay_min - t64_start + 10000.0*t_64_map_9 <= 10000.0\n", - "_C122073: PE9_time_delay_max - t65_end_ - 10000.0*t_65_map_9 >= -10000.0\n", - "_C122074: PE9_time_delay_min - t65_start + 10000.0*t_65_map_9 <= 10000.0\n", - "_C122075: PE9_time_delay_max - t66_end_ - 10000.0*t_66_map_9 >= -10000.0\n", - "_C122076: PE9_time_delay_min - t66_start + 10000.0*t_66_map_9 <= 10000.0\n", - "_C122077: PE9_time_delay_max - t67_end_ - 10000.0*t_67_map_9 >= -10000.0\n", - "_C122078: PE9_time_delay_min - t67_start + 10000.0*t_67_map_9 <= 10000.0\n", - "_C122079: PE9_time_delay_max - t68_end_ - 10000.0*t_68_map_9 >= -10000.0\n", - "_C122080: PE9_time_delay_min - t68_start + 10000.0*t_68_map_9 <= 10000.0\n", - "_C122081: PE9_time_delay_max - t69_end_ - 10000.0*t_69_map_9 >= -10000.0\n", - "_C122082: PE9_time_delay_min - t69_start + 10000.0*t_69_map_9 <= 10000.0\n", - "_C122083: -PE9_time_delay_max + PE9_time_delay_min + PE9_total_time_delay = 0\n", - "_C122084: -PE9_total_time_delay + max_router_delay >= 0\n", - "_C122085: PE9_total_time_delay <= 280\n", - "_C122086: -t0_end_ + t0_start - 10000.0*t_0_map_10 - t_send_0 + task_total_delay_router_router10_task0 >= -10000.0\n", - "_C122087: -10000.0*t_0_map_10 - t_mem_0 + task_total_memory_router_router10_task0 >= -10000.0\n", - "_C122088: -t1_end_ + t1_start - 10000.0*t_1_map_10 - t_send_1 + task_total_delay_router_router10_task1 >= -10000.0\n", - "_C122089: -10000.0*t_1_map_10 - t_mem_1 + task_total_memory_router_router10_task1 >= -10000.0\n", - "_C122090: -t2_end_ + t2_start - 10000.0*t_2_map_10 - t_send_2 + task_total_delay_router_router10_task2 >= -10000.0\n", - "_C122091: -10000.0*t_2_map_10 - t_mem_2 + task_total_memory_router_router10_task2 >= -10000.0\n", - "_C122092: -t3_end_ + t3_start - 10000.0*t_3_map_10 - t_send_3 + task_total_delay_router_router10_task3 >= -10000.0\n", - "_C122093: -10000.0*t_3_map_10 - t_mem_3 + task_total_memory_router_router10_task3 >= -10000.0\n", - "_C122094: -t4_end_ + t4_start - 10000.0*t_4_map_10 - t_send_4 + task_total_delay_router_router10_task4 >= -10000.0\n", - "_C122095: -10000.0*t_4_map_10 - t_mem_4 + task_total_memory_router_router10_task4 >= -10000.0\n", - "_C122096: -t5_end_ + t5_start - 10000.0*t_5_map_10 - t_send_5 + task_total_delay_router_router10_task5 >= -10000.0\n", - "_C122097: -10000.0*t_5_map_10 - t_mem_5 + task_total_memory_router_router10_task5 >= -10000.0\n", - "_C122098: -t6_end_ + t6_start - 10000.0*t_6_map_10 - t_send_6 + task_total_delay_router_router10_task6 >= -10000.0\n", - "_C122099: -10000.0*t_6_map_10 - t_mem_6 + task_total_memory_router_router10_task6 >= -10000.0\n", - "_C122100: -t7_end_ + t7_start - 10000.0*t_7_map_10 - t_send_7 + task_total_delay_router_router10_task7 >= -10000.0\n", - "_C122101: -10000.0*t_7_map_10 - t_mem_7 + task_total_memory_router_router10_task7 >= -10000.0\n", - "_C122102: -t8_end_ + t8_start - 10000.0*t_8_map_10 - t_send_8 + task_total_delay_router_router10_task8 >= -10000.0\n", - "_C122103: -10000.0*t_8_map_10 - t_mem_8 + task_total_memory_router_router10_task8 >= -10000.0\n", - "_C122104: -t9_end_ + t9_start - 10000.0*t_9_map_10 - t_send_9 + task_total_delay_router_router10_task9 >= -10000.0\n", - "_C122105: -10000.0*t_9_map_10 - t_mem_9 + task_total_memory_router_router10_task9 >= -10000.0\n", - "_C122106: -t10_end_ + t10_start - 10000.0*t_10_map_10 - t_send_10 + task_total_delay_router_router10_task10 >= -10000.0\n", - "_C122107: -10000.0*t_10_map_10 - t_mem_10 + task_total_memory_router_router10_task10 >= -10000.0\n", - "_C122108: -t11_end_ + t11_start - 10000.0*t_11_map_10 - t_send_11 + task_total_delay_router_router10_task11 >= -10000.0\n", - "_C122109: -10000.0*t_11_map_10 - t_mem_11 + task_total_memory_router_router10_task11 >= -10000.0\n", - "_C122110: -t12_end_ + t12_start - 10000.0*t_12_map_10 - t_send_12 + 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task_total_memory_router_router10_task2 - task_total_memory_router_router10_task20 - task_total_memory_router_router10_task21 - task_total_memory_router_router10_task22 - task_total_memory_router_router10_task23 - task_total_memory_router_router10_task24 - task_total_memory_router_router10_task25 - task_total_memory_router_router10_task26 - task_total_memory_router_router10_task27 - task_total_memory_router_router10_task28 - task_total_memory_router_router10_task29 - task_total_memory_router_router10_task3 - task_total_memory_router_router10_task30 - task_total_memory_router_router10_task31 - task_total_memory_router_router10_task32 - task_total_memory_router_router10_task33 - task_total_memory_router_router10_task34 - task_total_memory_router_router10_task35 - task_total_memory_router_router10_task36 - task_total_memory_router_router10_task37 - task_total_memory_router_router10_task38 - task_total_memory_router_router10_task39 - task_total_memory_router_router10_task4 - task_total_memory_router_router10_task40 - task_total_memory_router_router10_task41 - task_total_memory_router_router10_task42 - task_total_memory_router_router10_task43 - task_total_memory_router_router10_task44 - task_total_memory_router_router10_task45 - task_total_memory_router_router10_task46 - task_total_memory_router_router10_task47 - task_total_memory_router_router10_task48 - task_total_memory_router_router10_task49 - task_total_memory_router_router10_task5 - task_total_memory_router_router10_task50 - task_total_memory_router_router10_task51 - task_total_memory_router_router10_task52 - task_total_memory_router_router10_task53 - task_total_memory_router_router10_task54 - task_total_memory_router_router10_task55 - task_total_memory_router_router10_task56 - task_total_memory_router_router10_task57 - task_total_memory_router_router10_task58 - task_total_memory_router_router10_task59 - task_total_memory_router_router10_task6 - task_total_memory_router_router10_task60 - task_total_memory_router_router10_task61 - task_total_memory_router_router10_task62 - task_total_memory_router_router10_task63 - task_total_memory_router_router10_task64 - task_total_memory_router_router10_task65 - task_total_memory_router_router10_task66 - task_total_memory_router_router10_task67 - task_total_memory_router_router10_task68 - task_total_memory_router_router10_task69 - task_total_memory_router_router10_task7 - task_total_memory_router_router10_task8 - task_total_memory_router_router10_task9 >= -0.0\n", - "_C122227: PE10_total_delay - task_total_delay_router_router10_task0 - task_total_delay_router_router10_task1 - task_total_delay_router_router10_task10 - task_total_delay_router_router10_task11 - task_total_delay_router_router10_task12 - task_total_delay_router_router10_task13 - task_total_delay_router_router10_task14 - task_total_delay_router_router10_task15 - task_total_delay_router_router10_task16 - task_total_delay_router_router10_task17 - task_total_delay_router_router10_task18 - task_total_delay_router_router10_task19 - task_total_delay_router_router10_task2 - task_total_delay_router_router10_task20 - task_total_delay_router_router10_task21 - task_total_delay_router_router10_task22 - task_total_delay_router_router10_task23 - task_total_delay_router_router10_task24 - task_total_delay_router_router10_task25 - task_total_delay_router_router10_task26 - task_total_delay_router_router10_task27 - task_total_delay_router_router10_task28 - task_total_delay_router_router10_task29 - task_total_delay_router_router10_task3 - task_total_delay_router_router10_task30 - task_total_delay_router_router10_task31 - task_total_delay_router_router10_task32 - task_total_delay_router_router10_task33 - task_total_delay_router_router10_task34 - task_total_delay_router_router10_task35 - task_total_delay_router_router10_task36 - task_total_delay_router_router10_task37 - task_total_delay_router_router10_task38 - task_total_delay_router_router10_task39 - task_total_delay_router_router10_task4 - task_total_delay_router_router10_task40 - task_total_delay_router_router10_task41 - task_total_delay_router_router10_task42 - task_total_delay_router_router10_task43 - task_total_delay_router_router10_task44 - task_total_delay_router_router10_task45 - task_total_delay_router_router10_task46 - task_total_delay_router_router10_task47 - task_total_delay_router_router10_task48 - task_total_delay_router_router10_task49 - task_total_delay_router_router10_task5 - task_total_delay_router_router10_task50 - task_total_delay_router_router10_task51 - task_total_delay_router_router10_task52 - task_total_delay_router_router10_task53 - task_total_delay_router_router10_task54 - task_total_delay_router_router10_task55 - task_total_delay_router_router10_task56 - task_total_delay_router_router10_task57 - task_total_delay_router_router10_task58 - task_total_delay_router_router10_task59 - task_total_delay_router_router10_task6 - task_total_delay_router_router10_task60 - task_total_delay_router_router10_task61 - task_total_delay_router_router10_task62 - task_total_delay_router_router10_task63 - task_total_delay_router_router10_task64 - task_total_delay_router_router10_task65 - task_total_delay_router_router10_task66 - task_total_delay_router_router10_task67 - task_total_delay_router_router10_task68 - task_total_delay_router_router10_task69 - task_total_delay_router_router10_task7 - task_total_delay_router_router10_task8 - task_total_delay_router_router10_task9 >= -0.0\n", - "_C122228: PE10_total_memory - task_total_memory_router_router10_task0 - task_total_memory_router_router10_task1 - task_total_memory_router_router10_task10 - task_total_memory_router_router10_task11 - task_total_memory_router_router10_task12 - task_total_memory_router_router10_task13 - task_total_memory_router_router10_task14 - task_total_memory_router_router10_task15 - task_total_memory_router_router10_task16 - task_total_memory_router_router10_task17 - task_total_memory_router_router10_task18 - task_total_memory_router_router10_task19 - task_total_memory_router_router10_task2 - task_total_memory_router_router10_task20 - task_total_memory_router_router10_task21 - task_total_memory_router_router10_task22 - task_total_memory_router_router10_task23 - task_total_memory_router_router10_task24 - task_total_memory_router_router10_task25 - task_total_memory_router_router10_task26 - task_total_memory_router_router10_task27 - task_total_memory_router_router10_task28 - task_total_memory_router_router10_task29 - task_total_memory_router_router10_task3 - task_total_memory_router_router10_task30 - task_total_memory_router_router10_task31 - task_total_memory_router_router10_task32 - task_total_memory_router_router10_task33 - task_total_memory_router_router10_task34 - task_total_memory_router_router10_task35 - task_total_memory_router_router10_task36 - task_total_memory_router_router10_task37 - task_total_memory_router_router10_task38 - task_total_memory_router_router10_task39 - task_total_memory_router_router10_task4 - task_total_memory_router_router10_task40 - task_total_memory_router_router10_task41 - task_total_memory_router_router10_task42 - task_total_memory_router_router10_task43 - task_total_memory_router_router10_task44 - task_total_memory_router_router10_task45 - task_total_memory_router_router10_task46 - task_total_memory_router_router10_task47 - task_total_memory_router_router10_task48 - task_total_memory_router_router10_task49 - task_total_memory_router_router10_task5 - task_total_memory_router_router10_task50 - task_total_memory_router_router10_task51 - task_total_memory_router_router10_task52 - task_total_memory_router_router10_task53 - task_total_memory_router_router10_task54 - task_total_memory_router_router10_task55 - task_total_memory_router_router10_task56 - task_total_memory_router_router10_task57 - task_total_memory_router_router10_task58 - task_total_memory_router_router10_task59 - task_total_memory_router_router10_task6 - task_total_memory_router_router10_task60 - task_total_memory_router_router10_task61 - task_total_memory_router_router10_task62 - task_total_memory_router_router10_task63 - task_total_memory_router_router10_task64 - task_total_memory_router_router10_task65 - task_total_memory_router_router10_task66 - task_total_memory_router_router10_task67 - task_total_memory_router_router10_task68 - task_total_memory_router_router10_task69 - task_total_memory_router_router10_task7 - task_total_memory_router_router10_task8 - task_total_memory_router_router10_task9 >= -0.0\n", - "_C122229: -PE_mem_overflow10 + max_memory_overflow >= 0\n", - "_C122230: PE10_time_delay_max - t0_end_ - 10000.0*t_0_map_10 >= -10000.0\n", - "_C122231: PE10_time_delay_min - t0_start + 10000.0*t_0_map_10 <= 10000.0\n", - "_C122232: PE10_time_delay_max - t1_end_ - 10000.0*t_1_map_10 >= -10000.0\n", - "_C122233: PE10_time_delay_min - t1_start + 10000.0*t_1_map_10 <= 10000.0\n", - "_C122234: PE10_time_delay_max - t2_end_ - 10000.0*t_2_map_10 >= -10000.0\n", - "_C122235: PE10_time_delay_min - t2_start + 10000.0*t_2_map_10 <= 10000.0\n", - "_C122236: PE10_time_delay_max - t3_end_ - 10000.0*t_3_map_10 >= -10000.0\n", - "_C122237: PE10_time_delay_min - t3_start + 10000.0*t_3_map_10 <= 10000.0\n", - "_C122238: PE10_time_delay_max - t4_end_ - 10000.0*t_4_map_10 >= -10000.0\n", - "_C122239: PE10_time_delay_min - t4_start + 10000.0*t_4_map_10 <= 10000.0\n", - "_C122240: PE10_time_delay_max - t5_end_ - 10000.0*t_5_map_10 >= -10000.0\n", - "_C122241: PE10_time_delay_min - t5_start + 10000.0*t_5_map_10 <= 10000.0\n", - "_C122242: PE10_time_delay_max - t6_end_ - 10000.0*t_6_map_10 >= -10000.0\n", - "_C122243: PE10_time_delay_min - t6_start + 10000.0*t_6_map_10 <= 10000.0\n", - "_C122244: PE10_time_delay_max - t7_end_ - 10000.0*t_7_map_10 >= -10000.0\n", - "_C122245: PE10_time_delay_min - t7_start + 10000.0*t_7_map_10 <= 10000.0\n", - "_C122246: PE10_time_delay_max - t8_end_ - 10000.0*t_8_map_10 >= -10000.0\n", - "_C122247: PE10_time_delay_min - t8_start + 10000.0*t_8_map_10 <= 10000.0\n", - "_C122248: PE10_time_delay_max - t9_end_ - 10000.0*t_9_map_10 >= -10000.0\n", - "_C122249: PE10_time_delay_min - t9_start + 10000.0*t_9_map_10 <= 10000.0\n", - "_C122250: PE10_time_delay_max - t10_end_ - 10000.0*t_10_map_10 >= -10000.0\n", - "_C122251: PE10_time_delay_min - t10_start + 10000.0*t_10_map_10 <= 10000.0\n", - "_C122252: PE10_time_delay_max - t11_end_ - 10000.0*t_11_map_10 >= -10000.0\n", - "_C122253: PE10_time_delay_min - t11_start + 10000.0*t_11_map_10 <= 10000.0\n", - "_C122254: PE10_time_delay_max - t12_end_ - 10000.0*t_12_map_10 >= -10000.0\n", - "_C122255: PE10_time_delay_min - t12_start + 10000.0*t_12_map_10 <= 10000.0\n", - "_C122256: PE10_time_delay_max - t13_end_ - 10000.0*t_13_map_10 >= -10000.0\n", - "_C122257: PE10_time_delay_min - t13_start + 10000.0*t_13_map_10 <= 10000.0\n", - "_C122258: PE10_time_delay_max - t14_end_ - 10000.0*t_14_map_10 >= -10000.0\n", - "_C122259: PE10_time_delay_min - t14_start + 10000.0*t_14_map_10 <= 10000.0\n", - "_C122260: PE10_time_delay_max - t15_end_ - 10000.0*t_15_map_10 >= -10000.0\n", - "_C122261: PE10_time_delay_min - t15_start + 10000.0*t_15_map_10 <= 10000.0\n", - "_C122262: PE10_time_delay_max - t16_end_ - 10000.0*t_16_map_10 >= -10000.0\n", - "_C122263: PE10_time_delay_min - t16_start + 10000.0*t_16_map_10 <= 10000.0\n", - "_C122264: PE10_time_delay_max - t17_end_ - 10000.0*t_17_map_10 >= -10000.0\n", - "_C122265: PE10_time_delay_min - t17_start + 10000.0*t_17_map_10 <= 10000.0\n", - "_C122266: PE10_time_delay_max - t18_end_ - 10000.0*t_18_map_10 >= -10000.0\n", - "_C122267: PE10_time_delay_min - t18_start + 10000.0*t_18_map_10 <= 10000.0\n", - "_C122268: PE10_time_delay_max - t19_end_ - 10000.0*t_19_map_10 >= -10000.0\n", - "_C122269: PE10_time_delay_min - t19_start + 10000.0*t_19_map_10 <= 10000.0\n", - "_C122270: PE10_time_delay_max - t20_end_ - 10000.0*t_20_map_10 >= -10000.0\n", - "_C122271: PE10_time_delay_min - t20_start + 10000.0*t_20_map_10 <= 10000.0\n", - "_C122272: PE10_time_delay_max - t21_end_ - 10000.0*t_21_map_10 >= -10000.0\n", - "_C122273: PE10_time_delay_min - t21_start + 10000.0*t_21_map_10 <= 10000.0\n", - "_C122274: PE10_time_delay_max - t22_end_ - 10000.0*t_22_map_10 >= -10000.0\n", - "_C122275: PE10_time_delay_min - t22_start + 10000.0*t_22_map_10 <= 10000.0\n", - "_C122276: PE10_time_delay_max - t23_end_ - 10000.0*t_23_map_10 >= -10000.0\n", - "_C122277: PE10_time_delay_min - t23_start + 10000.0*t_23_map_10 <= 10000.0\n", - "_C122278: PE10_time_delay_max - t24_end_ - 10000.0*t_24_map_10 >= -10000.0\n", - "_C122279: PE10_time_delay_min - t24_start + 10000.0*t_24_map_10 <= 10000.0\n", - "_C122280: PE10_time_delay_max - t25_end_ - 10000.0*t_25_map_10 >= -10000.0\n", - "_C122281: PE10_time_delay_min - t25_start + 10000.0*t_25_map_10 <= 10000.0\n", - "_C122282: PE10_time_delay_max - t26_end_ - 10000.0*t_26_map_10 >= -10000.0\n", - "_C122283: PE10_time_delay_min - t26_start + 10000.0*t_26_map_10 <= 10000.0\n", - "_C122284: PE10_time_delay_max - t27_end_ - 10000.0*t_27_map_10 >= -10000.0\n", - "_C122285: PE10_time_delay_min - t27_start + 10000.0*t_27_map_10 <= 10000.0\n", - "_C122286: PE10_time_delay_max - t28_end_ - 10000.0*t_28_map_10 >= -10000.0\n", - "_C122287: PE10_time_delay_min - t28_start + 10000.0*t_28_map_10 <= 10000.0\n", - "_C122288: PE10_time_delay_max - t29_end_ - 10000.0*t_29_map_10 >= -10000.0\n", - "_C122289: PE10_time_delay_min - t29_start + 10000.0*t_29_map_10 <= 10000.0\n", - "_C122290: PE10_time_delay_max - t30_end_ - 10000.0*t_30_map_10 >= -10000.0\n", - "_C122291: PE10_time_delay_min - t30_start + 10000.0*t_30_map_10 <= 10000.0\n", - "_C122292: PE10_time_delay_max - t31_end_ - 10000.0*t_31_map_10 >= -10000.0\n", - "_C122293: PE10_time_delay_min - t31_start + 10000.0*t_31_map_10 <= 10000.0\n", - "_C122294: PE10_time_delay_max - t32_end_ - 10000.0*t_32_map_10 >= -10000.0\n", - "_C122295: PE10_time_delay_min - t32_start + 10000.0*t_32_map_10 <= 10000.0\n", - "_C122296: PE10_time_delay_max - t33_end_ - 10000.0*t_33_map_10 >= -10000.0\n", - "_C122297: PE10_time_delay_min - t33_start + 10000.0*t_33_map_10 <= 10000.0\n", - "_C122298: PE10_time_delay_max - t34_end_ - 10000.0*t_34_map_10 >= -10000.0\n", - "_C122299: PE10_time_delay_min - t34_start + 10000.0*t_34_map_10 <= 10000.0\n", - "_C122300: PE10_time_delay_max - t35_end_ - 10000.0*t_35_map_10 >= -10000.0\n", - "_C122301: PE10_time_delay_min - t35_start + 10000.0*t_35_map_10 <= 10000.0\n", - "_C122302: PE10_time_delay_max - t36_end_ - 10000.0*t_36_map_10 >= -10000.0\n", - "_C122303: PE10_time_delay_min - t36_start + 10000.0*t_36_map_10 <= 10000.0\n", - "_C122304: PE10_time_delay_max - t37_end_ - 10000.0*t_37_map_10 >= -10000.0\n", - "_C122305: PE10_time_delay_min - t37_start + 10000.0*t_37_map_10 <= 10000.0\n", - "_C122306: PE10_time_delay_max - t38_end_ - 10000.0*t_38_map_10 >= -10000.0\n", - "_C122307: PE10_time_delay_min - t38_start + 10000.0*t_38_map_10 <= 10000.0\n", - "_C122308: PE10_time_delay_max - t39_end_ - 10000.0*t_39_map_10 >= -10000.0\n", - "_C122309: PE10_time_delay_min - t39_start + 10000.0*t_39_map_10 <= 10000.0\n", - "_C122310: PE10_time_delay_max - t40_end_ - 10000.0*t_40_map_10 >= -10000.0\n", - "_C122311: PE10_time_delay_min - t40_start + 10000.0*t_40_map_10 <= 10000.0\n", - "_C122312: PE10_time_delay_max - t41_end_ - 10000.0*t_41_map_10 >= -10000.0\n", - "_C122313: PE10_time_delay_min - t41_start + 10000.0*t_41_map_10 <= 10000.0\n", - "_C122314: PE10_time_delay_max - t42_end_ - 10000.0*t_42_map_10 >= -10000.0\n", - "_C122315: PE10_time_delay_min - t42_start + 10000.0*t_42_map_10 <= 10000.0\n", - "_C122316: PE10_time_delay_max - t43_end_ - 10000.0*t_43_map_10 >= -10000.0\n", - "_C122317: PE10_time_delay_min - t43_start + 10000.0*t_43_map_10 <= 10000.0\n", - "_C122318: PE10_time_delay_max - t44_end_ - 10000.0*t_44_map_10 >= -10000.0\n", - "_C122319: PE10_time_delay_min - t44_start + 10000.0*t_44_map_10 <= 10000.0\n", - "_C122320: PE10_time_delay_max - t45_end_ - 10000.0*t_45_map_10 >= -10000.0\n", - "_C122321: PE10_time_delay_min - t45_start + 10000.0*t_45_map_10 <= 10000.0\n", - "_C122322: PE10_time_delay_max - t46_end_ - 10000.0*t_46_map_10 >= -10000.0\n", - "_C122323: PE10_time_delay_min - t46_start + 10000.0*t_46_map_10 <= 10000.0\n", - "_C122324: PE10_time_delay_max - t47_end_ - 10000.0*t_47_map_10 >= -10000.0\n", - "_C122325: PE10_time_delay_min - t47_start + 10000.0*t_47_map_10 <= 10000.0\n", - "_C122326: PE10_time_delay_max - t48_end_ - 10000.0*t_48_map_10 >= -10000.0\n", - "_C122327: PE10_time_delay_min - t48_start + 10000.0*t_48_map_10 <= 10000.0\n", - "_C122328: PE10_time_delay_max - t49_end_ - 10000.0*t_49_map_10 >= -10000.0\n", - "_C122329: PE10_time_delay_min - t49_start + 10000.0*t_49_map_10 <= 10000.0\n", - "_C122330: PE10_time_delay_max - t50_end_ - 10000.0*t_50_map_10 >= -10000.0\n", - "_C122331: PE10_time_delay_min - t50_start + 10000.0*t_50_map_10 <= 10000.0\n", - "_C122332: PE10_time_delay_max - t51_end_ - 10000.0*t_51_map_10 >= -10000.0\n", - "_C122333: PE10_time_delay_min - t51_start + 10000.0*t_51_map_10 <= 10000.0\n", - "_C122334: PE10_time_delay_max - t52_end_ - 10000.0*t_52_map_10 >= -10000.0\n", - "_C122335: PE10_time_delay_min - t52_start + 10000.0*t_52_map_10 <= 10000.0\n", - "_C122336: PE10_time_delay_max - t53_end_ - 10000.0*t_53_map_10 >= -10000.0\n", - "_C122337: PE10_time_delay_min - t53_start + 10000.0*t_53_map_10 <= 10000.0\n", - "_C122338: PE10_time_delay_max - t54_end_ - 10000.0*t_54_map_10 >= -10000.0\n", - "_C122339: PE10_time_delay_min - t54_start + 10000.0*t_54_map_10 <= 10000.0\n", - "_C122340: PE10_time_delay_max - t55_end_ - 10000.0*t_55_map_10 >= -10000.0\n", - "_C122341: PE10_time_delay_min - t55_start + 10000.0*t_55_map_10 <= 10000.0\n", - "_C122342: PE10_time_delay_max - t56_end_ - 10000.0*t_56_map_10 >= -10000.0\n", - "_C122343: PE10_time_delay_min - t56_start + 10000.0*t_56_map_10 <= 10000.0\n", - "_C122344: PE10_time_delay_max - t57_end_ - 10000.0*t_57_map_10 >= -10000.0\n", - "_C122345: PE10_time_delay_min - t57_start + 10000.0*t_57_map_10 <= 10000.0\n", - "_C122346: PE10_time_delay_max - t58_end_ - 10000.0*t_58_map_10 >= -10000.0\n", - "_C122347: PE10_time_delay_min - t58_start + 10000.0*t_58_map_10 <= 10000.0\n", - "_C122348: PE10_time_delay_max - t59_end_ - 10000.0*t_59_map_10 >= -10000.0\n", - "_C122349: PE10_time_delay_min - t59_start + 10000.0*t_59_map_10 <= 10000.0\n", - "_C122350: PE10_time_delay_max - t60_end_ - 10000.0*t_60_map_10 >= -10000.0\n", - "_C122351: PE10_time_delay_min - t60_start + 10000.0*t_60_map_10 <= 10000.0\n", - "_C122352: PE10_time_delay_max - t61_end_ - 10000.0*t_61_map_10 >= -10000.0\n", - "_C122353: PE10_time_delay_min - t61_start + 10000.0*t_61_map_10 <= 10000.0\n", - "_C122354: PE10_time_delay_max - t62_end_ - 10000.0*t_62_map_10 >= -10000.0\n", - "_C122355: PE10_time_delay_min - t62_start + 10000.0*t_62_map_10 <= 10000.0\n", - "_C122356: PE10_time_delay_max - t63_end_ - 10000.0*t_63_map_10 >= -10000.0\n", - "_C122357: PE10_time_delay_min - t63_start + 10000.0*t_63_map_10 <= 10000.0\n", - "_C122358: PE10_time_delay_max - t64_end_ - 10000.0*t_64_map_10 >= -10000.0\n", - "_C122359: PE10_time_delay_min - t64_start + 10000.0*t_64_map_10 <= 10000.0\n", - "_C122360: PE10_time_delay_max - t65_end_ - 10000.0*t_65_map_10 >= -10000.0\n", - "_C122361: PE10_time_delay_min - t65_start + 10000.0*t_65_map_10 <= 10000.0\n", - "_C122362: PE10_time_delay_max - t66_end_ - 10000.0*t_66_map_10 >= -10000.0\n", - "_C122363: PE10_time_delay_min - t66_start + 10000.0*t_66_map_10 <= 10000.0\n", - "_C122364: PE10_time_delay_max - t67_end_ - 10000.0*t_67_map_10 >= -10000.0\n", - "_C122365: PE10_time_delay_min - t67_start + 10000.0*t_67_map_10 <= 10000.0\n", - "_C122366: PE10_time_delay_max - t68_end_ - 10000.0*t_68_map_10 >= -10000.0\n", - "_C122367: PE10_time_delay_min - t68_start + 10000.0*t_68_map_10 <= 10000.0\n", - "_C122368: PE10_time_delay_max - t69_end_ - 10000.0*t_69_map_10 >= -10000.0\n", - "_C122369: PE10_time_delay_min - t69_start + 10000.0*t_69_map_10 <= 10000.0\n", - "_C122370: -PE10_time_delay_max + PE10_time_delay_min + PE10_total_time_delay = 0\n", - "_C122371: -PE10_total_time_delay + max_router_delay >= 0\n", - "_C122372: PE10_total_time_delay <= 280\n", - "_C122373: -t0_end_ + t0_start - 10000.0*t_0_map_11 - t_send_0 + task_total_delay_router_router11_task0 >= -10000.0\n", - "_C122374: -10000.0*t_0_map_11 - t_mem_0 + task_total_memory_router_router11_task0 >= -10000.0\n", - "_C122375: -t1_end_ + t1_start - 10000.0*t_1_map_11 - t_send_1 + task_total_delay_router_router11_task1 >= -10000.0\n", - "_C122376: -10000.0*t_1_map_11 - t_mem_1 + task_total_memory_router_router11_task1 >= 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task_total_memory_router_router11_task12 - task_total_memory_router_router11_task13 - task_total_memory_router_router11_task14 - task_total_memory_router_router11_task15 - task_total_memory_router_router11_task16 - task_total_memory_router_router11_task17 - task_total_memory_router_router11_task18 - task_total_memory_router_router11_task19 - task_total_memory_router_router11_task2 - task_total_memory_router_router11_task20 - task_total_memory_router_router11_task21 - task_total_memory_router_router11_task22 - task_total_memory_router_router11_task23 - task_total_memory_router_router11_task24 - task_total_memory_router_router11_task25 - task_total_memory_router_router11_task26 - task_total_memory_router_router11_task27 - task_total_memory_router_router11_task28 - task_total_memory_router_router11_task29 - task_total_memory_router_router11_task3 - task_total_memory_router_router11_task30 - task_total_memory_router_router11_task31 - task_total_memory_router_router11_task32 - task_total_memory_router_router11_task33 - task_total_memory_router_router11_task34 - task_total_memory_router_router11_task35 - task_total_memory_router_router11_task36 - task_total_memory_router_router11_task37 - task_total_memory_router_router11_task38 - task_total_memory_router_router11_task39 - task_total_memory_router_router11_task4 - task_total_memory_router_router11_task40 - task_total_memory_router_router11_task41 - task_total_memory_router_router11_task42 - task_total_memory_router_router11_task43 - task_total_memory_router_router11_task44 - task_total_memory_router_router11_task45 - task_total_memory_router_router11_task46 - task_total_memory_router_router11_task47 - task_total_memory_router_router11_task48 - task_total_memory_router_router11_task49 - task_total_memory_router_router11_task5 - task_total_memory_router_router11_task50 - task_total_memory_router_router11_task51 - task_total_memory_router_router11_task52 - task_total_memory_router_router11_task53 - task_total_memory_router_router11_task54 - task_total_memory_router_router11_task55 - task_total_memory_router_router11_task56 - task_total_memory_router_router11_task57 - task_total_memory_router_router11_task58 - task_total_memory_router_router11_task59 - task_total_memory_router_router11_task6 - task_total_memory_router_router11_task60 - task_total_memory_router_router11_task61 - task_total_memory_router_router11_task62 - task_total_memory_router_router11_task63 - task_total_memory_router_router11_task64 - task_total_memory_router_router11_task65 - task_total_memory_router_router11_task66 - task_total_memory_router_router11_task67 - task_total_memory_router_router11_task68 - task_total_memory_router_router11_task69 - task_total_memory_router_router11_task7 - task_total_memory_router_router11_task8 - task_total_memory_router_router11_task9 >= -0.0\n", - "_C122514: PE11_total_delay - task_total_delay_router_router11_task0 - task_total_delay_router_router11_task1 - task_total_delay_router_router11_task10 - task_total_delay_router_router11_task11 - task_total_delay_router_router11_task12 - task_total_delay_router_router11_task13 - task_total_delay_router_router11_task14 - task_total_delay_router_router11_task15 - task_total_delay_router_router11_task16 - task_total_delay_router_router11_task17 - task_total_delay_router_router11_task18 - task_total_delay_router_router11_task19 - task_total_delay_router_router11_task2 - task_total_delay_router_router11_task20 - task_total_delay_router_router11_task21 - task_total_delay_router_router11_task22 - task_total_delay_router_router11_task23 - task_total_delay_router_router11_task24 - task_total_delay_router_router11_task25 - task_total_delay_router_router11_task26 - task_total_delay_router_router11_task27 - task_total_delay_router_router11_task28 - task_total_delay_router_router11_task29 - task_total_delay_router_router11_task3 - task_total_delay_router_router11_task30 - task_total_delay_router_router11_task31 - task_total_delay_router_router11_task32 - task_total_delay_router_router11_task33 - task_total_delay_router_router11_task34 - task_total_delay_router_router11_task35 - task_total_delay_router_router11_task36 - task_total_delay_router_router11_task37 - task_total_delay_router_router11_task38 - task_total_delay_router_router11_task39 - task_total_delay_router_router11_task4 - task_total_delay_router_router11_task40 - task_total_delay_router_router11_task41 - task_total_delay_router_router11_task42 - task_total_delay_router_router11_task43 - task_total_delay_router_router11_task44 - task_total_delay_router_router11_task45 - task_total_delay_router_router11_task46 - task_total_delay_router_router11_task47 - task_total_delay_router_router11_task48 - task_total_delay_router_router11_task49 - task_total_delay_router_router11_task5 - task_total_delay_router_router11_task50 - task_total_delay_router_router11_task51 - task_total_delay_router_router11_task52 - task_total_delay_router_router11_task53 - task_total_delay_router_router11_task54 - task_total_delay_router_router11_task55 - task_total_delay_router_router11_task56 - task_total_delay_router_router11_task57 - task_total_delay_router_router11_task58 - task_total_delay_router_router11_task59 - task_total_delay_router_router11_task6 - task_total_delay_router_router11_task60 - task_total_delay_router_router11_task61 - task_total_delay_router_router11_task62 - task_total_delay_router_router11_task63 - task_total_delay_router_router11_task64 - task_total_delay_router_router11_task65 - task_total_delay_router_router11_task66 - task_total_delay_router_router11_task67 - task_total_delay_router_router11_task68 - task_total_delay_router_router11_task69 - task_total_delay_router_router11_task7 - task_total_delay_router_router11_task8 - task_total_delay_router_router11_task9 >= -0.0\n", - "_C122515: PE11_total_memory - task_total_memory_router_router11_task0 - task_total_memory_router_router11_task1 - task_total_memory_router_router11_task10 - task_total_memory_router_router11_task11 - task_total_memory_router_router11_task12 - task_total_memory_router_router11_task13 - task_total_memory_router_router11_task14 - task_total_memory_router_router11_task15 - task_total_memory_router_router11_task16 - task_total_memory_router_router11_task17 - task_total_memory_router_router11_task18 - task_total_memory_router_router11_task19 - task_total_memory_router_router11_task2 - task_total_memory_router_router11_task20 - task_total_memory_router_router11_task21 - task_total_memory_router_router11_task22 - task_total_memory_router_router11_task23 - task_total_memory_router_router11_task24 - task_total_memory_router_router11_task25 - task_total_memory_router_router11_task26 - task_total_memory_router_router11_task27 - task_total_memory_router_router11_task28 - task_total_memory_router_router11_task29 - task_total_memory_router_router11_task3 - task_total_memory_router_router11_task30 - task_total_memory_router_router11_task31 - task_total_memory_router_router11_task32 - task_total_memory_router_router11_task33 - task_total_memory_router_router11_task34 - task_total_memory_router_router11_task35 - task_total_memory_router_router11_task36 - task_total_memory_router_router11_task37 - task_total_memory_router_router11_task38 - task_total_memory_router_router11_task39 - task_total_memory_router_router11_task4 - task_total_memory_router_router11_task40 - task_total_memory_router_router11_task41 - task_total_memory_router_router11_task42 - task_total_memory_router_router11_task43 - task_total_memory_router_router11_task44 - task_total_memory_router_router11_task45 - task_total_memory_router_router11_task46 - task_total_memory_router_router11_task47 - task_total_memory_router_router11_task48 - task_total_memory_router_router11_task49 - task_total_memory_router_router11_task5 - task_total_memory_router_router11_task50 - task_total_memory_router_router11_task51 - task_total_memory_router_router11_task52 - task_total_memory_router_router11_task53 - task_total_memory_router_router11_task54 - task_total_memory_router_router11_task55 - task_total_memory_router_router11_task56 - task_total_memory_router_router11_task57 - task_total_memory_router_router11_task58 - task_total_memory_router_router11_task59 - task_total_memory_router_router11_task6 - task_total_memory_router_router11_task60 - task_total_memory_router_router11_task61 - task_total_memory_router_router11_task62 - task_total_memory_router_router11_task63 - task_total_memory_router_router11_task64 - task_total_memory_router_router11_task65 - task_total_memory_router_router11_task66 - task_total_memory_router_router11_task67 - task_total_memory_router_router11_task68 - task_total_memory_router_router11_task69 - task_total_memory_router_router11_task7 - task_total_memory_router_router11_task8 - task_total_memory_router_router11_task9 >= -0.0\n", - "_C122516: -PE_mem_overflow11 + max_memory_overflow >= 0\n", - "_C122517: PE11_time_delay_max - t0_end_ - 10000.0*t_0_map_11 >= -10000.0\n", - "_C122518: PE11_time_delay_min - t0_start + 10000.0*t_0_map_11 <= 10000.0\n", - "_C122519: PE11_time_delay_max - t1_end_ - 10000.0*t_1_map_11 >= -10000.0\n", - "_C122520: PE11_time_delay_min - t1_start + 10000.0*t_1_map_11 <= 10000.0\n", - "_C122521: PE11_time_delay_max - t2_end_ - 10000.0*t_2_map_11 >= -10000.0\n", - "_C122522: PE11_time_delay_min - t2_start + 10000.0*t_2_map_11 <= 10000.0\n", - "_C122523: PE11_time_delay_max - t3_end_ - 10000.0*t_3_map_11 >= -10000.0\n", - "_C122524: PE11_time_delay_min - t3_start + 10000.0*t_3_map_11 <= 10000.0\n", - "_C122525: PE11_time_delay_max - t4_end_ - 10000.0*t_4_map_11 >= -10000.0\n", - "_C122526: PE11_time_delay_min - t4_start + 10000.0*t_4_map_11 <= 10000.0\n", - "_C122527: PE11_time_delay_max - t5_end_ - 10000.0*t_5_map_11 >= -10000.0\n", - "_C122528: PE11_time_delay_min - t5_start + 10000.0*t_5_map_11 <= 10000.0\n", - "_C122529: PE11_time_delay_max - t6_end_ - 10000.0*t_6_map_11 >= -10000.0\n", - "_C122530: PE11_time_delay_min - t6_start + 10000.0*t_6_map_11 <= 10000.0\n", - "_C122531: PE11_time_delay_max - t7_end_ - 10000.0*t_7_map_11 >= -10000.0\n", - "_C122532: PE11_time_delay_min - t7_start + 10000.0*t_7_map_11 <= 10000.0\n", - "_C122533: PE11_time_delay_max - t8_end_ - 10000.0*t_8_map_11 >= -10000.0\n", - "_C122534: PE11_time_delay_min - t8_start + 10000.0*t_8_map_11 <= 10000.0\n", - "_C122535: PE11_time_delay_max - t9_end_ - 10000.0*t_9_map_11 >= -10000.0\n", - "_C122536: PE11_time_delay_min - t9_start + 10000.0*t_9_map_11 <= 10000.0\n", - "_C122537: PE11_time_delay_max - t10_end_ - 10000.0*t_10_map_11 >= -10000.0\n", - "_C122538: PE11_time_delay_min - t10_start + 10000.0*t_10_map_11 <= 10000.0\n", - "_C122539: PE11_time_delay_max - t11_end_ - 10000.0*t_11_map_11 >= -10000.0\n", - "_C122540: PE11_time_delay_min - t11_start + 10000.0*t_11_map_11 <= 10000.0\n", - "_C122541: PE11_time_delay_max - t12_end_ - 10000.0*t_12_map_11 >= -10000.0\n", - "_C122542: PE11_time_delay_min - t12_start + 10000.0*t_12_map_11 <= 10000.0\n", - "_C122543: PE11_time_delay_max - t13_end_ - 10000.0*t_13_map_11 >= -10000.0\n", - "_C122544: PE11_time_delay_min - t13_start + 10000.0*t_13_map_11 <= 10000.0\n", - "_C122545: PE11_time_delay_max - t14_end_ - 10000.0*t_14_map_11 >= -10000.0\n", - "_C122546: PE11_time_delay_min - t14_start + 10000.0*t_14_map_11 <= 10000.0\n", - "_C122547: PE11_time_delay_max - t15_end_ - 10000.0*t_15_map_11 >= -10000.0\n", - "_C122548: PE11_time_delay_min - t15_start + 10000.0*t_15_map_11 <= 10000.0\n", - "_C122549: PE11_time_delay_max - t16_end_ - 10000.0*t_16_map_11 >= -10000.0\n", - "_C122550: PE11_time_delay_min - t16_start + 10000.0*t_16_map_11 <= 10000.0\n", - "_C122551: PE11_time_delay_max - t17_end_ - 10000.0*t_17_map_11 >= -10000.0\n", - "_C122552: PE11_time_delay_min - t17_start + 10000.0*t_17_map_11 <= 10000.0\n", - "_C122553: PE11_time_delay_max - t18_end_ - 10000.0*t_18_map_11 >= -10000.0\n", - "_C122554: PE11_time_delay_min - t18_start + 10000.0*t_18_map_11 <= 10000.0\n", - "_C122555: PE11_time_delay_max - t19_end_ - 10000.0*t_19_map_11 >= -10000.0\n", - "_C122556: PE11_time_delay_min - t19_start + 10000.0*t_19_map_11 <= 10000.0\n", - "_C122557: PE11_time_delay_max - t20_end_ - 10000.0*t_20_map_11 >= -10000.0\n", - "_C122558: PE11_time_delay_min - t20_start + 10000.0*t_20_map_11 <= 10000.0\n", - "_C122559: PE11_time_delay_max - t21_end_ - 10000.0*t_21_map_11 >= -10000.0\n", - "_C122560: PE11_time_delay_min - t21_start + 10000.0*t_21_map_11 <= 10000.0\n", - "_C122561: PE11_time_delay_max - t22_end_ - 10000.0*t_22_map_11 >= -10000.0\n", - "_C122562: PE11_time_delay_min - t22_start + 10000.0*t_22_map_11 <= 10000.0\n", - "_C122563: PE11_time_delay_max - t23_end_ - 10000.0*t_23_map_11 >= -10000.0\n", - "_C122564: PE11_time_delay_min - t23_start + 10000.0*t_23_map_11 <= 10000.0\n", - "_C122565: PE11_time_delay_max - t24_end_ - 10000.0*t_24_map_11 >= -10000.0\n", - "_C122566: PE11_time_delay_min - t24_start + 10000.0*t_24_map_11 <= 10000.0\n", - "_C122567: PE11_time_delay_max - t25_end_ - 10000.0*t_25_map_11 >= -10000.0\n", - "_C122568: PE11_time_delay_min - t25_start + 10000.0*t_25_map_11 <= 10000.0\n", - "_C122569: PE11_time_delay_max - t26_end_ - 10000.0*t_26_map_11 >= -10000.0\n", - "_C122570: PE11_time_delay_min - t26_start + 10000.0*t_26_map_11 <= 10000.0\n", - "_C122571: PE11_time_delay_max - t27_end_ - 10000.0*t_27_map_11 >= -10000.0\n", - "_C122572: PE11_time_delay_min - t27_start + 10000.0*t_27_map_11 <= 10000.0\n", - "_C122573: PE11_time_delay_max - t28_end_ - 10000.0*t_28_map_11 >= -10000.0\n", - "_C122574: PE11_time_delay_min - t28_start + 10000.0*t_28_map_11 <= 10000.0\n", - "_C122575: PE11_time_delay_max - t29_end_ - 10000.0*t_29_map_11 >= -10000.0\n", - "_C122576: PE11_time_delay_min - t29_start + 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10000.0*t_41_map_11 <= 10000.0\n", - "_C122601: PE11_time_delay_max - t42_end_ - 10000.0*t_42_map_11 >= -10000.0\n", - "_C122602: PE11_time_delay_min - t42_start + 10000.0*t_42_map_11 <= 10000.0\n", - "_C122603: PE11_time_delay_max - t43_end_ - 10000.0*t_43_map_11 >= -10000.0\n", - "_C122604: PE11_time_delay_min - t43_start + 10000.0*t_43_map_11 <= 10000.0\n", - "_C122605: PE11_time_delay_max - t44_end_ - 10000.0*t_44_map_11 >= -10000.0\n", - "_C122606: PE11_time_delay_min - t44_start + 10000.0*t_44_map_11 <= 10000.0\n", - "_C122607: PE11_time_delay_max - t45_end_ - 10000.0*t_45_map_11 >= -10000.0\n", - "_C122608: PE11_time_delay_min - t45_start + 10000.0*t_45_map_11 <= 10000.0\n", - "_C122609: PE11_time_delay_max - t46_end_ - 10000.0*t_46_map_11 >= -10000.0\n", - "_C122610: PE11_time_delay_min - t46_start + 10000.0*t_46_map_11 <= 10000.0\n", - "_C122611: PE11_time_delay_max - t47_end_ - 10000.0*t_47_map_11 >= -10000.0\n", - "_C122612: PE11_time_delay_min - t47_start + 10000.0*t_47_map_11 <= 10000.0\n", - "_C122613: PE11_time_delay_max - t48_end_ - 10000.0*t_48_map_11 >= -10000.0\n", - "_C122614: PE11_time_delay_min - t48_start + 10000.0*t_48_map_11 <= 10000.0\n", - "_C122615: PE11_time_delay_max - t49_end_ - 10000.0*t_49_map_11 >= -10000.0\n", - "_C122616: PE11_time_delay_min - t49_start + 10000.0*t_49_map_11 <= 10000.0\n", - "_C122617: PE11_time_delay_max - t50_end_ - 10000.0*t_50_map_11 >= -10000.0\n", - "_C122618: PE11_time_delay_min - t50_start + 10000.0*t_50_map_11 <= 10000.0\n", - "_C122619: PE11_time_delay_max - t51_end_ - 10000.0*t_51_map_11 >= -10000.0\n", - "_C122620: PE11_time_delay_min - t51_start + 10000.0*t_51_map_11 <= 10000.0\n", - "_C122621: PE11_time_delay_max - t52_end_ - 10000.0*t_52_map_11 >= -10000.0\n", - "_C122622: PE11_time_delay_min - t52_start + 10000.0*t_52_map_11 <= 10000.0\n", - "_C122623: PE11_time_delay_max - t53_end_ - 10000.0*t_53_map_11 >= -10000.0\n", - "_C122624: PE11_time_delay_min - t53_start + 10000.0*t_53_map_11 <= 10000.0\n", - "_C122625: PE11_time_delay_max - t54_end_ - 10000.0*t_54_map_11 >= -10000.0\n", - "_C122626: PE11_time_delay_min - t54_start + 10000.0*t_54_map_11 <= 10000.0\n", - "_C122627: PE11_time_delay_max - t55_end_ - 10000.0*t_55_map_11 >= -10000.0\n", - "_C122628: PE11_time_delay_min - t55_start + 10000.0*t_55_map_11 <= 10000.0\n", - "_C122629: PE11_time_delay_max - t56_end_ - 10000.0*t_56_map_11 >= -10000.0\n", - "_C122630: PE11_time_delay_min - t56_start + 10000.0*t_56_map_11 <= 10000.0\n", - "_C122631: PE11_time_delay_max - t57_end_ - 10000.0*t_57_map_11 >= -10000.0\n", - "_C122632: PE11_time_delay_min - t57_start + 10000.0*t_57_map_11 <= 10000.0\n", - "_C122633: PE11_time_delay_max - t58_end_ - 10000.0*t_58_map_11 >= -10000.0\n", - "_C122634: PE11_time_delay_min - t58_start + 10000.0*t_58_map_11 <= 10000.0\n", - "_C122635: PE11_time_delay_max - t59_end_ - 10000.0*t_59_map_11 >= -10000.0\n", - "_C122636: PE11_time_delay_min - t59_start + 10000.0*t_59_map_11 <= 10000.0\n", - "_C122637: PE11_time_delay_max - t60_end_ - 10000.0*t_60_map_11 >= -10000.0\n", - "_C122638: PE11_time_delay_min - t60_start + 10000.0*t_60_map_11 <= 10000.0\n", - "_C122639: PE11_time_delay_max - t61_end_ - 10000.0*t_61_map_11 >= -10000.0\n", - "_C122640: PE11_time_delay_min - t61_start + 10000.0*t_61_map_11 <= 10000.0\n", - "_C122641: PE11_time_delay_max - t62_end_ - 10000.0*t_62_map_11 >= -10000.0\n", - "_C122642: PE11_time_delay_min - t62_start + 10000.0*t_62_map_11 <= 10000.0\n", - "_C122643: PE11_time_delay_max - t63_end_ - 10000.0*t_63_map_11 >= -10000.0\n", - "_C122644: PE11_time_delay_min - t63_start + 10000.0*t_63_map_11 <= 10000.0\n", - "_C122645: PE11_time_delay_max - t64_end_ - 10000.0*t_64_map_11 >= -10000.0\n", - "_C122646: PE11_time_delay_min - t64_start + 10000.0*t_64_map_11 <= 10000.0\n", - "_C122647: PE11_time_delay_max - t65_end_ - 10000.0*t_65_map_11 >= -10000.0\n", - "_C122648: PE11_time_delay_min - t65_start + 10000.0*t_65_map_11 <= 10000.0\n", - "_C122649: PE11_time_delay_max - t66_end_ - 10000.0*t_66_map_11 >= -10000.0\n", - "_C122650: PE11_time_delay_min - t66_start + 10000.0*t_66_map_11 <= 10000.0\n", - "_C122651: PE11_time_delay_max - t67_end_ - 10000.0*t_67_map_11 >= -10000.0\n", - "_C122652: PE11_time_delay_min - t67_start + 10000.0*t_67_map_11 <= 10000.0\n", - "_C122653: PE11_time_delay_max - t68_end_ - 10000.0*t_68_map_11 >= -10000.0\n", - "_C122654: PE11_time_delay_min - t68_start + 10000.0*t_68_map_11 <= 10000.0\n", - "_C122655: PE11_time_delay_max - t69_end_ - 10000.0*t_69_map_11 >= -10000.0\n", - "_C122656: PE11_time_delay_min - t69_start + 10000.0*t_69_map_11 <= 10000.0\n", - "_C122657: -PE11_time_delay_max + PE11_time_delay_min + PE11_total_time_delay = 0\n", - "_C122658: -PE11_total_time_delay + max_router_delay >= 0\n", - "_C122659: PE11_total_time_delay <= 280\n", - "_C122660: -t0_end_ + t0_start - 10000.0*t_0_map_12 - t_send_0 + task_total_delay_router_router12_task0 >= -10000.0\n", - "_C122661: -10000.0*t_0_map_12 - t_mem_0 + task_total_memory_router_router12_task0 >= -10000.0\n", - "_C122662: -t1_end_ + t1_start - 10000.0*t_1_map_12 - t_send_1 + task_total_delay_router_router12_task1 >= -10000.0\n", - "_C122663: -10000.0*t_1_map_12 - t_mem_1 + task_total_memory_router_router12_task1 >= -10000.0\n", - "_C122664: -t2_end_ + t2_start - 10000.0*t_2_map_12 - t_send_2 + task_total_delay_router_router12_task2 >= -10000.0\n", - "_C122665: -10000.0*t_2_map_12 - t_mem_2 + task_total_memory_router_router12_task2 >= -10000.0\n", - "_C122666: -t3_end_ + t3_start - 10000.0*t_3_map_12 - t_send_3 + task_total_delay_router_router12_task3 >= -10000.0\n", - "_C122667: -10000.0*t_3_map_12 - t_mem_3 + task_total_memory_router_router12_task3 >= -10000.0\n", - "_C122668: -t4_end_ + t4_start - 10000.0*t_4_map_12 - t_send_4 + task_total_delay_router_router12_task4 >= -10000.0\n", - "_C122669: -10000.0*t_4_map_12 - t_mem_4 + task_total_memory_router_router12_task4 >= -10000.0\n", - "_C122670: -t5_end_ + t5_start - 10000.0*t_5_map_12 - t_send_5 + task_total_delay_router_router12_task5 >= -10000.0\n", - "_C122671: -10000.0*t_5_map_12 - t_mem_5 + task_total_memory_router_router12_task5 >= -10000.0\n", - "_C122672: -t6_end_ + t6_start - 10000.0*t_6_map_12 - t_send_6 + task_total_delay_router_router12_task6 >= -10000.0\n", - "_C122673: -10000.0*t_6_map_12 - t_mem_6 + task_total_memory_router_router12_task6 >= -10000.0\n", - "_C122674: -t7_end_ + t7_start - 10000.0*t_7_map_12 - t_send_7 + task_total_delay_router_router12_task7 >= -10000.0\n", - "_C122675: -10000.0*t_7_map_12 - t_mem_7 + task_total_memory_router_router12_task7 >= -10000.0\n", - "_C122676: -t8_end_ + t8_start - 10000.0*t_8_map_12 - t_send_8 + task_total_delay_router_router12_task8 >= -10000.0\n", - "_C122677: -10000.0*t_8_map_12 - t_mem_8 + task_total_memory_router_router12_task8 >= -10000.0\n", - "_C122678: -t9_end_ + t9_start - 10000.0*t_9_map_12 - t_send_9 + task_total_delay_router_router12_task9 >= -10000.0\n", - "_C122679: -10000.0*t_9_map_12 - t_mem_9 + task_total_memory_router_router12_task9 >= -10000.0\n", - "_C122680: -t10_end_ + t10_start - 10000.0*t_10_map_12 - t_send_10 + task_total_delay_router_router12_task10 >= -10000.0\n", - "_C122681: -10000.0*t_10_map_12 - t_mem_10 + task_total_memory_router_router12_task10 >= -10000.0\n", - "_C122682: -t11_end_ + t11_start - 10000.0*t_11_map_12 - t_send_11 + task_total_delay_router_router12_task11 >= -10000.0\n", - "_C122683: -10000.0*t_11_map_12 - t_mem_11 + task_total_memory_router_router12_task11 >= -10000.0\n", - "_C122684: -t12_end_ + t12_start - 10000.0*t_12_map_12 - t_send_12 + task_total_delay_router_router12_task12 >= -10000.0\n", - "_C122685: -10000.0*t_12_map_12 - t_mem_12 + task_total_memory_router_router12_task12 >= -10000.0\n", - "_C122686: -t13_end_ + t13_start - 10000.0*t_13_map_12 - t_send_13 + task_total_delay_router_router12_task13 >= -10000.0\n", - "_C122687: -10000.0*t_13_map_12 - t_mem_13 + task_total_memory_router_router12_task13 >= -10000.0\n", - "_C122688: -t14_end_ + t14_start - 10000.0*t_14_map_12 - t_send_14 + task_total_delay_router_router12_task14 >= -10000.0\n", - "_C122689: -10000.0*t_14_map_12 - t_mem_14 + task_total_memory_router_router12_task14 >= -10000.0\n", - "_C122690: -t15_end_ + t15_start - 10000.0*t_15_map_12 - t_send_15 + task_total_delay_router_router12_task15 >= -10000.0\n", - "_C122691: -10000.0*t_15_map_12 - t_mem_15 + task_total_memory_router_router12_task15 >= -10000.0\n", - "_C122692: -t16_end_ + t16_start - 10000.0*t_16_map_12 - t_send_16 + task_total_delay_router_router12_task16 >= -10000.0\n", - "_C122693: -10000.0*t_16_map_12 - t_mem_16 + task_total_memory_router_router12_task16 >= -10000.0\n", - "_C122694: -t17_end_ + t17_start - 10000.0*t_17_map_12 - t_send_17 + task_total_delay_router_router12_task17 >= -10000.0\n", - "_C122695: -10000.0*t_17_map_12 - t_mem_17 + task_total_memory_router_router12_task17 >= -10000.0\n", - "_C122696: -t18_end_ + t18_start - 10000.0*t_18_map_12 - t_send_18 + task_total_delay_router_router12_task18 >= -10000.0\n", - "_C122697: -10000.0*t_18_map_12 - t_mem_18 + task_total_memory_router_router12_task18 >= -10000.0\n", - "_C122698: -t19_end_ + t19_start - 10000.0*t_19_map_12 - t_send_19 + task_total_delay_router_router12_task19 >= -10000.0\n", - "_C122699: -10000.0*t_19_map_12 - t_mem_19 + task_total_memory_router_router12_task19 >= -10000.0\n", - "_C122700: -t20_end_ + t20_start - 10000.0*t_20_map_12 - t_send_20 + task_total_delay_router_router12_task20 >= -10000.0\n", - "_C122701: -10000.0*t_20_map_12 - t_mem_20 + task_total_memory_router_router12_task20 >= -10000.0\n", - "_C122702: -t21_end_ + t21_start - 10000.0*t_21_map_12 - t_send_21 + task_total_delay_router_router12_task21 >= -10000.0\n", - "_C122703: -10000.0*t_21_map_12 - t_mem_21 + task_total_memory_router_router12_task21 >= -10000.0\n", - "_C122704: -t22_end_ + t22_start - 10000.0*t_22_map_12 - t_send_22 + task_total_delay_router_router12_task22 >= -10000.0\n", - "_C122705: -10000.0*t_22_map_12 - t_mem_22 + task_total_memory_router_router12_task22 >= -10000.0\n", - "_C122706: -t23_end_ + t23_start - 10000.0*t_23_map_12 - t_send_23 + task_total_delay_router_router12_task23 >= -10000.0\n", - "_C122707: -10000.0*t_23_map_12 - t_mem_23 + task_total_memory_router_router12_task23 >= -10000.0\n", - "_C122708: -t24_end_ + t24_start - 10000.0*t_24_map_12 - t_send_24 + task_total_delay_router_router12_task24 >= -10000.0\n", - "_C122709: -10000.0*t_24_map_12 - t_mem_24 + task_total_memory_router_router12_task24 >= -10000.0\n", - "_C122710: -t25_end_ + t25_start - 10000.0*t_25_map_12 - t_send_25 + task_total_delay_router_router12_task25 >= -10000.0\n", - "_C122711: -10000.0*t_25_map_12 - t_mem_25 + task_total_memory_router_router12_task25 >= -10000.0\n", - "_C122712: -t26_end_ + t26_start - 10000.0*t_26_map_12 - t_send_26 + task_total_delay_router_router12_task26 >= -10000.0\n", - "_C122713: -10000.0*t_26_map_12 - t_mem_26 + task_total_memory_router_router12_task26 >= -10000.0\n", - "_C122714: -t27_end_ + t27_start - 10000.0*t_27_map_12 - t_send_27 + task_total_delay_router_router12_task27 >= -10000.0\n", - "_C122715: -10000.0*t_27_map_12 - t_mem_27 + task_total_memory_router_router12_task27 >= -10000.0\n", - "_C122716: -t28_end_ + t28_start - 10000.0*t_28_map_12 - t_send_28 + task_total_delay_router_router12_task28 >= -10000.0\n", - "_C122717: -10000.0*t_28_map_12 - t_mem_28 + task_total_memory_router_router12_task28 >= -10000.0\n", - "_C122718: -t29_end_ + t29_start - 10000.0*t_29_map_12 - t_send_29 + task_total_delay_router_router12_task29 >= -10000.0\n", - "_C122719: -10000.0*t_29_map_12 - t_mem_29 + task_total_memory_router_router12_task29 >= -10000.0\n", - "_C122720: -t30_end_ + t30_start - 10000.0*t_30_map_12 - t_send_30 + task_total_delay_router_router12_task30 >= -10000.0\n", - "_C122721: -10000.0*t_30_map_12 - t_mem_30 + task_total_memory_router_router12_task30 >= -10000.0\n", - "_C122722: -t31_end_ + t31_start - 10000.0*t_31_map_12 - t_send_31 + task_total_delay_router_router12_task31 >= -10000.0\n", - "_C122723: -10000.0*t_31_map_12 - t_mem_31 + task_total_memory_router_router12_task31 >= -10000.0\n", - "_C122724: -t32_end_ + t32_start - 10000.0*t_32_map_12 - t_send_32 + task_total_delay_router_router12_task32 >= -10000.0\n", - "_C122725: -10000.0*t_32_map_12 - t_mem_32 + task_total_memory_router_router12_task32 >= -10000.0\n", - "_C122726: -t33_end_ + t33_start - 10000.0*t_33_map_12 - t_send_33 + task_total_delay_router_router12_task33 >= -10000.0\n", - "_C122727: -10000.0*t_33_map_12 - t_mem_33 + task_total_memory_router_router12_task33 >= -10000.0\n", - "_C122728: -t34_end_ + t34_start - 10000.0*t_34_map_12 - t_send_34 + task_total_delay_router_router12_task34 >= -10000.0\n", - "_C122729: -10000.0*t_34_map_12 - t_mem_34 + task_total_memory_router_router12_task34 >= -10000.0\n", - "_C122730: 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task_total_delay_router_router12_task39 >= -10000.0\n", - "_C122739: -10000.0*t_39_map_12 - t_mem_39 + task_total_memory_router_router12_task39 >= -10000.0\n", - "_C122740: -t40_end_ + t40_start - 10000.0*t_40_map_12 - t_send_40 + task_total_delay_router_router12_task40 >= -10000.0\n", - "_C122741: -10000.0*t_40_map_12 - t_mem_40 + task_total_memory_router_router12_task40 >= -10000.0\n", - "_C122742: -t41_end_ + t41_start - 10000.0*t_41_map_12 - t_send_41 + task_total_delay_router_router12_task41 >= -10000.0\n", - "_C122743: -10000.0*t_41_map_12 - t_mem_41 + task_total_memory_router_router12_task41 >= -10000.0\n", - "_C122744: -t42_end_ + t42_start - 10000.0*t_42_map_12 - t_send_42 + task_total_delay_router_router12_task42 >= -10000.0\n", - "_C122745: -10000.0*t_42_map_12 - t_mem_42 + task_total_memory_router_router12_task42 >= -10000.0\n", - "_C122746: -t43_end_ + t43_start - 10000.0*t_43_map_12 - t_send_43 + task_total_delay_router_router12_task43 >= -10000.0\n", - "_C122747: 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>= -10000.0\n", - "_C122756: -t48_end_ + t48_start - 10000.0*t_48_map_12 - t_send_48 + task_total_delay_router_router12_task48 >= -10000.0\n", - "_C122757: -10000.0*t_48_map_12 - t_mem_48 + task_total_memory_router_router12_task48 >= -10000.0\n", - "_C122758: -t49_end_ + t49_start - 10000.0*t_49_map_12 - t_send_49 + task_total_delay_router_router12_task49 >= -10000.0\n", - "_C122759: -10000.0*t_49_map_12 - t_mem_49 + task_total_memory_router_router12_task49 >= -10000.0\n", - "_C122760: -t50_end_ + t50_start - 10000.0*t_50_map_12 - t_send_50 + task_total_delay_router_router12_task50 >= -10000.0\n", - "_C122761: -10000.0*t_50_map_12 - t_mem_50 + task_total_memory_router_router12_task50 >= -10000.0\n", - "_C122762: -t51_end_ + t51_start - 10000.0*t_51_map_12 - t_send_51 + task_total_delay_router_router12_task51 >= -10000.0\n", - "_C122763: -10000.0*t_51_map_12 - t_mem_51 + task_total_memory_router_router12_task51 >= -10000.0\n", - "_C122764: -t52_end_ + t52_start - 10000.0*t_52_map_12 - 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task_total_memory_router_router12_task60 >= -10000.0\n", - "_C122782: -t61_end_ + t61_start - 10000.0*t_61_map_12 - t_send_61 + task_total_delay_router_router12_task61 >= -10000.0\n", - "_C122783: -10000.0*t_61_map_12 - t_mem_61 + task_total_memory_router_router12_task61 >= -10000.0\n", - "_C122784: -t62_end_ + t62_start - 10000.0*t_62_map_12 - t_send_62 + task_total_delay_router_router12_task62 >= -10000.0\n", - "_C122785: -10000.0*t_62_map_12 - t_mem_62 + task_total_memory_router_router12_task62 >= -10000.0\n", - "_C122786: -t63_end_ + t63_start - 10000.0*t_63_map_12 - t_send_63 + task_total_delay_router_router12_task63 >= -10000.0\n", - "_C122787: -10000.0*t_63_map_12 - t_mem_63 + task_total_memory_router_router12_task63 >= -10000.0\n", - "_C122788: -t64_end_ + t64_start - 10000.0*t_64_map_12 - t_send_64 + task_total_delay_router_router12_task64 >= -10000.0\n", - "_C122789: -10000.0*t_64_map_12 - t_mem_64 + task_total_memory_router_router12_task64 >= -10000.0\n", - "_C122790: -t65_end_ + t65_start - 10000.0*t_65_map_12 - t_send_65 + task_total_delay_router_router12_task65 >= -10000.0\n", - "_C122791: -10000.0*t_65_map_12 - t_mem_65 + task_total_memory_router_router12_task65 >= -10000.0\n", - "_C122792: -t66_end_ + t66_start - 10000.0*t_66_map_12 - t_send_66 + task_total_delay_router_router12_task66 >= -10000.0\n", - "_C122793: -10000.0*t_66_map_12 - t_mem_66 + task_total_memory_router_router12_task66 >= -10000.0\n", - "_C122794: -t67_end_ + t67_start - 10000.0*t_67_map_12 - t_send_67 + task_total_delay_router_router12_task67 >= -10000.0\n", - "_C122795: -10000.0*t_67_map_12 - t_mem_67 + task_total_memory_router_router12_task67 >= -10000.0\n", - "_C122796: -t68_end_ + t68_start - 10000.0*t_68_map_12 - t_send_68 + task_total_delay_router_router12_task68 >= -10000.0\n", - "_C122797: -10000.0*t_68_map_12 - t_mem_68 + task_total_memory_router_router12_task68 >= -10000.0\n", - "_C122798: -t69_end_ + t69_start - 10000.0*t_69_map_12 - t_send_69 + task_total_delay_router_router12_task69 >= -10000.0\n", - "_C122799: -10000.0*t_69_map_12 - t_mem_69 + task_total_memory_router_router12_task69 >= -10000.0\n", - "_C122800: PE_mem_overflow12 - task_total_memory_router_router12_task0 - task_total_memory_router_router12_task1 - task_total_memory_router_router12_task10 - task_total_memory_router_router12_task11 - task_total_memory_router_router12_task12 - task_total_memory_router_router12_task13 - task_total_memory_router_router12_task14 - task_total_memory_router_router12_task15 - task_total_memory_router_router12_task16 - task_total_memory_router_router12_task17 - task_total_memory_router_router12_task18 - task_total_memory_router_router12_task19 - task_total_memory_router_router12_task2 - task_total_memory_router_router12_task20 - task_total_memory_router_router12_task21 - task_total_memory_router_router12_task22 - task_total_memory_router_router12_task23 - task_total_memory_router_router12_task24 - task_total_memory_router_router12_task25 - task_total_memory_router_router12_task26 - task_total_memory_router_router12_task27 - task_total_memory_router_router12_task28 - task_total_memory_router_router12_task29 - task_total_memory_router_router12_task3 - task_total_memory_router_router12_task30 - task_total_memory_router_router12_task31 - task_total_memory_router_router12_task32 - task_total_memory_router_router12_task33 - task_total_memory_router_router12_task34 - task_total_memory_router_router12_task35 - task_total_memory_router_router12_task36 - task_total_memory_router_router12_task37 - task_total_memory_router_router12_task38 - task_total_memory_router_router12_task39 - task_total_memory_router_router12_task4 - task_total_memory_router_router12_task40 - task_total_memory_router_router12_task41 - task_total_memory_router_router12_task42 - task_total_memory_router_router12_task43 - task_total_memory_router_router12_task44 - task_total_memory_router_router12_task45 - task_total_memory_router_router12_task46 - task_total_memory_router_router12_task47 - task_total_memory_router_router12_task48 - task_total_memory_router_router12_task49 - task_total_memory_router_router12_task5 - task_total_memory_router_router12_task50 - task_total_memory_router_router12_task51 - task_total_memory_router_router12_task52 - task_total_memory_router_router12_task53 - task_total_memory_router_router12_task54 - task_total_memory_router_router12_task55 - task_total_memory_router_router12_task56 - task_total_memory_router_router12_task57 - task_total_memory_router_router12_task58 - task_total_memory_router_router12_task59 - task_total_memory_router_router12_task6 - task_total_memory_router_router12_task60 - task_total_memory_router_router12_task61 - task_total_memory_router_router12_task62 - task_total_memory_router_router12_task63 - task_total_memory_router_router12_task64 - task_total_memory_router_router12_task65 - task_total_memory_router_router12_task66 - task_total_memory_router_router12_task67 - task_total_memory_router_router12_task68 - task_total_memory_router_router12_task69 - task_total_memory_router_router12_task7 - task_total_memory_router_router12_task8 - task_total_memory_router_router12_task9 >= -0.0\n", - "_C122801: PE12_total_delay - task_total_delay_router_router12_task0 - task_total_delay_router_router12_task1 - task_total_delay_router_router12_task10 - task_total_delay_router_router12_task11 - task_total_delay_router_router12_task12 - task_total_delay_router_router12_task13 - task_total_delay_router_router12_task14 - task_total_delay_router_router12_task15 - task_total_delay_router_router12_task16 - task_total_delay_router_router12_task17 - task_total_delay_router_router12_task18 - task_total_delay_router_router12_task19 - task_total_delay_router_router12_task2 - task_total_delay_router_router12_task20 - task_total_delay_router_router12_task21 - task_total_delay_router_router12_task22 - task_total_delay_router_router12_task23 - task_total_delay_router_router12_task24 - task_total_delay_router_router12_task25 - task_total_delay_router_router12_task26 - task_total_delay_router_router12_task27 - task_total_delay_router_router12_task28 - task_total_delay_router_router12_task29 - task_total_delay_router_router12_task3 - task_total_delay_router_router12_task30 - task_total_delay_router_router12_task31 - task_total_delay_router_router12_task32 - task_total_delay_router_router12_task33 - task_total_delay_router_router12_task34 - task_total_delay_router_router12_task35 - task_total_delay_router_router12_task36 - task_total_delay_router_router12_task37 - task_total_delay_router_router12_task38 - task_total_delay_router_router12_task39 - task_total_delay_router_router12_task4 - task_total_delay_router_router12_task40 - task_total_delay_router_router12_task41 - task_total_delay_router_router12_task42 - task_total_delay_router_router12_task43 - task_total_delay_router_router12_task44 - task_total_delay_router_router12_task45 - task_total_delay_router_router12_task46 - task_total_delay_router_router12_task47 - task_total_delay_router_router12_task48 - task_total_delay_router_router12_task49 - task_total_delay_router_router12_task5 - task_total_delay_router_router12_task50 - task_total_delay_router_router12_task51 - task_total_delay_router_router12_task52 - task_total_delay_router_router12_task53 - task_total_delay_router_router12_task54 - task_total_delay_router_router12_task55 - task_total_delay_router_router12_task56 - task_total_delay_router_router12_task57 - task_total_delay_router_router12_task58 - task_total_delay_router_router12_task59 - task_total_delay_router_router12_task6 - task_total_delay_router_router12_task60 - task_total_delay_router_router12_task61 - task_total_delay_router_router12_task62 - task_total_delay_router_router12_task63 - task_total_delay_router_router12_task64 - task_total_delay_router_router12_task65 - task_total_delay_router_router12_task66 - task_total_delay_router_router12_task67 - task_total_delay_router_router12_task68 - task_total_delay_router_router12_task69 - task_total_delay_router_router12_task7 - task_total_delay_router_router12_task8 - task_total_delay_router_router12_task9 >= -0.0\n", - "_C122802: PE12_total_memory - task_total_memory_router_router12_task0 - task_total_memory_router_router12_task1 - task_total_memory_router_router12_task10 - task_total_memory_router_router12_task11 - task_total_memory_router_router12_task12 - task_total_memory_router_router12_task13 - task_total_memory_router_router12_task14 - task_total_memory_router_router12_task15 - task_total_memory_router_router12_task16 - task_total_memory_router_router12_task17 - task_total_memory_router_router12_task18 - task_total_memory_router_router12_task19 - task_total_memory_router_router12_task2 - task_total_memory_router_router12_task20 - task_total_memory_router_router12_task21 - task_total_memory_router_router12_task22 - task_total_memory_router_router12_task23 - task_total_memory_router_router12_task24 - task_total_memory_router_router12_task25 - task_total_memory_router_router12_task26 - task_total_memory_router_router12_task27 - task_total_memory_router_router12_task28 - task_total_memory_router_router12_task29 - task_total_memory_router_router12_task3 - task_total_memory_router_router12_task30 - task_total_memory_router_router12_task31 - task_total_memory_router_router12_task32 - task_total_memory_router_router12_task33 - task_total_memory_router_router12_task34 - task_total_memory_router_router12_task35 - task_total_memory_router_router12_task36 - task_total_memory_router_router12_task37 - task_total_memory_router_router12_task38 - task_total_memory_router_router12_task39 - task_total_memory_router_router12_task4 - task_total_memory_router_router12_task40 - task_total_memory_router_router12_task41 - task_total_memory_router_router12_task42 - task_total_memory_router_router12_task43 - task_total_memory_router_router12_task44 - task_total_memory_router_router12_task45 - task_total_memory_router_router12_task46 - task_total_memory_router_router12_task47 - task_total_memory_router_router12_task48 - task_total_memory_router_router12_task49 - task_total_memory_router_router12_task5 - task_total_memory_router_router12_task50 - task_total_memory_router_router12_task51 - task_total_memory_router_router12_task52 - task_total_memory_router_router12_task53 - task_total_memory_router_router12_task54 - task_total_memory_router_router12_task55 - task_total_memory_router_router12_task56 - task_total_memory_router_router12_task57 - task_total_memory_router_router12_task58 - task_total_memory_router_router12_task59 - task_total_memory_router_router12_task6 - task_total_memory_router_router12_task60 - task_total_memory_router_router12_task61 - task_total_memory_router_router12_task62 - task_total_memory_router_router12_task63 - task_total_memory_router_router12_task64 - task_total_memory_router_router12_task65 - task_total_memory_router_router12_task66 - task_total_memory_router_router12_task67 - task_total_memory_router_router12_task68 - task_total_memory_router_router12_task69 - task_total_memory_router_router12_task7 - task_total_memory_router_router12_task8 - task_total_memory_router_router12_task9 >= -0.0\n", - "_C122803: -PE_mem_overflow12 + max_memory_overflow >= 0\n", - "_C122804: PE12_time_delay_max - t0_end_ - 10000.0*t_0_map_12 >= -10000.0\n", - "_C122805: PE12_time_delay_min - t0_start + 10000.0*t_0_map_12 <= 10000.0\n", - "_C122806: PE12_time_delay_max - t1_end_ - 10000.0*t_1_map_12 >= -10000.0\n", - "_C122807: PE12_time_delay_min - t1_start + 10000.0*t_1_map_12 <= 10000.0\n", - "_C122808: PE12_time_delay_max - t2_end_ - 10000.0*t_2_map_12 >= -10000.0\n", - "_C122809: PE12_time_delay_min - t2_start + 10000.0*t_2_map_12 <= 10000.0\n", - "_C122810: PE12_time_delay_max - t3_end_ - 10000.0*t_3_map_12 >= -10000.0\n", - "_C122811: PE12_time_delay_min - t3_start + 10000.0*t_3_map_12 <= 10000.0\n", - "_C122812: PE12_time_delay_max - t4_end_ - 10000.0*t_4_map_12 >= -10000.0\n", - "_C122813: PE12_time_delay_min - t4_start + 10000.0*t_4_map_12 <= 10000.0\n", - "_C122814: PE12_time_delay_max - t5_end_ - 10000.0*t_5_map_12 >= -10000.0\n", - "_C122815: PE12_time_delay_min - t5_start + 10000.0*t_5_map_12 <= 10000.0\n", - "_C122816: PE12_time_delay_max - t6_end_ - 10000.0*t_6_map_12 >= -10000.0\n", - "_C122817: PE12_time_delay_min - t6_start + 10000.0*t_6_map_12 <= 10000.0\n", - "_C122818: PE12_time_delay_max - t7_end_ - 10000.0*t_7_map_12 >= -10000.0\n", - "_C122819: PE12_time_delay_min - t7_start + 10000.0*t_7_map_12 <= 10000.0\n", - "_C122820: PE12_time_delay_max - t8_end_ - 10000.0*t_8_map_12 >= -10000.0\n", - "_C122821: PE12_time_delay_min - t8_start + 10000.0*t_8_map_12 <= 10000.0\n", - "_C122822: PE12_time_delay_max - t9_end_ - 10000.0*t_9_map_12 >= -10000.0\n", - "_C122823: PE12_time_delay_min - t9_start + 10000.0*t_9_map_12 <= 10000.0\n", - "_C122824: PE12_time_delay_max - t10_end_ - 10000.0*t_10_map_12 >= -10000.0\n", - "_C122825: PE12_time_delay_min - t10_start + 10000.0*t_10_map_12 <= 10000.0\n", - "_C122826: PE12_time_delay_max - t11_end_ - 10000.0*t_11_map_12 >= -10000.0\n", - "_C122827: PE12_time_delay_min - t11_start + 10000.0*t_11_map_12 <= 10000.0\n", - "_C122828: PE12_time_delay_max - t12_end_ - 10000.0*t_12_map_12 >= -10000.0\n", - "_C122829: PE12_time_delay_min - t12_start + 10000.0*t_12_map_12 <= 10000.0\n", - "_C122830: PE12_time_delay_max - t13_end_ - 10000.0*t_13_map_12 >= -10000.0\n", - "_C122831: PE12_time_delay_min - t13_start + 10000.0*t_13_map_12 <= 10000.0\n", - "_C122832: PE12_time_delay_max - t14_end_ - 10000.0*t_14_map_12 >= -10000.0\n", - "_C122833: PE12_time_delay_min - t14_start + 10000.0*t_14_map_12 <= 10000.0\n", - "_C122834: PE12_time_delay_max - t15_end_ - 10000.0*t_15_map_12 >= -10000.0\n", - "_C122835: PE12_time_delay_min - t15_start + 10000.0*t_15_map_12 <= 10000.0\n", - "_C122836: PE12_time_delay_max - t16_end_ - 10000.0*t_16_map_12 >= -10000.0\n", - "_C122837: PE12_time_delay_min - t16_start + 10000.0*t_16_map_12 <= 10000.0\n", - "_C122838: PE12_time_delay_max - t17_end_ - 10000.0*t_17_map_12 >= -10000.0\n", - "_C122839: PE12_time_delay_min - t17_start + 10000.0*t_17_map_12 <= 10000.0\n", - "_C122840: PE12_time_delay_max - t18_end_ - 10000.0*t_18_map_12 >= -10000.0\n", - "_C122841: PE12_time_delay_min - t18_start + 10000.0*t_18_map_12 <= 10000.0\n", - "_C122842: PE12_time_delay_max - t19_end_ - 10000.0*t_19_map_12 >= -10000.0\n", - "_C122843: PE12_time_delay_min - t19_start + 10000.0*t_19_map_12 <= 10000.0\n", - "_C122844: PE12_time_delay_max - t20_end_ - 10000.0*t_20_map_12 >= -10000.0\n", - "_C122845: PE12_time_delay_min - t20_start + 10000.0*t_20_map_12 <= 10000.0\n", - "_C122846: PE12_time_delay_max - t21_end_ - 10000.0*t_21_map_12 >= -10000.0\n", - "_C122847: PE12_time_delay_min - t21_start + 10000.0*t_21_map_12 <= 10000.0\n", - "_C122848: PE12_time_delay_max - t22_end_ - 10000.0*t_22_map_12 >= -10000.0\n", - "_C122849: PE12_time_delay_min - t22_start + 10000.0*t_22_map_12 <= 10000.0\n", - "_C122850: PE12_time_delay_max - t23_end_ - 10000.0*t_23_map_12 >= -10000.0\n", - "_C122851: PE12_time_delay_min - t23_start + 10000.0*t_23_map_12 <= 10000.0\n", - "_C122852: PE12_time_delay_max - t24_end_ - 10000.0*t_24_map_12 >= -10000.0\n", - "_C122853: PE12_time_delay_min - t24_start + 10000.0*t_24_map_12 <= 10000.0\n", - "_C122854: PE12_time_delay_max - t25_end_ - 10000.0*t_25_map_12 >= -10000.0\n", - "_C122855: PE12_time_delay_min - t25_start + 10000.0*t_25_map_12 <= 10000.0\n", - "_C122856: PE12_time_delay_max - t26_end_ - 10000.0*t_26_map_12 >= -10000.0\n", - "_C122857: PE12_time_delay_min - t26_start + 10000.0*t_26_map_12 <= 10000.0\n", - "_C122858: PE12_time_delay_max - t27_end_ - 10000.0*t_27_map_12 >= -10000.0\n", - "_C122859: PE12_time_delay_min - t27_start + 10000.0*t_27_map_12 <= 10000.0\n", - "_C122860: PE12_time_delay_max - t28_end_ - 10000.0*t_28_map_12 >= -10000.0\n", - "_C122861: PE12_time_delay_min - t28_start + 10000.0*t_28_map_12 <= 10000.0\n", - "_C122862: PE12_time_delay_max - t29_end_ - 10000.0*t_29_map_12 >= -10000.0\n", - "_C122863: PE12_time_delay_min - t29_start + 10000.0*t_29_map_12 <= 10000.0\n", - "_C122864: PE12_time_delay_max - t30_end_ - 10000.0*t_30_map_12 >= -10000.0\n", - "_C122865: PE12_time_delay_min - t30_start + 10000.0*t_30_map_12 <= 10000.0\n", - "_C122866: PE12_time_delay_max - t31_end_ - 10000.0*t_31_map_12 >= -10000.0\n", - "_C122867: PE12_time_delay_min - t31_start + 10000.0*t_31_map_12 <= 10000.0\n", - "_C122868: PE12_time_delay_max - t32_end_ - 10000.0*t_32_map_12 >= -10000.0\n", - "_C122869: PE12_time_delay_min - t32_start + 10000.0*t_32_map_12 <= 10000.0\n", - "_C122870: PE12_time_delay_max - t33_end_ - 10000.0*t_33_map_12 >= -10000.0\n", - "_C122871: PE12_time_delay_min - t33_start + 10000.0*t_33_map_12 <= 10000.0\n", - "_C122872: PE12_time_delay_max - t34_end_ - 10000.0*t_34_map_12 >= -10000.0\n", - "_C122873: PE12_time_delay_min - t34_start + 10000.0*t_34_map_12 <= 10000.0\n", - "_C122874: PE12_time_delay_max - t35_end_ - 10000.0*t_35_map_12 >= -10000.0\n", - "_C122875: PE12_time_delay_min - t35_start + 10000.0*t_35_map_12 <= 10000.0\n", - "_C122876: PE12_time_delay_max - t36_end_ - 10000.0*t_36_map_12 >= -10000.0\n", - "_C122877: PE12_time_delay_min - t36_start + 10000.0*t_36_map_12 <= 10000.0\n", - "_C122878: PE12_time_delay_max - t37_end_ - 10000.0*t_37_map_12 >= -10000.0\n", - "_C122879: PE12_time_delay_min - t37_start + 10000.0*t_37_map_12 <= 10000.0\n", - "_C122880: PE12_time_delay_max - t38_end_ - 10000.0*t_38_map_12 >= -10000.0\n", - "_C122881: PE12_time_delay_min - t38_start + 10000.0*t_38_map_12 <= 10000.0\n", - "_C122882: PE12_time_delay_max - t39_end_ - 10000.0*t_39_map_12 >= -10000.0\n", - "_C122883: PE12_time_delay_min - t39_start + 10000.0*t_39_map_12 <= 10000.0\n", - "_C122884: PE12_time_delay_max - t40_end_ - 10000.0*t_40_map_12 >= -10000.0\n", - "_C122885: PE12_time_delay_min - t40_start + 10000.0*t_40_map_12 <= 10000.0\n", - "_C122886: PE12_time_delay_max - t41_end_ - 10000.0*t_41_map_12 >= -10000.0\n", - "_C122887: PE12_time_delay_min - t41_start + 10000.0*t_41_map_12 <= 10000.0\n", - "_C122888: PE12_time_delay_max - t42_end_ - 10000.0*t_42_map_12 >= -10000.0\n", - "_C122889: PE12_time_delay_min - t42_start + 10000.0*t_42_map_12 <= 10000.0\n", - "_C122890: PE12_time_delay_max - t43_end_ - 10000.0*t_43_map_12 >= -10000.0\n", - "_C122891: PE12_time_delay_min - t43_start + 10000.0*t_43_map_12 <= 10000.0\n", - "_C122892: PE12_time_delay_max - t44_end_ - 10000.0*t_44_map_12 >= -10000.0\n", - "_C122893: PE12_time_delay_min - t44_start + 10000.0*t_44_map_12 <= 10000.0\n", - "_C122894: PE12_time_delay_max - t45_end_ - 10000.0*t_45_map_12 >= -10000.0\n", - "_C122895: PE12_time_delay_min - t45_start + 10000.0*t_45_map_12 <= 10000.0\n", - "_C122896: PE12_time_delay_max - t46_end_ - 10000.0*t_46_map_12 >= -10000.0\n", - "_C122897: PE12_time_delay_min - t46_start + 10000.0*t_46_map_12 <= 10000.0\n", - "_C122898: PE12_time_delay_max - t47_end_ - 10000.0*t_47_map_12 >= -10000.0\n", - "_C122899: PE12_time_delay_min - t47_start + 10000.0*t_47_map_12 <= 10000.0\n", - "_C122900: PE12_time_delay_max - t48_end_ - 10000.0*t_48_map_12 >= -10000.0\n", - "_C122901: PE12_time_delay_min - t48_start + 10000.0*t_48_map_12 <= 10000.0\n", - "_C122902: PE12_time_delay_max - t49_end_ - 10000.0*t_49_map_12 >= -10000.0\n", - "_C122903: PE12_time_delay_min - t49_start + 10000.0*t_49_map_12 <= 10000.0\n", - "_C122904: PE12_time_delay_max - t50_end_ - 10000.0*t_50_map_12 >= -10000.0\n", - "_C122905: PE12_time_delay_min - t50_start + 10000.0*t_50_map_12 <= 10000.0\n", - "_C122906: PE12_time_delay_max - t51_end_ - 10000.0*t_51_map_12 >= -10000.0\n", - "_C122907: PE12_time_delay_min - t51_start + 10000.0*t_51_map_12 <= 10000.0\n", - "_C122908: PE12_time_delay_max - t52_end_ - 10000.0*t_52_map_12 >= -10000.0\n", - "_C122909: PE12_time_delay_min - t52_start + 10000.0*t_52_map_12 <= 10000.0\n", - "_C122910: PE12_time_delay_max - t53_end_ - 10000.0*t_53_map_12 >= -10000.0\n", - "_C122911: PE12_time_delay_min - t53_start + 10000.0*t_53_map_12 <= 10000.0\n", - "_C122912: PE12_time_delay_max - t54_end_ - 10000.0*t_54_map_12 >= -10000.0\n", - "_C122913: PE12_time_delay_min - t54_start + 10000.0*t_54_map_12 <= 10000.0\n", - "_C122914: PE12_time_delay_max - t55_end_ - 10000.0*t_55_map_12 >= -10000.0\n", - "_C122915: PE12_time_delay_min - t55_start + 10000.0*t_55_map_12 <= 10000.0\n", - "_C122916: PE12_time_delay_max - t56_end_ - 10000.0*t_56_map_12 >= -10000.0\n", - "_C122917: PE12_time_delay_min - t56_start + 10000.0*t_56_map_12 <= 10000.0\n", - "_C122918: PE12_time_delay_max - t57_end_ - 10000.0*t_57_map_12 >= -10000.0\n", - "_C122919: PE12_time_delay_min - t57_start + 10000.0*t_57_map_12 <= 10000.0\n", - "_C122920: PE12_time_delay_max - t58_end_ - 10000.0*t_58_map_12 >= -10000.0\n", - "_C122921: PE12_time_delay_min - t58_start + 10000.0*t_58_map_12 <= 10000.0\n", - "_C122922: PE12_time_delay_max - t59_end_ - 10000.0*t_59_map_12 >= -10000.0\n", - "_C122923: PE12_time_delay_min - t59_start + 10000.0*t_59_map_12 <= 10000.0\n", - "_C122924: PE12_time_delay_max - t60_end_ - 10000.0*t_60_map_12 >= -10000.0\n", - "_C122925: PE12_time_delay_min - t60_start + 10000.0*t_60_map_12 <= 10000.0\n", - "_C122926: PE12_time_delay_max - t61_end_ - 10000.0*t_61_map_12 >= -10000.0\n", - "_C122927: PE12_time_delay_min - t61_start + 10000.0*t_61_map_12 <= 10000.0\n", - "_C122928: PE12_time_delay_max - t62_end_ - 10000.0*t_62_map_12 >= -10000.0\n", - "_C122929: PE12_time_delay_min - t62_start + 10000.0*t_62_map_12 <= 10000.0\n", - "_C122930: PE12_time_delay_max - t63_end_ - 10000.0*t_63_map_12 >= -10000.0\n", - "_C122931: PE12_time_delay_min - t63_start + 10000.0*t_63_map_12 <= 10000.0\n", - "_C122932: PE12_time_delay_max - t64_end_ - 10000.0*t_64_map_12 >= -10000.0\n", - "_C122933: PE12_time_delay_min - t64_start + 10000.0*t_64_map_12 <= 10000.0\n", - "_C122934: PE12_time_delay_max - t65_end_ - 10000.0*t_65_map_12 >= -10000.0\n", - "_C122935: PE12_time_delay_min - t65_start + 10000.0*t_65_map_12 <= 10000.0\n", - "_C122936: PE12_time_delay_max - t66_end_ - 10000.0*t_66_map_12 >= -10000.0\n", - "_C122937: PE12_time_delay_min - t66_start + 10000.0*t_66_map_12 <= 10000.0\n", - "_C122938: PE12_time_delay_max - t67_end_ - 10000.0*t_67_map_12 >= -10000.0\n", - "_C122939: PE12_time_delay_min - t67_start + 10000.0*t_67_map_12 <= 10000.0\n", - "_C122940: PE12_time_delay_max - t68_end_ - 10000.0*t_68_map_12 >= -10000.0\n", - "_C122941: PE12_time_delay_min - t68_start + 10000.0*t_68_map_12 <= 10000.0\n", - "_C122942: PE12_time_delay_max - t69_end_ - 10000.0*t_69_map_12 >= -10000.0\n", - "_C122943: PE12_time_delay_min - t69_start + 10000.0*t_69_map_12 <= 10000.0\n", - "_C122944: -PE12_time_delay_max + PE12_time_delay_min + PE12_total_time_delay = 0\n", - "_C122945: -PE12_total_time_delay + max_router_delay >= 0\n", - "_C122946: PE12_total_time_delay <= 280\n", - "_C122947: -t0_end_ + t0_start - 10000.0*t_0_map_13 - t_send_0 + task_total_delay_router_router13_task0 >= -10000.0\n", - "_C122948: -10000.0*t_0_map_13 - t_mem_0 + task_total_memory_router_router13_task0 >= -10000.0\n", - "_C122949: -t1_end_ + t1_start - 10000.0*t_1_map_13 - t_send_1 + task_total_delay_router_router13_task1 >= -10000.0\n", - "_C122950: -10000.0*t_1_map_13 - t_mem_1 + task_total_memory_router_router13_task1 >= -10000.0\n", - "_C122951: -t2_end_ + t2_start - 10000.0*t_2_map_13 - t_send_2 + task_total_delay_router_router13_task2 >= -10000.0\n", - "_C122952: -10000.0*t_2_map_13 - t_mem_2 + task_total_memory_router_router13_task2 >= -10000.0\n", - "_C122953: -t3_end_ + t3_start - 10000.0*t_3_map_13 - t_send_3 + task_total_delay_router_router13_task3 >= -10000.0\n", - "_C122954: -10000.0*t_3_map_13 - t_mem_3 + task_total_memory_router_router13_task3 >= -10000.0\n", - "_C122955: -t4_end_ + t4_start - 10000.0*t_4_map_13 - t_send_4 + task_total_delay_router_router13_task4 >= -10000.0\n", - "_C122956: -10000.0*t_4_map_13 - t_mem_4 + task_total_memory_router_router13_task4 >= -10000.0\n", - "_C122957: -t5_end_ + t5_start - 10000.0*t_5_map_13 - t_send_5 + task_total_delay_router_router13_task5 >= -10000.0\n", - "_C122958: -10000.0*t_5_map_13 - t_mem_5 + task_total_memory_router_router13_task5 >= -10000.0\n", - "_C122959: -t6_end_ + t6_start - 10000.0*t_6_map_13 - t_send_6 + task_total_delay_router_router13_task6 >= -10000.0\n", - "_C122960: -10000.0*t_6_map_13 - t_mem_6 + task_total_memory_router_router13_task6 >= -10000.0\n", - "_C122961: -t7_end_ + t7_start - 10000.0*t_7_map_13 - t_send_7 + task_total_delay_router_router13_task7 >= -10000.0\n", - "_C122962: -10000.0*t_7_map_13 - t_mem_7 + task_total_memory_router_router13_task7 >= -10000.0\n", - "_C122963: -t8_end_ + t8_start - 10000.0*t_8_map_13 - t_send_8 + task_total_delay_router_router13_task8 >= -10000.0\n", - "_C122964: -10000.0*t_8_map_13 - t_mem_8 + task_total_memory_router_router13_task8 >= -10000.0\n", - "_C122965: -t9_end_ + t9_start - 10000.0*t_9_map_13 - t_send_9 + task_total_delay_router_router13_task9 >= -10000.0\n", - "_C122966: -10000.0*t_9_map_13 - t_mem_9 + task_total_memory_router_router13_task9 >= -10000.0\n", - "_C122967: -t10_end_ + t10_start - 10000.0*t_10_map_13 - t_send_10 + task_total_delay_router_router13_task10 >= -10000.0\n", - "_C122968: -10000.0*t_10_map_13 - t_mem_10 + task_total_memory_router_router13_task10 >= -10000.0\n", - "_C122969: -t11_end_ + t11_start - 10000.0*t_11_map_13 - t_send_11 + task_total_delay_router_router13_task11 >= -10000.0\n", - "_C122970: -10000.0*t_11_map_13 - t_mem_11 + task_total_memory_router_router13_task11 >= -10000.0\n", - "_C122971: -t12_end_ + t12_start - 10000.0*t_12_map_13 - t_send_12 + task_total_delay_router_router13_task12 >= -10000.0\n", - "_C122972: -10000.0*t_12_map_13 - t_mem_12 + task_total_memory_router_router13_task12 >= -10000.0\n", - "_C122973: -t13_end_ + t13_start - 10000.0*t_13_map_13 - t_send_13 + task_total_delay_router_router13_task13 >= -10000.0\n", - "_C122974: -10000.0*t_13_map_13 - t_mem_13 + task_total_memory_router_router13_task13 >= -10000.0\n", - "_C122975: -t14_end_ + t14_start - 10000.0*t_14_map_13 - t_send_14 + task_total_delay_router_router13_task14 >= -10000.0\n", - "_C122976: -10000.0*t_14_map_13 - t_mem_14 + task_total_memory_router_router13_task14 >= -10000.0\n", - "_C122977: -t15_end_ + t15_start - 10000.0*t_15_map_13 - t_send_15 + task_total_delay_router_router13_task15 >= -10000.0\n", - "_C122978: -10000.0*t_15_map_13 - t_mem_15 + task_total_memory_router_router13_task15 >= -10000.0\n", - "_C122979: -t16_end_ + t16_start - 10000.0*t_16_map_13 - t_send_16 + task_total_delay_router_router13_task16 >= -10000.0\n", - "_C122980: -10000.0*t_16_map_13 - t_mem_16 + task_total_memory_router_router13_task16 >= -10000.0\n", - "_C122981: -t17_end_ + t17_start - 10000.0*t_17_map_13 - t_send_17 + task_total_delay_router_router13_task17 >= -10000.0\n", - "_C122982: -10000.0*t_17_map_13 - t_mem_17 + task_total_memory_router_router13_task17 >= -10000.0\n", - "_C122983: -t18_end_ + t18_start - 10000.0*t_18_map_13 - t_send_18 + task_total_delay_router_router13_task18 >= -10000.0\n", - "_C122984: -10000.0*t_18_map_13 - t_mem_18 + task_total_memory_router_router13_task18 >= -10000.0\n", - "_C122985: -t19_end_ + t19_start - 10000.0*t_19_map_13 - t_send_19 + task_total_delay_router_router13_task19 >= -10000.0\n", - "_C122986: -10000.0*t_19_map_13 - t_mem_19 + task_total_memory_router_router13_task19 >= -10000.0\n", - "_C122987: -t20_end_ + t20_start - 10000.0*t_20_map_13 - t_send_20 + task_total_delay_router_router13_task20 >= -10000.0\n", - "_C122988: -10000.0*t_20_map_13 - t_mem_20 + task_total_memory_router_router13_task20 >= -10000.0\n", - "_C122989: -t21_end_ + t21_start - 10000.0*t_21_map_13 - t_send_21 + task_total_delay_router_router13_task21 >= -10000.0\n", - "_C122990: -10000.0*t_21_map_13 - t_mem_21 + task_total_memory_router_router13_task21 >= -10000.0\n", - "_C122991: -t22_end_ + t22_start - 10000.0*t_22_map_13 - t_send_22 + task_total_delay_router_router13_task22 >= -10000.0\n", - "_C122992: -10000.0*t_22_map_13 - t_mem_22 + task_total_memory_router_router13_task22 >= -10000.0\n", - "_C122993: -t23_end_ + t23_start - 10000.0*t_23_map_13 - t_send_23 + task_total_delay_router_router13_task23 >= -10000.0\n", - "_C122994: -10000.0*t_23_map_13 - t_mem_23 + task_total_memory_router_router13_task23 >= -10000.0\n", - "_C122995: -t24_end_ + t24_start - 10000.0*t_24_map_13 - t_send_24 + task_total_delay_router_router13_task24 >= -10000.0\n", - "_C122996: -10000.0*t_24_map_13 - t_mem_24 + task_total_memory_router_router13_task24 >= -10000.0\n", - "_C122997: 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task_total_delay_router_router13_task29 >= -10000.0\n", - "_C123006: -10000.0*t_29_map_13 - t_mem_29 + task_total_memory_router_router13_task29 >= -10000.0\n", - "_C123007: -t30_end_ + t30_start - 10000.0*t_30_map_13 - t_send_30 + task_total_delay_router_router13_task30 >= -10000.0\n", - "_C123008: -10000.0*t_30_map_13 - t_mem_30 + task_total_memory_router_router13_task30 >= -10000.0\n", - "_C123009: -t31_end_ + t31_start - 10000.0*t_31_map_13 - t_send_31 + task_total_delay_router_router13_task31 >= -10000.0\n", - "_C123010: -10000.0*t_31_map_13 - t_mem_31 + task_total_memory_router_router13_task31 >= -10000.0\n", - "_C123011: -t32_end_ + t32_start - 10000.0*t_32_map_13 - t_send_32 + task_total_delay_router_router13_task32 >= -10000.0\n", - "_C123012: -10000.0*t_32_map_13 - t_mem_32 + task_total_memory_router_router13_task32 >= -10000.0\n", - "_C123013: -t33_end_ + t33_start - 10000.0*t_33_map_13 - t_send_33 + task_total_delay_router_router13_task33 >= -10000.0\n", - "_C123014: 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task_total_memory_router_router13_task19 - task_total_memory_router_router13_task2 - task_total_memory_router_router13_task20 - task_total_memory_router_router13_task21 - task_total_memory_router_router13_task22 - task_total_memory_router_router13_task23 - task_total_memory_router_router13_task24 - task_total_memory_router_router13_task25 - task_total_memory_router_router13_task26 - task_total_memory_router_router13_task27 - task_total_memory_router_router13_task28 - task_total_memory_router_router13_task29 - task_total_memory_router_router13_task3 - task_total_memory_router_router13_task30 - task_total_memory_router_router13_task31 - task_total_memory_router_router13_task32 - task_total_memory_router_router13_task33 - task_total_memory_router_router13_task34 - task_total_memory_router_router13_task35 - task_total_memory_router_router13_task36 - task_total_memory_router_router13_task37 - task_total_memory_router_router13_task38 - task_total_memory_router_router13_task39 - task_total_memory_router_router13_task4 - task_total_memory_router_router13_task40 - task_total_memory_router_router13_task41 - task_total_memory_router_router13_task42 - task_total_memory_router_router13_task43 - task_total_memory_router_router13_task44 - task_total_memory_router_router13_task45 - task_total_memory_router_router13_task46 - task_total_memory_router_router13_task47 - task_total_memory_router_router13_task48 - task_total_memory_router_router13_task49 - task_total_memory_router_router13_task5 - task_total_memory_router_router13_task50 - task_total_memory_router_router13_task51 - task_total_memory_router_router13_task52 - task_total_memory_router_router13_task53 - task_total_memory_router_router13_task54 - task_total_memory_router_router13_task55 - task_total_memory_router_router13_task56 - task_total_memory_router_router13_task57 - task_total_memory_router_router13_task58 - task_total_memory_router_router13_task59 - task_total_memory_router_router13_task6 - task_total_memory_router_router13_task60 - task_total_memory_router_router13_task61 - task_total_memory_router_router13_task62 - task_total_memory_router_router13_task63 - task_total_memory_router_router13_task64 - task_total_memory_router_router13_task65 - task_total_memory_router_router13_task66 - task_total_memory_router_router13_task67 - task_total_memory_router_router13_task68 - task_total_memory_router_router13_task69 - task_total_memory_router_router13_task7 - task_total_memory_router_router13_task8 - task_total_memory_router_router13_task9 >= -0.0\n", - "_C123088: PE13_total_delay - task_total_delay_router_router13_task0 - task_total_delay_router_router13_task1 - task_total_delay_router_router13_task10 - task_total_delay_router_router13_task11 - task_total_delay_router_router13_task12 - task_total_delay_router_router13_task13 - task_total_delay_router_router13_task14 - task_total_delay_router_router13_task15 - task_total_delay_router_router13_task16 - task_total_delay_router_router13_task17 - task_total_delay_router_router13_task18 - task_total_delay_router_router13_task19 - task_total_delay_router_router13_task2 - task_total_delay_router_router13_task20 - task_total_delay_router_router13_task21 - task_total_delay_router_router13_task22 - task_total_delay_router_router13_task23 - task_total_delay_router_router13_task24 - task_total_delay_router_router13_task25 - task_total_delay_router_router13_task26 - task_total_delay_router_router13_task27 - task_total_delay_router_router13_task28 - task_total_delay_router_router13_task29 - task_total_delay_router_router13_task3 - task_total_delay_router_router13_task30 - task_total_delay_router_router13_task31 - task_total_delay_router_router13_task32 - task_total_delay_router_router13_task33 - task_total_delay_router_router13_task34 - task_total_delay_router_router13_task35 - task_total_delay_router_router13_task36 - task_total_delay_router_router13_task37 - task_total_delay_router_router13_task38 - task_total_delay_router_router13_task39 - task_total_delay_router_router13_task4 - task_total_delay_router_router13_task40 - task_total_delay_router_router13_task41 - task_total_delay_router_router13_task42 - task_total_delay_router_router13_task43 - task_total_delay_router_router13_task44 - task_total_delay_router_router13_task45 - task_total_delay_router_router13_task46 - task_total_delay_router_router13_task47 - task_total_delay_router_router13_task48 - task_total_delay_router_router13_task49 - task_total_delay_router_router13_task5 - task_total_delay_router_router13_task50 - task_total_delay_router_router13_task51 - task_total_delay_router_router13_task52 - task_total_delay_router_router13_task53 - task_total_delay_router_router13_task54 - task_total_delay_router_router13_task55 - task_total_delay_router_router13_task56 - task_total_delay_router_router13_task57 - task_total_delay_router_router13_task58 - task_total_delay_router_router13_task59 - task_total_delay_router_router13_task6 - task_total_delay_router_router13_task60 - task_total_delay_router_router13_task61 - task_total_delay_router_router13_task62 - task_total_delay_router_router13_task63 - task_total_delay_router_router13_task64 - task_total_delay_router_router13_task65 - task_total_delay_router_router13_task66 - task_total_delay_router_router13_task67 - task_total_delay_router_router13_task68 - task_total_delay_router_router13_task69 - task_total_delay_router_router13_task7 - task_total_delay_router_router13_task8 - task_total_delay_router_router13_task9 >= -0.0\n", - "_C123089: PE13_total_memory - task_total_memory_router_router13_task0 - task_total_memory_router_router13_task1 - task_total_memory_router_router13_task10 - task_total_memory_router_router13_task11 - task_total_memory_router_router13_task12 - task_total_memory_router_router13_task13 - task_total_memory_router_router13_task14 - task_total_memory_router_router13_task15 - task_total_memory_router_router13_task16 - task_total_memory_router_router13_task17 - task_total_memory_router_router13_task18 - task_total_memory_router_router13_task19 - task_total_memory_router_router13_task2 - task_total_memory_router_router13_task20 - task_total_memory_router_router13_task21 - task_total_memory_router_router13_task22 - task_total_memory_router_router13_task23 - task_total_memory_router_router13_task24 - task_total_memory_router_router13_task25 - task_total_memory_router_router13_task26 - task_total_memory_router_router13_task27 - task_total_memory_router_router13_task28 - task_total_memory_router_router13_task29 - task_total_memory_router_router13_task3 - task_total_memory_router_router13_task30 - task_total_memory_router_router13_task31 - task_total_memory_router_router13_task32 - task_total_memory_router_router13_task33 - task_total_memory_router_router13_task34 - task_total_memory_router_router13_task35 - task_total_memory_router_router13_task36 - task_total_memory_router_router13_task37 - task_total_memory_router_router13_task38 - task_total_memory_router_router13_task39 - task_total_memory_router_router13_task4 - task_total_memory_router_router13_task40 - task_total_memory_router_router13_task41 - task_total_memory_router_router13_task42 - task_total_memory_router_router13_task43 - task_total_memory_router_router13_task44 - task_total_memory_router_router13_task45 - task_total_memory_router_router13_task46 - task_total_memory_router_router13_task47 - task_total_memory_router_router13_task48 - task_total_memory_router_router13_task49 - task_total_memory_router_router13_task5 - task_total_memory_router_router13_task50 - task_total_memory_router_router13_task51 - task_total_memory_router_router13_task52 - task_total_memory_router_router13_task53 - task_total_memory_router_router13_task54 - task_total_memory_router_router13_task55 - task_total_memory_router_router13_task56 - task_total_memory_router_router13_task57 - task_total_memory_router_router13_task58 - task_total_memory_router_router13_task59 - task_total_memory_router_router13_task6 - task_total_memory_router_router13_task60 - task_total_memory_router_router13_task61 - task_total_memory_router_router13_task62 - task_total_memory_router_router13_task63 - task_total_memory_router_router13_task64 - task_total_memory_router_router13_task65 - task_total_memory_router_router13_task66 - task_total_memory_router_router13_task67 - task_total_memory_router_router13_task68 - task_total_memory_router_router13_task69 - task_total_memory_router_router13_task7 - task_total_memory_router_router13_task8 - task_total_memory_router_router13_task9 >= -0.0\n", - "_C123090: -PE_mem_overflow13 + max_memory_overflow >= 0\n", - "_C123091: PE13_time_delay_max - t0_end_ - 10000.0*t_0_map_13 >= -10000.0\n", - "_C123092: PE13_time_delay_min - t0_start + 10000.0*t_0_map_13 <= 10000.0\n", - "_C123093: PE13_time_delay_max - t1_end_ - 10000.0*t_1_map_13 >= -10000.0\n", - "_C123094: PE13_time_delay_min - t1_start + 10000.0*t_1_map_13 <= 10000.0\n", - "_C123095: PE13_time_delay_max - t2_end_ - 10000.0*t_2_map_13 >= -10000.0\n", - "_C123096: PE13_time_delay_min - t2_start + 10000.0*t_2_map_13 <= 10000.0\n", - "_C123097: PE13_time_delay_max - t3_end_ - 10000.0*t_3_map_13 >= -10000.0\n", - "_C123098: PE13_time_delay_min - t3_start + 10000.0*t_3_map_13 <= 10000.0\n", - "_C123099: PE13_time_delay_max - t4_end_ - 10000.0*t_4_map_13 >= -10000.0\n", - "_C123100: PE13_time_delay_min - t4_start + 10000.0*t_4_map_13 <= 10000.0\n", - "_C123101: PE13_time_delay_max - t5_end_ - 10000.0*t_5_map_13 >= -10000.0\n", - "_C123102: PE13_time_delay_min - t5_start + 10000.0*t_5_map_13 <= 10000.0\n", - "_C123103: PE13_time_delay_max - t6_end_ - 10000.0*t_6_map_13 >= -10000.0\n", - "_C123104: PE13_time_delay_min - t6_start + 10000.0*t_6_map_13 <= 10000.0\n", - "_C123105: PE13_time_delay_max - t7_end_ - 10000.0*t_7_map_13 >= -10000.0\n", - "_C123106: PE13_time_delay_min - t7_start + 10000.0*t_7_map_13 <= 10000.0\n", - "_C123107: PE13_time_delay_max - t8_end_ - 10000.0*t_8_map_13 >= -10000.0\n", - "_C123108: PE13_time_delay_min - t8_start + 10000.0*t_8_map_13 <= 10000.0\n", - "_C123109: PE13_time_delay_max - t9_end_ - 10000.0*t_9_map_13 >= -10000.0\n", - "_C123110: PE13_time_delay_min - t9_start + 10000.0*t_9_map_13 <= 10000.0\n", - "_C123111: PE13_time_delay_max - t10_end_ - 10000.0*t_10_map_13 >= -10000.0\n", - "_C123112: PE13_time_delay_min - t10_start + 10000.0*t_10_map_13 <= 10000.0\n", - "_C123113: PE13_time_delay_max - t11_end_ - 10000.0*t_11_map_13 >= -10000.0\n", - "_C123114: PE13_time_delay_min - t11_start + 10000.0*t_11_map_13 <= 10000.0\n", - "_C123115: PE13_time_delay_max - t12_end_ - 10000.0*t_12_map_13 >= -10000.0\n", - "_C123116: PE13_time_delay_min - t12_start + 10000.0*t_12_map_13 <= 10000.0\n", - "_C123117: PE13_time_delay_max - t13_end_ - 10000.0*t_13_map_13 >= -10000.0\n", - "_C123118: PE13_time_delay_min - t13_start + 10000.0*t_13_map_13 <= 10000.0\n", - "_C123119: PE13_time_delay_max - t14_end_ - 10000.0*t_14_map_13 >= -10000.0\n", - "_C123120: PE13_time_delay_min - t14_start + 10000.0*t_14_map_13 <= 10000.0\n", - "_C123121: PE13_time_delay_max - t15_end_ - 10000.0*t_15_map_13 >= -10000.0\n", - "_C123122: PE13_time_delay_min - t15_start + 10000.0*t_15_map_13 <= 10000.0\n", - "_C123123: PE13_time_delay_max - t16_end_ - 10000.0*t_16_map_13 >= -10000.0\n", - "_C123124: PE13_time_delay_min - t16_start + 10000.0*t_16_map_13 <= 10000.0\n", - "_C123125: PE13_time_delay_max - t17_end_ - 10000.0*t_17_map_13 >= -10000.0\n", - "_C123126: PE13_time_delay_min - t17_start + 10000.0*t_17_map_13 <= 10000.0\n", - "_C123127: PE13_time_delay_max - t18_end_ - 10000.0*t_18_map_13 >= -10000.0\n", - "_C123128: PE13_time_delay_min - t18_start + 10000.0*t_18_map_13 <= 10000.0\n", - "_C123129: PE13_time_delay_max - t19_end_ - 10000.0*t_19_map_13 >= -10000.0\n", - "_C123130: PE13_time_delay_min - t19_start + 10000.0*t_19_map_13 <= 10000.0\n", - "_C123131: PE13_time_delay_max - t20_end_ - 10000.0*t_20_map_13 >= -10000.0\n", - "_C123132: PE13_time_delay_min - t20_start + 10000.0*t_20_map_13 <= 10000.0\n", - "_C123133: PE13_time_delay_max - t21_end_ - 10000.0*t_21_map_13 >= -10000.0\n", - "_C123134: PE13_time_delay_min - t21_start + 10000.0*t_21_map_13 <= 10000.0\n", - "_C123135: PE13_time_delay_max - t22_end_ - 10000.0*t_22_map_13 >= -10000.0\n", - "_C123136: PE13_time_delay_min - t22_start + 10000.0*t_22_map_13 <= 10000.0\n", - "_C123137: PE13_time_delay_max - t23_end_ - 10000.0*t_23_map_13 >= -10000.0\n", - "_C123138: PE13_time_delay_min - t23_start + 10000.0*t_23_map_13 <= 10000.0\n", - "_C123139: PE13_time_delay_max - t24_end_ - 10000.0*t_24_map_13 >= -10000.0\n", - "_C123140: PE13_time_delay_min - t24_start + 10000.0*t_24_map_13 <= 10000.0\n", - "_C123141: PE13_time_delay_max - t25_end_ - 10000.0*t_25_map_13 >= -10000.0\n", - "_C123142: PE13_time_delay_min - t25_start + 10000.0*t_25_map_13 <= 10000.0\n", - "_C123143: PE13_time_delay_max - t26_end_ - 10000.0*t_26_map_13 >= -10000.0\n", - "_C123144: PE13_time_delay_min - t26_start + 10000.0*t_26_map_13 <= 10000.0\n", - "_C123145: PE13_time_delay_max - t27_end_ - 10000.0*t_27_map_13 >= -10000.0\n", - "_C123146: PE13_time_delay_min - t27_start + 10000.0*t_27_map_13 <= 10000.0\n", - "_C123147: PE13_time_delay_max - t28_end_ - 10000.0*t_28_map_13 >= -10000.0\n", - "_C123148: PE13_time_delay_min - t28_start + 10000.0*t_28_map_13 <= 10000.0\n", - "_C123149: PE13_time_delay_max - t29_end_ - 10000.0*t_29_map_13 >= -10000.0\n", - "_C123150: PE13_time_delay_min - t29_start + 10000.0*t_29_map_13 <= 10000.0\n", - "_C123151: PE13_time_delay_max - t30_end_ - 10000.0*t_30_map_13 >= -10000.0\n", - "_C123152: PE13_time_delay_min - t30_start + 10000.0*t_30_map_13 <= 10000.0\n", - "_C123153: PE13_time_delay_max - t31_end_ - 10000.0*t_31_map_13 >= -10000.0\n", - "_C123154: PE13_time_delay_min - t31_start + 10000.0*t_31_map_13 <= 10000.0\n", - "_C123155: PE13_time_delay_max - t32_end_ - 10000.0*t_32_map_13 >= -10000.0\n", - "_C123156: PE13_time_delay_min - t32_start + 10000.0*t_32_map_13 <= 10000.0\n", - "_C123157: PE13_time_delay_max - t33_end_ - 10000.0*t_33_map_13 >= -10000.0\n", - "_C123158: PE13_time_delay_min - t33_start + 10000.0*t_33_map_13 <= 10000.0\n", - "_C123159: PE13_time_delay_max - t34_end_ - 10000.0*t_34_map_13 >= -10000.0\n", - "_C123160: PE13_time_delay_min - t34_start + 10000.0*t_34_map_13 <= 10000.0\n", - "_C123161: PE13_time_delay_max - t35_end_ - 10000.0*t_35_map_13 >= -10000.0\n", - "_C123162: PE13_time_delay_min - t35_start + 10000.0*t_35_map_13 <= 10000.0\n", - "_C123163: PE13_time_delay_max - t36_end_ - 10000.0*t_36_map_13 >= -10000.0\n", - "_C123164: PE13_time_delay_min - t36_start + 10000.0*t_36_map_13 <= 10000.0\n", - "_C123165: PE13_time_delay_max - t37_end_ - 10000.0*t_37_map_13 >= -10000.0\n", - "_C123166: PE13_time_delay_min - t37_start + 10000.0*t_37_map_13 <= 10000.0\n", - "_C123167: PE13_time_delay_max - t38_end_ - 10000.0*t_38_map_13 >= -10000.0\n", - "_C123168: PE13_time_delay_min - t38_start + 10000.0*t_38_map_13 <= 10000.0\n", - "_C123169: PE13_time_delay_max - t39_end_ - 10000.0*t_39_map_13 >= -10000.0\n", - "_C123170: PE13_time_delay_min - t39_start + 10000.0*t_39_map_13 <= 10000.0\n", - "_C123171: PE13_time_delay_max - t40_end_ - 10000.0*t_40_map_13 >= -10000.0\n", - "_C123172: PE13_time_delay_min - t40_start + 10000.0*t_40_map_13 <= 10000.0\n", - "_C123173: PE13_time_delay_max - t41_end_ - 10000.0*t_41_map_13 >= -10000.0\n", - "_C123174: PE13_time_delay_min - t41_start + 10000.0*t_41_map_13 <= 10000.0\n", - "_C123175: PE13_time_delay_max - t42_end_ - 10000.0*t_42_map_13 >= -10000.0\n", - "_C123176: PE13_time_delay_min - t42_start + 10000.0*t_42_map_13 <= 10000.0\n", - "_C123177: PE13_time_delay_max - t43_end_ - 10000.0*t_43_map_13 >= -10000.0\n", - "_C123178: PE13_time_delay_min - t43_start + 10000.0*t_43_map_13 <= 10000.0\n", - "_C123179: PE13_time_delay_max - t44_end_ - 10000.0*t_44_map_13 >= -10000.0\n", - "_C123180: PE13_time_delay_min - t44_start + 10000.0*t_44_map_13 <= 10000.0\n", - "_C123181: PE13_time_delay_max - t45_end_ - 10000.0*t_45_map_13 >= -10000.0\n", - "_C123182: PE13_time_delay_min - t45_start + 10000.0*t_45_map_13 <= 10000.0\n", - "_C123183: PE13_time_delay_max - t46_end_ - 10000.0*t_46_map_13 >= -10000.0\n", - "_C123184: PE13_time_delay_min - t46_start + 10000.0*t_46_map_13 <= 10000.0\n", - "_C123185: PE13_time_delay_max - t47_end_ - 10000.0*t_47_map_13 >= -10000.0\n", - "_C123186: PE13_time_delay_min - t47_start + 10000.0*t_47_map_13 <= 10000.0\n", - "_C123187: PE13_time_delay_max - t48_end_ - 10000.0*t_48_map_13 >= -10000.0\n", - "_C123188: PE13_time_delay_min - t48_start + 10000.0*t_48_map_13 <= 10000.0\n", - "_C123189: PE13_time_delay_max - t49_end_ - 10000.0*t_49_map_13 >= -10000.0\n", - "_C123190: PE13_time_delay_min - t49_start + 10000.0*t_49_map_13 <= 10000.0\n", - "_C123191: PE13_time_delay_max - t50_end_ - 10000.0*t_50_map_13 >= -10000.0\n", - "_C123192: PE13_time_delay_min - t50_start + 10000.0*t_50_map_13 <= 10000.0\n", - "_C123193: PE13_time_delay_max - t51_end_ - 10000.0*t_51_map_13 >= -10000.0\n", - "_C123194: PE13_time_delay_min - t51_start + 10000.0*t_51_map_13 <= 10000.0\n", - "_C123195: PE13_time_delay_max - t52_end_ - 10000.0*t_52_map_13 >= -10000.0\n", - "_C123196: PE13_time_delay_min - t52_start + 10000.0*t_52_map_13 <= 10000.0\n", - "_C123197: PE13_time_delay_max - t53_end_ - 10000.0*t_53_map_13 >= -10000.0\n", - "_C123198: PE13_time_delay_min - t53_start + 10000.0*t_53_map_13 <= 10000.0\n", - "_C123199: PE13_time_delay_max - t54_end_ - 10000.0*t_54_map_13 >= -10000.0\n", - "_C123200: PE13_time_delay_min - t54_start + 10000.0*t_54_map_13 <= 10000.0\n", - "_C123201: PE13_time_delay_max - t55_end_ - 10000.0*t_55_map_13 >= -10000.0\n", - "_C123202: PE13_time_delay_min - t55_start + 10000.0*t_55_map_13 <= 10000.0\n", - "_C123203: PE13_time_delay_max - t56_end_ - 10000.0*t_56_map_13 >= -10000.0\n", - "_C123204: PE13_time_delay_min - t56_start + 10000.0*t_56_map_13 <= 10000.0\n", - "_C123205: PE13_time_delay_max - t57_end_ - 10000.0*t_57_map_13 >= -10000.0\n", - "_C123206: PE13_time_delay_min - t57_start + 10000.0*t_57_map_13 <= 10000.0\n", - "_C123207: PE13_time_delay_max - t58_end_ - 10000.0*t_58_map_13 >= -10000.0\n", - "_C123208: PE13_time_delay_min - t58_start + 10000.0*t_58_map_13 <= 10000.0\n", - "_C123209: PE13_time_delay_max - t59_end_ - 10000.0*t_59_map_13 >= -10000.0\n", - "_C123210: PE13_time_delay_min - t59_start + 10000.0*t_59_map_13 <= 10000.0\n", - "_C123211: PE13_time_delay_max - t60_end_ - 10000.0*t_60_map_13 >= -10000.0\n", - "_C123212: PE13_time_delay_min - t60_start + 10000.0*t_60_map_13 <= 10000.0\n", - "_C123213: PE13_time_delay_max - t61_end_ - 10000.0*t_61_map_13 >= -10000.0\n", - "_C123214: PE13_time_delay_min - t61_start + 10000.0*t_61_map_13 <= 10000.0\n", - "_C123215: PE13_time_delay_max - t62_end_ - 10000.0*t_62_map_13 >= -10000.0\n", - "_C123216: PE13_time_delay_min - t62_start + 10000.0*t_62_map_13 <= 10000.0\n", - "_C123217: PE13_time_delay_max - t63_end_ - 10000.0*t_63_map_13 >= -10000.0\n", - "_C123218: PE13_time_delay_min - t63_start + 10000.0*t_63_map_13 <= 10000.0\n", - "_C123219: PE13_time_delay_max - t64_end_ - 10000.0*t_64_map_13 >= -10000.0\n", - "_C123220: PE13_time_delay_min - t64_start + 10000.0*t_64_map_13 <= 10000.0\n", - "_C123221: PE13_time_delay_max - t65_end_ - 10000.0*t_65_map_13 >= -10000.0\n", - "_C123222: PE13_time_delay_min - t65_start + 10000.0*t_65_map_13 <= 10000.0\n", - "_C123223: PE13_time_delay_max - t66_end_ - 10000.0*t_66_map_13 >= -10000.0\n", - "_C123224: PE13_time_delay_min - t66_start + 10000.0*t_66_map_13 <= 10000.0\n", - "_C123225: PE13_time_delay_max - t67_end_ - 10000.0*t_67_map_13 >= -10000.0\n", - "_C123226: PE13_time_delay_min - t67_start + 10000.0*t_67_map_13 <= 10000.0\n", - "_C123227: PE13_time_delay_max - t68_end_ - 10000.0*t_68_map_13 >= -10000.0\n", - "_C123228: PE13_time_delay_min - t68_start + 10000.0*t_68_map_13 <= 10000.0\n", - "_C123229: PE13_time_delay_max - t69_end_ - 10000.0*t_69_map_13 >= -10000.0\n", - "_C123230: PE13_time_delay_min - t69_start + 10000.0*t_69_map_13 <= 10000.0\n", - "_C123231: -PE13_time_delay_max + PE13_time_delay_min + PE13_total_time_delay = 0\n", - "_C123232: -PE13_total_time_delay + max_router_delay >= 0\n", - "_C123233: PE13_total_time_delay <= 280\n", - "_C123234: -t0_end_ + t0_start - 10000.0*t_0_map_14 - t_send_0 + task_total_delay_router_router14_task0 >= -10000.0\n", - "_C123235: -10000.0*t_0_map_14 - t_mem_0 + task_total_memory_router_router14_task0 >= -10000.0\n", - "_C123236: -t1_end_ + t1_start - 10000.0*t_1_map_14 - t_send_1 + task_total_delay_router_router14_task1 >= -10000.0\n", - "_C123237: -10000.0*t_1_map_14 - t_mem_1 + task_total_memory_router_router14_task1 >= -10000.0\n", - "_C123238: -t2_end_ + t2_start - 10000.0*t_2_map_14 - t_send_2 + task_total_delay_router_router14_task2 >= -10000.0\n", - "_C123239: -10000.0*t_2_map_14 - t_mem_2 + task_total_memory_router_router14_task2 >= -10000.0\n", - "_C123240: -t3_end_ + t3_start - 10000.0*t_3_map_14 - t_send_3 + task_total_delay_router_router14_task3 >= -10000.0\n", - "_C123241: -10000.0*t_3_map_14 - t_mem_3 + task_total_memory_router_router14_task3 >= -10000.0\n", - "_C123242: -t4_end_ + t4_start - 10000.0*t_4_map_14 - t_send_4 + task_total_delay_router_router14_task4 >= -10000.0\n", - "_C123243: -10000.0*t_4_map_14 - t_mem_4 + task_total_memory_router_router14_task4 >= -10000.0\n", - "_C123244: -t5_end_ + t5_start - 10000.0*t_5_map_14 - t_send_5 + task_total_delay_router_router14_task5 >= -10000.0\n", - "_C123245: -10000.0*t_5_map_14 - t_mem_5 + task_total_memory_router_router14_task5 >= -10000.0\n", - "_C123246: -t6_end_ + t6_start - 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task_total_memory_router_router14_task10 - task_total_memory_router_router14_task11 - task_total_memory_router_router14_task12 - task_total_memory_router_router14_task13 - task_total_memory_router_router14_task14 - task_total_memory_router_router14_task15 - task_total_memory_router_router14_task16 - task_total_memory_router_router14_task17 - task_total_memory_router_router14_task18 - task_total_memory_router_router14_task19 - task_total_memory_router_router14_task2 - task_total_memory_router_router14_task20 - task_total_memory_router_router14_task21 - task_total_memory_router_router14_task22 - task_total_memory_router_router14_task23 - task_total_memory_router_router14_task24 - task_total_memory_router_router14_task25 - task_total_memory_router_router14_task26 - task_total_memory_router_router14_task27 - task_total_memory_router_router14_task28 - task_total_memory_router_router14_task29 - task_total_memory_router_router14_task3 - task_total_memory_router_router14_task30 - task_total_memory_router_router14_task31 - task_total_memory_router_router14_task32 - task_total_memory_router_router14_task33 - task_total_memory_router_router14_task34 - task_total_memory_router_router14_task35 - task_total_memory_router_router14_task36 - task_total_memory_router_router14_task37 - task_total_memory_router_router14_task38 - task_total_memory_router_router14_task39 - task_total_memory_router_router14_task4 - task_total_memory_router_router14_task40 - task_total_memory_router_router14_task41 - task_total_memory_router_router14_task42 - task_total_memory_router_router14_task43 - task_total_memory_router_router14_task44 - task_total_memory_router_router14_task45 - task_total_memory_router_router14_task46 - task_total_memory_router_router14_task47 - task_total_memory_router_router14_task48 - task_total_memory_router_router14_task49 - task_total_memory_router_router14_task5 - task_total_memory_router_router14_task50 - task_total_memory_router_router14_task51 - task_total_memory_router_router14_task52 - task_total_memory_router_router14_task53 - task_total_memory_router_router14_task54 - task_total_memory_router_router14_task55 - task_total_memory_router_router14_task56 - task_total_memory_router_router14_task57 - task_total_memory_router_router14_task58 - task_total_memory_router_router14_task59 - task_total_memory_router_router14_task6 - task_total_memory_router_router14_task60 - task_total_memory_router_router14_task61 - task_total_memory_router_router14_task62 - task_total_memory_router_router14_task63 - task_total_memory_router_router14_task64 - task_total_memory_router_router14_task65 - task_total_memory_router_router14_task66 - task_total_memory_router_router14_task67 - task_total_memory_router_router14_task68 - task_total_memory_router_router14_task69 - task_total_memory_router_router14_task7 - task_total_memory_router_router14_task8 - task_total_memory_router_router14_task9 >= -0.0\n", - "_C123375: PE14_total_delay - task_total_delay_router_router14_task0 - task_total_delay_router_router14_task1 - task_total_delay_router_router14_task10 - task_total_delay_router_router14_task11 - task_total_delay_router_router14_task12 - task_total_delay_router_router14_task13 - task_total_delay_router_router14_task14 - task_total_delay_router_router14_task15 - task_total_delay_router_router14_task16 - task_total_delay_router_router14_task17 - task_total_delay_router_router14_task18 - task_total_delay_router_router14_task19 - task_total_delay_router_router14_task2 - task_total_delay_router_router14_task20 - task_total_delay_router_router14_task21 - task_total_delay_router_router14_task22 - task_total_delay_router_router14_task23 - task_total_delay_router_router14_task24 - task_total_delay_router_router14_task25 - task_total_delay_router_router14_task26 - task_total_delay_router_router14_task27 - task_total_delay_router_router14_task28 - task_total_delay_router_router14_task29 - task_total_delay_router_router14_task3 - task_total_delay_router_router14_task30 - task_total_delay_router_router14_task31 - task_total_delay_router_router14_task32 - task_total_delay_router_router14_task33 - task_total_delay_router_router14_task34 - task_total_delay_router_router14_task35 - task_total_delay_router_router14_task36 - task_total_delay_router_router14_task37 - task_total_delay_router_router14_task38 - task_total_delay_router_router14_task39 - task_total_delay_router_router14_task4 - task_total_delay_router_router14_task40 - task_total_delay_router_router14_task41 - task_total_delay_router_router14_task42 - task_total_delay_router_router14_task43 - task_total_delay_router_router14_task44 - task_total_delay_router_router14_task45 - task_total_delay_router_router14_task46 - task_total_delay_router_router14_task47 - task_total_delay_router_router14_task48 - task_total_delay_router_router14_task49 - task_total_delay_router_router14_task5 - task_total_delay_router_router14_task50 - task_total_delay_router_router14_task51 - task_total_delay_router_router14_task52 - task_total_delay_router_router14_task53 - task_total_delay_router_router14_task54 - task_total_delay_router_router14_task55 - task_total_delay_router_router14_task56 - task_total_delay_router_router14_task57 - task_total_delay_router_router14_task58 - task_total_delay_router_router14_task59 - task_total_delay_router_router14_task6 - task_total_delay_router_router14_task60 - task_total_delay_router_router14_task61 - task_total_delay_router_router14_task62 - task_total_delay_router_router14_task63 - task_total_delay_router_router14_task64 - task_total_delay_router_router14_task65 - task_total_delay_router_router14_task66 - task_total_delay_router_router14_task67 - task_total_delay_router_router14_task68 - task_total_delay_router_router14_task69 - task_total_delay_router_router14_task7 - task_total_delay_router_router14_task8 - task_total_delay_router_router14_task9 >= -0.0\n", - "_C123376: PE14_total_memory - task_total_memory_router_router14_task0 - task_total_memory_router_router14_task1 - task_total_memory_router_router14_task10 - task_total_memory_router_router14_task11 - task_total_memory_router_router14_task12 - task_total_memory_router_router14_task13 - task_total_memory_router_router14_task14 - task_total_memory_router_router14_task15 - task_total_memory_router_router14_task16 - task_total_memory_router_router14_task17 - task_total_memory_router_router14_task18 - task_total_memory_router_router14_task19 - task_total_memory_router_router14_task2 - task_total_memory_router_router14_task20 - task_total_memory_router_router14_task21 - task_total_memory_router_router14_task22 - task_total_memory_router_router14_task23 - task_total_memory_router_router14_task24 - task_total_memory_router_router14_task25 - task_total_memory_router_router14_task26 - task_total_memory_router_router14_task27 - task_total_memory_router_router14_task28 - task_total_memory_router_router14_task29 - task_total_memory_router_router14_task3 - task_total_memory_router_router14_task30 - task_total_memory_router_router14_task31 - task_total_memory_router_router14_task32 - task_total_memory_router_router14_task33 - task_total_memory_router_router14_task34 - task_total_memory_router_router14_task35 - task_total_memory_router_router14_task36 - task_total_memory_router_router14_task37 - task_total_memory_router_router14_task38 - task_total_memory_router_router14_task39 - task_total_memory_router_router14_task4 - task_total_memory_router_router14_task40 - task_total_memory_router_router14_task41 - task_total_memory_router_router14_task42 - task_total_memory_router_router14_task43 - task_total_memory_router_router14_task44 - task_total_memory_router_router14_task45 - task_total_memory_router_router14_task46 - task_total_memory_router_router14_task47 - task_total_memory_router_router14_task48 - task_total_memory_router_router14_task49 - task_total_memory_router_router14_task5 - task_total_memory_router_router14_task50 - task_total_memory_router_router14_task51 - task_total_memory_router_router14_task52 - task_total_memory_router_router14_task53 - task_total_memory_router_router14_task54 - task_total_memory_router_router14_task55 - task_total_memory_router_router14_task56 - task_total_memory_router_router14_task57 - task_total_memory_router_router14_task58 - task_total_memory_router_router14_task59 - task_total_memory_router_router14_task6 - task_total_memory_router_router14_task60 - task_total_memory_router_router14_task61 - task_total_memory_router_router14_task62 - task_total_memory_router_router14_task63 - task_total_memory_router_router14_task64 - task_total_memory_router_router14_task65 - task_total_memory_router_router14_task66 - task_total_memory_router_router14_task67 - task_total_memory_router_router14_task68 - task_total_memory_router_router14_task69 - task_total_memory_router_router14_task7 - task_total_memory_router_router14_task8 - task_total_memory_router_router14_task9 >= -0.0\n", - "_C123377: -PE_mem_overflow14 + max_memory_overflow >= 0\n", - "_C123378: PE14_time_delay_max - t0_end_ - 10000.0*t_0_map_14 >= -10000.0\n", - "_C123379: PE14_time_delay_min - t0_start + 10000.0*t_0_map_14 <= 10000.0\n", - "_C123380: PE14_time_delay_max - t1_end_ - 10000.0*t_1_map_14 >= -10000.0\n", - "_C123381: PE14_time_delay_min - t1_start + 10000.0*t_1_map_14 <= 10000.0\n", - "_C123382: PE14_time_delay_max - t2_end_ - 10000.0*t_2_map_14 >= -10000.0\n", - "_C123383: PE14_time_delay_min - t2_start + 10000.0*t_2_map_14 <= 10000.0\n", - "_C123384: PE14_time_delay_max - t3_end_ - 10000.0*t_3_map_14 >= -10000.0\n", - "_C123385: PE14_time_delay_min - t3_start + 10000.0*t_3_map_14 <= 10000.0\n", - "_C123386: PE14_time_delay_max - t4_end_ - 10000.0*t_4_map_14 >= -10000.0\n", - "_C123387: PE14_time_delay_min - t4_start + 10000.0*t_4_map_14 <= 10000.0\n", - "_C123388: PE14_time_delay_max - t5_end_ - 10000.0*t_5_map_14 >= -10000.0\n", - "_C123389: PE14_time_delay_min - t5_start + 10000.0*t_5_map_14 <= 10000.0\n", - "_C123390: PE14_time_delay_max - t6_end_ - 10000.0*t_6_map_14 >= -10000.0\n", - "_C123391: PE14_time_delay_min - t6_start + 10000.0*t_6_map_14 <= 10000.0\n", - "_C123392: PE14_time_delay_max - t7_end_ - 10000.0*t_7_map_14 >= -10000.0\n", - "_C123393: PE14_time_delay_min - t7_start + 10000.0*t_7_map_14 <= 10000.0\n", - "_C123394: PE14_time_delay_max - t8_end_ - 10000.0*t_8_map_14 >= -10000.0\n", - "_C123395: PE14_time_delay_min - t8_start + 10000.0*t_8_map_14 <= 10000.0\n", - "_C123396: PE14_time_delay_max - t9_end_ - 10000.0*t_9_map_14 >= -10000.0\n", - "_C123397: PE14_time_delay_min - t9_start + 10000.0*t_9_map_14 <= 10000.0\n", - "_C123398: PE14_time_delay_max - t10_end_ - 10000.0*t_10_map_14 >= -10000.0\n", - "_C123399: PE14_time_delay_min - t10_start + 10000.0*t_10_map_14 <= 10000.0\n", - "_C123400: PE14_time_delay_max - t11_end_ - 10000.0*t_11_map_14 >= -10000.0\n", - "_C123401: PE14_time_delay_min - t11_start + 10000.0*t_11_map_14 <= 10000.0\n", - "_C123402: PE14_time_delay_max - t12_end_ - 10000.0*t_12_map_14 >= -10000.0\n", - "_C123403: PE14_time_delay_min - t12_start + 10000.0*t_12_map_14 <= 10000.0\n", - "_C123404: PE14_time_delay_max - t13_end_ - 10000.0*t_13_map_14 >= -10000.0\n", - "_C123405: PE14_time_delay_min - t13_start + 10000.0*t_13_map_14 <= 10000.0\n", - "_C123406: PE14_time_delay_max - t14_end_ - 10000.0*t_14_map_14 >= -10000.0\n", - "_C123407: PE14_time_delay_min - t14_start + 10000.0*t_14_map_14 <= 10000.0\n", - "_C123408: PE14_time_delay_max - t15_end_ - 10000.0*t_15_map_14 >= -10000.0\n", - "_C123409: PE14_time_delay_min - t15_start + 10000.0*t_15_map_14 <= 10000.0\n", - "_C123410: PE14_time_delay_max - t16_end_ - 10000.0*t_16_map_14 >= -10000.0\n", - "_C123411: PE14_time_delay_min - t16_start + 10000.0*t_16_map_14 <= 10000.0\n", - "_C123412: PE14_time_delay_max - t17_end_ - 10000.0*t_17_map_14 >= -10000.0\n", - "_C123413: PE14_time_delay_min - t17_start + 10000.0*t_17_map_14 <= 10000.0\n", - "_C123414: PE14_time_delay_max - t18_end_ - 10000.0*t_18_map_14 >= -10000.0\n", - "_C123415: PE14_time_delay_min - t18_start + 10000.0*t_18_map_14 <= 10000.0\n", - "_C123416: PE14_time_delay_max - t19_end_ - 10000.0*t_19_map_14 >= -10000.0\n", - "_C123417: PE14_time_delay_min - t19_start + 10000.0*t_19_map_14 <= 10000.0\n", - "_C123418: PE14_time_delay_max - t20_end_ - 10000.0*t_20_map_14 >= -10000.0\n", - "_C123419: PE14_time_delay_min - t20_start + 10000.0*t_20_map_14 <= 10000.0\n", - "_C123420: PE14_time_delay_max - t21_end_ - 10000.0*t_21_map_14 >= -10000.0\n", - "_C123421: PE14_time_delay_min - t21_start + 10000.0*t_21_map_14 <= 10000.0\n", - "_C123422: PE14_time_delay_max - t22_end_ - 10000.0*t_22_map_14 >= -10000.0\n", - "_C123423: PE14_time_delay_min - t22_start + 10000.0*t_22_map_14 <= 10000.0\n", - "_C123424: PE14_time_delay_max - t23_end_ - 10000.0*t_23_map_14 >= -10000.0\n", - "_C123425: PE14_time_delay_min - t23_start + 10000.0*t_23_map_14 <= 10000.0\n", - "_C123426: PE14_time_delay_max - t24_end_ - 10000.0*t_24_map_14 >= -10000.0\n", - "_C123427: PE14_time_delay_min - t24_start + 10000.0*t_24_map_14 <= 10000.0\n", - "_C123428: PE14_time_delay_max - t25_end_ - 10000.0*t_25_map_14 >= -10000.0\n", - "_C123429: PE14_time_delay_min - t25_start + 10000.0*t_25_map_14 <= 10000.0\n", - "_C123430: PE14_time_delay_max - t26_end_ - 10000.0*t_26_map_14 >= -10000.0\n", - "_C123431: PE14_time_delay_min - t26_start + 10000.0*t_26_map_14 <= 10000.0\n", - "_C123432: PE14_time_delay_max - t27_end_ - 10000.0*t_27_map_14 >= -10000.0\n", - "_C123433: PE14_time_delay_min - t27_start + 10000.0*t_27_map_14 <= 10000.0\n", - "_C123434: PE14_time_delay_max - t28_end_ - 10000.0*t_28_map_14 >= -10000.0\n", - "_C123435: PE14_time_delay_min - t28_start + 10000.0*t_28_map_14 <= 10000.0\n", - "_C123436: PE14_time_delay_max - t29_end_ - 10000.0*t_29_map_14 >= -10000.0\n", - "_C123437: PE14_time_delay_min - t29_start + 10000.0*t_29_map_14 <= 10000.0\n", - "_C123438: PE14_time_delay_max - t30_end_ - 10000.0*t_30_map_14 >= -10000.0\n", - "_C123439: PE14_time_delay_min - t30_start + 10000.0*t_30_map_14 <= 10000.0\n", - "_C123440: PE14_time_delay_max - t31_end_ - 10000.0*t_31_map_14 >= -10000.0\n", - "_C123441: PE14_time_delay_min - t31_start + 10000.0*t_31_map_14 <= 10000.0\n", - "_C123442: PE14_time_delay_max - t32_end_ - 10000.0*t_32_map_14 >= -10000.0\n", - "_C123443: PE14_time_delay_min - t32_start + 10000.0*t_32_map_14 <= 10000.0\n", - "_C123444: PE14_time_delay_max - t33_end_ - 10000.0*t_33_map_14 >= -10000.0\n", - "_C123445: PE14_time_delay_min - t33_start + 10000.0*t_33_map_14 <= 10000.0\n", - "_C123446: PE14_time_delay_max - t34_end_ - 10000.0*t_34_map_14 >= -10000.0\n", - "_C123447: PE14_time_delay_min - t34_start + 10000.0*t_34_map_14 <= 10000.0\n", - "_C123448: PE14_time_delay_max - t35_end_ - 10000.0*t_35_map_14 >= -10000.0\n", - "_C123449: PE14_time_delay_min - t35_start + 10000.0*t_35_map_14 <= 10000.0\n", - "_C123450: PE14_time_delay_max - t36_end_ - 10000.0*t_36_map_14 >= -10000.0\n", - "_C123451: PE14_time_delay_min - t36_start + 10000.0*t_36_map_14 <= 10000.0\n", - "_C123452: PE14_time_delay_max - t37_end_ - 10000.0*t_37_map_14 >= -10000.0\n", - "_C123453: PE14_time_delay_min - t37_start + 10000.0*t_37_map_14 <= 10000.0\n", - "_C123454: PE14_time_delay_max - t38_end_ - 10000.0*t_38_map_14 >= -10000.0\n", - "_C123455: PE14_time_delay_min - t38_start + 10000.0*t_38_map_14 <= 10000.0\n", - "_C123456: PE14_time_delay_max - t39_end_ - 10000.0*t_39_map_14 >= -10000.0\n", - "_C123457: PE14_time_delay_min - t39_start + 10000.0*t_39_map_14 <= 10000.0\n", - "_C123458: PE14_time_delay_max - t40_end_ - 10000.0*t_40_map_14 >= -10000.0\n", - "_C123459: PE14_time_delay_min - t40_start + 10000.0*t_40_map_14 <= 10000.0\n", - "_C123460: PE14_time_delay_max - t41_end_ - 10000.0*t_41_map_14 >= -10000.0\n", - "_C123461: PE14_time_delay_min - t41_start + 10000.0*t_41_map_14 <= 10000.0\n", - "_C123462: PE14_time_delay_max - t42_end_ - 10000.0*t_42_map_14 >= -10000.0\n", - "_C123463: PE14_time_delay_min - t42_start + 10000.0*t_42_map_14 <= 10000.0\n", - "_C123464: PE14_time_delay_max - t43_end_ - 10000.0*t_43_map_14 >= -10000.0\n", - "_C123465: PE14_time_delay_min - t43_start + 10000.0*t_43_map_14 <= 10000.0\n", - "_C123466: PE14_time_delay_max - t44_end_ - 10000.0*t_44_map_14 >= -10000.0\n", - "_C123467: PE14_time_delay_min - t44_start + 10000.0*t_44_map_14 <= 10000.0\n", - "_C123468: PE14_time_delay_max - t45_end_ - 10000.0*t_45_map_14 >= -10000.0\n", - "_C123469: PE14_time_delay_min - t45_start + 10000.0*t_45_map_14 <= 10000.0\n", - "_C123470: PE14_time_delay_max - t46_end_ - 10000.0*t_46_map_14 >= -10000.0\n", - "_C123471: PE14_time_delay_min - t46_start + 10000.0*t_46_map_14 <= 10000.0\n", - "_C123472: PE14_time_delay_max - t47_end_ - 10000.0*t_47_map_14 >= -10000.0\n", - "_C123473: PE14_time_delay_min - t47_start + 10000.0*t_47_map_14 <= 10000.0\n", - "_C123474: PE14_time_delay_max - t48_end_ - 10000.0*t_48_map_14 >= -10000.0\n", - "_C123475: PE14_time_delay_min - t48_start + 10000.0*t_48_map_14 <= 10000.0\n", - "_C123476: PE14_time_delay_max - t49_end_ - 10000.0*t_49_map_14 >= -10000.0\n", - "_C123477: PE14_time_delay_min - t49_start + 10000.0*t_49_map_14 <= 10000.0\n", - "_C123478: PE14_time_delay_max - t50_end_ - 10000.0*t_50_map_14 >= -10000.0\n", - "_C123479: PE14_time_delay_min - t50_start + 10000.0*t_50_map_14 <= 10000.0\n", - "_C123480: PE14_time_delay_max - t51_end_ - 10000.0*t_51_map_14 >= -10000.0\n", - "_C123481: PE14_time_delay_min - t51_start + 10000.0*t_51_map_14 <= 10000.0\n", - "_C123482: PE14_time_delay_max - t52_end_ - 10000.0*t_52_map_14 >= -10000.0\n", - "_C123483: PE14_time_delay_min - t52_start + 10000.0*t_52_map_14 <= 10000.0\n", - "_C123484: PE14_time_delay_max - t53_end_ - 10000.0*t_53_map_14 >= -10000.0\n", - "_C123485: PE14_time_delay_min - t53_start + 10000.0*t_53_map_14 <= 10000.0\n", - "_C123486: PE14_time_delay_max - t54_end_ - 10000.0*t_54_map_14 >= -10000.0\n", - "_C123487: PE14_time_delay_min - t54_start + 10000.0*t_54_map_14 <= 10000.0\n", - "_C123488: PE14_time_delay_max - t55_end_ - 10000.0*t_55_map_14 >= -10000.0\n", - "_C123489: PE14_time_delay_min - t55_start + 10000.0*t_55_map_14 <= 10000.0\n", - "_C123490: PE14_time_delay_max - t56_end_ - 10000.0*t_56_map_14 >= -10000.0\n", - "_C123491: PE14_time_delay_min - t56_start + 10000.0*t_56_map_14 <= 10000.0\n", - "_C123492: PE14_time_delay_max - t57_end_ - 10000.0*t_57_map_14 >= -10000.0\n", - "_C123493: PE14_time_delay_min - t57_start + 10000.0*t_57_map_14 <= 10000.0\n", - "_C123494: PE14_time_delay_max - t58_end_ - 10000.0*t_58_map_14 >= -10000.0\n", - "_C123495: PE14_time_delay_min - t58_start + 10000.0*t_58_map_14 <= 10000.0\n", - "_C123496: PE14_time_delay_max - t59_end_ - 10000.0*t_59_map_14 >= -10000.0\n", - "_C123497: PE14_time_delay_min - t59_start + 10000.0*t_59_map_14 <= 10000.0\n", - "_C123498: PE14_time_delay_max - t60_end_ - 10000.0*t_60_map_14 >= -10000.0\n", - "_C123499: PE14_time_delay_min - t60_start + 10000.0*t_60_map_14 <= 10000.0\n", - "_C123500: PE14_time_delay_max - t61_end_ - 10000.0*t_61_map_14 >= -10000.0\n", - "_C123501: PE14_time_delay_min - t61_start + 10000.0*t_61_map_14 <= 10000.0\n", - "_C123502: PE14_time_delay_max - t62_end_ - 10000.0*t_62_map_14 >= -10000.0\n", - "_C123503: PE14_time_delay_min - t62_start + 10000.0*t_62_map_14 <= 10000.0\n", - "_C123504: PE14_time_delay_max - t63_end_ - 10000.0*t_63_map_14 >= -10000.0\n", - "_C123505: PE14_time_delay_min - t63_start + 10000.0*t_63_map_14 <= 10000.0\n", - "_C123506: PE14_time_delay_max - t64_end_ - 10000.0*t_64_map_14 >= -10000.0\n", - "_C123507: PE14_time_delay_min - t64_start + 10000.0*t_64_map_14 <= 10000.0\n", - "_C123508: PE14_time_delay_max - t65_end_ - 10000.0*t_65_map_14 >= -10000.0\n", - "_C123509: PE14_time_delay_min - t65_start + 10000.0*t_65_map_14 <= 10000.0\n", - "_C123510: PE14_time_delay_max - t66_end_ - 10000.0*t_66_map_14 >= -10000.0\n", - "_C123511: PE14_time_delay_min - t66_start + 10000.0*t_66_map_14 <= 10000.0\n", - "_C123512: PE14_time_delay_max - t67_end_ - 10000.0*t_67_map_14 >= -10000.0\n", - "_C123513: PE14_time_delay_min - t67_start + 10000.0*t_67_map_14 <= 10000.0\n", - "_C123514: PE14_time_delay_max - t68_end_ - 10000.0*t_68_map_14 >= -10000.0\n", - "_C123515: PE14_time_delay_min - t68_start + 10000.0*t_68_map_14 <= 10000.0\n", - "_C123516: PE14_time_delay_max - t69_end_ - 10000.0*t_69_map_14 >= -10000.0\n", - "_C123517: PE14_time_delay_min - t69_start + 10000.0*t_69_map_14 <= 10000.0\n", - "_C123518: -PE14_time_delay_max + PE14_time_delay_min + PE14_total_time_delay = 0\n", - "_C123519: -PE14_total_time_delay + max_router_delay >= 0\n", - "_C123520: PE14_total_time_delay <= 280\n", - "_C123521: -t0_end_ + 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task_total_delay_router_router15_task13 >= -10000.0\n", - "_C123548: -10000.0*t_13_map_15 - t_mem_13 + task_total_memory_router_router15_task13 >= -10000.0\n", - "_C123549: -t14_end_ + t14_start - 10000.0*t_14_map_15 - t_send_14 + task_total_delay_router_router15_task14 >= -10000.0\n", - "_C123550: -10000.0*t_14_map_15 - t_mem_14 + task_total_memory_router_router15_task14 >= -10000.0\n", - "_C123551: -t15_end_ + t15_start - 10000.0*t_15_map_15 - t_send_15 + task_total_delay_router_router15_task15 >= -10000.0\n", - "_C123552: -10000.0*t_15_map_15 - t_mem_15 + task_total_memory_router_router15_task15 >= -10000.0\n", - "_C123553: -t16_end_ + t16_start - 10000.0*t_16_map_15 - t_send_16 + task_total_delay_router_router15_task16 >= -10000.0\n", - "_C123554: -10000.0*t_16_map_15 - t_mem_16 + task_total_memory_router_router15_task16 >= -10000.0\n", - "_C123555: -t17_end_ + t17_start - 10000.0*t_17_map_15 - t_send_17 + task_total_delay_router_router15_task17 >= -10000.0\n", - "_C123556: 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task_total_memory_router_router15_task24 - task_total_memory_router_router15_task25 - task_total_memory_router_router15_task26 - task_total_memory_router_router15_task27 - task_total_memory_router_router15_task28 - task_total_memory_router_router15_task29 - task_total_memory_router_router15_task3 - task_total_memory_router_router15_task30 - task_total_memory_router_router15_task31 - task_total_memory_router_router15_task32 - task_total_memory_router_router15_task33 - task_total_memory_router_router15_task34 - task_total_memory_router_router15_task35 - task_total_memory_router_router15_task36 - task_total_memory_router_router15_task37 - task_total_memory_router_router15_task38 - task_total_memory_router_router15_task39 - task_total_memory_router_router15_task4 - task_total_memory_router_router15_task40 - task_total_memory_router_router15_task41 - task_total_memory_router_router15_task42 - task_total_memory_router_router15_task43 - task_total_memory_router_router15_task44 - task_total_memory_router_router15_task45 - task_total_memory_router_router15_task46 - task_total_memory_router_router15_task47 - task_total_memory_router_router15_task48 - task_total_memory_router_router15_task49 - task_total_memory_router_router15_task5 - task_total_memory_router_router15_task50 - task_total_memory_router_router15_task51 - task_total_memory_router_router15_task52 - task_total_memory_router_router15_task53 - task_total_memory_router_router15_task54 - task_total_memory_router_router15_task55 - task_total_memory_router_router15_task56 - task_total_memory_router_router15_task57 - task_total_memory_router_router15_task58 - task_total_memory_router_router15_task59 - task_total_memory_router_router15_task6 - task_total_memory_router_router15_task60 - task_total_memory_router_router15_task61 - task_total_memory_router_router15_task62 - task_total_memory_router_router15_task63 - task_total_memory_router_router15_task64 - task_total_memory_router_router15_task65 - task_total_memory_router_router15_task66 - task_total_memory_router_router15_task67 - task_total_memory_router_router15_task68 - task_total_memory_router_router15_task69 - task_total_memory_router_router15_task7 - task_total_memory_router_router15_task8 - task_total_memory_router_router15_task9 >= -0.0\n", - "_C123662: PE15_total_delay - task_total_delay_router_router15_task0 - task_total_delay_router_router15_task1 - task_total_delay_router_router15_task10 - task_total_delay_router_router15_task11 - task_total_delay_router_router15_task12 - task_total_delay_router_router15_task13 - task_total_delay_router_router15_task14 - task_total_delay_router_router15_task15 - task_total_delay_router_router15_task16 - task_total_delay_router_router15_task17 - task_total_delay_router_router15_task18 - task_total_delay_router_router15_task19 - task_total_delay_router_router15_task2 - task_total_delay_router_router15_task20 - task_total_delay_router_router15_task21 - task_total_delay_router_router15_task22 - task_total_delay_router_router15_task23 - task_total_delay_router_router15_task24 - task_total_delay_router_router15_task25 - task_total_delay_router_router15_task26 - task_total_delay_router_router15_task27 - task_total_delay_router_router15_task28 - task_total_delay_router_router15_task29 - task_total_delay_router_router15_task3 - task_total_delay_router_router15_task30 - task_total_delay_router_router15_task31 - task_total_delay_router_router15_task32 - task_total_delay_router_router15_task33 - task_total_delay_router_router15_task34 - task_total_delay_router_router15_task35 - task_total_delay_router_router15_task36 - task_total_delay_router_router15_task37 - task_total_delay_router_router15_task38 - task_total_delay_router_router15_task39 - task_total_delay_router_router15_task4 - task_total_delay_router_router15_task40 - task_total_delay_router_router15_task41 - task_total_delay_router_router15_task42 - task_total_delay_router_router15_task43 - task_total_delay_router_router15_task44 - task_total_delay_router_router15_task45 - task_total_delay_router_router15_task46 - task_total_delay_router_router15_task47 - task_total_delay_router_router15_task48 - task_total_delay_router_router15_task49 - task_total_delay_router_router15_task5 - task_total_delay_router_router15_task50 - task_total_delay_router_router15_task51 - task_total_delay_router_router15_task52 - task_total_delay_router_router15_task53 - task_total_delay_router_router15_task54 - task_total_delay_router_router15_task55 - task_total_delay_router_router15_task56 - task_total_delay_router_router15_task57 - task_total_delay_router_router15_task58 - task_total_delay_router_router15_task59 - task_total_delay_router_router15_task6 - task_total_delay_router_router15_task60 - task_total_delay_router_router15_task61 - task_total_delay_router_router15_task62 - task_total_delay_router_router15_task63 - task_total_delay_router_router15_task64 - task_total_delay_router_router15_task65 - task_total_delay_router_router15_task66 - task_total_delay_router_router15_task67 - task_total_delay_router_router15_task68 - task_total_delay_router_router15_task69 - task_total_delay_router_router15_task7 - task_total_delay_router_router15_task8 - task_total_delay_router_router15_task9 >= -0.0\n", - "_C123663: PE15_total_memory - task_total_memory_router_router15_task0 - task_total_memory_router_router15_task1 - task_total_memory_router_router15_task10 - task_total_memory_router_router15_task11 - task_total_memory_router_router15_task12 - task_total_memory_router_router15_task13 - task_total_memory_router_router15_task14 - task_total_memory_router_router15_task15 - task_total_memory_router_router15_task16 - task_total_memory_router_router15_task17 - task_total_memory_router_router15_task18 - task_total_memory_router_router15_task19 - task_total_memory_router_router15_task2 - task_total_memory_router_router15_task20 - task_total_memory_router_router15_task21 - task_total_memory_router_router15_task22 - task_total_memory_router_router15_task23 - task_total_memory_router_router15_task24 - task_total_memory_router_router15_task25 - task_total_memory_router_router15_task26 - task_total_memory_router_router15_task27 - task_total_memory_router_router15_task28 - task_total_memory_router_router15_task29 - task_total_memory_router_router15_task3 - task_total_memory_router_router15_task30 - task_total_memory_router_router15_task31 - task_total_memory_router_router15_task32 - task_total_memory_router_router15_task33 - task_total_memory_router_router15_task34 - task_total_memory_router_router15_task35 - task_total_memory_router_router15_task36 - task_total_memory_router_router15_task37 - task_total_memory_router_router15_task38 - task_total_memory_router_router15_task39 - task_total_memory_router_router15_task4 - task_total_memory_router_router15_task40 - task_total_memory_router_router15_task41 - task_total_memory_router_router15_task42 - task_total_memory_router_router15_task43 - task_total_memory_router_router15_task44 - task_total_memory_router_router15_task45 - task_total_memory_router_router15_task46 - task_total_memory_router_router15_task47 - task_total_memory_router_router15_task48 - task_total_memory_router_router15_task49 - task_total_memory_router_router15_task5 - task_total_memory_router_router15_task50 - task_total_memory_router_router15_task51 - task_total_memory_router_router15_task52 - task_total_memory_router_router15_task53 - task_total_memory_router_router15_task54 - task_total_memory_router_router15_task55 - task_total_memory_router_router15_task56 - task_total_memory_router_router15_task57 - task_total_memory_router_router15_task58 - task_total_memory_router_router15_task59 - task_total_memory_router_router15_task6 - task_total_memory_router_router15_task60 - task_total_memory_router_router15_task61 - task_total_memory_router_router15_task62 - task_total_memory_router_router15_task63 - task_total_memory_router_router15_task64 - task_total_memory_router_router15_task65 - task_total_memory_router_router15_task66 - task_total_memory_router_router15_task67 - task_total_memory_router_router15_task68 - task_total_memory_router_router15_task69 - task_total_memory_router_router15_task7 - task_total_memory_router_router15_task8 - task_total_memory_router_router15_task9 >= -0.0\n", - "_C123664: -PE_mem_overflow15 + max_memory_overflow >= 0\n", - "_C123665: PE15_time_delay_max - t0_end_ - 10000.0*t_0_map_15 >= -10000.0\n", - "_C123666: PE15_time_delay_min - t0_start + 10000.0*t_0_map_15 <= 10000.0\n", - "_C123667: PE15_time_delay_max - t1_end_ - 10000.0*t_1_map_15 >= -10000.0\n", - "_C123668: PE15_time_delay_min - t1_start + 10000.0*t_1_map_15 <= 10000.0\n", - "_C123669: PE15_time_delay_max - t2_end_ - 10000.0*t_2_map_15 >= -10000.0\n", - "_C123670: PE15_time_delay_min - t2_start + 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PE15_time_delay_max - t33_end_ - 10000.0*t_33_map_15 >= -10000.0\n", - "_C123732: PE15_time_delay_min - t33_start + 10000.0*t_33_map_15 <= 10000.0\n", - "_C123733: PE15_time_delay_max - t34_end_ - 10000.0*t_34_map_15 >= -10000.0\n", - "_C123734: PE15_time_delay_min - t34_start + 10000.0*t_34_map_15 <= 10000.0\n", - "_C123735: PE15_time_delay_max - t35_end_ - 10000.0*t_35_map_15 >= -10000.0\n", - "_C123736: PE15_time_delay_min - t35_start + 10000.0*t_35_map_15 <= 10000.0\n", - "_C123737: PE15_time_delay_max - t36_end_ - 10000.0*t_36_map_15 >= -10000.0\n", - "_C123738: PE15_time_delay_min - t36_start + 10000.0*t_36_map_15 <= 10000.0\n", - "_C123739: PE15_time_delay_max - t37_end_ - 10000.0*t_37_map_15 >= -10000.0\n", - "_C123740: PE15_time_delay_min - t37_start + 10000.0*t_37_map_15 <= 10000.0\n", - "_C123741: PE15_time_delay_max - t38_end_ - 10000.0*t_38_map_15 >= -10000.0\n", - "_C123742: PE15_time_delay_min - t38_start + 10000.0*t_38_map_15 <= 10000.0\n", - "_C123743: PE15_time_delay_max - t39_end_ - 10000.0*t_39_map_15 >= -10000.0\n", - "_C123744: PE15_time_delay_min - t39_start + 10000.0*t_39_map_15 <= 10000.0\n", - "_C123745: PE15_time_delay_max - t40_end_ - 10000.0*t_40_map_15 >= -10000.0\n", - "_C123746: PE15_time_delay_min - t40_start + 10000.0*t_40_map_15 <= 10000.0\n", - "_C123747: PE15_time_delay_max - t41_end_ - 10000.0*t_41_map_15 >= -10000.0\n", - "_C123748: PE15_time_delay_min - t41_start + 10000.0*t_41_map_15 <= 10000.0\n", - "_C123749: PE15_time_delay_max - t42_end_ - 10000.0*t_42_map_15 >= -10000.0\n", - "_C123750: PE15_time_delay_min - t42_start + 10000.0*t_42_map_15 <= 10000.0\n", - "_C123751: PE15_time_delay_max - t43_end_ - 10000.0*t_43_map_15 >= -10000.0\n", - "_C123752: PE15_time_delay_min - t43_start + 10000.0*t_43_map_15 <= 10000.0\n", - "_C123753: PE15_time_delay_max - t44_end_ - 10000.0*t_44_map_15 >= -10000.0\n", - "_C123754: PE15_time_delay_min - t44_start + 10000.0*t_44_map_15 <= 10000.0\n", - "_C123755: PE15_time_delay_max - t45_end_ - 10000.0*t_45_map_15 >= -10000.0\n", - "_C123756: PE15_time_delay_min - t45_start + 10000.0*t_45_map_15 <= 10000.0\n", - "_C123757: PE15_time_delay_max - t46_end_ - 10000.0*t_46_map_15 >= -10000.0\n", - "_C123758: PE15_time_delay_min - t46_start + 10000.0*t_46_map_15 <= 10000.0\n", - "_C123759: PE15_time_delay_max - t47_end_ - 10000.0*t_47_map_15 >= -10000.0\n", - "_C123760: PE15_time_delay_min - t47_start + 10000.0*t_47_map_15 <= 10000.0\n", - "_C123761: PE15_time_delay_max - t48_end_ - 10000.0*t_48_map_15 >= -10000.0\n", - "_C123762: PE15_time_delay_min - t48_start + 10000.0*t_48_map_15 <= 10000.0\n", - "_C123763: PE15_time_delay_max - t49_end_ - 10000.0*t_49_map_15 >= -10000.0\n", - "_C123764: PE15_time_delay_min - t49_start + 10000.0*t_49_map_15 <= 10000.0\n", - "_C123765: PE15_time_delay_max - t50_end_ - 10000.0*t_50_map_15 >= -10000.0\n", - "_C123766: PE15_time_delay_min - t50_start + 10000.0*t_50_map_15 <= 10000.0\n", - "_C123767: PE15_time_delay_max - t51_end_ - 10000.0*t_51_map_15 >= -10000.0\n", - "_C123768: PE15_time_delay_min - t51_start + 10000.0*t_51_map_15 <= 10000.0\n", - "_C123769: PE15_time_delay_max - t52_end_ - 10000.0*t_52_map_15 >= -10000.0\n", - "_C123770: PE15_time_delay_min - t52_start + 10000.0*t_52_map_15 <= 10000.0\n", - "_C123771: PE15_time_delay_max - t53_end_ - 10000.0*t_53_map_15 >= -10000.0\n", - "_C123772: PE15_time_delay_min - t53_start + 10000.0*t_53_map_15 <= 10000.0\n", - "_C123773: PE15_time_delay_max - t54_end_ - 10000.0*t_54_map_15 >= -10000.0\n", - "_C123774: PE15_time_delay_min - t54_start + 10000.0*t_54_map_15 <= 10000.0\n", - "_C123775: PE15_time_delay_max - t55_end_ - 10000.0*t_55_map_15 >= -10000.0\n", - "_C123776: PE15_time_delay_min - t55_start + 10000.0*t_55_map_15 <= 10000.0\n", - "_C123777: PE15_time_delay_max - t56_end_ - 10000.0*t_56_map_15 >= -10000.0\n", - "_C123778: PE15_time_delay_min - t56_start + 10000.0*t_56_map_15 <= 10000.0\n", - "_C123779: PE15_time_delay_max - t57_end_ - 10000.0*t_57_map_15 >= -10000.0\n", - "_C123780: PE15_time_delay_min - t57_start + 10000.0*t_57_map_15 <= 10000.0\n", - "_C123781: PE15_time_delay_max - t58_end_ - 10000.0*t_58_map_15 >= -10000.0\n", - "_C123782: PE15_time_delay_min - t58_start + 10000.0*t_58_map_15 <= 10000.0\n", - "_C123783: PE15_time_delay_max - t59_end_ - 10000.0*t_59_map_15 >= -10000.0\n", - "_C123784: PE15_time_delay_min - t59_start + 10000.0*t_59_map_15 <= 10000.0\n", - "_C123785: PE15_time_delay_max - t60_end_ - 10000.0*t_60_map_15 >= -10000.0\n", - "_C123786: PE15_time_delay_min - t60_start + 10000.0*t_60_map_15 <= 10000.0\n", - "_C123787: PE15_time_delay_max - t61_end_ - 10000.0*t_61_map_15 >= -10000.0\n", - "_C123788: PE15_time_delay_min - t61_start + 10000.0*t_61_map_15 <= 10000.0\n", - "_C123789: PE15_time_delay_max - t62_end_ - 10000.0*t_62_map_15 >= -10000.0\n", - "_C123790: PE15_time_delay_min - t62_start + 10000.0*t_62_map_15 <= 10000.0\n", - "_C123791: PE15_time_delay_max - t63_end_ - 10000.0*t_63_map_15 >= -10000.0\n", - "_C123792: PE15_time_delay_min - t63_start + 10000.0*t_63_map_15 <= 10000.0\n", - "_C123793: PE15_time_delay_max - t64_end_ - 10000.0*t_64_map_15 >= -10000.0\n", - "_C123794: PE15_time_delay_min - t64_start + 10000.0*t_64_map_15 <= 10000.0\n", - "_C123795: PE15_time_delay_max - t65_end_ - 10000.0*t_65_map_15 >= -10000.0\n", - "_C123796: PE15_time_delay_min - t65_start + 10000.0*t_65_map_15 <= 10000.0\n", - "_C123797: PE15_time_delay_max - t66_end_ - 10000.0*t_66_map_15 >= -10000.0\n", - "_C123798: PE15_time_delay_min - t66_start + 10000.0*t_66_map_15 <= 10000.0\n", - "_C123799: PE15_time_delay_max - t67_end_ - 10000.0*t_67_map_15 >= -10000.0\n", - "_C123800: PE15_time_delay_min - t67_start + 10000.0*t_67_map_15 <= 10000.0\n", - "_C123801: PE15_time_delay_max - t68_end_ - 10000.0*t_68_map_15 >= -10000.0\n", - "_C123802: PE15_time_delay_min - t68_start + 10000.0*t_68_map_15 <= 10000.0\n", - "_C123803: PE15_time_delay_max - t69_end_ - 10000.0*t_69_map_15 >= -10000.0\n", - "_C123804: PE15_time_delay_min - t69_start + 10000.0*t_69_map_15 <= 10000.0\n", - "_C123805: -PE15_time_delay_max + PE15_time_delay_min + PE15_total_time_delay = 0\n", - "_C123806: -PE15_total_time_delay + max_router_delay >= 0\n", - "_C123807: PE15_total_time_delay <= 280\n", - "Debug: Found max_router_delay variable with value 280.0\n", - "Debug: Found mapping variable t_0_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '0', 'map', '12']\n", - "Debug: Mapping task 0 to PE 12\n", - "Debug: reverse_mapping[12] now [0]\n", - "Debug: Found mapping variable t_10_map_2 with value 1.0\n", - "Debug: Split parts: ['t', '10', 'map', '2']\n", - "Debug: Mapping task 10 to PE 2\n", - "Debug: reverse_mapping[2] now [10]\n", - "Debug: Found mapping variable t_11_map_11 with value 1.0\n", - "Debug: Split parts: ['t', '11', 'map', '11']\n", - "Debug: Mapping task 11 to PE 11\n", - "Debug: reverse_mapping[11] now [11]\n", - "Debug: Found mapping variable t_12_map_11 with value 1.0\n", - "Debug: Split parts: ['t', '12', 'map', '11']\n", - "Debug: Mapping task 12 to PE 11\n", - "Debug: reverse_mapping[11] now [11, 12]\n", - "Debug: Found mapping variable t_13_map_11 with value 1.0\n", - "Debug: Split parts: ['t', '13', 'map', '11']\n", - "Debug: Mapping task 13 to PE 11\n", - "Debug: reverse_mapping[11] now [11, 12, 13]\n", - "Debug: Found mapping variable t_14_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '14', 'map', '13']\n", - "Debug: Mapping task 14 to PE 13\n", - "Debug: reverse_mapping[13] now [14]\n", - "Debug: Found mapping variable t_15_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '15', 'map', '13']\n", - "Debug: Mapping task 15 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15]\n", - "Debug: Found mapping variable t_16_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '16', 'map', '13']\n", - "Debug: Mapping task 16 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16]\n", - "Debug: Found mapping variable t_17_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '17', 'map', '13']\n", - "Debug: Mapping task 17 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17]\n", - "Debug: Found mapping variable t_18_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '18', 'map', '13']\n", - "Debug: Mapping task 18 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18]\n", - "Debug: Found mapping variable t_19_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '19', 'map', '13']\n", - "Debug: Mapping task 19 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19]\n", - "Debug: Found mapping variable t_1_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '1', 'map', '12']\n", - "Debug: Mapping task 1 to PE 12\n", - "Debug: reverse_mapping[12] now [0, 1]\n", - "Debug: Found mapping variable t_20_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '20', 'map', '13']\n", - "Debug: Mapping task 20 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19, 20]\n", - "Debug: Found mapping variable t_21_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '21', 'map', '13']\n", - "Debug: Mapping task 21 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19, 20, 21]\n", - "Debug: Found mapping variable t_22_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '22', 'map', '13']\n", - "Debug: Mapping task 22 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19, 20, 21, 22]\n", - "Debug: Found mapping variable t_23_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '23', 'map', '13']\n", - "Debug: Mapping task 23 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19, 20, 21, 22, 23]\n", - "Debug: Found mapping variable t_24_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '24', 'map', '13']\n", - "Debug: Mapping task 24 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]\n", - "Debug: Found mapping variable t_25_map_13 with value 1.0\n", - "Debug: Split parts: ['t', '25', 'map', '13']\n", - "Debug: Mapping task 25 to PE 13\n", - "Debug: reverse_mapping[13] now [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]\n", - "Debug: Found mapping variable t_26_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '26', 'map', '5']\n", - "Debug: Mapping task 26 to PE 5\n", - "Debug: reverse_mapping[5] now [26]\n", - "Debug: Found mapping variable t_27_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '27', 'map', '5']\n", - "Debug: Mapping task 27 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27]\n", - "Debug: Found mapping variable t_28_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '28', 'map', '5']\n", - "Debug: Mapping task 28 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28]\n", - "Debug: Found mapping variable t_29_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '29', 'map', '5']\n", - "Debug: Mapping task 29 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29]\n", - "Debug: Found mapping variable t_2_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '2', 'map', '12']\n", - "Debug: Mapping task 2 to PE 12\n", - "Debug: reverse_mapping[12] now [0, 1, 2]\n", - "Debug: Found mapping variable t_30_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '30', 'map', '5']\n", - "Debug: Mapping task 30 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30]\n", - "Debug: Found mapping variable t_31_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '31', 'map', '5']\n", - "Debug: Mapping task 31 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31]\n", - "Debug: Found mapping variable t_32_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '32', 'map', '5']\n", - "Debug: Mapping task 32 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32]\n", - "Debug: Found mapping variable t_33_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '33', 'map', '5']\n", - "Debug: Mapping task 33 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33]\n", - "Debug: Found mapping variable t_34_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '34', 'map', '5']\n", - "Debug: Mapping task 34 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34]\n", - "Debug: Found mapping variable t_35_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '35', 'map', '5']\n", - "Debug: Mapping task 35 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35]\n", - "Debug: Found mapping variable t_36_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '36', 'map', '5']\n", - "Debug: Mapping task 36 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]\n", - "Debug: Found mapping variable t_37_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '37', 'map', '5']\n", - "Debug: Mapping task 37 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37]\n", - "Debug: Found mapping variable t_38_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '38', 'map', '5']\n", - "Debug: Mapping task 38 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]\n", - "Debug: Found mapping variable t_39_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '39', 'map', '5']\n", - "Debug: Mapping task 39 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]\n", - "Debug: Found mapping variable t_3_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '3', 'map', '12']\n", - "Debug: Mapping task 3 to PE 12\n", - "Debug: reverse_mapping[12] now [0, 1, 2, 3]\n", - "Debug: Found mapping variable t_40_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '40', 'map', '5']\n", - "Debug: Mapping task 40 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40]\n", - "Debug: Found mapping variable t_41_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '41', 'map', '5']\n", - "Debug: Mapping task 41 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41]\n", - "Debug: Found mapping variable t_42_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '42', 'map', '5']\n", - "Debug: Mapping task 42 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]\n", - "Debug: Found mapping variable t_43_map_5 with value 1.0\n", - "Debug: Split parts: ['t', '43', 'map', '5']\n", - "Debug: Mapping task 43 to PE 5\n", - "Debug: reverse_mapping[5] now [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]\n", - "Debug: Found mapping variable t_44_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '44', 'map', '10']\n", - "Debug: Mapping task 44 to PE 10\n", - "Debug: reverse_mapping[10] now [44]\n", - "Debug: Found mapping variable t_45_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '45', 'map', '10']\n", - "Debug: Mapping task 45 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45]\n", - "Debug: Found mapping variable t_46_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '46', 'map', '10']\n", - "Debug: Mapping task 46 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46]\n", - "Debug: Found mapping variable t_47_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '47', 'map', '10']\n", - "Debug: Mapping task 47 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46, 47]\n", - "Debug: Found mapping variable t_48_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '48', 'map', '10']\n", - "Debug: Mapping task 48 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46, 47, 48]\n", - "Debug: Found mapping variable t_49_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '49', 'map', '10']\n", - "Debug: Mapping task 49 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46, 47, 48, 49]\n", - "Debug: Found mapping variable t_4_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '4', 'map', '12']\n", - "Debug: Mapping task 4 to PE 12\n", - "Debug: reverse_mapping[12] now [0, 1, 2, 3, 4]\n", - "Debug: Found mapping variable t_50_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '50', 'map', '10']\n", - "Debug: Mapping task 50 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46, 47, 48, 49, 50]\n", - "Debug: Found mapping variable t_51_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '51', 'map', '10']\n", - "Debug: Mapping task 51 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46, 47, 48, 49, 50, 51]\n", - "Debug: Found mapping variable t_52_map_10 with value 1.0\n", - "Debug: Split parts: ['t', '52', 'map', '10']\n", - "Debug: Mapping task 52 to PE 10\n", - "Debug: reverse_mapping[10] now [44, 45, 46, 47, 48, 49, 50, 51, 52]\n", - "Debug: Found mapping variable t_53_map_8 with value 1.0\n", - "Debug: Split parts: ['t', '53', 'map', '8']\n", - "Debug: Mapping task 53 to PE 8\n", - "Debug: reverse_mapping[8] now [53]\n", - "Debug: Found mapping variable t_54_map_8 with value 1.0\n", - "Debug: Split parts: ['t', '54', 'map', '8']\n", - "Debug: Mapping task 54 to PE 8\n", - "Debug: reverse_mapping[8] now [53, 54]\n", - "Debug: Found mapping variable t_55_map_8 with value 1.0\n", - "Debug: Split parts: ['t', '55', 'map', '8']\n", - "Debug: Mapping task 55 to PE 8\n", - "Debug: reverse_mapping[8] now [53, 54, 55]\n", - "Debug: Found mapping variable t_56_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '56', 'map', '15']\n", - "Debug: Mapping task 56 to PE 15\n", - "Debug: reverse_mapping[15] now [56]\n", - "Debug: Found mapping variable t_57_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '57', 'map', '15']\n", - "Debug: Mapping task 57 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57]\n", - "Debug: Found mapping variable t_58_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '58', 'map', '15']\n", - "Debug: Mapping task 58 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58]\n", - "Debug: Found mapping variable t_59_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '59', 'map', '15']\n", - "Debug: Mapping task 59 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59]\n", - "Debug: Found mapping variable t_5_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '5', 'map', '12']\n", - "Debug: Mapping task 5 to PE 12\n", - "Debug: reverse_mapping[12] now [0, 1, 2, 3, 4, 5]\n", - "Debug: Found mapping variable t_60_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '60', 'map', '15']\n", - "Debug: Mapping task 60 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60]\n", - "Debug: Found mapping variable t_61_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '61', 'map', '15']\n", - "Debug: Mapping task 61 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61]\n", - "Debug: Found mapping variable t_62_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '62', 'map', '15']\n", - "Debug: Mapping task 62 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62]\n", - "Debug: Found mapping variable t_63_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '63', 'map', '15']\n", - "Debug: Mapping task 63 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63]\n", - "Debug: Found mapping variable t_64_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '64', 'map', '15']\n", - "Debug: Mapping task 64 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63, 64]\n", - "Debug: Found mapping variable t_65_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '65', 'map', '15']\n", - "Debug: Mapping task 65 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63, 64, 65]\n", - "Debug: Found mapping variable t_66_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '66', 'map', '15']\n", - "Debug: Mapping task 66 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66]\n", - "Debug: Found mapping variable t_67_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '67', 'map', '15']\n", - "Debug: Mapping task 67 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67]\n", - "Debug: Found mapping variable t_68_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '68', 'map', '15']\n", - "Debug: Mapping task 68 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68]\n", - "Debug: Found mapping variable t_69_map_15 with value 1.0\n", - "Debug: Split parts: ['t', '69', 'map', '15']\n", - "Debug: Mapping task 69 to PE 15\n", - "Debug: reverse_mapping[15] now [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]\n", - "Debug: Found mapping variable t_6_map_12 with value 1.0\n", - "Debug: Split parts: ['t', '6', 'map', '12']\n", - "Debug: Mapping task 6 to PE 12\n", - "Debug: reverse_mapping[12] now [0, 1, 2, 3, 4, 5, 6]\n", - "Debug: Found mapping variable t_7_map_11 with value 1.0\n", - "Debug: Split parts: ['t', '7', 'map', '11']\n", - "Debug: Mapping task 7 to PE 11\n", - "Debug: reverse_mapping[11] now [11, 12, 13, 7]\n", - "Debug: Found mapping variable t_8_map_2 with value 1.0\n", - "Debug: Split parts: ['t', '8', 'map', '2']\n", - "Debug: Mapping task 8 to PE 2\n", - "Debug: reverse_mapping[2] now [10, 8]\n", - "Debug: Found mapping variable t_9_map_2 with value 1.0\n", - "Debug: Split parts: ['t', '9', 'map', '2']\n", - "Debug: Mapping task 9 to PE 2\n", - "Debug: reverse_mapping[2] now [10, 8, 9]\n", - "Reverse mapping: {12: [0, 1, 2, 3, 4, 5, 6], 2: [10, 8, 9], 11: [11, 12, 13, 7], 13: [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], 5: [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43], 10: [44, 45, 46, 47, 48, 49, 50, 51, 52], 8: [53, 54, 55], 15: [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]}\n", - "12 [0, 1, 2, 3, 4, 5, 6]\n", - "2 [10, 8, 9]\n", - "11 [11, 12, 13, 7]\n", - "13 [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]\n", - "5 [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]\n", - "10 [44, 45, 46, 47, 48, 49, 50, 51, 52]\n", - "8 [53, 54, 55]\n", - "15 [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]\n", - "Combined mapping: {0: ([0, 1, 2, 3, 4, 5, 6], 1456), 10: ([10, 8, 9], 274), 11: ([11, 12, 13, 7], 1775), 14: ([14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], 1426), 26: ([26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43], 2554), 44: ([44, 45, 46, 47, 48, 49, 50, 51, 52], 6439), 53: ([53, 54, 55], 3913), 56: ([56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69], 11745)}\n", - "Debug: Checking end time for pe=12, task=0, v.name=t0_end_, v.varValue=6.0, current delay_max=0\n", - "Debug: Updated delay_max[12] to 6.0\n", - "Debug: Checking start time for pe=12, task=0, v.name=t0_start, v.varValue=0.0, current delay_min=inf\n", - "Debug: Updated delay_min[12] to 0.0\n", - "Debug: found t_comp pe=12, task=0, v.name=t_comp_0, v.varValue=6.0 new total comp=6\n", - "Debug: Checking end time for pe=12, task=1, v.name=t1_end_, v.varValue=62.0, current delay_max=6.0\n", - "Debug: Updated delay_max[12] to 62.0\n", - "Debug: Checking start time for pe=12, task=1, v.name=t1_start, v.varValue=6.0, current delay_min=0.0\n", - "Debug: found t_comp pe=12, task=1, v.name=t_comp_1, v.varValue=56.0 new total comp=62\n", - "Debug: Checking end time for pe=12, task=2, v.name=t2_end_, v.varValue=174.0, current delay_max=62.0\n", - "Debug: Updated delay_max[12] to 174.0\n", - "Debug: Checking start time for pe=12, task=2, v.name=t2_start, v.varValue=62.0, current delay_min=0.0\n", - "Debug: found t_comp pe=12, task=2, v.name=t_comp_2, v.varValue=112.0 new total comp=174\n", - "Debug: Checking end time for pe=12, task=3, v.name=t3_end_, v.varValue=258.0, current delay_max=174.0\n", - "Debug: Updated delay_max[12] to 258.0\n", - "Debug: Checking start time for pe=12, task=3, v.name=t3_start, v.varValue=257.0, current delay_min=0.0\n", - "Debug: found t_comp pe=12, task=3, v.name=t_comp_3, v.varValue=1.0 new total comp=175\n", - "Debug: Checking end time for pe=12, task=4, v.name=t4_end_, v.varValue=257.0, current delay_max=258.0\n", - "Debug: Checking start time for pe=12, task=4, v.name=t4_start, v.varValue=174.0, current delay_min=0.0\n", - "Debug: found t_comp pe=12, task=4, v.name=t_comp_4, v.varValue=83.0 new total comp=258\n", - "Debug: Checking end time for pe=12, task=5, v.name=t5_end_, v.varValue=258.0, current delay_max=258.0\n", - "Debug: Checking start time for pe=12, task=5, v.name=t5_start, v.varValue=258.0, current delay_min=0.0\n", - "Debug: found t_comp pe=12, task=5, v.name=t_comp_5, v.varValue=0.0 new total comp=258\n", - "Debug: Checking end time for pe=12, task=6, v.name=t6_end_, v.varValue=274.0, current delay_max=258.0\n", - "Debug: Updated delay_max[12] to 274.0\n", - "Debug: Checking start time for pe=12, task=6, v.name=t6_start, v.varValue=258.0, current delay_min=0.0\n", - "Debug: found t_comp pe=12, task=6, v.name=t_comp_6, v.varValue=16.0 new total comp=274\n", - "Debug: Checking end time for pe=2, task=10, v.name=t10_end_, v.varValue=360.0, current delay_max=0\n", - "Debug: Updated delay_max[2] to 360.0\n", - "Debug: Checking start time for pe=2, task=10, v.name=t10_start, v.varValue=317.0, current delay_min=inf\n", - "Debug: Updated delay_min[2] to 317.0\n", - "Debug: found t_comp pe=2, task=10, v.name=t_comp_10, v.varValue=43.0 new total comp=43\n", - "Debug: Checking end time for pe=2, task=8, v.name=t8_end_, v.varValue=274.0, current delay_max=360.0\n", - "Debug: Checking start time for pe=2, task=8, v.name=t8_start, v.varValue=258.0, current delay_min=317.0\n", - "Debug: Updated delay_min[2] to 258.0\n", - "Debug: found t_comp pe=2, task=8, v.name=t_comp_8, v.varValue=16.0 new total comp=59\n", - "Debug: Checking end time for pe=2, task=9, v.name=t9_end_, v.varValue=317.0, current delay_max=360.0\n", - "Debug: Checking start time for pe=2, task=9, v.name=t9_start, v.varValue=274.0, current delay_min=258.0\n", - "Debug: found t_comp pe=2, task=9, v.name=t_comp_9, v.varValue=43.0 new total comp=102\n", - "Debug: Checking end time for pe=11, task=11, v.name=t11_end_, v.varValue=575.0, current delay_max=0\n", - "Debug: Updated delay_max[11] to 575.0\n", - "Debug: Checking start time for pe=11, task=11, v.name=t11_start, v.varValue=497.0, current delay_min=inf\n", - "Debug: Updated delay_min[11] to 497.0\n", - "Debug: found t_comp pe=11, task=11, v.name=t_comp_11, v.varValue=78.0 new total comp=78\n", - "Debug: Checking end time for pe=11, task=12, v.name=t12_end_, v.varValue=653.0, current delay_max=575.0\n", - "Debug: Updated delay_max[11] to 653.0\n", - "Debug: Checking start time for pe=11, task=12, v.name=t12_start, v.varValue=653.0, current delay_min=497.0\n", - "Debug: found t_comp pe=11, task=12, v.name=t_comp_12, v.varValue=0.0 new total comp=78\n", - "Debug: Checking end time for pe=11, task=13, v.name=t13_end_, v.varValue=767.0, current delay_max=653.0\n", - "Debug: Updated delay_max[11] to 767.0\n", - "Debug: Checking start time for pe=11, task=13, v.name=t13_start, v.varValue=653.0, current delay_min=497.0\n", - "Debug: found t_comp pe=11, task=13, v.name=t_comp_13, v.varValue=114.0 new total comp=192\n", - "Debug: Checking end time for pe=11, task=7, v.name=t7_end_, v.varValue=653.0, current delay_max=767.0\n", - "Debug: Checking start time for pe=11, task=7, v.name=t7_start, v.varValue=575.0, current delay_min=497.0\n", - "Debug: found t_comp pe=11, task=7, v.name=t_comp_7, v.varValue=78.0 new total comp=270\n", - "Debug: Checking end time for pe=13, task=14, v.name=t14_end_, v.varValue=862.0, current delay_max=0\n", - "Debug: Updated delay_max[13] to 862.0\n", - "Debug: Checking start time for pe=13, task=14, v.name=t14_start, v.varValue=861.0, current delay_min=inf\n", - "Debug: Updated delay_min[13] to 861.0\n", - "Debug: found t_comp pe=13, task=14, v.name=t_comp_14, v.varValue=1.0 new total comp=1\n", - "Debug: Checking end time for pe=13, task=15, v.name=t15_end_, v.varValue=862.0, current delay_max=862.0\n", - "Debug: Checking start time for pe=13, task=15, v.name=t15_start, v.varValue=862.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=15, v.name=t_comp_15, v.varValue=0.0 new total comp=1\n", - "Debug: Checking end time for pe=13, task=16, v.name=t16_end_, v.varValue=1128.0, current delay_max=862.0\n", - "Debug: Updated delay_max[13] to 1128.0\n", - "Debug: Checking start time for pe=13, task=16, v.name=t16_start, v.varValue=1115.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=16, v.name=t_comp_16, v.varValue=13.0 new total comp=14\n", - "Debug: Checking end time for pe=13, task=17, v.name=t17_end_, v.varValue=900.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=17, v.name=t17_start, v.varValue=891.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=17, v.name=t_comp_17, v.varValue=9.0 new total comp=23\n", - "Debug: Checking end time for pe=13, task=18, v.name=t18_end_, v.varValue=932.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=18, v.name=t18_start, v.varValue=913.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=18, v.name=t_comp_18, v.varValue=19.0 new total comp=42\n", - "Debug: Checking end time for pe=13, task=19, v.name=t19_end_, v.varValue=871.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=19, v.name=t19_start, v.varValue=862.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=19, v.name=t_comp_19, v.varValue=9.0 new total comp=51\n", - "Debug: Checking end time for pe=13, task=20, v.name=t20_end_, v.varValue=891.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=20, v.name=t20_start, v.varValue=872.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=20, v.name=t_comp_20, v.varValue=19.0 new total comp=70\n", - "Debug: Checking end time for pe=13, task=21, v.name=t21_end_, v.varValue=1115.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=21, v.name=t21_start, v.varValue=1086.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=21, v.name=t_comp_21, v.varValue=29.0 new total comp=99\n", - "Debug: Checking end time for pe=13, task=22, v.name=t22_end_, v.varValue=872.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=22, v.name=t22_start, v.varValue=871.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=22, v.name=t_comp_22, v.varValue=1.0 new total comp=100\n", - "Debug: Checking end time for pe=13, task=23, v.name=t23_end_, v.varValue=913.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=23, v.name=t23_start, v.varValue=900.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=23, v.name=t_comp_23, v.varValue=13.0 new total comp=113\n", - "Debug: Checking end time for pe=13, task=24, v.name=t24_end_, v.varValue=1128.0, current delay_max=1128.0\n", - "Debug: Checking start time for pe=13, task=24, v.name=t24_start, v.varValue=1128.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=24, v.name=t_comp_24, v.varValue=0.0 new total comp=113\n", - "Debug: Checking end time for pe=13, task=25, v.name=t25_end_, v.varValue=1141.0, current delay_max=1128.0\n", - "Debug: Updated delay_max[13] to 1141.0\n", - "Debug: Checking start time for pe=13, task=25, v.name=t25_start, v.varValue=1128.0, current delay_min=861.0\n", - "Debug: found t_comp pe=13, task=25, v.name=t_comp_25, v.varValue=13.0 new total comp=126\n", - "Debug: Checking end time for pe=5, task=26, v.name=t26_end_, v.varValue=1137.0, current delay_max=0\n", - "Debug: Updated delay_max[5] to 1137.0\n", - "Debug: Checking start time for pe=5, task=26, v.name=t26_start, v.varValue=1128.0, current delay_min=inf\n", - "Debug: Updated delay_min[5] to 1128.0\n", - "Debug: found t_comp pe=5, task=26, v.name=t_comp_26, v.varValue=9.0 new total comp=9\n", - "Debug: Checking end time for pe=5, task=27, v.name=t27_end_, v.varValue=1184.0, current delay_max=1137.0\n", - "Debug: Updated delay_max[5] to 1184.0\n", - "Debug: Checking start time for pe=5, task=27, v.name=t27_start, v.varValue=1165.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=27, v.name=t_comp_27, v.varValue=19.0 new total comp=28\n", - "Debug: Checking end time for pe=5, task=28, v.name=t28_end_, v.varValue=1146.0, current delay_max=1184.0\n", - "Debug: Checking start time for pe=5, task=28, v.name=t28_start, v.varValue=1137.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=28, v.name=t_comp_28, v.varValue=9.0 new total comp=37\n", - "Debug: Checking end time for pe=5, task=29, v.name=t29_end_, v.varValue=1165.0, current delay_max=1184.0\n", - "Debug: Checking start time for pe=5, task=29, v.name=t29_start, v.varValue=1146.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=29, v.name=t_comp_29, v.varValue=19.0 new total comp=56\n", - "Debug: Checking end time for pe=5, task=30, v.name=t30_end_, v.varValue=1227.0, current delay_max=1184.0\n", - "Debug: Updated delay_max[5] to 1227.0\n", - "Debug: Checking start time for pe=5, task=30, v.name=t30_start, v.varValue=1198.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=30, v.name=t_comp_30, v.varValue=29.0 new total comp=85\n", - "Debug: Checking end time for pe=5, task=31, v.name=t31_end_, v.varValue=1185.0, current delay_max=1227.0\n", - "Debug: Checking start time for pe=5, task=31, v.name=t31_start, v.varValue=1184.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=31, v.name=t_comp_31, v.varValue=1.0 new total comp=86\n", - "Debug: Checking end time for pe=5, task=32, v.name=t32_end_, v.varValue=1198.0, current delay_max=1227.0\n", - "Debug: Checking start time for pe=5, task=32, v.name=t32_start, v.varValue=1185.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=32, v.name=t_comp_32, v.varValue=13.0 new total comp=99\n", - "Debug: Checking end time for pe=5, task=33, v.name=t33_end_, v.varValue=1227.0, current delay_max=1227.0\n", - "Debug: Checking start time for pe=5, task=33, v.name=t33_start, v.varValue=1227.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=33, v.name=t_comp_33, v.varValue=0.0 new total comp=99\n", - "Debug: Checking end time for pe=5, task=34, v.name=t34_end_, v.varValue=1305.0, current delay_max=1227.0\n", - "Debug: Updated delay_max[5] to 1305.0\n", - "Debug: Checking start time for pe=5, task=34, v.name=t34_start, v.varValue=1292.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=34, v.name=t_comp_34, v.varValue=13.0 new total comp=112\n", - "Debug: Checking end time for pe=5, task=35, v.name=t35_end_, v.varValue=1315.0, current delay_max=1305.0\n", - "Debug: Updated delay_max[5] to 1315.0\n", - "Debug: Checking start time for pe=5, task=35, v.name=t35_start, v.varValue=1306.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=35, v.name=t_comp_35, v.varValue=9.0 new total comp=121\n", - "Debug: Checking end time for pe=5, task=36, v.name=t36_end_, v.varValue=1366.0, current delay_max=1315.0\n", - "Debug: Updated delay_max[5] to 1366.0\n", - "Debug: Checking start time for pe=5, task=36, v.name=t36_start, v.varValue=1347.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=36, v.name=t_comp_36, v.varValue=19.0 new total comp=140\n", - "Debug: Checking end time for pe=5, task=37, v.name=t37_end_, v.varValue=1236.0, current delay_max=1366.0\n", - "Debug: Checking start time for pe=5, task=37, v.name=t37_start, v.varValue=1227.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=37, v.name=t_comp_37, v.varValue=9.0 new total comp=149\n", - "Debug: Checking end time for pe=5, task=38, v.name=t38_end_, v.varValue=1334.0, current delay_max=1366.0\n", - "Debug: Checking start time for pe=5, task=38, v.name=t38_start, v.varValue=1315.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=38, v.name=t_comp_38, v.varValue=19.0 new total comp=168\n", - "Debug: Checking end time for pe=5, task=39, v.name=t39_end_, v.varValue=1395.0, current delay_max=1366.0\n", - "Debug: Updated delay_max[5] to 1395.0\n", - "Debug: Checking start time for pe=5, task=39, v.name=t39_start, v.varValue=1366.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=39, v.name=t_comp_39, v.varValue=29.0 new total comp=197\n", - "Debug: Checking end time for pe=5, task=40, v.name=t40_end_, v.varValue=1306.0, current delay_max=1395.0\n", - "Debug: Checking start time for pe=5, task=40, v.name=t40_start, v.varValue=1305.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=40, v.name=t_comp_40, v.varValue=1.0 new total comp=198\n", - "Debug: Checking end time for pe=5, task=41, v.name=t41_end_, v.varValue=1347.0, current delay_max=1395.0\n", - "Debug: Checking start time for pe=5, task=41, v.name=t41_start, v.varValue=1334.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=41, v.name=t_comp_41, v.varValue=13.0 new total comp=211\n", - "Debug: Checking end time for pe=5, task=42, v.name=t42_end_, v.varValue=1395.0, current delay_max=1395.0\n", - "Debug: Checking start time for pe=5, task=42, v.name=t42_start, v.varValue=1395.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=42, v.name=t_comp_42, v.varValue=0.0 new total comp=211\n", - "Debug: Checking end time for pe=5, task=43, v.name=t43_end_, v.varValue=1408.0, current delay_max=1395.0\n", - "Debug: Updated delay_max[5] to 1408.0\n", - "Debug: Checking start time for pe=5, task=43, v.name=t43_start, v.varValue=1395.0, current delay_min=1128.0\n", - "Debug: found t_comp pe=5, task=43, v.name=t_comp_43, v.varValue=13.0 new total comp=224\n", - "Debug: Checking end time for pe=10, task=44, v.name=t44_end_, v.varValue=1500.0, current delay_max=0\n", - "Debug: Updated delay_max[10] to 1500.0\n", - "Debug: Checking start time for pe=10, task=44, v.name=t44_start, v.varValue=1491.0, current delay_min=inf\n", - "Debug: Updated delay_min[10] to 1491.0\n", - "Debug: found t_comp pe=10, task=44, v.name=t_comp_44, v.varValue=9.0 new total comp=9\n", - "Debug: Checking end time for pe=10, task=45, v.name=t45_end_, v.varValue=1519.0, current delay_max=1500.0\n", - "Debug: Updated delay_max[10] to 1519.0\n", - "Debug: Checking start time for pe=10, task=45, v.name=t45_start, v.varValue=1500.0, current delay_min=1491.0\n", - "Debug: found t_comp pe=10, task=45, v.name=t_comp_45, v.varValue=19.0 new total comp=28\n", - "Debug: Checking end time for pe=10, task=46, v.name=t46_end_, v.varValue=1418.0, current delay_max=1519.0\n", - "Debug: Checking start time for pe=10, task=46, v.name=t46_start, v.varValue=1409.0, current delay_min=1491.0\n", - "Debug: Updated delay_min[10] to 1409.0\n", - "Debug: found t_comp pe=10, task=46, v.name=t_comp_46, v.varValue=9.0 new total comp=37\n", - "Debug: Checking end time for pe=10, task=47, v.name=t47_end_, v.varValue=1538.0, current delay_max=1519.0\n", - "Debug: Updated delay_max[10] to 1538.0\n", - "Debug: Checking start time for pe=10, task=47, v.name=t47_start, v.varValue=1519.0, current delay_min=1409.0\n", - "Debug: found t_comp pe=10, task=47, v.name=t_comp_47, v.varValue=19.0 new total comp=56\n", - "Debug: Checking end time for pe=10, task=48, v.name=t48_end_, v.varValue=1567.0, current delay_max=1538.0\n", - "Debug: Updated delay_max[10] to 1567.0\n", - "Debug: Checking start time for pe=10, task=48, v.name=t48_start, v.varValue=1538.0, current delay_min=1409.0\n", - "Debug: found t_comp pe=10, task=48, v.name=t_comp_48, v.varValue=29.0 new total comp=85\n", - "Debug: Checking end time for pe=10, task=49, v.name=t49_end_, v.varValue=1396.0, current delay_max=1567.0\n", - "Debug: Checking start time for pe=10, task=49, v.name=t49_start, v.varValue=1395.0, current delay_min=1409.0\n", - "Debug: Updated delay_min[10] to 1395.0\n", - "Debug: found t_comp pe=10, task=49, v.name=t_comp_49, v.varValue=1.0 new total comp=86\n", - "Debug: Checking end time for pe=10, task=50, v.name=t50_end_, v.varValue=1409.0, current delay_max=1567.0\n", - "Debug: Checking start time for pe=10, task=50, v.name=t50_start, v.varValue=1396.0, current delay_min=1395.0\n", - "Debug: found t_comp pe=10, task=50, v.name=t_comp_50, v.varValue=13.0 new total comp=99\n", - "Debug: Checking end time for pe=10, task=51, v.name=t51_end_, v.varValue=1567.0, current delay_max=1567.0\n", - "Debug: Checking start time for pe=10, task=51, v.name=t51_start, v.varValue=1567.0, current delay_min=1395.0\n", - "Debug: found t_comp pe=10, task=51, v.name=t_comp_51, v.varValue=0.0 new total comp=99\n", - "Debug: Checking end time for pe=10, task=52, v.name=t52_end_, v.varValue=1675.0, current delay_max=1567.0\n", - "Debug: Updated delay_max[10] to 1675.0\n", - "Debug: Checking start time for pe=10, task=52, v.name=t52_start, v.varValue=1567.0, current delay_min=1395.0\n", - "Debug: found t_comp pe=10, task=52, v.name=t_comp_52, v.varValue=108.0 new total comp=207\n", - "Debug: Checking end time for pe=8, task=53, v.name=t53_end_, v.varValue=1593.0, current delay_max=0\n", - "Debug: Updated delay_max[8] to 1593.0\n", - "Debug: Checking start time for pe=8, task=53, v.name=t53_start, v.varValue=1567.0, current delay_min=inf\n", - "Debug: Updated delay_min[8] to 1567.0\n", - "Debug: found t_comp pe=8, task=53, v.name=t_comp_53, v.varValue=26.0 new total comp=26\n", - "Debug: Checking end time for pe=8, task=54, v.name=t54_end_, v.varValue=1726.0, current delay_max=1593.0\n", - "Debug: Updated delay_max[8] to 1726.0\n", - "Debug: Checking start time for pe=8, task=54, v.name=t54_start, v.varValue=1593.0, current delay_min=1567.0\n", - "Debug: found t_comp pe=8, task=54, v.name=t_comp_54, v.varValue=133.0 new total comp=159\n", - "Debug: Checking end time for pe=8, task=55, v.name=t55_end_, v.varValue=1768.0, current delay_max=1726.0\n", - "Debug: Updated delay_max[8] to 1768.0\n", - "Debug: Checking start time for pe=8, task=55, v.name=t55_start, v.varValue=1726.0, current delay_min=1567.0\n", - "Debug: found t_comp pe=8, task=55, v.name=t_comp_55, v.varValue=42.0 new total comp=201\n", - "Debug: Checking end time for pe=15, task=56, v.name=t56_end_, v.varValue=1772.0, current delay_max=0\n", - "Debug: Updated delay_max[15] to 1772.0\n", - "Debug: Checking start time for pe=15, task=56, v.name=t56_start, v.varValue=1771.0, current delay_min=inf\n", - "Debug: Updated delay_min[15] to 1771.0\n", - "Debug: found t_comp pe=15, task=56, v.name=t_comp_56, v.varValue=1.0 new total comp=1\n", - "Debug: Checking end time for pe=15, task=57, v.name=t57_end_, v.varValue=1798.0, current delay_max=1772.0\n", - "Debug: Updated delay_max[15] to 1798.0\n", - "Debug: Checking start time for pe=15, task=57, v.name=t57_start, v.varValue=1798.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=57, v.name=t_comp_57, v.varValue=0.0 new total comp=1\n", - "Debug: Checking end time for pe=15, task=58, v.name=t58_end_, v.varValue=1863.0, current delay_max=1798.0\n", - "Debug: Updated delay_max[15] to 1863.0\n", - "Debug: Checking start time for pe=15, task=58, v.name=t58_start, v.varValue=1831.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=58, v.name=t_comp_58, v.varValue=32.0 new total comp=33\n", - "Debug: Checking end time for pe=15, task=59, v.name=t59_end_, v.varValue=1814.0, current delay_max=1863.0\n", - "Debug: Checking start time for pe=15, task=59, v.name=t59_start, v.varValue=1798.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=59, v.name=t_comp_59, v.varValue=16.0 new total comp=49\n", - "Debug: Checking end time for pe=15, task=60, v.name=t60_end_, v.varValue=1934.0, current delay_max=1863.0\n", - "Debug: Updated delay_max[15] to 1934.0\n", - "Debug: Checking start time for pe=15, task=60, v.name=t60_start, v.varValue=1909.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=60, v.name=t_comp_60, v.varValue=25.0 new total comp=74\n", - "Debug: Checking end time for pe=15, task=61, v.name=t61_end_, v.varValue=2040.0, current delay_max=1934.0\n", - "Debug: Updated delay_max[15] to 2040.0\n", - "Debug: Checking start time for pe=15, task=61, v.name=t61_start, v.varValue=2007.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=61, v.name=t_comp_61, v.varValue=33.0 new total comp=107\n", - "Debug: Checking end time for pe=15, task=62, v.name=t62_end_, v.varValue=1830.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=62, v.name=t62_start, v.varValue=1814.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=62, v.name=t_comp_62, v.varValue=16.0 new total comp=123\n", - "Debug: Checking end time for pe=15, task=63, v.name=t63_end_, v.varValue=1884.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=63, v.name=t63_start, v.varValue=1863.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=63, v.name=t_comp_63, v.varValue=21.0 new total comp=144\n", - "Debug: Checking end time for pe=15, task=64, v.name=t64_end_, v.varValue=1909.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=64, v.name=t64_start, v.varValue=1884.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=64, v.name=t_comp_64, v.varValue=25.0 new total comp=169\n", - "Debug: Checking end time for pe=15, task=65, v.name=t65_end_, v.varValue=1963.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=65, v.name=t65_start, v.varValue=1934.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=65, v.name=t_comp_65, v.varValue=29.0 new total comp=198\n", - "Debug: Checking end time for pe=15, task=66, v.name=t66_end_, v.varValue=2007.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=66, v.name=t66_start, v.varValue=1974.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=66, v.name=t_comp_66, v.varValue=33.0 new total comp=231\n", - "Debug: Checking end time for pe=15, task=67, v.name=t67_end_, v.varValue=1831.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=67, v.name=t67_start, v.varValue=1830.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=67, v.name=t_comp_67, v.varValue=1.0 new total comp=232\n", - "Debug: Checking end time for pe=15, task=68, v.name=t68_end_, v.varValue=1974.0, current delay_max=2040.0\n", - "Debug: Checking start time for pe=15, task=68, v.name=t68_start, v.varValue=1963.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=68, v.name=t_comp_68, v.varValue=11.0 new total comp=243\n", - "Debug: Checking end time for pe=15, task=69, v.name=t69_end_, v.varValue=2051.0, current delay_max=2040.0\n", - "Debug: Updated delay_max[15] to 2051.0\n", - "Debug: Checking start time for pe=15, task=69, v.name=t69_start, v.varValue=2040.0, current delay_min=1771.0\n", - "Debug: found t_comp pe=15, task=69, v.name=t_comp_69, v.varValue=11.0 new total comp=254\n", - "Reverse mapping: {12: [0, 1, 2, 3, 4, 5, 6], 2: [10, 8, 9], 11: [11, 12, 13, 7], 13: [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], 5: [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43], 10: [44, 45, 46, 47, 48, 49, 50, 51, 52], 8: [53, 54, 55], 15: [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]}\n", - "total_comp: {12: 274, 2: 102, 11: 270, 13: 126, 5: 224, 10: 207, 8: 201, 15: 254}\n", - "total_sending: {12: 137.0, 2: 137.0, 11: 95.0, 13: 48.0, 5: 48.0, 10: 45.0, 8: 30.0, 15: 0.0}\n", - "total_memory: {12: 1456.0, 2: 274.0, 11: 1775.0, 13: 1426.0, 5: 2554.0, 10: 6439.0, 8: 3913.0, 15: 11745.0}\n", - "delay_max: {12: 274.0, 2: 360.0, 11: 767.0, 13: 1141.0, 5: 1408.0, 10: 1675.0, 8: 1768.0, 15: 2051.0}\n", - "delay_min: {12: 0.0, 2: 258.0, 11: 497.0, 13: 861.0, 5: 1128.0, 10: 1395.0, 8: 1567.0, 15: 1771.0}\n", - "delay_duration: {12: 274.0, 2: 102.0, 11: 270.0, 13: 280.0, 5: 280.0, 10: 280.0, 8: 201.0, 15: 280.0}\n", + "_C119502: -t0_end_ + t0_start - 250000.0*t_0_map_1 - t_send_0 + task_total_delay_router_router1_task0 >= -250000.0\n", + "_C119503: -250000.0*t_0_map_1 - t_mem_0 + task_total_memory_router_router1_task0 >= -250000.0\n", + "_C119504: -t1_end_ + t1_start - 250000.0*t_1_map_1 - t_send_1 + task_total_delay_router_router1_task1 >= -250000.0\n", + "_C119505: -250000.0*t_1_map_1 - t_mem_1 + task_total_memory_router_router1_task1 >= -250000.0\n", + "_C119506: -t2_end_ + t2_start - 250000.0*t_2_map_1 - t_send_2 + task_total_delay_router_router1_task2 >= -250000.0\n", + "_C119507: -250000.0*t_2_map_1 - t_mem_2 + task_total_memory_router_router1_task2 >= -250000.0\n", + "_C119508: -t3_end_ + t3_start - 250000.0*t_3_map_1 - t_send_3 + task_total_delay_router_router1_task3 >= -250000.0\n", + "_C119509: -250000.0*t_3_map_1 - t_mem_3 + task_total_memory_router_router1_task3 >= -250000.0\n", + "_C119510: -t4_end_ + t4_start - 250000.0*t_4_map_1 - t_send_4 + task_total_delay_router_router1_task4 >= -250000.0\n", + "_C119511: -250000.0*t_4_map_1 - t_mem_4 + task_total_memory_router_router1_task4 >= -250000.0\n", + "_C119512: -t5_end_ + t5_start - 250000.0*t_5_map_1 - t_send_5 + task_total_delay_router_router1_task5 >= -250000.0\n", + "_C119513: -250000.0*t_5_map_1 - t_mem_5 + task_total_memory_router_router1_task5 >= -250000.0\n", + "_C119514: -t6_end_ + t6_start - 250000.0*t_6_map_1 - t_send_6 + task_total_delay_router_router1_task6 >= -250000.0\n", + "_C119515: -250000.0*t_6_map_1 - t_mem_6 + task_total_memory_router_router1_task6 >= -250000.0\n", + "_C119516: -t7_end_ + t7_start - 250000.0*t_7_map_1 - t_send_7 + task_total_delay_router_router1_task7 >= -250000.0\n", + "_C119517: -250000.0*t_7_map_1 - t_mem_7 + task_total_memory_router_router1_task7 >= -250000.0\n", + "_C119518: -t8_end_ + t8_start - 250000.0*t_8_map_1 - t_send_8 + task_total_delay_router_router1_task8 >= -250000.0\n", + "_C119519: -250000.0*t_8_map_1 - t_mem_8 + task_total_memory_router_router1_task8 >= -250000.0\n", + "_C119520: -t9_end_ + t9_start - 250000.0*t_9_map_1 - t_send_9 + task_total_delay_router_router1_task9 >= -250000.0\n", + "_C119521: -250000.0*t_9_map_1 - t_mem_9 + task_total_memory_router_router1_task9 >= -250000.0\n", + "_C119522: -t10_end_ + t10_start - 250000.0*t_10_map_1 - t_send_10 + task_total_delay_router_router1_task10 >= -250000.0\n", + "_C119523: -250000.0*t_10_map_1 - t_mem_10 + task_total_memory_router_router1_task10 >= -250000.0\n", + "_C119524: -t11_end_ + t11_start - 250000.0*t_11_map_1 - t_send_11 + task_total_delay_router_router1_task11 >= -250000.0\n", + "_C119525: -250000.0*t_11_map_1 - t_mem_11 + task_total_memory_router_router1_task11 >= -250000.0\n", + "_C119526: -t12_end_ + t12_start - 250000.0*t_12_map_1 - t_send_12 + task_total_delay_router_router1_task12 >= -250000.0\n", + "_C119527: -250000.0*t_12_map_1 - t_mem_12 + task_total_memory_router_router1_task12 >= -250000.0\n", + "_C119528: -t13_end_ + t13_start - 250000.0*t_13_map_1 - t_send_13 + task_total_delay_router_router1_task13 >= -250000.0\n", + "_C119529: -250000.0*t_13_map_1 - t_mem_13 + task_total_memory_router_router1_task13 >= -250000.0\n", + "_C119530: -t14_end_ + t14_start - 250000.0*t_14_map_1 - t_send_14 + task_total_delay_router_router1_task14 >= -250000.0\n", + "_C119531: -250000.0*t_14_map_1 - t_mem_14 + task_total_memory_router_router1_task14 >= -250000.0\n", + "_C119532: -t15_end_ + t15_start - 250000.0*t_15_map_1 - t_send_15 + task_total_delay_router_router1_task15 >= -250000.0\n", + "_C119533: -250000.0*t_15_map_1 - t_mem_15 + task_total_memory_router_router1_task15 >= -250000.0\n", + "_C119534: -t16_end_ + t16_start - 250000.0*t_16_map_1 - t_send_16 + 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task_total_memory_router_router1_task18 - task_total_memory_router_router1_task19 - task_total_memory_router_router1_task2 - task_total_memory_router_router1_task20 - task_total_memory_router_router1_task21 - task_total_memory_router_router1_task22 - task_total_memory_router_router1_task23 - task_total_memory_router_router1_task24 - task_total_memory_router_router1_task25 - task_total_memory_router_router1_task26 - task_total_memory_router_router1_task27 - task_total_memory_router_router1_task28 - task_total_memory_router_router1_task29 - task_total_memory_router_router1_task3 - task_total_memory_router_router1_task30 - task_total_memory_router_router1_task31 - task_total_memory_router_router1_task32 - task_total_memory_router_router1_task33 - task_total_memory_router_router1_task34 - task_total_memory_router_router1_task35 - task_total_memory_router_router1_task36 - task_total_memory_router_router1_task37 - task_total_memory_router_router1_task38 - task_total_memory_router_router1_task39 - task_total_memory_router_router1_task4 - task_total_memory_router_router1_task40 - task_total_memory_router_router1_task41 - task_total_memory_router_router1_task42 - task_total_memory_router_router1_task43 - task_total_memory_router_router1_task44 - task_total_memory_router_router1_task45 - task_total_memory_router_router1_task46 - task_total_memory_router_router1_task47 - task_total_memory_router_router1_task48 - task_total_memory_router_router1_task49 - task_total_memory_router_router1_task5 - task_total_memory_router_router1_task50 - task_total_memory_router_router1_task51 - task_total_memory_router_router1_task52 - task_total_memory_router_router1_task53 - task_total_memory_router_router1_task54 - task_total_memory_router_router1_task55 - task_total_memory_router_router1_task56 - task_total_memory_router_router1_task57 - task_total_memory_router_router1_task58 - task_total_memory_router_router1_task59 - task_total_memory_router_router1_task6 - task_total_memory_router_router1_task60 - task_total_memory_router_router1_task61 - task_total_memory_router_router1_task62 - task_total_memory_router_router1_task63 - task_total_memory_router_router1_task64 - task_total_memory_router_router1_task65 - task_total_memory_router_router1_task66 - task_total_memory_router_router1_task67 - task_total_memory_router_router1_task68 - task_total_memory_router_router1_task69 - task_total_memory_router_router1_task7 - task_total_memory_router_router1_task8 - task_total_memory_router_router1_task9 >= -0.0\n", + "_C119643: PE1_total_delay - task_total_delay_router_router1_task0 - task_total_delay_router_router1_task1 - task_total_delay_router_router1_task10 - task_total_delay_router_router1_task11 - task_total_delay_router_router1_task12 - task_total_delay_router_router1_task13 - task_total_delay_router_router1_task14 - task_total_delay_router_router1_task15 - task_total_delay_router_router1_task16 - task_total_delay_router_router1_task17 - task_total_delay_router_router1_task18 - task_total_delay_router_router1_task19 - task_total_delay_router_router1_task2 - task_total_delay_router_router1_task20 - task_total_delay_router_router1_task21 - task_total_delay_router_router1_task22 - task_total_delay_router_router1_task23 - task_total_delay_router_router1_task24 - task_total_delay_router_router1_task25 - task_total_delay_router_router1_task26 - task_total_delay_router_router1_task27 - task_total_delay_router_router1_task28 - task_total_delay_router_router1_task29 - task_total_delay_router_router1_task3 - task_total_delay_router_router1_task30 - task_total_delay_router_router1_task31 - task_total_delay_router_router1_task32 - task_total_delay_router_router1_task33 - task_total_delay_router_router1_task34 - task_total_delay_router_router1_task35 - task_total_delay_router_router1_task36 - task_total_delay_router_router1_task37 - task_total_delay_router_router1_task38 - task_total_delay_router_router1_task39 - task_total_delay_router_router1_task4 - task_total_delay_router_router1_task40 - task_total_delay_router_router1_task41 - task_total_delay_router_router1_task42 - task_total_delay_router_router1_task43 - task_total_delay_router_router1_task44 - task_total_delay_router_router1_task45 - task_total_delay_router_router1_task46 - task_total_delay_router_router1_task47 - task_total_delay_router_router1_task48 - task_total_delay_router_router1_task49 - task_total_delay_router_router1_task5 - task_total_delay_router_router1_task50 - task_total_delay_router_router1_task51 - task_total_delay_router_router1_task52 - task_total_delay_router_router1_task53 - task_total_delay_router_router1_task54 - task_total_delay_router_router1_task55 - task_total_delay_router_router1_task56 - task_total_delay_router_router1_task57 - task_total_delay_router_router1_task58 - task_total_delay_router_router1_task59 - task_total_delay_router_router1_task6 - task_total_delay_router_router1_task60 - task_total_delay_router_router1_task61 - task_total_delay_router_router1_task62 - task_total_delay_router_router1_task63 - task_total_delay_router_router1_task64 - task_total_delay_router_router1_task65 - task_total_delay_router_router1_task66 - task_total_delay_router_router1_task67 - task_total_delay_router_router1_task68 - task_total_delay_router_router1_task69 - task_total_delay_router_router1_task7 - task_total_delay_router_router1_task8 - task_total_delay_router_router1_task9 >= -0.0\n", + "_C119644: PE1_total_memory - task_total_memory_router_router1_task0 - task_total_memory_router_router1_task1 - task_total_memory_router_router1_task10 - task_total_memory_router_router1_task11 - task_total_memory_router_router1_task12 - task_total_memory_router_router1_task13 - task_total_memory_router_router1_task14 - task_total_memory_router_router1_task15 - task_total_memory_router_router1_task16 - task_total_memory_router_router1_task17 - task_total_memory_router_router1_task18 - task_total_memory_router_router1_task19 - task_total_memory_router_router1_task2 - task_total_memory_router_router1_task20 - task_total_memory_router_router1_task21 - task_total_memory_router_router1_task22 - task_total_memory_router_router1_task23 - task_total_memory_router_router1_task24 - task_total_memory_router_router1_task25 - task_total_memory_router_router1_task26 - task_total_memory_router_router1_task27 - task_total_memory_router_router1_task28 - task_total_memory_router_router1_task29 - task_total_memory_router_router1_task3 - task_total_memory_router_router1_task30 - task_total_memory_router_router1_task31 - task_total_memory_router_router1_task32 - task_total_memory_router_router1_task33 - task_total_memory_router_router1_task34 - task_total_memory_router_router1_task35 - task_total_memory_router_router1_task36 - task_total_memory_router_router1_task37 - task_total_memory_router_router1_task38 - task_total_memory_router_router1_task39 - task_total_memory_router_router1_task4 - task_total_memory_router_router1_task40 - task_total_memory_router_router1_task41 - task_total_memory_router_router1_task42 - task_total_memory_router_router1_task43 - task_total_memory_router_router1_task44 - task_total_memory_router_router1_task45 - task_total_memory_router_router1_task46 - task_total_memory_router_router1_task47 - task_total_memory_router_router1_task48 - task_total_memory_router_router1_task49 - task_total_memory_router_router1_task5 - task_total_memory_router_router1_task50 - task_total_memory_router_router1_task51 - task_total_memory_router_router1_task52 - task_total_memory_router_router1_task53 - task_total_memory_router_router1_task54 - task_total_memory_router_router1_task55 - task_total_memory_router_router1_task56 - task_total_memory_router_router1_task57 - task_total_memory_router_router1_task58 - task_total_memory_router_router1_task59 - task_total_memory_router_router1_task6 - task_total_memory_router_router1_task60 - task_total_memory_router_router1_task61 - task_total_memory_router_router1_task62 - task_total_memory_router_router1_task63 - task_total_memory_router_router1_task64 - task_total_memory_router_router1_task65 - task_total_memory_router_router1_task66 - task_total_memory_router_router1_task67 - task_total_memory_router_router1_task68 - task_total_memory_router_router1_task69 - task_total_memory_router_router1_task7 - task_total_memory_router_router1_task8 - task_total_memory_router_router1_task9 >= -0.0\n", + "_C119645: -PE_mem_overflow1 + max_memory_overflow >= 0\n", + "_C119646: PE1_time_delay_max - t0_end_ - 250000.0*t_0_map_1 >= -250000.0\n", + "_C119647: PE1_time_delay_min - t0_start + 250000.0*t_0_map_1 <= 250000.0\n", + "_C119648: PE1_time_delay_max - t1_end_ - 250000.0*t_1_map_1 >= -250000.0\n", + "_C119649: PE1_time_delay_min - t1_start + 250000.0*t_1_map_1 <= 250000.0\n", + "_C119650: 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-250000.0\n", + "_C119914: -t63_end_ + t63_start - 250000.0*t_63_map_2 - t_send_63 + task_total_delay_router_router2_task63 >= -250000.0\n", + "_C119915: -250000.0*t_63_map_2 - t_mem_63 + task_total_memory_router_router2_task63 >= -250000.0\n", + "_C119916: -t64_end_ + t64_start - 250000.0*t_64_map_2 - t_send_64 + task_total_delay_router_router2_task64 >= -250000.0\n", + "_C119917: -250000.0*t_64_map_2 - t_mem_64 + task_total_memory_router_router2_task64 >= -250000.0\n", + "_C119918: -t65_end_ + t65_start - 250000.0*t_65_map_2 - t_send_65 + task_total_delay_router_router2_task65 >= -250000.0\n", + "_C119919: -250000.0*t_65_map_2 - t_mem_65 + task_total_memory_router_router2_task65 >= -250000.0\n", + "_C119920: -t66_end_ + t66_start - 250000.0*t_66_map_2 - t_send_66 + task_total_delay_router_router2_task66 >= -250000.0\n", + "_C119921: -250000.0*t_66_map_2 - t_mem_66 + task_total_memory_router_router2_task66 >= -250000.0\n", + "_C119922: -t67_end_ + t67_start - 250000.0*t_67_map_2 - t_send_67 + task_total_delay_router_router2_task67 >= -250000.0\n", + "_C119923: -250000.0*t_67_map_2 - t_mem_67 + task_total_memory_router_router2_task67 >= -250000.0\n", + "_C119924: -t68_end_ + t68_start - 250000.0*t_68_map_2 - t_send_68 + task_total_delay_router_router2_task68 >= -250000.0\n", + "_C119925: -250000.0*t_68_map_2 - t_mem_68 + task_total_memory_router_router2_task68 >= -250000.0\n", + "_C119926: -t69_end_ + t69_start - 250000.0*t_69_map_2 - t_send_69 + task_total_delay_router_router2_task69 >= -250000.0\n", + "_C119927: -250000.0*t_69_map_2 - t_mem_69 + task_total_memory_router_router2_task69 >= -250000.0\n", + "_C119928: PE_mem_overflow2 - task_total_memory_router_router2_task0 - task_total_memory_router_router2_task1 - task_total_memory_router_router2_task10 - task_total_memory_router_router2_task11 - task_total_memory_router_router2_task12 - task_total_memory_router_router2_task13 - task_total_memory_router_router2_task14 - task_total_memory_router_router2_task15 - task_total_memory_router_router2_task16 - task_total_memory_router_router2_task17 - task_total_memory_router_router2_task18 - task_total_memory_router_router2_task19 - task_total_memory_router_router2_task2 - task_total_memory_router_router2_task20 - task_total_memory_router_router2_task21 - task_total_memory_router_router2_task22 - task_total_memory_router_router2_task23 - task_total_memory_router_router2_task24 - task_total_memory_router_router2_task25 - task_total_memory_router_router2_task26 - task_total_memory_router_router2_task27 - task_total_memory_router_router2_task28 - task_total_memory_router_router2_task29 - task_total_memory_router_router2_task3 - task_total_memory_router_router2_task30 - task_total_memory_router_router2_task31 - task_total_memory_router_router2_task32 - task_total_memory_router_router2_task33 - task_total_memory_router_router2_task34 - task_total_memory_router_router2_task35 - task_total_memory_router_router2_task36 - task_total_memory_router_router2_task37 - task_total_memory_router_router2_task38 - task_total_memory_router_router2_task39 - task_total_memory_router_router2_task4 - task_total_memory_router_router2_task40 - task_total_memory_router_router2_task41 - task_total_memory_router_router2_task42 - task_total_memory_router_router2_task43 - task_total_memory_router_router2_task44 - task_total_memory_router_router2_task45 - task_total_memory_router_router2_task46 - task_total_memory_router_router2_task47 - task_total_memory_router_router2_task48 - task_total_memory_router_router2_task49 - task_total_memory_router_router2_task5 - task_total_memory_router_router2_task50 - task_total_memory_router_router2_task51 - task_total_memory_router_router2_task52 - task_total_memory_router_router2_task53 - task_total_memory_router_router2_task54 - task_total_memory_router_router2_task55 - task_total_memory_router_router2_task56 - task_total_memory_router_router2_task57 - task_total_memory_router_router2_task58 - task_total_memory_router_router2_task59 - task_total_memory_router_router2_task6 - task_total_memory_router_router2_task60 - task_total_memory_router_router2_task61 - task_total_memory_router_router2_task62 - task_total_memory_router_router2_task63 - task_total_memory_router_router2_task64 - task_total_memory_router_router2_task65 - task_total_memory_router_router2_task66 - task_total_memory_router_router2_task67 - task_total_memory_router_router2_task68 - task_total_memory_router_router2_task69 - task_total_memory_router_router2_task7 - task_total_memory_router_router2_task8 - task_total_memory_router_router2_task9 >= -0.0\n", + "_C119929: PE2_total_delay - task_total_delay_router_router2_task0 - task_total_delay_router_router2_task1 - task_total_delay_router_router2_task10 - task_total_delay_router_router2_task11 - task_total_delay_router_router2_task12 - task_total_delay_router_router2_task13 - task_total_delay_router_router2_task14 - task_total_delay_router_router2_task15 - task_total_delay_router_router2_task16 - task_total_delay_router_router2_task17 - task_total_delay_router_router2_task18 - task_total_delay_router_router2_task19 - task_total_delay_router_router2_task2 - task_total_delay_router_router2_task20 - task_total_delay_router_router2_task21 - task_total_delay_router_router2_task22 - task_total_delay_router_router2_task23 - task_total_delay_router_router2_task24 - task_total_delay_router_router2_task25 - task_total_delay_router_router2_task26 - task_total_delay_router_router2_task27 - task_total_delay_router_router2_task28 - task_total_delay_router_router2_task29 - task_total_delay_router_router2_task3 - task_total_delay_router_router2_task30 - task_total_delay_router_router2_task31 - task_total_delay_router_router2_task32 - task_total_delay_router_router2_task33 - task_total_delay_router_router2_task34 - task_total_delay_router_router2_task35 - task_total_delay_router_router2_task36 - task_total_delay_router_router2_task37 - task_total_delay_router_router2_task38 - task_total_delay_router_router2_task39 - task_total_delay_router_router2_task4 - task_total_delay_router_router2_task40 - task_total_delay_router_router2_task41 - task_total_delay_router_router2_task42 - task_total_delay_router_router2_task43 - task_total_delay_router_router2_task44 - task_total_delay_router_router2_task45 - task_total_delay_router_router2_task46 - task_total_delay_router_router2_task47 - task_total_delay_router_router2_task48 - task_total_delay_router_router2_task49 - task_total_delay_router_router2_task5 - task_total_delay_router_router2_task50 - task_total_delay_router_router2_task51 - task_total_delay_router_router2_task52 - task_total_delay_router_router2_task53 - task_total_delay_router_router2_task54 - task_total_delay_router_router2_task55 - task_total_delay_router_router2_task56 - task_total_delay_router_router2_task57 - task_total_delay_router_router2_task58 - task_total_delay_router_router2_task59 - task_total_delay_router_router2_task6 - task_total_delay_router_router2_task60 - task_total_delay_router_router2_task61 - task_total_delay_router_router2_task62 - task_total_delay_router_router2_task63 - task_total_delay_router_router2_task64 - task_total_delay_router_router2_task65 - task_total_delay_router_router2_task66 - task_total_delay_router_router2_task67 - task_total_delay_router_router2_task68 - task_total_delay_router_router2_task69 - task_total_delay_router_router2_task7 - task_total_delay_router_router2_task8 - task_total_delay_router_router2_task9 >= -0.0\n", + "_C119930: PE2_total_memory - task_total_memory_router_router2_task0 - task_total_memory_router_router2_task1 - task_total_memory_router_router2_task10 - task_total_memory_router_router2_task11 - task_total_memory_router_router2_task12 - task_total_memory_router_router2_task13 - task_total_memory_router_router2_task14 - task_total_memory_router_router2_task15 - task_total_memory_router_router2_task16 - task_total_memory_router_router2_task17 - task_total_memory_router_router2_task18 - task_total_memory_router_router2_task19 - task_total_memory_router_router2_task2 - task_total_memory_router_router2_task20 - task_total_memory_router_router2_task21 - task_total_memory_router_router2_task22 - task_total_memory_router_router2_task23 - task_total_memory_router_router2_task24 - task_total_memory_router_router2_task25 - task_total_memory_router_router2_task26 - task_total_memory_router_router2_task27 - task_total_memory_router_router2_task28 - task_total_memory_router_router2_task29 - task_total_memory_router_router2_task3 - task_total_memory_router_router2_task30 - task_total_memory_router_router2_task31 - task_total_memory_router_router2_task32 - task_total_memory_router_router2_task33 - task_total_memory_router_router2_task34 - task_total_memory_router_router2_task35 - task_total_memory_router_router2_task36 - task_total_memory_router_router2_task37 - task_total_memory_router_router2_task38 - task_total_memory_router_router2_task39 - task_total_memory_router_router2_task4 - task_total_memory_router_router2_task40 - task_total_memory_router_router2_task41 - task_total_memory_router_router2_task42 - task_total_memory_router_router2_task43 - task_total_memory_router_router2_task44 - task_total_memory_router_router2_task45 - task_total_memory_router_router2_task46 - task_total_memory_router_router2_task47 - task_total_memory_router_router2_task48 - task_total_memory_router_router2_task49 - task_total_memory_router_router2_task5 - task_total_memory_router_router2_task50 - task_total_memory_router_router2_task51 - task_total_memory_router_router2_task52 - task_total_memory_router_router2_task53 - task_total_memory_router_router2_task54 - task_total_memory_router_router2_task55 - task_total_memory_router_router2_task56 - task_total_memory_router_router2_task57 - task_total_memory_router_router2_task58 - task_total_memory_router_router2_task59 - task_total_memory_router_router2_task6 - task_total_memory_router_router2_task60 - task_total_memory_router_router2_task61 - task_total_memory_router_router2_task62 - task_total_memory_router_router2_task63 - task_total_memory_router_router2_task64 - task_total_memory_router_router2_task65 - task_total_memory_router_router2_task66 - task_total_memory_router_router2_task67 - task_total_memory_router_router2_task68 - task_total_memory_router_router2_task69 - task_total_memory_router_router2_task7 - task_total_memory_router_router2_task8 - task_total_memory_router_router2_task9 >= -0.0\n", + "_C119931: -PE_mem_overflow2 + max_memory_overflow >= 0\n", + "_C119932: PE2_time_delay_max - t0_end_ - 250000.0*t_0_map_2 >= -250000.0\n", + "_C119933: PE2_time_delay_min - t0_start + 250000.0*t_0_map_2 <= 250000.0\n", + "_C119934: PE2_time_delay_max - t1_end_ - 250000.0*t_1_map_2 >= -250000.0\n", + "_C119935: PE2_time_delay_min - t1_start + 250000.0*t_1_map_2 <= 250000.0\n", + "_C119936: PE2_time_delay_max - t2_end_ - 250000.0*t_2_map_2 >= -250000.0\n", + "_C119937: PE2_time_delay_min - t2_start + 250000.0*t_2_map_2 <= 250000.0\n", + "_C119938: PE2_time_delay_max - t3_end_ - 250000.0*t_3_map_2 >= -250000.0\n", + "_C119939: PE2_time_delay_min - t3_start + 250000.0*t_3_map_2 <= 250000.0\n", + "_C119940: PE2_time_delay_max - t4_end_ - 250000.0*t_4_map_2 >= -250000.0\n", + "_C119941: PE2_time_delay_min - t4_start + 250000.0*t_4_map_2 <= 250000.0\n", + "_C119942: PE2_time_delay_max - t5_end_ - 250000.0*t_5_map_2 >= -250000.0\n", + "_C119943: PE2_time_delay_min - t5_start + 250000.0*t_5_map_2 <= 250000.0\n", + "_C119944: PE2_time_delay_max - t6_end_ - 250000.0*t_6_map_2 >= -250000.0\n", + "_C119945: PE2_time_delay_min - t6_start + 250000.0*t_6_map_2 <= 250000.0\n", + "_C119946: PE2_time_delay_max - t7_end_ - 250000.0*t_7_map_2 >= -250000.0\n", + "_C119947: PE2_time_delay_min - t7_start + 250000.0*t_7_map_2 <= 250000.0\n", + "_C119948: PE2_time_delay_max - t8_end_ - 250000.0*t_8_map_2 >= -250000.0\n", + "_C119949: PE2_time_delay_min - t8_start + 250000.0*t_8_map_2 <= 250000.0\n", + "_C119950: PE2_time_delay_max - t9_end_ - 250000.0*t_9_map_2 >= -250000.0\n", + "_C119951: PE2_time_delay_min - t9_start + 250000.0*t_9_map_2 <= 250000.0\n", + "_C119952: PE2_time_delay_max - t10_end_ - 250000.0*t_10_map_2 >= -250000.0\n", + "_C119953: PE2_time_delay_min - t10_start + 250000.0*t_10_map_2 <= 250000.0\n", + "_C119954: PE2_time_delay_max - t11_end_ - 250000.0*t_11_map_2 >= -250000.0\n", + "_C119955: PE2_time_delay_min - t11_start + 250000.0*t_11_map_2 <= 250000.0\n", + "_C119956: PE2_time_delay_max - t12_end_ - 250000.0*t_12_map_2 >= -250000.0\n", + "_C119957: PE2_time_delay_min - t12_start + 250000.0*t_12_map_2 <= 250000.0\n", + "_C119958: PE2_time_delay_max - t13_end_ - 250000.0*t_13_map_2 >= -250000.0\n", + "_C119959: PE2_time_delay_min - t13_start + 250000.0*t_13_map_2 <= 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"_C119972: PE2_time_delay_max - t20_end_ - 250000.0*t_20_map_2 >= -250000.0\n", + "_C119973: PE2_time_delay_min - t20_start + 250000.0*t_20_map_2 <= 250000.0\n", + "_C119974: PE2_time_delay_max - t21_end_ - 250000.0*t_21_map_2 >= -250000.0\n", + "_C119975: PE2_time_delay_min - t21_start + 250000.0*t_21_map_2 <= 250000.0\n", + "_C119976: PE2_time_delay_max - t22_end_ - 250000.0*t_22_map_2 >= -250000.0\n", + "_C119977: PE2_time_delay_min - t22_start + 250000.0*t_22_map_2 <= 250000.0\n", + "_C119978: PE2_time_delay_max - t23_end_ - 250000.0*t_23_map_2 >= -250000.0\n", + "_C119979: PE2_time_delay_min - t23_start + 250000.0*t_23_map_2 <= 250000.0\n", + "_C119980: PE2_time_delay_max - t24_end_ - 250000.0*t_24_map_2 >= -250000.0\n", + "_C119981: PE2_time_delay_min - t24_start + 250000.0*t_24_map_2 <= 250000.0\n", + "_C119982: PE2_time_delay_max - t25_end_ - 250000.0*t_25_map_2 >= -250000.0\n", + "_C119983: PE2_time_delay_min - t25_start + 250000.0*t_25_map_2 <= 250000.0\n", + "_C119984: PE2_time_delay_max - t26_end_ - 250000.0*t_26_map_2 >= -250000.0\n", + "_C119985: PE2_time_delay_min - t26_start + 250000.0*t_26_map_2 <= 250000.0\n", + "_C119986: PE2_time_delay_max - t27_end_ - 250000.0*t_27_map_2 >= -250000.0\n", + "_C119987: PE2_time_delay_min - t27_start + 250000.0*t_27_map_2 <= 250000.0\n", + "_C119988: PE2_time_delay_max - t28_end_ - 250000.0*t_28_map_2 >= -250000.0\n", + "_C119989: PE2_time_delay_min - t28_start + 250000.0*t_28_map_2 <= 250000.0\n", + "_C119990: PE2_time_delay_max - t29_end_ - 250000.0*t_29_map_2 >= -250000.0\n", + "_C119991: PE2_time_delay_min - t29_start + 250000.0*t_29_map_2 <= 250000.0\n", + "_C119992: PE2_time_delay_max - t30_end_ - 250000.0*t_30_map_2 >= -250000.0\n", + "_C119993: PE2_time_delay_min - t30_start + 250000.0*t_30_map_2 <= 250000.0\n", + "_C119994: PE2_time_delay_max - t31_end_ - 250000.0*t_31_map_2 >= -250000.0\n", + "_C119995: PE2_time_delay_min - t31_start + 250000.0*t_31_map_2 <= 250000.0\n", + "_C119996: PE2_time_delay_max - t32_end_ - 250000.0*t_32_map_2 >= -250000.0\n", + "_C119997: PE2_time_delay_min - t32_start + 250000.0*t_32_map_2 <= 250000.0\n", + "_C119998: PE2_time_delay_max - t33_end_ - 250000.0*t_33_map_2 >= -250000.0\n", + "_C119999: PE2_time_delay_min - t33_start + 250000.0*t_33_map_2 <= 250000.0\n", + "_C120000: PE2_time_delay_max - t34_end_ - 250000.0*t_34_map_2 >= -250000.0\n", + "_C120001: PE2_time_delay_min - t34_start + 250000.0*t_34_map_2 <= 250000.0\n", + "_C120002: PE2_time_delay_max - t35_end_ - 250000.0*t_35_map_2 >= -250000.0\n", + "_C120003: PE2_time_delay_min - t35_start + 250000.0*t_35_map_2 <= 250000.0\n", + "_C120004: PE2_time_delay_max - t36_end_ - 250000.0*t_36_map_2 >= -250000.0\n", + "_C120005: PE2_time_delay_min - t36_start + 250000.0*t_36_map_2 <= 250000.0\n", + "_C120006: PE2_time_delay_max - t37_end_ - 250000.0*t_37_map_2 >= -250000.0\n", + "_C120007: PE2_time_delay_min - t37_start + 250000.0*t_37_map_2 <= 250000.0\n", + "_C120008: PE2_time_delay_max - t38_end_ - 250000.0*t_38_map_2 >= -250000.0\n", + "_C120009: PE2_time_delay_min - t38_start + 250000.0*t_38_map_2 <= 250000.0\n", + "_C120010: PE2_time_delay_max - t39_end_ - 250000.0*t_39_map_2 >= -250000.0\n", + "_C120011: PE2_time_delay_min - t39_start + 250000.0*t_39_map_2 <= 250000.0\n", + "_C120012: PE2_time_delay_max - t40_end_ - 250000.0*t_40_map_2 >= -250000.0\n", + "_C120013: PE2_time_delay_min - t40_start + 250000.0*t_40_map_2 <= 250000.0\n", + "_C120014: PE2_time_delay_max - t41_end_ - 250000.0*t_41_map_2 >= -250000.0\n", + "_C120015: PE2_time_delay_min - t41_start + 250000.0*t_41_map_2 <= 250000.0\n", + "_C120016: PE2_time_delay_max - t42_end_ - 250000.0*t_42_map_2 >= -250000.0\n", + "_C120017: PE2_time_delay_min - t42_start + 250000.0*t_42_map_2 <= 250000.0\n", + "_C120018: PE2_time_delay_max - t43_end_ - 250000.0*t_43_map_2 >= -250000.0\n", + "_C120019: PE2_time_delay_min - t43_start + 250000.0*t_43_map_2 <= 250000.0\n", + "_C120020: PE2_time_delay_max - t44_end_ - 250000.0*t_44_map_2 >= -250000.0\n", + "_C120021: PE2_time_delay_min - t44_start + 250000.0*t_44_map_2 <= 250000.0\n", + "_C120022: PE2_time_delay_max - t45_end_ - 250000.0*t_45_map_2 >= -250000.0\n", + "_C120023: PE2_time_delay_min - t45_start + 250000.0*t_45_map_2 <= 250000.0\n", + "_C120024: PE2_time_delay_max - t46_end_ - 250000.0*t_46_map_2 >= -250000.0\n", + "_C120025: PE2_time_delay_min - t46_start + 250000.0*t_46_map_2 <= 250000.0\n", + "_C120026: PE2_time_delay_max - t47_end_ - 250000.0*t_47_map_2 >= -250000.0\n", + "_C120027: PE2_time_delay_min - t47_start + 250000.0*t_47_map_2 <= 250000.0\n", + "_C120028: PE2_time_delay_max - t48_end_ - 250000.0*t_48_map_2 >= -250000.0\n", + "_C120029: PE2_time_delay_min - t48_start + 250000.0*t_48_map_2 <= 250000.0\n", + "_C120030: PE2_time_delay_max - t49_end_ - 250000.0*t_49_map_2 >= -250000.0\n", + "_C120031: PE2_time_delay_min - t49_start + 250000.0*t_49_map_2 <= 250000.0\n", + "_C120032: PE2_time_delay_max - t50_end_ - 250000.0*t_50_map_2 >= -250000.0\n", + "_C120033: PE2_time_delay_min - t50_start + 250000.0*t_50_map_2 <= 250000.0\n", + "_C120034: PE2_time_delay_max - t51_end_ - 250000.0*t_51_map_2 >= -250000.0\n", + "_C120035: PE2_time_delay_min - t51_start + 250000.0*t_51_map_2 <= 250000.0\n", + "_C120036: PE2_time_delay_max - t52_end_ - 250000.0*t_52_map_2 >= -250000.0\n", + "_C120037: PE2_time_delay_min - t52_start + 250000.0*t_52_map_2 <= 250000.0\n", + "_C120038: PE2_time_delay_max - t53_end_ - 250000.0*t_53_map_2 >= -250000.0\n", + "_C120039: PE2_time_delay_min - t53_start + 250000.0*t_53_map_2 <= 250000.0\n", + "_C120040: PE2_time_delay_max - t54_end_ - 250000.0*t_54_map_2 >= -250000.0\n", + "_C120041: PE2_time_delay_min - t54_start + 250000.0*t_54_map_2 <= 250000.0\n", + "_C120042: PE2_time_delay_max - t55_end_ - 250000.0*t_55_map_2 >= -250000.0\n", + "_C120043: PE2_time_delay_min - t55_start + 250000.0*t_55_map_2 <= 250000.0\n", + "_C120044: PE2_time_delay_max - t56_end_ - 250000.0*t_56_map_2 >= -250000.0\n", + "_C120045: PE2_time_delay_min - t56_start + 250000.0*t_56_map_2 <= 250000.0\n", + "_C120046: PE2_time_delay_max - t57_end_ - 250000.0*t_57_map_2 >= -250000.0\n", + "_C120047: PE2_time_delay_min - t57_start + 250000.0*t_57_map_2 <= 250000.0\n", + "_C120048: PE2_time_delay_max - t58_end_ - 250000.0*t_58_map_2 >= -250000.0\n", + "_C120049: PE2_time_delay_min - t58_start + 250000.0*t_58_map_2 <= 250000.0\n", + "_C120050: PE2_time_delay_max - t59_end_ - 250000.0*t_59_map_2 >= -250000.0\n", + "_C120051: PE2_time_delay_min - t59_start + 250000.0*t_59_map_2 <= 250000.0\n", + "_C120052: PE2_time_delay_max - t60_end_ - 250000.0*t_60_map_2 >= -250000.0\n", + "_C120053: PE2_time_delay_min - t60_start + 250000.0*t_60_map_2 <= 250000.0\n", + "_C120054: PE2_time_delay_max - t61_end_ - 250000.0*t_61_map_2 >= -250000.0\n", + "_C120055: PE2_time_delay_min - t61_start + 250000.0*t_61_map_2 <= 250000.0\n", + "_C120056: PE2_time_delay_max - t62_end_ - 250000.0*t_62_map_2 >= -250000.0\n", + "_C120057: PE2_time_delay_min - t62_start + 250000.0*t_62_map_2 <= 250000.0\n", + "_C120058: PE2_time_delay_max - t63_end_ - 250000.0*t_63_map_2 >= -250000.0\n", + "_C120059: PE2_time_delay_min - t63_start + 250000.0*t_63_map_2 <= 250000.0\n", + "_C120060: PE2_time_delay_max - t64_end_ - 250000.0*t_64_map_2 >= -250000.0\n", + "_C120061: PE2_time_delay_min - t64_start + 250000.0*t_64_map_2 <= 250000.0\n", + "_C120062: PE2_time_delay_max - t65_end_ - 250000.0*t_65_map_2 >= -250000.0\n", + "_C120063: PE2_time_delay_min - t65_start + 250000.0*t_65_map_2 <= 250000.0\n", + "_C120064: PE2_time_delay_max - t66_end_ - 250000.0*t_66_map_2 >= -250000.0\n", + "_C120065: PE2_time_delay_min - t66_start + 250000.0*t_66_map_2 <= 250000.0\n", + "_C120066: PE2_time_delay_max - t67_end_ - 250000.0*t_67_map_2 >= -250000.0\n", + "_C120067: PE2_time_delay_min - t67_start + 250000.0*t_67_map_2 <= 250000.0\n", + "_C120068: PE2_time_delay_max - t68_end_ - 250000.0*t_68_map_2 >= -250000.0\n", + "_C120069: PE2_time_delay_min - t68_start + 250000.0*t_68_map_2 <= 250000.0\n", + "_C120070: PE2_time_delay_max - t69_end_ - 250000.0*t_69_map_2 >= -250000.0\n", + "_C120071: PE2_time_delay_min - t69_start + 250000.0*t_69_map_2 <= 250000.0\n", + "_C120072: -PE2_time_delay_max + PE2_time_delay_min + PE2_total_time_delay = 0\n", + "_C120073: -PE2_total_time_delay + max_router_delay >= 0\n", + "_C120074: -t0_end_ + t0_start - 250000.0*t_0_map_3 - t_send_0 + task_total_delay_router_router3_task0 >= -250000.0\n", + "_C120075: -250000.0*t_0_map_3 - t_mem_0 + task_total_memory_router_router3_task0 >= -250000.0\n", + "_C120076: -t1_end_ + t1_start - 250000.0*t_1_map_3 - t_send_1 + task_total_delay_router_router3_task1 >= -250000.0\n", + "_C120077: -250000.0*t_1_map_3 - t_mem_1 + task_total_memory_router_router3_task1 >= -250000.0\n", + "_C120078: -t2_end_ + t2_start - 250000.0*t_2_map_3 - t_send_2 + task_total_delay_router_router3_task2 >= -250000.0\n", + "_C120079: -250000.0*t_2_map_3 - t_mem_2 + task_total_memory_router_router3_task2 >= -250000.0\n", + "_C120080: -t3_end_ + t3_start - 250000.0*t_3_map_3 - t_send_3 + task_total_delay_router_router3_task3 >= -250000.0\n", + "_C120081: -250000.0*t_3_map_3 - t_mem_3 + task_total_memory_router_router3_task3 >= -250000.0\n", + "_C120082: -t4_end_ + t4_start - 250000.0*t_4_map_3 - t_send_4 + task_total_delay_router_router3_task4 >= -250000.0\n", + "_C120083: -250000.0*t_4_map_3 - t_mem_4 + task_total_memory_router_router3_task4 >= -250000.0\n", + "_C120084: -t5_end_ + t5_start - 250000.0*t_5_map_3 - t_send_5 + task_total_delay_router_router3_task5 >= -250000.0\n", + "_C120085: -250000.0*t_5_map_3 - t_mem_5 + task_total_memory_router_router3_task5 >= -250000.0\n", + "_C120086: -t6_end_ + t6_start - 250000.0*t_6_map_3 - t_send_6 + task_total_delay_router_router3_task6 >= -250000.0\n", + "_C120087: -250000.0*t_6_map_3 - t_mem_6 + task_total_memory_router_router3_task6 >= -250000.0\n", + "_C120088: -t7_end_ + t7_start - 250000.0*t_7_map_3 - t_send_7 + task_total_delay_router_router3_task7 >= -250000.0\n", + "_C120089: -250000.0*t_7_map_3 - t_mem_7 + task_total_memory_router_router3_task7 >= -250000.0\n", + "_C120090: -t8_end_ + t8_start - 250000.0*t_8_map_3 - t_send_8 + task_total_delay_router_router3_task8 >= -250000.0\n", + "_C120091: -250000.0*t_8_map_3 - t_mem_8 + task_total_memory_router_router3_task8 >= -250000.0\n", + "_C120092: -t9_end_ + t9_start - 250000.0*t_9_map_3 - t_send_9 + task_total_delay_router_router3_task9 >= -250000.0\n", + "_C120093: -250000.0*t_9_map_3 - t_mem_9 + task_total_memory_router_router3_task9 >= -250000.0\n", + "_C120094: -t10_end_ + t10_start - 250000.0*t_10_map_3 - t_send_10 + task_total_delay_router_router3_task10 >= -250000.0\n", + "_C120095: -250000.0*t_10_map_3 - t_mem_10 + task_total_memory_router_router3_task10 >= -250000.0\n", + "_C120096: -t11_end_ + t11_start - 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task_total_delay_router_router3_task58 >= -250000.0\n", + "_C120191: -250000.0*t_58_map_3 - t_mem_58 + task_total_memory_router_router3_task58 >= -250000.0\n", + "_C120192: -t59_end_ + t59_start - 250000.0*t_59_map_3 - t_send_59 + task_total_delay_router_router3_task59 >= -250000.0\n", + "_C120193: -250000.0*t_59_map_3 - t_mem_59 + task_total_memory_router_router3_task59 >= -250000.0\n", + "_C120194: -t60_end_ + t60_start - 250000.0*t_60_map_3 - t_send_60 + task_total_delay_router_router3_task60 >= -250000.0\n", + "_C120195: -250000.0*t_60_map_3 - t_mem_60 + task_total_memory_router_router3_task60 >= -250000.0\n", + "_C120196: -t61_end_ + t61_start - 250000.0*t_61_map_3 - t_send_61 + task_total_delay_router_router3_task61 >= -250000.0\n", + "_C120197: -250000.0*t_61_map_3 - t_mem_61 + task_total_memory_router_router3_task61 >= -250000.0\n", + "_C120198: -t62_end_ + t62_start - 250000.0*t_62_map_3 - t_send_62 + task_total_delay_router_router3_task62 >= -250000.0\n", + "_C120199: -250000.0*t_62_map_3 - t_mem_62 + task_total_memory_router_router3_task62 >= -250000.0\n", + "_C120200: -t63_end_ + t63_start - 250000.0*t_63_map_3 - t_send_63 + task_total_delay_router_router3_task63 >= -250000.0\n", + "_C120201: -250000.0*t_63_map_3 - t_mem_63 + task_total_memory_router_router3_task63 >= -250000.0\n", + "_C120202: -t64_end_ + t64_start - 250000.0*t_64_map_3 - t_send_64 + task_total_delay_router_router3_task64 >= -250000.0\n", + "_C120203: -250000.0*t_64_map_3 - t_mem_64 + task_total_memory_router_router3_task64 >= -250000.0\n", + "_C120204: -t65_end_ + t65_start - 250000.0*t_65_map_3 - t_send_65 + task_total_delay_router_router3_task65 >= -250000.0\n", + "_C120205: -250000.0*t_65_map_3 - t_mem_65 + task_total_memory_router_router3_task65 >= -250000.0\n", + "_C120206: -t66_end_ + t66_start - 250000.0*t_66_map_3 - t_send_66 + task_total_delay_router_router3_task66 >= -250000.0\n", + "_C120207: -250000.0*t_66_map_3 - t_mem_66 + task_total_memory_router_router3_task66 >= 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task_total_memory_router_router3_task14 - task_total_memory_router_router3_task15 - task_total_memory_router_router3_task16 - task_total_memory_router_router3_task17 - task_total_memory_router_router3_task18 - task_total_memory_router_router3_task19 - task_total_memory_router_router3_task2 - task_total_memory_router_router3_task20 - task_total_memory_router_router3_task21 - task_total_memory_router_router3_task22 - task_total_memory_router_router3_task23 - task_total_memory_router_router3_task24 - task_total_memory_router_router3_task25 - task_total_memory_router_router3_task26 - task_total_memory_router_router3_task27 - task_total_memory_router_router3_task28 - task_total_memory_router_router3_task29 - task_total_memory_router_router3_task3 - task_total_memory_router_router3_task30 - task_total_memory_router_router3_task31 - task_total_memory_router_router3_task32 - task_total_memory_router_router3_task33 - task_total_memory_router_router3_task34 - task_total_memory_router_router3_task35 - task_total_memory_router_router3_task36 - task_total_memory_router_router3_task37 - task_total_memory_router_router3_task38 - task_total_memory_router_router3_task39 - task_total_memory_router_router3_task4 - task_total_memory_router_router3_task40 - task_total_memory_router_router3_task41 - task_total_memory_router_router3_task42 - task_total_memory_router_router3_task43 - task_total_memory_router_router3_task44 - task_total_memory_router_router3_task45 - task_total_memory_router_router3_task46 - task_total_memory_router_router3_task47 - task_total_memory_router_router3_task48 - task_total_memory_router_router3_task49 - task_total_memory_router_router3_task5 - task_total_memory_router_router3_task50 - task_total_memory_router_router3_task51 - task_total_memory_router_router3_task52 - task_total_memory_router_router3_task53 - task_total_memory_router_router3_task54 - task_total_memory_router_router3_task55 - task_total_memory_router_router3_task56 - task_total_memory_router_router3_task57 - task_total_memory_router_router3_task58 - task_total_memory_router_router3_task59 - task_total_memory_router_router3_task6 - task_total_memory_router_router3_task60 - task_total_memory_router_router3_task61 - task_total_memory_router_router3_task62 - task_total_memory_router_router3_task63 - task_total_memory_router_router3_task64 - task_total_memory_router_router3_task65 - task_total_memory_router_router3_task66 - task_total_memory_router_router3_task67 - task_total_memory_router_router3_task68 - task_total_memory_router_router3_task69 - task_total_memory_router_router3_task7 - task_total_memory_router_router3_task8 - task_total_memory_router_router3_task9 >= -0.0\n", + "_C120215: PE3_total_delay - task_total_delay_router_router3_task0 - task_total_delay_router_router3_task1 - task_total_delay_router_router3_task10 - task_total_delay_router_router3_task11 - task_total_delay_router_router3_task12 - task_total_delay_router_router3_task13 - task_total_delay_router_router3_task14 - task_total_delay_router_router3_task15 - task_total_delay_router_router3_task16 - task_total_delay_router_router3_task17 - task_total_delay_router_router3_task18 - task_total_delay_router_router3_task19 - task_total_delay_router_router3_task2 - task_total_delay_router_router3_task20 - task_total_delay_router_router3_task21 - task_total_delay_router_router3_task22 - task_total_delay_router_router3_task23 - task_total_delay_router_router3_task24 - task_total_delay_router_router3_task25 - task_total_delay_router_router3_task26 - task_total_delay_router_router3_task27 - task_total_delay_router_router3_task28 - task_total_delay_router_router3_task29 - task_total_delay_router_router3_task3 - task_total_delay_router_router3_task30 - task_total_delay_router_router3_task31 - task_total_delay_router_router3_task32 - task_total_delay_router_router3_task33 - task_total_delay_router_router3_task34 - task_total_delay_router_router3_task35 - task_total_delay_router_router3_task36 - task_total_delay_router_router3_task37 - task_total_delay_router_router3_task38 - task_total_delay_router_router3_task39 - task_total_delay_router_router3_task4 - task_total_delay_router_router3_task40 - task_total_delay_router_router3_task41 - task_total_delay_router_router3_task42 - task_total_delay_router_router3_task43 - task_total_delay_router_router3_task44 - task_total_delay_router_router3_task45 - task_total_delay_router_router3_task46 - task_total_delay_router_router3_task47 - task_total_delay_router_router3_task48 - task_total_delay_router_router3_task49 - task_total_delay_router_router3_task5 - task_total_delay_router_router3_task50 - task_total_delay_router_router3_task51 - task_total_delay_router_router3_task52 - task_total_delay_router_router3_task53 - task_total_delay_router_router3_task54 - task_total_delay_router_router3_task55 - task_total_delay_router_router3_task56 - task_total_delay_router_router3_task57 - task_total_delay_router_router3_task58 - task_total_delay_router_router3_task59 - task_total_delay_router_router3_task6 - task_total_delay_router_router3_task60 - task_total_delay_router_router3_task61 - task_total_delay_router_router3_task62 - task_total_delay_router_router3_task63 - task_total_delay_router_router3_task64 - task_total_delay_router_router3_task65 - task_total_delay_router_router3_task66 - task_total_delay_router_router3_task67 - task_total_delay_router_router3_task68 - task_total_delay_router_router3_task69 - task_total_delay_router_router3_task7 - task_total_delay_router_router3_task8 - task_total_delay_router_router3_task9 >= -0.0\n", + "_C120216: PE3_total_memory - task_total_memory_router_router3_task0 - task_total_memory_router_router3_task1 - task_total_memory_router_router3_task10 - task_total_memory_router_router3_task11 - task_total_memory_router_router3_task12 - task_total_memory_router_router3_task13 - task_total_memory_router_router3_task14 - task_total_memory_router_router3_task15 - task_total_memory_router_router3_task16 - task_total_memory_router_router3_task17 - task_total_memory_router_router3_task18 - task_total_memory_router_router3_task19 - task_total_memory_router_router3_task2 - task_total_memory_router_router3_task20 - task_total_memory_router_router3_task21 - task_total_memory_router_router3_task22 - task_total_memory_router_router3_task23 - task_total_memory_router_router3_task24 - task_total_memory_router_router3_task25 - task_total_memory_router_router3_task26 - task_total_memory_router_router3_task27 - task_total_memory_router_router3_task28 - task_total_memory_router_router3_task29 - task_total_memory_router_router3_task3 - task_total_memory_router_router3_task30 - task_total_memory_router_router3_task31 - task_total_memory_router_router3_task32 - task_total_memory_router_router3_task33 - task_total_memory_router_router3_task34 - task_total_memory_router_router3_task35 - task_total_memory_router_router3_task36 - task_total_memory_router_router3_task37 - task_total_memory_router_router3_task38 - task_total_memory_router_router3_task39 - task_total_memory_router_router3_task4 - task_total_memory_router_router3_task40 - task_total_memory_router_router3_task41 - task_total_memory_router_router3_task42 - task_total_memory_router_router3_task43 - task_total_memory_router_router3_task44 - task_total_memory_router_router3_task45 - task_total_memory_router_router3_task46 - task_total_memory_router_router3_task47 - task_total_memory_router_router3_task48 - task_total_memory_router_router3_task49 - task_total_memory_router_router3_task5 - task_total_memory_router_router3_task50 - task_total_memory_router_router3_task51 - task_total_memory_router_router3_task52 - task_total_memory_router_router3_task53 - task_total_memory_router_router3_task54 - task_total_memory_router_router3_task55 - task_total_memory_router_router3_task56 - task_total_memory_router_router3_task57 - task_total_memory_router_router3_task58 - task_total_memory_router_router3_task59 - task_total_memory_router_router3_task6 - task_total_memory_router_router3_task60 - task_total_memory_router_router3_task61 - task_total_memory_router_router3_task62 - task_total_memory_router_router3_task63 - task_total_memory_router_router3_task64 - task_total_memory_router_router3_task65 - task_total_memory_router_router3_task66 - task_total_memory_router_router3_task67 - task_total_memory_router_router3_task68 - task_total_memory_router_router3_task69 - task_total_memory_router_router3_task7 - task_total_memory_router_router3_task8 - task_total_memory_router_router3_task9 >= -0.0\n", + "_C120217: -PE_mem_overflow3 + max_memory_overflow >= 0\n", + "_C120218: PE3_time_delay_max - t0_end_ - 250000.0*t_0_map_3 >= -250000.0\n", + "_C120219: PE3_time_delay_min - t0_start + 250000.0*t_0_map_3 <= 250000.0\n", + "_C120220: PE3_time_delay_max - t1_end_ - 250000.0*t_1_map_3 >= -250000.0\n", + "_C120221: PE3_time_delay_min - t1_start + 250000.0*t_1_map_3 <= 250000.0\n", + "_C120222: PE3_time_delay_max - t2_end_ - 250000.0*t_2_map_3 >= -250000.0\n", + "_C120223: PE3_time_delay_min - t2_start + 250000.0*t_2_map_3 <= 250000.0\n", + "_C120224: PE3_time_delay_max - t3_end_ - 250000.0*t_3_map_3 >= -250000.0\n", + "_C120225: PE3_time_delay_min - t3_start + 250000.0*t_3_map_3 <= 250000.0\n", + "_C120226: PE3_time_delay_max - t4_end_ - 250000.0*t_4_map_3 >= -250000.0\n", + "_C120227: PE3_time_delay_min - t4_start + 250000.0*t_4_map_3 <= 250000.0\n", + "_C120228: PE3_time_delay_max - t5_end_ - 250000.0*t_5_map_3 >= -250000.0\n", + "_C120229: PE3_time_delay_min - t5_start + 250000.0*t_5_map_3 <= 250000.0\n", + "_C120230: PE3_time_delay_max - t6_end_ - 250000.0*t_6_map_3 >= -250000.0\n", + "_C120231: PE3_time_delay_min - t6_start + 250000.0*t_6_map_3 <= 250000.0\n", + "_C120232: PE3_time_delay_max - t7_end_ - 250000.0*t_7_map_3 >= -250000.0\n", + "_C120233: PE3_time_delay_min - t7_start + 250000.0*t_7_map_3 <= 250000.0\n", + "_C120234: PE3_time_delay_max - t8_end_ - 250000.0*t_8_map_3 >= -250000.0\n", + "_C120235: PE3_time_delay_min - t8_start + 250000.0*t_8_map_3 <= 250000.0\n", + "_C120236: PE3_time_delay_max - t9_end_ - 250000.0*t_9_map_3 >= -250000.0\n", + "_C120237: PE3_time_delay_min - t9_start + 250000.0*t_9_map_3 <= 250000.0\n", + "_C120238: PE3_time_delay_max - t10_end_ - 250000.0*t_10_map_3 >= -250000.0\n", + "_C120239: PE3_time_delay_min - t10_start + 250000.0*t_10_map_3 <= 250000.0\n", + "_C120240: PE3_time_delay_max - t11_end_ - 250000.0*t_11_map_3 >= -250000.0\n", + "_C120241: PE3_time_delay_min - t11_start + 250000.0*t_11_map_3 <= 250000.0\n", + "_C120242: PE3_time_delay_max - t12_end_ - 250000.0*t_12_map_3 >= -250000.0\n", + "_C120243: PE3_time_delay_min - t12_start + 250000.0*t_12_map_3 <= 250000.0\n", + "_C120244: PE3_time_delay_max - t13_end_ - 250000.0*t_13_map_3 >= -250000.0\n", + "_C120245: PE3_time_delay_min - t13_start + 250000.0*t_13_map_3 <= 250000.0\n", + "_C120246: PE3_time_delay_max - t14_end_ - 250000.0*t_14_map_3 >= -250000.0\n", + "_C120247: PE3_time_delay_min - t14_start + 250000.0*t_14_map_3 <= 250000.0\n", + "_C120248: PE3_time_delay_max - t15_end_ - 250000.0*t_15_map_3 >= -250000.0\n", + "_C120249: PE3_time_delay_min - t15_start + 250000.0*t_15_map_3 <= 250000.0\n", + "_C120250: PE3_time_delay_max - t16_end_ - 250000.0*t_16_map_3 >= -250000.0\n", + "_C120251: PE3_time_delay_min - t16_start + 250000.0*t_16_map_3 <= 250000.0\n", + "_C120252: PE3_time_delay_max - t17_end_ - 250000.0*t_17_map_3 >= -250000.0\n", + "_C120253: PE3_time_delay_min - t17_start + 250000.0*t_17_map_3 <= 250000.0\n", + "_C120254: PE3_time_delay_max - t18_end_ - 250000.0*t_18_map_3 >= -250000.0\n", + "_C120255: PE3_time_delay_min - t18_start + 250000.0*t_18_map_3 <= 250000.0\n", + "_C120256: PE3_time_delay_max - t19_end_ - 250000.0*t_19_map_3 >= -250000.0\n", + "_C120257: PE3_time_delay_min - t19_start + 250000.0*t_19_map_3 <= 250000.0\n", + "_C120258: PE3_time_delay_max - t20_end_ - 250000.0*t_20_map_3 >= -250000.0\n", + "_C120259: PE3_time_delay_min - t20_start + 250000.0*t_20_map_3 <= 250000.0\n", + "_C120260: PE3_time_delay_max - t21_end_ - 250000.0*t_21_map_3 >= -250000.0\n", + "_C120261: PE3_time_delay_min - t21_start + 250000.0*t_21_map_3 <= 250000.0\n", + "_C120262: PE3_time_delay_max - t22_end_ - 250000.0*t_22_map_3 >= -250000.0\n", + "_C120263: PE3_time_delay_min - t22_start + 250000.0*t_22_map_3 <= 250000.0\n", + "_C120264: PE3_time_delay_max - t23_end_ - 250000.0*t_23_map_3 >= -250000.0\n", + "_C120265: PE3_time_delay_min - t23_start + 250000.0*t_23_map_3 <= 250000.0\n", + "_C120266: PE3_time_delay_max - t24_end_ - 250000.0*t_24_map_3 >= -250000.0\n", + "_C120267: PE3_time_delay_min - t24_start + 250000.0*t_24_map_3 <= 250000.0\n", + "_C120268: PE3_time_delay_max - t25_end_ - 250000.0*t_25_map_3 >= -250000.0\n", + "_C120269: PE3_time_delay_min - t25_start + 250000.0*t_25_map_3 <= 250000.0\n", + "_C120270: PE3_time_delay_max - t26_end_ - 250000.0*t_26_map_3 >= -250000.0\n", + "_C120271: PE3_time_delay_min - t26_start + 250000.0*t_26_map_3 <= 250000.0\n", + "_C120272: PE3_time_delay_max - t27_end_ - 250000.0*t_27_map_3 >= -250000.0\n", + "_C120273: PE3_time_delay_min - t27_start + 250000.0*t_27_map_3 <= 250000.0\n", + "_C120274: PE3_time_delay_max - t28_end_ - 250000.0*t_28_map_3 >= -250000.0\n", + "_C120275: PE3_time_delay_min - t28_start + 250000.0*t_28_map_3 <= 250000.0\n", + "_C120276: PE3_time_delay_max - t29_end_ - 250000.0*t_29_map_3 >= -250000.0\n", + "_C120277: PE3_time_delay_min - t29_start + 250000.0*t_29_map_3 <= 250000.0\n", + "_C120278: PE3_time_delay_max - t30_end_ - 250000.0*t_30_map_3 >= -250000.0\n", + "_C120279: PE3_time_delay_min - t30_start + 250000.0*t_30_map_3 <= 250000.0\n", + "_C120280: PE3_time_delay_max - t31_end_ - 250000.0*t_31_map_3 >= -250000.0\n", + "_C120281: PE3_time_delay_min - t31_start + 250000.0*t_31_map_3 <= 250000.0\n", + "_C120282: PE3_time_delay_max - t32_end_ - 250000.0*t_32_map_3 >= -250000.0\n", + "_C120283: PE3_time_delay_min - t32_start + 250000.0*t_32_map_3 <= 250000.0\n", + "_C120284: PE3_time_delay_max - t33_end_ - 250000.0*t_33_map_3 >= -250000.0\n", + "_C120285: PE3_time_delay_min - t33_start + 250000.0*t_33_map_3 <= 250000.0\n", + "_C120286: PE3_time_delay_max - t34_end_ - 250000.0*t_34_map_3 >= -250000.0\n", + "_C120287: PE3_time_delay_min - t34_start + 250000.0*t_34_map_3 <= 250000.0\n", + "_C120288: PE3_time_delay_max - t35_end_ - 250000.0*t_35_map_3 >= -250000.0\n", + "_C120289: PE3_time_delay_min - t35_start + 250000.0*t_35_map_3 <= 250000.0\n", + "_C120290: PE3_time_delay_max - t36_end_ - 250000.0*t_36_map_3 >= -250000.0\n", + "_C120291: PE3_time_delay_min - t36_start + 250000.0*t_36_map_3 <= 250000.0\n", + "_C120292: PE3_time_delay_max - t37_end_ - 250000.0*t_37_map_3 >= -250000.0\n", + "_C120293: PE3_time_delay_min - t37_start + 250000.0*t_37_map_3 <= 250000.0\n", + "_C120294: PE3_time_delay_max - t38_end_ - 250000.0*t_38_map_3 >= -250000.0\n", + "_C120295: PE3_time_delay_min - t38_start + 250000.0*t_38_map_3 <= 250000.0\n", + "_C120296: PE3_time_delay_max - t39_end_ - 250000.0*t_39_map_3 >= -250000.0\n", + "_C120297: PE3_time_delay_min - t39_start + 250000.0*t_39_map_3 <= 250000.0\n", + "_C120298: PE3_time_delay_max - t40_end_ - 250000.0*t_40_map_3 >= -250000.0\n", + "_C120299: PE3_time_delay_min - t40_start + 250000.0*t_40_map_3 <= 250000.0\n", + "_C120300: PE3_time_delay_max - t41_end_ - 250000.0*t_41_map_3 >= -250000.0\n", + "_C120301: PE3_time_delay_min - t41_start + 250000.0*t_41_map_3 <= 250000.0\n", + "_C120302: PE3_time_delay_max - t42_end_ - 250000.0*t_42_map_3 >= -250000.0\n", + "_C120303: PE3_time_delay_min - t42_start + 250000.0*t_42_map_3 <= 250000.0\n", + "_C120304: PE3_time_delay_max - t43_end_ - 250000.0*t_43_map_3 >= -250000.0\n", + "_C120305: PE3_time_delay_min - t43_start + 250000.0*t_43_map_3 <= 250000.0\n", + "_C120306: PE3_time_delay_max - t44_end_ - 250000.0*t_44_map_3 >= -250000.0\n", + "_C120307: PE3_time_delay_min - t44_start + 250000.0*t_44_map_3 <= 250000.0\n", + "_C120308: PE3_time_delay_max - t45_end_ - 250000.0*t_45_map_3 >= -250000.0\n", + "_C120309: PE3_time_delay_min - t45_start + 250000.0*t_45_map_3 <= 250000.0\n", + "_C120310: PE3_time_delay_max - t46_end_ - 250000.0*t_46_map_3 >= -250000.0\n", + "_C120311: PE3_time_delay_min - t46_start + 250000.0*t_46_map_3 <= 250000.0\n", + "_C120312: PE3_time_delay_max - t47_end_ - 250000.0*t_47_map_3 >= -250000.0\n", + "_C120313: PE3_time_delay_min - t47_start + 250000.0*t_47_map_3 <= 250000.0\n", + "_C120314: PE3_time_delay_max - t48_end_ - 250000.0*t_48_map_3 >= -250000.0\n", + "_C120315: PE3_time_delay_min - t48_start + 250000.0*t_48_map_3 <= 250000.0\n", + "_C120316: PE3_time_delay_max - t49_end_ - 250000.0*t_49_map_3 >= -250000.0\n", + "_C120317: PE3_time_delay_min - t49_start + 250000.0*t_49_map_3 <= 250000.0\n", + "_C120318: PE3_time_delay_max - t50_end_ - 250000.0*t_50_map_3 >= -250000.0\n", + "_C120319: PE3_time_delay_min - t50_start + 250000.0*t_50_map_3 <= 250000.0\n", + "_C120320: PE3_time_delay_max - t51_end_ - 250000.0*t_51_map_3 >= -250000.0\n", + "_C120321: PE3_time_delay_min - t51_start + 250000.0*t_51_map_3 <= 250000.0\n", + "_C120322: PE3_time_delay_max - t52_end_ - 250000.0*t_52_map_3 >= -250000.0\n", + "_C120323: PE3_time_delay_min - t52_start + 250000.0*t_52_map_3 <= 250000.0\n", + "_C120324: PE3_time_delay_max - t53_end_ - 250000.0*t_53_map_3 >= -250000.0\n", + "_C120325: PE3_time_delay_min - t53_start + 250000.0*t_53_map_3 <= 250000.0\n", + "_C120326: PE3_time_delay_max - t54_end_ - 250000.0*t_54_map_3 >= -250000.0\n", + "_C120327: PE3_time_delay_min - t54_start + 250000.0*t_54_map_3 <= 250000.0\n", + "_C120328: PE3_time_delay_max - t55_end_ - 250000.0*t_55_map_3 >= -250000.0\n", + "_C120329: PE3_time_delay_min - t55_start + 250000.0*t_55_map_3 <= 250000.0\n", + "_C120330: PE3_time_delay_max - t56_end_ - 250000.0*t_56_map_3 >= -250000.0\n", + "_C120331: PE3_time_delay_min - t56_start + 250000.0*t_56_map_3 <= 250000.0\n", + "_C120332: PE3_time_delay_max - t57_end_ - 250000.0*t_57_map_3 >= -250000.0\n", + "_C120333: PE3_time_delay_min - t57_start + 250000.0*t_57_map_3 <= 250000.0\n", + "_C120334: PE3_time_delay_max - t58_end_ - 250000.0*t_58_map_3 >= -250000.0\n", + "_C120335: PE3_time_delay_min - t58_start + 250000.0*t_58_map_3 <= 250000.0\n", + "_C120336: PE3_time_delay_max - t59_end_ - 250000.0*t_59_map_3 >= -250000.0\n", + "_C120337: PE3_time_delay_min - t59_start + 250000.0*t_59_map_3 <= 250000.0\n", + "_C120338: PE3_time_delay_max - t60_end_ - 250000.0*t_60_map_3 >= -250000.0\n", + "_C120339: PE3_time_delay_min - t60_start + 250000.0*t_60_map_3 <= 250000.0\n", + "_C120340: PE3_time_delay_max - t61_end_ - 250000.0*t_61_map_3 >= -250000.0\n", + "_C120341: PE3_time_delay_min - t61_start + 250000.0*t_61_map_3 <= 250000.0\n", + "_C120342: PE3_time_delay_max - t62_end_ - 250000.0*t_62_map_3 >= -250000.0\n", + "_C120343: PE3_time_delay_min - t62_start + 250000.0*t_62_map_3 <= 250000.0\n", + "_C120344: PE3_time_delay_max - t63_end_ - 250000.0*t_63_map_3 >= -250000.0\n", + "_C120345: PE3_time_delay_min - t63_start + 250000.0*t_63_map_3 <= 250000.0\n", + "_C120346: PE3_time_delay_max - t64_end_ - 250000.0*t_64_map_3 >= -250000.0\n", + "_C120347: PE3_time_delay_min - t64_start + 250000.0*t_64_map_3 <= 250000.0\n", + "_C120348: PE3_time_delay_max - t65_end_ - 250000.0*t_65_map_3 >= -250000.0\n", + "_C120349: PE3_time_delay_min - t65_start + 250000.0*t_65_map_3 <= 250000.0\n", + "_C120350: PE3_time_delay_max - t66_end_ - 250000.0*t_66_map_3 >= -250000.0\n", + "_C120351: PE3_time_delay_min - t66_start + 250000.0*t_66_map_3 <= 250000.0\n", + "_C120352: PE3_time_delay_max - t67_end_ - 250000.0*t_67_map_3 >= -250000.0\n", + "_C120353: PE3_time_delay_min - t67_start + 250000.0*t_67_map_3 <= 250000.0\n", + "_C120354: PE3_time_delay_max - t68_end_ - 250000.0*t_68_map_3 >= -250000.0\n", + "_C120355: PE3_time_delay_min - t68_start + 250000.0*t_68_map_3 <= 250000.0\n", + "_C120356: PE3_time_delay_max - t69_end_ - 250000.0*t_69_map_3 >= -250000.0\n", + "_C120357: PE3_time_delay_min - t69_start + 250000.0*t_69_map_3 <= 250000.0\n", + "_C120358: -PE3_time_delay_max + PE3_time_delay_min + PE3_total_time_delay = 0\n", + "_C120359: -PE3_total_time_delay + max_router_delay >= 0\n", + "_C120360: -t0_end_ + t0_start - 250000.0*t_0_map_4 - t_send_0 + task_total_delay_router_router4_task0 >= -250000.0\n", + "_C120361: -250000.0*t_0_map_4 - t_mem_0 + task_total_memory_router_router4_task0 >= -250000.0\n", + "_C120362: -t1_end_ + t1_start - 250000.0*t_1_map_4 - t_send_1 + task_total_delay_router_router4_task1 >= -250000.0\n", + "_C120363: -250000.0*t_1_map_4 - t_mem_1 + task_total_memory_router_router4_task1 >= -250000.0\n", + "_C120364: -t2_end_ + t2_start - 250000.0*t_2_map_4 - t_send_2 + task_total_delay_router_router4_task2 >= -250000.0\n", + "_C120365: -250000.0*t_2_map_4 - t_mem_2 + task_total_memory_router_router4_task2 >= -250000.0\n", + "_C120366: -t3_end_ + t3_start - 250000.0*t_3_map_4 - t_send_3 + task_total_delay_router_router4_task3 >= -250000.0\n", + "_C120367: -250000.0*t_3_map_4 - t_mem_3 + task_total_memory_router_router4_task3 >= -250000.0\n", + "_C120368: -t4_end_ + t4_start - 250000.0*t_4_map_4 - t_send_4 + task_total_delay_router_router4_task4 >= -250000.0\n", + "_C120369: -250000.0*t_4_map_4 - t_mem_4 + task_total_memory_router_router4_task4 >= -250000.0\n", + "_C120370: -t5_end_ + t5_start - 250000.0*t_5_map_4 - t_send_5 + task_total_delay_router_router4_task5 >= -250000.0\n", + "_C120371: -250000.0*t_5_map_4 - t_mem_5 + task_total_memory_router_router4_task5 >= -250000.0\n", + "_C120372: -t6_end_ + t6_start - 250000.0*t_6_map_4 - t_send_6 + task_total_delay_router_router4_task6 >= 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task_total_memory_router_router4_task33 - task_total_memory_router_router4_task34 - task_total_memory_router_router4_task35 - task_total_memory_router_router4_task36 - task_total_memory_router_router4_task37 - task_total_memory_router_router4_task38 - task_total_memory_router_router4_task39 - task_total_memory_router_router4_task4 - task_total_memory_router_router4_task40 - task_total_memory_router_router4_task41 - task_total_memory_router_router4_task42 - task_total_memory_router_router4_task43 - task_total_memory_router_router4_task44 - task_total_memory_router_router4_task45 - task_total_memory_router_router4_task46 - task_total_memory_router_router4_task47 - task_total_memory_router_router4_task48 - task_total_memory_router_router4_task49 - task_total_memory_router_router4_task5 - task_total_memory_router_router4_task50 - task_total_memory_router_router4_task51 - task_total_memory_router_router4_task52 - task_total_memory_router_router4_task53 - task_total_memory_router_router4_task54 - task_total_memory_router_router4_task55 - task_total_memory_router_router4_task56 - task_total_memory_router_router4_task57 - task_total_memory_router_router4_task58 - task_total_memory_router_router4_task59 - task_total_memory_router_router4_task6 - task_total_memory_router_router4_task60 - task_total_memory_router_router4_task61 - task_total_memory_router_router4_task62 - task_total_memory_router_router4_task63 - task_total_memory_router_router4_task64 - task_total_memory_router_router4_task65 - task_total_memory_router_router4_task66 - task_total_memory_router_router4_task67 - task_total_memory_router_router4_task68 - task_total_memory_router_router4_task69 - task_total_memory_router_router4_task7 - task_total_memory_router_router4_task8 - task_total_memory_router_router4_task9 >= -0.0\n", + "_C120501: PE4_total_delay - task_total_delay_router_router4_task0 - task_total_delay_router_router4_task1 - task_total_delay_router_router4_task10 - task_total_delay_router_router4_task11 - task_total_delay_router_router4_task12 - task_total_delay_router_router4_task13 - task_total_delay_router_router4_task14 - task_total_delay_router_router4_task15 - task_total_delay_router_router4_task16 - task_total_delay_router_router4_task17 - task_total_delay_router_router4_task18 - task_total_delay_router_router4_task19 - task_total_delay_router_router4_task2 - task_total_delay_router_router4_task20 - task_total_delay_router_router4_task21 - task_total_delay_router_router4_task22 - task_total_delay_router_router4_task23 - task_total_delay_router_router4_task24 - task_total_delay_router_router4_task25 - task_total_delay_router_router4_task26 - task_total_delay_router_router4_task27 - task_total_delay_router_router4_task28 - task_total_delay_router_router4_task29 - task_total_delay_router_router4_task3 - task_total_delay_router_router4_task30 - task_total_delay_router_router4_task31 - task_total_delay_router_router4_task32 - task_total_delay_router_router4_task33 - task_total_delay_router_router4_task34 - task_total_delay_router_router4_task35 - task_total_delay_router_router4_task36 - task_total_delay_router_router4_task37 - task_total_delay_router_router4_task38 - task_total_delay_router_router4_task39 - task_total_delay_router_router4_task4 - task_total_delay_router_router4_task40 - task_total_delay_router_router4_task41 - task_total_delay_router_router4_task42 - task_total_delay_router_router4_task43 - task_total_delay_router_router4_task44 - task_total_delay_router_router4_task45 - task_total_delay_router_router4_task46 - task_total_delay_router_router4_task47 - task_total_delay_router_router4_task48 - task_total_delay_router_router4_task49 - task_total_delay_router_router4_task5 - task_total_delay_router_router4_task50 - task_total_delay_router_router4_task51 - task_total_delay_router_router4_task52 - task_total_delay_router_router4_task53 - task_total_delay_router_router4_task54 - task_total_delay_router_router4_task55 - task_total_delay_router_router4_task56 - task_total_delay_router_router4_task57 - task_total_delay_router_router4_task58 - task_total_delay_router_router4_task59 - task_total_delay_router_router4_task6 - task_total_delay_router_router4_task60 - task_total_delay_router_router4_task61 - task_total_delay_router_router4_task62 - task_total_delay_router_router4_task63 - task_total_delay_router_router4_task64 - task_total_delay_router_router4_task65 - task_total_delay_router_router4_task66 - task_total_delay_router_router4_task67 - task_total_delay_router_router4_task68 - task_total_delay_router_router4_task69 - task_total_delay_router_router4_task7 - task_total_delay_router_router4_task8 - task_total_delay_router_router4_task9 >= -0.0\n", + "_C120502: PE4_total_memory - task_total_memory_router_router4_task0 - task_total_memory_router_router4_task1 - task_total_memory_router_router4_task10 - task_total_memory_router_router4_task11 - task_total_memory_router_router4_task12 - task_total_memory_router_router4_task13 - task_total_memory_router_router4_task14 - task_total_memory_router_router4_task15 - task_total_memory_router_router4_task16 - task_total_memory_router_router4_task17 - task_total_memory_router_router4_task18 - task_total_memory_router_router4_task19 - task_total_memory_router_router4_task2 - task_total_memory_router_router4_task20 - task_total_memory_router_router4_task21 - task_total_memory_router_router4_task22 - task_total_memory_router_router4_task23 - task_total_memory_router_router4_task24 - task_total_memory_router_router4_task25 - task_total_memory_router_router4_task26 - task_total_memory_router_router4_task27 - task_total_memory_router_router4_task28 - task_total_memory_router_router4_task29 - task_total_memory_router_router4_task3 - task_total_memory_router_router4_task30 - task_total_memory_router_router4_task31 - task_total_memory_router_router4_task32 - task_total_memory_router_router4_task33 - task_total_memory_router_router4_task34 - task_total_memory_router_router4_task35 - task_total_memory_router_router4_task36 - task_total_memory_router_router4_task37 - task_total_memory_router_router4_task38 - task_total_memory_router_router4_task39 - task_total_memory_router_router4_task4 - task_total_memory_router_router4_task40 - task_total_memory_router_router4_task41 - task_total_memory_router_router4_task42 - task_total_memory_router_router4_task43 - task_total_memory_router_router4_task44 - task_total_memory_router_router4_task45 - task_total_memory_router_router4_task46 - task_total_memory_router_router4_task47 - task_total_memory_router_router4_task48 - task_total_memory_router_router4_task49 - task_total_memory_router_router4_task5 - task_total_memory_router_router4_task50 - task_total_memory_router_router4_task51 - task_total_memory_router_router4_task52 - task_total_memory_router_router4_task53 - task_total_memory_router_router4_task54 - task_total_memory_router_router4_task55 - task_total_memory_router_router4_task56 - task_total_memory_router_router4_task57 - task_total_memory_router_router4_task58 - task_total_memory_router_router4_task59 - task_total_memory_router_router4_task6 - task_total_memory_router_router4_task60 - task_total_memory_router_router4_task61 - task_total_memory_router_router4_task62 - task_total_memory_router_router4_task63 - task_total_memory_router_router4_task64 - task_total_memory_router_router4_task65 - task_total_memory_router_router4_task66 - task_total_memory_router_router4_task67 - task_total_memory_router_router4_task68 - task_total_memory_router_router4_task69 - task_total_memory_router_router4_task7 - task_total_memory_router_router4_task8 - task_total_memory_router_router4_task9 >= -0.0\n", + "_C120503: -PE_mem_overflow4 + max_memory_overflow >= 0\n", + "_C120504: PE4_time_delay_max - t0_end_ - 250000.0*t_0_map_4 >= -250000.0\n", + "_C120505: PE4_time_delay_min - t0_start + 250000.0*t_0_map_4 <= 250000.0\n", + "_C120506: PE4_time_delay_max - t1_end_ - 250000.0*t_1_map_4 >= -250000.0\n", + "_C120507: PE4_time_delay_min - t1_start + 250000.0*t_1_map_4 <= 250000.0\n", + "_C120508: PE4_time_delay_max - t2_end_ - 250000.0*t_2_map_4 >= -250000.0\n", + "_C120509: PE4_time_delay_min - t2_start + 250000.0*t_2_map_4 <= 250000.0\n", + "_C120510: PE4_time_delay_max - t3_end_ - 250000.0*t_3_map_4 >= -250000.0\n", + "_C120511: PE4_time_delay_min - t3_start + 250000.0*t_3_map_4 <= 250000.0\n", + "_C120512: PE4_time_delay_max - t4_end_ - 250000.0*t_4_map_4 >= -250000.0\n", + "_C120513: PE4_time_delay_min - t4_start + 250000.0*t_4_map_4 <= 250000.0\n", + "_C120514: PE4_time_delay_max - t5_end_ - 250000.0*t_5_map_4 >= -250000.0\n", + "_C120515: PE4_time_delay_min - t5_start + 250000.0*t_5_map_4 <= 250000.0\n", + "_C120516: PE4_time_delay_max - t6_end_ - 250000.0*t_6_map_4 >= -250000.0\n", + "_C120517: PE4_time_delay_min - t6_start + 250000.0*t_6_map_4 <= 250000.0\n", + "_C120518: PE4_time_delay_max - t7_end_ - 250000.0*t_7_map_4 >= -250000.0\n", + "_C120519: PE4_time_delay_min - t7_start + 250000.0*t_7_map_4 <= 250000.0\n", + "_C120520: PE4_time_delay_max - t8_end_ - 250000.0*t_8_map_4 >= -250000.0\n", + "_C120521: PE4_time_delay_min - t8_start + 250000.0*t_8_map_4 <= 250000.0\n", + "_C120522: PE4_time_delay_max - t9_end_ - 250000.0*t_9_map_4 >= -250000.0\n", + "_C120523: PE4_time_delay_min - t9_start + 250000.0*t_9_map_4 <= 250000.0\n", + "_C120524: PE4_time_delay_max - t10_end_ - 250000.0*t_10_map_4 >= -250000.0\n", + "_C120525: PE4_time_delay_min - t10_start + 250000.0*t_10_map_4 <= 250000.0\n", + "_C120526: PE4_time_delay_max - t11_end_ - 250000.0*t_11_map_4 >= -250000.0\n", + "_C120527: PE4_time_delay_min - t11_start + 250000.0*t_11_map_4 <= 250000.0\n", + "_C120528: PE4_time_delay_max - t12_end_ - 250000.0*t_12_map_4 >= -250000.0\n", + "_C120529: PE4_time_delay_min - t12_start + 250000.0*t_12_map_4 <= 250000.0\n", + "_C120530: PE4_time_delay_max - t13_end_ - 250000.0*t_13_map_4 >= -250000.0\n", + "_C120531: PE4_time_delay_min - t13_start + 250000.0*t_13_map_4 <= 250000.0\n", + "_C120532: PE4_time_delay_max - t14_end_ - 250000.0*t_14_map_4 >= -250000.0\n", + "_C120533: PE4_time_delay_min - t14_start + 250000.0*t_14_map_4 <= 250000.0\n", + "_C120534: PE4_time_delay_max - t15_end_ - 250000.0*t_15_map_4 >= -250000.0\n", + "_C120535: PE4_time_delay_min - t15_start + 250000.0*t_15_map_4 <= 250000.0\n", + "_C120536: PE4_time_delay_max - t16_end_ - 250000.0*t_16_map_4 >= -250000.0\n", + "_C120537: PE4_time_delay_min - t16_start + 250000.0*t_16_map_4 <= 250000.0\n", + "_C120538: PE4_time_delay_max - t17_end_ - 250000.0*t_17_map_4 >= -250000.0\n", + "_C120539: PE4_time_delay_min - t17_start + 250000.0*t_17_map_4 <= 250000.0\n", + "_C120540: PE4_time_delay_max - t18_end_ - 250000.0*t_18_map_4 >= -250000.0\n", + "_C120541: PE4_time_delay_min - t18_start + 250000.0*t_18_map_4 <= 250000.0\n", + "_C120542: PE4_time_delay_max - t19_end_ - 250000.0*t_19_map_4 >= -250000.0\n", + "_C120543: PE4_time_delay_min - t19_start + 250000.0*t_19_map_4 <= 250000.0\n", + "_C120544: PE4_time_delay_max - t20_end_ - 250000.0*t_20_map_4 >= -250000.0\n", + "_C120545: PE4_time_delay_min - t20_start + 250000.0*t_20_map_4 <= 250000.0\n", + "_C120546: PE4_time_delay_max - t21_end_ - 250000.0*t_21_map_4 >= -250000.0\n", + "_C120547: PE4_time_delay_min - t21_start + 250000.0*t_21_map_4 <= 250000.0\n", + "_C120548: PE4_time_delay_max - t22_end_ - 250000.0*t_22_map_4 >= -250000.0\n", + "_C120549: PE4_time_delay_min - t22_start + 250000.0*t_22_map_4 <= 250000.0\n", + "_C120550: PE4_time_delay_max - t23_end_ - 250000.0*t_23_map_4 >= -250000.0\n", + "_C120551: PE4_time_delay_min - t23_start + 250000.0*t_23_map_4 <= 250000.0\n", + "_C120552: PE4_time_delay_max - t24_end_ - 250000.0*t_24_map_4 >= -250000.0\n", + "_C120553: PE4_time_delay_min - t24_start + 250000.0*t_24_map_4 <= 250000.0\n", + "_C120554: PE4_time_delay_max - t25_end_ - 250000.0*t_25_map_4 >= -250000.0\n", + "_C120555: PE4_time_delay_min - t25_start + 250000.0*t_25_map_4 <= 250000.0\n", + "_C120556: PE4_time_delay_max - t26_end_ - 250000.0*t_26_map_4 >= -250000.0\n", + "_C120557: PE4_time_delay_min - t26_start + 250000.0*t_26_map_4 <= 250000.0\n", + "_C120558: PE4_time_delay_max - t27_end_ - 250000.0*t_27_map_4 >= -250000.0\n", + "_C120559: PE4_time_delay_min - t27_start + 250000.0*t_27_map_4 <= 250000.0\n", + "_C120560: PE4_time_delay_max - t28_end_ - 250000.0*t_28_map_4 >= -250000.0\n", + "_C120561: PE4_time_delay_min - t28_start + 250000.0*t_28_map_4 <= 250000.0\n", + "_C120562: PE4_time_delay_max - t29_end_ - 250000.0*t_29_map_4 >= -250000.0\n", + "_C120563: PE4_time_delay_min - t29_start + 250000.0*t_29_map_4 <= 250000.0\n", + "_C120564: PE4_time_delay_max - t30_end_ - 250000.0*t_30_map_4 >= -250000.0\n", + "_C120565: PE4_time_delay_min - t30_start + 250000.0*t_30_map_4 <= 250000.0\n", + "_C120566: PE4_time_delay_max - t31_end_ - 250000.0*t_31_map_4 >= -250000.0\n", + "_C120567: PE4_time_delay_min - t31_start + 250000.0*t_31_map_4 <= 250000.0\n", + "_C120568: PE4_time_delay_max - t32_end_ - 250000.0*t_32_map_4 >= -250000.0\n", + "_C120569: PE4_time_delay_min - t32_start + 250000.0*t_32_map_4 <= 250000.0\n", + "_C120570: PE4_time_delay_max - t33_end_ - 250000.0*t_33_map_4 >= -250000.0\n", + "_C120571: PE4_time_delay_min - t33_start + 250000.0*t_33_map_4 <= 250000.0\n", + "_C120572: PE4_time_delay_max - t34_end_ - 250000.0*t_34_map_4 >= -250000.0\n", + "_C120573: PE4_time_delay_min - t34_start + 250000.0*t_34_map_4 <= 250000.0\n", + "_C120574: PE4_time_delay_max - t35_end_ - 250000.0*t_35_map_4 >= -250000.0\n", + "_C120575: PE4_time_delay_min - t35_start + 250000.0*t_35_map_4 <= 250000.0\n", + "_C120576: PE4_time_delay_max - t36_end_ - 250000.0*t_36_map_4 >= -250000.0\n", + "_C120577: PE4_time_delay_min - t36_start + 250000.0*t_36_map_4 <= 250000.0\n", + "_C120578: PE4_time_delay_max - t37_end_ - 250000.0*t_37_map_4 >= -250000.0\n", + "_C120579: PE4_time_delay_min - t37_start + 250000.0*t_37_map_4 <= 250000.0\n", + "_C120580: PE4_time_delay_max - t38_end_ - 250000.0*t_38_map_4 >= -250000.0\n", + "_C120581: PE4_time_delay_min - t38_start + 250000.0*t_38_map_4 <= 250000.0\n", + "_C120582: PE4_time_delay_max - t39_end_ - 250000.0*t_39_map_4 >= -250000.0\n", + "_C120583: PE4_time_delay_min - t39_start + 250000.0*t_39_map_4 <= 250000.0\n", + "_C120584: PE4_time_delay_max - t40_end_ - 250000.0*t_40_map_4 >= -250000.0\n", + "_C120585: PE4_time_delay_min - t40_start + 250000.0*t_40_map_4 <= 250000.0\n", + "_C120586: PE4_time_delay_max - t41_end_ - 250000.0*t_41_map_4 >= -250000.0\n", + "_C120587: PE4_time_delay_min - t41_start + 250000.0*t_41_map_4 <= 250000.0\n", + "_C120588: PE4_time_delay_max - t42_end_ - 250000.0*t_42_map_4 >= -250000.0\n", + "_C120589: PE4_time_delay_min - t42_start + 250000.0*t_42_map_4 <= 250000.0\n", + "_C120590: PE4_time_delay_max - t43_end_ - 250000.0*t_43_map_4 >= -250000.0\n", + "_C120591: PE4_time_delay_min - t43_start + 250000.0*t_43_map_4 <= 250000.0\n", + "_C120592: PE4_time_delay_max - t44_end_ - 250000.0*t_44_map_4 >= -250000.0\n", + "_C120593: PE4_time_delay_min - t44_start + 250000.0*t_44_map_4 <= 250000.0\n", + "_C120594: PE4_time_delay_max - t45_end_ - 250000.0*t_45_map_4 >= -250000.0\n", + "_C120595: PE4_time_delay_min - t45_start + 250000.0*t_45_map_4 <= 250000.0\n", + "_C120596: PE4_time_delay_max - t46_end_ - 250000.0*t_46_map_4 >= -250000.0\n", + "_C120597: PE4_time_delay_min - t46_start + 250000.0*t_46_map_4 <= 250000.0\n", + "_C120598: PE4_time_delay_max - t47_end_ - 250000.0*t_47_map_4 >= -250000.0\n", + "_C120599: PE4_time_delay_min - t47_start + 250000.0*t_47_map_4 <= 250000.0\n", + "_C120600: PE4_time_delay_max - t48_end_ - 250000.0*t_48_map_4 >= -250000.0\n", + "_C120601: PE4_time_delay_min - t48_start + 250000.0*t_48_map_4 <= 250000.0\n", + "_C120602: 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t_send_66 + task_total_delay_router_router5_task66 >= -250000.0\n", + "_C120779: -250000.0*t_66_map_5 - t_mem_66 + task_total_memory_router_router5_task66 >= -250000.0\n", + "_C120780: -t67_end_ + t67_start - 250000.0*t_67_map_5 - t_send_67 + task_total_delay_router_router5_task67 >= -250000.0\n", + "_C120781: -250000.0*t_67_map_5 - t_mem_67 + task_total_memory_router_router5_task67 >= -250000.0\n", + "_C120782: -t68_end_ + t68_start - 250000.0*t_68_map_5 - t_send_68 + task_total_delay_router_router5_task68 >= -250000.0\n", + "_C120783: -250000.0*t_68_map_5 - t_mem_68 + task_total_memory_router_router5_task68 >= -250000.0\n", + "_C120784: -t69_end_ + t69_start - 250000.0*t_69_map_5 - t_send_69 + task_total_delay_router_router5_task69 >= -250000.0\n", + "_C120785: -250000.0*t_69_map_5 - t_mem_69 + task_total_memory_router_router5_task69 >= -250000.0\n", + "_C120786: PE_mem_overflow5 - task_total_memory_router_router5_task0 - task_total_memory_router_router5_task1 - task_total_memory_router_router5_task10 - task_total_memory_router_router5_task11 - task_total_memory_router_router5_task12 - task_total_memory_router_router5_task13 - task_total_memory_router_router5_task14 - task_total_memory_router_router5_task15 - task_total_memory_router_router5_task16 - task_total_memory_router_router5_task17 - task_total_memory_router_router5_task18 - task_total_memory_router_router5_task19 - task_total_memory_router_router5_task2 - task_total_memory_router_router5_task20 - task_total_memory_router_router5_task21 - task_total_memory_router_router5_task22 - task_total_memory_router_router5_task23 - task_total_memory_router_router5_task24 - task_total_memory_router_router5_task25 - task_total_memory_router_router5_task26 - task_total_memory_router_router5_task27 - task_total_memory_router_router5_task28 - task_total_memory_router_router5_task29 - task_total_memory_router_router5_task3 - task_total_memory_router_router5_task30 - task_total_memory_router_router5_task31 - task_total_memory_router_router5_task32 - task_total_memory_router_router5_task33 - task_total_memory_router_router5_task34 - task_total_memory_router_router5_task35 - task_total_memory_router_router5_task36 - task_total_memory_router_router5_task37 - task_total_memory_router_router5_task38 - task_total_memory_router_router5_task39 - task_total_memory_router_router5_task4 - task_total_memory_router_router5_task40 - task_total_memory_router_router5_task41 - task_total_memory_router_router5_task42 - task_total_memory_router_router5_task43 - task_total_memory_router_router5_task44 - task_total_memory_router_router5_task45 - task_total_memory_router_router5_task46 - task_total_memory_router_router5_task47 - task_total_memory_router_router5_task48 - task_total_memory_router_router5_task49 - task_total_memory_router_router5_task5 - task_total_memory_router_router5_task50 - task_total_memory_router_router5_task51 - task_total_memory_router_router5_task52 - task_total_memory_router_router5_task53 - task_total_memory_router_router5_task54 - task_total_memory_router_router5_task55 - task_total_memory_router_router5_task56 - task_total_memory_router_router5_task57 - task_total_memory_router_router5_task58 - task_total_memory_router_router5_task59 - task_total_memory_router_router5_task6 - task_total_memory_router_router5_task60 - task_total_memory_router_router5_task61 - task_total_memory_router_router5_task62 - task_total_memory_router_router5_task63 - task_total_memory_router_router5_task64 - task_total_memory_router_router5_task65 - task_total_memory_router_router5_task66 - task_total_memory_router_router5_task67 - task_total_memory_router_router5_task68 - task_total_memory_router_router5_task69 - task_total_memory_router_router5_task7 - task_total_memory_router_router5_task8 - task_total_memory_router_router5_task9 >= -0.0\n", + "_C120787: PE5_total_delay - task_total_delay_router_router5_task0 - task_total_delay_router_router5_task1 - task_total_delay_router_router5_task10 - task_total_delay_router_router5_task11 - task_total_delay_router_router5_task12 - task_total_delay_router_router5_task13 - task_total_delay_router_router5_task14 - task_total_delay_router_router5_task15 - task_total_delay_router_router5_task16 - task_total_delay_router_router5_task17 - task_total_delay_router_router5_task18 - task_total_delay_router_router5_task19 - task_total_delay_router_router5_task2 - task_total_delay_router_router5_task20 - task_total_delay_router_router5_task21 - task_total_delay_router_router5_task22 - task_total_delay_router_router5_task23 - task_total_delay_router_router5_task24 - task_total_delay_router_router5_task25 - task_total_delay_router_router5_task26 - task_total_delay_router_router5_task27 - task_total_delay_router_router5_task28 - task_total_delay_router_router5_task29 - task_total_delay_router_router5_task3 - task_total_delay_router_router5_task30 - task_total_delay_router_router5_task31 - task_total_delay_router_router5_task32 - task_total_delay_router_router5_task33 - task_total_delay_router_router5_task34 - task_total_delay_router_router5_task35 - task_total_delay_router_router5_task36 - task_total_delay_router_router5_task37 - task_total_delay_router_router5_task38 - task_total_delay_router_router5_task39 - task_total_delay_router_router5_task4 - task_total_delay_router_router5_task40 - task_total_delay_router_router5_task41 - task_total_delay_router_router5_task42 - task_total_delay_router_router5_task43 - task_total_delay_router_router5_task44 - task_total_delay_router_router5_task45 - task_total_delay_router_router5_task46 - task_total_delay_router_router5_task47 - task_total_delay_router_router5_task48 - task_total_delay_router_router5_task49 - task_total_delay_router_router5_task5 - task_total_delay_router_router5_task50 - task_total_delay_router_router5_task51 - task_total_delay_router_router5_task52 - task_total_delay_router_router5_task53 - task_total_delay_router_router5_task54 - task_total_delay_router_router5_task55 - task_total_delay_router_router5_task56 - task_total_delay_router_router5_task57 - task_total_delay_router_router5_task58 - task_total_delay_router_router5_task59 - task_total_delay_router_router5_task6 - task_total_delay_router_router5_task60 - task_total_delay_router_router5_task61 - task_total_delay_router_router5_task62 - task_total_delay_router_router5_task63 - task_total_delay_router_router5_task64 - task_total_delay_router_router5_task65 - task_total_delay_router_router5_task66 - task_total_delay_router_router5_task67 - task_total_delay_router_router5_task68 - task_total_delay_router_router5_task69 - task_total_delay_router_router5_task7 - task_total_delay_router_router5_task8 - task_total_delay_router_router5_task9 >= -0.0\n", + "_C120788: PE5_total_memory - task_total_memory_router_router5_task0 - task_total_memory_router_router5_task1 - task_total_memory_router_router5_task10 - task_total_memory_router_router5_task11 - task_total_memory_router_router5_task12 - task_total_memory_router_router5_task13 - task_total_memory_router_router5_task14 - task_total_memory_router_router5_task15 - task_total_memory_router_router5_task16 - task_total_memory_router_router5_task17 - task_total_memory_router_router5_task18 - task_total_memory_router_router5_task19 - task_total_memory_router_router5_task2 - task_total_memory_router_router5_task20 - task_total_memory_router_router5_task21 - task_total_memory_router_router5_task22 - task_total_memory_router_router5_task23 - task_total_memory_router_router5_task24 - task_total_memory_router_router5_task25 - task_total_memory_router_router5_task26 - task_total_memory_router_router5_task27 - task_total_memory_router_router5_task28 - task_total_memory_router_router5_task29 - task_total_memory_router_router5_task3 - task_total_memory_router_router5_task30 - task_total_memory_router_router5_task31 - task_total_memory_router_router5_task32 - task_total_memory_router_router5_task33 - task_total_memory_router_router5_task34 - task_total_memory_router_router5_task35 - task_total_memory_router_router5_task36 - task_total_memory_router_router5_task37 - task_total_memory_router_router5_task38 - task_total_memory_router_router5_task39 - task_total_memory_router_router5_task4 - task_total_memory_router_router5_task40 - task_total_memory_router_router5_task41 - task_total_memory_router_router5_task42 - task_total_memory_router_router5_task43 - task_total_memory_router_router5_task44 - task_total_memory_router_router5_task45 - task_total_memory_router_router5_task46 - task_total_memory_router_router5_task47 - task_total_memory_router_router5_task48 - task_total_memory_router_router5_task49 - task_total_memory_router_router5_task5 - task_total_memory_router_router5_task50 - task_total_memory_router_router5_task51 - task_total_memory_router_router5_task52 - task_total_memory_router_router5_task53 - task_total_memory_router_router5_task54 - task_total_memory_router_router5_task55 - task_total_memory_router_router5_task56 - task_total_memory_router_router5_task57 - task_total_memory_router_router5_task58 - task_total_memory_router_router5_task59 - task_total_memory_router_router5_task6 - task_total_memory_router_router5_task60 - task_total_memory_router_router5_task61 - task_total_memory_router_router5_task62 - task_total_memory_router_router5_task63 - task_total_memory_router_router5_task64 - task_total_memory_router_router5_task65 - task_total_memory_router_router5_task66 - task_total_memory_router_router5_task67 - task_total_memory_router_router5_task68 - task_total_memory_router_router5_task69 - task_total_memory_router_router5_task7 - task_total_memory_router_router5_task8 - task_total_memory_router_router5_task9 >= -0.0\n", + "_C120789: -PE_mem_overflow5 + max_memory_overflow >= 0\n", + "_C120790: PE5_time_delay_max - t0_end_ - 250000.0*t_0_map_5 >= -250000.0\n", + "_C120791: PE5_time_delay_min - t0_start + 250000.0*t_0_map_5 <= 250000.0\n", + "_C120792: PE5_time_delay_max - t1_end_ - 250000.0*t_1_map_5 >= -250000.0\n", + "_C120793: PE5_time_delay_min - t1_start + 250000.0*t_1_map_5 <= 250000.0\n", + "_C120794: PE5_time_delay_max - t2_end_ - 250000.0*t_2_map_5 >= -250000.0\n", + "_C120795: PE5_time_delay_min - t2_start + 250000.0*t_2_map_5 <= 250000.0\n", + "_C120796: PE5_time_delay_max - t3_end_ - 250000.0*t_3_map_5 >= -250000.0\n", + "_C120797: PE5_time_delay_min - t3_start + 250000.0*t_3_map_5 <= 250000.0\n", + "_C120798: PE5_time_delay_max - t4_end_ - 250000.0*t_4_map_5 >= -250000.0\n", + "_C120799: PE5_time_delay_min - t4_start + 250000.0*t_4_map_5 <= 250000.0\n", + "_C120800: PE5_time_delay_max - t5_end_ - 250000.0*t_5_map_5 >= -250000.0\n", + "_C120801: PE5_time_delay_min - t5_start + 250000.0*t_5_map_5 <= 250000.0\n", + "_C120802: PE5_time_delay_max - t6_end_ 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PE5_time_delay_min - t30_start + 250000.0*t_30_map_5 <= 250000.0\n", + "_C120852: PE5_time_delay_max - t31_end_ - 250000.0*t_31_map_5 >= -250000.0\n", + "_C120853: PE5_time_delay_min - t31_start + 250000.0*t_31_map_5 <= 250000.0\n", + "_C120854: PE5_time_delay_max - t32_end_ - 250000.0*t_32_map_5 >= -250000.0\n", + "_C120855: PE5_time_delay_min - t32_start + 250000.0*t_32_map_5 <= 250000.0\n", + "_C120856: PE5_time_delay_max - t33_end_ - 250000.0*t_33_map_5 >= -250000.0\n", + "_C120857: PE5_time_delay_min - t33_start + 250000.0*t_33_map_5 <= 250000.0\n", + "_C120858: PE5_time_delay_max - t34_end_ - 250000.0*t_34_map_5 >= -250000.0\n", + "_C120859: PE5_time_delay_min - t34_start + 250000.0*t_34_map_5 <= 250000.0\n", + "_C120860: PE5_time_delay_max - t35_end_ - 250000.0*t_35_map_5 >= -250000.0\n", + "_C120861: PE5_time_delay_min - t35_start + 250000.0*t_35_map_5 <= 250000.0\n", + "_C120862: PE5_time_delay_max - t36_end_ - 250000.0*t_36_map_5 >= -250000.0\n", + "_C120863: PE5_time_delay_min - t36_start + 250000.0*t_36_map_5 <= 250000.0\n", + "_C120864: PE5_time_delay_max - t37_end_ - 250000.0*t_37_map_5 >= -250000.0\n", + "_C120865: PE5_time_delay_min - t37_start + 250000.0*t_37_map_5 <= 250000.0\n", + "_C120866: PE5_time_delay_max - t38_end_ - 250000.0*t_38_map_5 >= -250000.0\n", + "_C120867: PE5_time_delay_min - t38_start + 250000.0*t_38_map_5 <= 250000.0\n", + "_C120868: PE5_time_delay_max - t39_end_ - 250000.0*t_39_map_5 >= -250000.0\n", + "_C120869: PE5_time_delay_min - t39_start + 250000.0*t_39_map_5 <= 250000.0\n", + "_C120870: PE5_time_delay_max - t40_end_ - 250000.0*t_40_map_5 >= -250000.0\n", + "_C120871: PE5_time_delay_min - t40_start + 250000.0*t_40_map_5 <= 250000.0\n", + "_C120872: PE5_time_delay_max - t41_end_ - 250000.0*t_41_map_5 >= -250000.0\n", + "_C120873: PE5_time_delay_min - t41_start + 250000.0*t_41_map_5 <= 250000.0\n", + "_C120874: PE5_time_delay_max - t42_end_ - 250000.0*t_42_map_5 >= -250000.0\n", + "_C120875: PE5_time_delay_min - t42_start + 250000.0*t_42_map_5 <= 250000.0\n", + "_C120876: PE5_time_delay_max - t43_end_ - 250000.0*t_43_map_5 >= -250000.0\n", + "_C120877: PE5_time_delay_min - t43_start + 250000.0*t_43_map_5 <= 250000.0\n", + "_C120878: PE5_time_delay_max - t44_end_ - 250000.0*t_44_map_5 >= -250000.0\n", + "_C120879: PE5_time_delay_min - t44_start + 250000.0*t_44_map_5 <= 250000.0\n", + "_C120880: PE5_time_delay_max - t45_end_ - 250000.0*t_45_map_5 >= -250000.0\n", + "_C120881: PE5_time_delay_min - t45_start + 250000.0*t_45_map_5 <= 250000.0\n", + "_C120882: PE5_time_delay_max - t46_end_ - 250000.0*t_46_map_5 >= -250000.0\n", + "_C120883: PE5_time_delay_min - t46_start + 250000.0*t_46_map_5 <= 250000.0\n", + "_C120884: PE5_time_delay_max - t47_end_ - 250000.0*t_47_map_5 >= -250000.0\n", + "_C120885: PE5_time_delay_min - t47_start + 250000.0*t_47_map_5 <= 250000.0\n", + "_C120886: PE5_time_delay_max - t48_end_ - 250000.0*t_48_map_5 >= -250000.0\n", + "_C120887: PE5_time_delay_min - t48_start + 250000.0*t_48_map_5 <= 250000.0\n", + "_C120888: PE5_time_delay_max - t49_end_ - 250000.0*t_49_map_5 >= -250000.0\n", + "_C120889: PE5_time_delay_min - t49_start + 250000.0*t_49_map_5 <= 250000.0\n", + "_C120890: PE5_time_delay_max - t50_end_ - 250000.0*t_50_map_5 >= -250000.0\n", + "_C120891: PE5_time_delay_min - t50_start + 250000.0*t_50_map_5 <= 250000.0\n", + "_C120892: PE5_time_delay_max - t51_end_ - 250000.0*t_51_map_5 >= -250000.0\n", + "_C120893: PE5_time_delay_min - t51_start + 250000.0*t_51_map_5 <= 250000.0\n", + "_C120894: PE5_time_delay_max - t52_end_ - 250000.0*t_52_map_5 >= -250000.0\n", + "_C120895: PE5_time_delay_min - t52_start + 250000.0*t_52_map_5 <= 250000.0\n", + "_C120896: PE5_time_delay_max - t53_end_ - 250000.0*t_53_map_5 >= -250000.0\n", + "_C120897: PE5_time_delay_min - t53_start + 250000.0*t_53_map_5 <= 250000.0\n", + "_C120898: PE5_time_delay_max - t54_end_ - 250000.0*t_54_map_5 >= -250000.0\n", + "_C120899: PE5_time_delay_min - t54_start + 250000.0*t_54_map_5 <= 250000.0\n", + "_C120900: PE5_time_delay_max - t55_end_ - 250000.0*t_55_map_5 >= -250000.0\n", + "_C120901: PE5_time_delay_min - t55_start + 250000.0*t_55_map_5 <= 250000.0\n", + "_C120902: PE5_time_delay_max - t56_end_ - 250000.0*t_56_map_5 >= -250000.0\n", + "_C120903: PE5_time_delay_min - t56_start + 250000.0*t_56_map_5 <= 250000.0\n", + "_C120904: PE5_time_delay_max - t57_end_ - 250000.0*t_57_map_5 >= -250000.0\n", + "_C120905: PE5_time_delay_min - t57_start + 250000.0*t_57_map_5 <= 250000.0\n", + "_C120906: PE5_time_delay_max - t58_end_ - 250000.0*t_58_map_5 >= -250000.0\n", + "_C120907: PE5_time_delay_min - t58_start + 250000.0*t_58_map_5 <= 250000.0\n", + "_C120908: PE5_time_delay_max - t59_end_ - 250000.0*t_59_map_5 >= -250000.0\n", + "_C120909: PE5_time_delay_min - t59_start + 250000.0*t_59_map_5 <= 250000.0\n", + "_C120910: PE5_time_delay_max - t60_end_ - 250000.0*t_60_map_5 >= -250000.0\n", + "_C120911: PE5_time_delay_min - t60_start + 250000.0*t_60_map_5 <= 250000.0\n", + "_C120912: PE5_time_delay_max - t61_end_ - 250000.0*t_61_map_5 >= -250000.0\n", + "_C120913: PE5_time_delay_min - t61_start + 250000.0*t_61_map_5 <= 250000.0\n", + "_C120914: PE5_time_delay_max - t62_end_ - 250000.0*t_62_map_5 >= -250000.0\n", + "_C120915: PE5_time_delay_min - t62_start + 250000.0*t_62_map_5 <= 250000.0\n", + "_C120916: PE5_time_delay_max - t63_end_ - 250000.0*t_63_map_5 >= -250000.0\n", + "_C120917: PE5_time_delay_min - t63_start + 250000.0*t_63_map_5 <= 250000.0\n", + "_C120918: PE5_time_delay_max - t64_end_ - 250000.0*t_64_map_5 >= -250000.0\n", + "_C120919: PE5_time_delay_min - t64_start + 250000.0*t_64_map_5 <= 250000.0\n", + "_C120920: PE5_time_delay_max - t65_end_ - 250000.0*t_65_map_5 >= -250000.0\n", + "_C120921: PE5_time_delay_min - t65_start + 250000.0*t_65_map_5 <= 250000.0\n", + "_C120922: PE5_time_delay_max - t66_end_ - 250000.0*t_66_map_5 >= -250000.0\n", + "_C120923: PE5_time_delay_min - t66_start + 250000.0*t_66_map_5 <= 250000.0\n", + "_C120924: PE5_time_delay_max - t67_end_ - 250000.0*t_67_map_5 >= -250000.0\n", + "_C120925: PE5_time_delay_min - t67_start + 250000.0*t_67_map_5 <= 250000.0\n", + "_C120926: PE5_time_delay_max - t68_end_ - 250000.0*t_68_map_5 >= -250000.0\n", + "_C120927: PE5_time_delay_min - t68_start + 250000.0*t_68_map_5 <= 250000.0\n", + "_C120928: PE5_time_delay_max - t69_end_ - 250000.0*t_69_map_5 >= -250000.0\n", + "_C120929: PE5_time_delay_min - t69_start + 250000.0*t_69_map_5 <= 250000.0\n", + "_C120930: -PE5_time_delay_max + PE5_time_delay_min + PE5_total_time_delay = 0\n", + "_C120931: -PE5_total_time_delay + max_router_delay >= 0\n", + "_C120932: -t0_end_ + t0_start - 250000.0*t_0_map_6 - t_send_0 + task_total_delay_router_router6_task0 >= -250000.0\n", + "_C120933: -250000.0*t_0_map_6 - t_mem_0 + task_total_memory_router_router6_task0 >= -250000.0\n", + "_C120934: -t1_end_ + t1_start - 250000.0*t_1_map_6 - t_send_1 + task_total_delay_router_router6_task1 >= -250000.0\n", + "_C120935: -250000.0*t_1_map_6 - t_mem_1 + task_total_memory_router_router6_task1 >= -250000.0\n", + "_C120936: -t2_end_ + t2_start - 250000.0*t_2_map_6 - t_send_2 + task_total_delay_router_router6_task2 >= -250000.0\n", + "_C120937: -250000.0*t_2_map_6 - t_mem_2 + task_total_memory_router_router6_task2 >= -250000.0\n", + "_C120938: -t3_end_ + t3_start - 250000.0*t_3_map_6 - t_send_3 + task_total_delay_router_router6_task3 >= -250000.0\n", + "_C120939: -250000.0*t_3_map_6 - t_mem_3 + task_total_memory_router_router6_task3 >= -250000.0\n", + "_C120940: -t4_end_ + t4_start - 250000.0*t_4_map_6 - t_send_4 + task_total_delay_router_router6_task4 >= -250000.0\n", + "_C120941: -250000.0*t_4_map_6 - t_mem_4 + task_total_memory_router_router6_task4 >= -250000.0\n", + "_C120942: -t5_end_ + t5_start - 250000.0*t_5_map_6 - t_send_5 + task_total_delay_router_router6_task5 >= -250000.0\n", + "_C120943: -250000.0*t_5_map_6 - t_mem_5 + task_total_memory_router_router6_task5 >= -250000.0\n", + "_C120944: -t6_end_ + t6_start - 250000.0*t_6_map_6 - t_send_6 + task_total_delay_router_router6_task6 >= -250000.0\n", + "_C120945: -250000.0*t_6_map_6 - t_mem_6 + task_total_memory_router_router6_task6 >= -250000.0\n", + "_C120946: -t7_end_ + t7_start - 250000.0*t_7_map_6 - t_send_7 + task_total_delay_router_router6_task7 >= -250000.0\n", + "_C120947: -250000.0*t_7_map_6 - t_mem_7 + task_total_memory_router_router6_task7 >= -250000.0\n", + "_C120948: -t8_end_ + t8_start - 250000.0*t_8_map_6 - t_send_8 + task_total_delay_router_router6_task8 >= -250000.0\n", + "_C120949: -250000.0*t_8_map_6 - t_mem_8 + task_total_memory_router_router6_task8 >= -250000.0\n", + "_C120950: -t9_end_ + t9_start - 250000.0*t_9_map_6 - t_send_9 + task_total_delay_router_router6_task9 >= -250000.0\n", + "_C120951: -250000.0*t_9_map_6 - t_mem_9 + task_total_memory_router_router6_task9 >= -250000.0\n", + "_C120952: -t10_end_ + t10_start - 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task_total_delay_router_router6_task57 >= -250000.0\n", + "_C121047: -250000.0*t_57_map_6 - t_mem_57 + task_total_memory_router_router6_task57 >= -250000.0\n", + "_C121048: -t58_end_ + t58_start - 250000.0*t_58_map_6 - t_send_58 + task_total_delay_router_router6_task58 >= -250000.0\n", + "_C121049: -250000.0*t_58_map_6 - t_mem_58 + task_total_memory_router_router6_task58 >= -250000.0\n", + "_C121050: -t59_end_ + t59_start - 250000.0*t_59_map_6 - t_send_59 + task_total_delay_router_router6_task59 >= -250000.0\n", + "_C121051: -250000.0*t_59_map_6 - t_mem_59 + task_total_memory_router_router6_task59 >= -250000.0\n", + "_C121052: -t60_end_ + t60_start - 250000.0*t_60_map_6 - t_send_60 + task_total_delay_router_router6_task60 >= -250000.0\n", + "_C121053: -250000.0*t_60_map_6 - t_mem_60 + task_total_memory_router_router6_task60 >= -250000.0\n", + "_C121054: -t61_end_ + t61_start - 250000.0*t_61_map_6 - t_send_61 + task_total_delay_router_router6_task61 >= -250000.0\n", + "_C121055: 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task_total_memory_router_router6_task0 - task_total_memory_router_router6_task1 - task_total_memory_router_router6_task10 - task_total_memory_router_router6_task11 - task_total_memory_router_router6_task12 - task_total_memory_router_router6_task13 - task_total_memory_router_router6_task14 - task_total_memory_router_router6_task15 - task_total_memory_router_router6_task16 - task_total_memory_router_router6_task17 - task_total_memory_router_router6_task18 - task_total_memory_router_router6_task19 - task_total_memory_router_router6_task2 - task_total_memory_router_router6_task20 - task_total_memory_router_router6_task21 - task_total_memory_router_router6_task22 - task_total_memory_router_router6_task23 - task_total_memory_router_router6_task24 - task_total_memory_router_router6_task25 - task_total_memory_router_router6_task26 - task_total_memory_router_router6_task27 - task_total_memory_router_router6_task28 - task_total_memory_router_router6_task29 - task_total_memory_router_router6_task3 - task_total_memory_router_router6_task30 - task_total_memory_router_router6_task31 - task_total_memory_router_router6_task32 - task_total_memory_router_router6_task33 - task_total_memory_router_router6_task34 - task_total_memory_router_router6_task35 - task_total_memory_router_router6_task36 - task_total_memory_router_router6_task37 - task_total_memory_router_router6_task38 - task_total_memory_router_router6_task39 - task_total_memory_router_router6_task4 - task_total_memory_router_router6_task40 - task_total_memory_router_router6_task41 - task_total_memory_router_router6_task42 - task_total_memory_router_router6_task43 - task_total_memory_router_router6_task44 - task_total_memory_router_router6_task45 - task_total_memory_router_router6_task46 - task_total_memory_router_router6_task47 - task_total_memory_router_router6_task48 - task_total_memory_router_router6_task49 - task_total_memory_router_router6_task5 - task_total_memory_router_router6_task50 - task_total_memory_router_router6_task51 - task_total_memory_router_router6_task52 - task_total_memory_router_router6_task53 - task_total_memory_router_router6_task54 - task_total_memory_router_router6_task55 - task_total_memory_router_router6_task56 - task_total_memory_router_router6_task57 - task_total_memory_router_router6_task58 - task_total_memory_router_router6_task59 - task_total_memory_router_router6_task6 - task_total_memory_router_router6_task60 - task_total_memory_router_router6_task61 - task_total_memory_router_router6_task62 - task_total_memory_router_router6_task63 - task_total_memory_router_router6_task64 - task_total_memory_router_router6_task65 - task_total_memory_router_router6_task66 - task_total_memory_router_router6_task67 - task_total_memory_router_router6_task68 - task_total_memory_router_router6_task69 - task_total_memory_router_router6_task7 - task_total_memory_router_router6_task8 - task_total_memory_router_router6_task9 >= -0.0\n", + "_C121073: PE6_total_delay - task_total_delay_router_router6_task0 - task_total_delay_router_router6_task1 - task_total_delay_router_router6_task10 - task_total_delay_router_router6_task11 - task_total_delay_router_router6_task12 - task_total_delay_router_router6_task13 - task_total_delay_router_router6_task14 - task_total_delay_router_router6_task15 - task_total_delay_router_router6_task16 - task_total_delay_router_router6_task17 - task_total_delay_router_router6_task18 - task_total_delay_router_router6_task19 - task_total_delay_router_router6_task2 - task_total_delay_router_router6_task20 - task_total_delay_router_router6_task21 - task_total_delay_router_router6_task22 - task_total_delay_router_router6_task23 - task_total_delay_router_router6_task24 - task_total_delay_router_router6_task25 - task_total_delay_router_router6_task26 - task_total_delay_router_router6_task27 - task_total_delay_router_router6_task28 - task_total_delay_router_router6_task29 - task_total_delay_router_router6_task3 - task_total_delay_router_router6_task30 - task_total_delay_router_router6_task31 - task_total_delay_router_router6_task32 - task_total_delay_router_router6_task33 - task_total_delay_router_router6_task34 - task_total_delay_router_router6_task35 - task_total_delay_router_router6_task36 - task_total_delay_router_router6_task37 - task_total_delay_router_router6_task38 - task_total_delay_router_router6_task39 - task_total_delay_router_router6_task4 - task_total_delay_router_router6_task40 - task_total_delay_router_router6_task41 - task_total_delay_router_router6_task42 - task_total_delay_router_router6_task43 - task_total_delay_router_router6_task44 - task_total_delay_router_router6_task45 - task_total_delay_router_router6_task46 - task_total_delay_router_router6_task47 - task_total_delay_router_router6_task48 - task_total_delay_router_router6_task49 - task_total_delay_router_router6_task5 - task_total_delay_router_router6_task50 - task_total_delay_router_router6_task51 - task_total_delay_router_router6_task52 - task_total_delay_router_router6_task53 - task_total_delay_router_router6_task54 - task_total_delay_router_router6_task55 - task_total_delay_router_router6_task56 - task_total_delay_router_router6_task57 - task_total_delay_router_router6_task58 - task_total_delay_router_router6_task59 - task_total_delay_router_router6_task6 - task_total_delay_router_router6_task60 - task_total_delay_router_router6_task61 - task_total_delay_router_router6_task62 - task_total_delay_router_router6_task63 - task_total_delay_router_router6_task64 - task_total_delay_router_router6_task65 - task_total_delay_router_router6_task66 - task_total_delay_router_router6_task67 - task_total_delay_router_router6_task68 - task_total_delay_router_router6_task69 - task_total_delay_router_router6_task7 - task_total_delay_router_router6_task8 - task_total_delay_router_router6_task9 >= -0.0\n", + "_C121074: PE6_total_memory - task_total_memory_router_router6_task0 - task_total_memory_router_router6_task1 - task_total_memory_router_router6_task10 - task_total_memory_router_router6_task11 - task_total_memory_router_router6_task12 - task_total_memory_router_router6_task13 - task_total_memory_router_router6_task14 - task_total_memory_router_router6_task15 - task_total_memory_router_router6_task16 - task_total_memory_router_router6_task17 - task_total_memory_router_router6_task18 - task_total_memory_router_router6_task19 - task_total_memory_router_router6_task2 - task_total_memory_router_router6_task20 - task_total_memory_router_router6_task21 - task_total_memory_router_router6_task22 - task_total_memory_router_router6_task23 - task_total_memory_router_router6_task24 - task_total_memory_router_router6_task25 - task_total_memory_router_router6_task26 - task_total_memory_router_router6_task27 - task_total_memory_router_router6_task28 - task_total_memory_router_router6_task29 - task_total_memory_router_router6_task3 - task_total_memory_router_router6_task30 - task_total_memory_router_router6_task31 - task_total_memory_router_router6_task32 - task_total_memory_router_router6_task33 - task_total_memory_router_router6_task34 - task_total_memory_router_router6_task35 - task_total_memory_router_router6_task36 - task_total_memory_router_router6_task37 - task_total_memory_router_router6_task38 - task_total_memory_router_router6_task39 - task_total_memory_router_router6_task4 - task_total_memory_router_router6_task40 - task_total_memory_router_router6_task41 - task_total_memory_router_router6_task42 - task_total_memory_router_router6_task43 - task_total_memory_router_router6_task44 - task_total_memory_router_router6_task45 - task_total_memory_router_router6_task46 - task_total_memory_router_router6_task47 - task_total_memory_router_router6_task48 - task_total_memory_router_router6_task49 - task_total_memory_router_router6_task5 - task_total_memory_router_router6_task50 - task_total_memory_router_router6_task51 - task_total_memory_router_router6_task52 - task_total_memory_router_router6_task53 - task_total_memory_router_router6_task54 - task_total_memory_router_router6_task55 - task_total_memory_router_router6_task56 - task_total_memory_router_router6_task57 - task_total_memory_router_router6_task58 - task_total_memory_router_router6_task59 - task_total_memory_router_router6_task6 - task_total_memory_router_router6_task60 - task_total_memory_router_router6_task61 - task_total_memory_router_router6_task62 - task_total_memory_router_router6_task63 - task_total_memory_router_router6_task64 - task_total_memory_router_router6_task65 - task_total_memory_router_router6_task66 - task_total_memory_router_router6_task67 - task_total_memory_router_router6_task68 - task_total_memory_router_router6_task69 - task_total_memory_router_router6_task7 - task_total_memory_router_router6_task8 - 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task_total_memory_router_router7_task7 - task_total_memory_router_router7_task8 - task_total_memory_router_router7_task9 >= -0.0\n", + "_C121359: PE7_total_delay - task_total_delay_router_router7_task0 - task_total_delay_router_router7_task1 - task_total_delay_router_router7_task10 - task_total_delay_router_router7_task11 - task_total_delay_router_router7_task12 - task_total_delay_router_router7_task13 - task_total_delay_router_router7_task14 - task_total_delay_router_router7_task15 - task_total_delay_router_router7_task16 - task_total_delay_router_router7_task17 - task_total_delay_router_router7_task18 - task_total_delay_router_router7_task19 - task_total_delay_router_router7_task2 - task_total_delay_router_router7_task20 - task_total_delay_router_router7_task21 - task_total_delay_router_router7_task22 - task_total_delay_router_router7_task23 - task_total_delay_router_router7_task24 - task_total_delay_router_router7_task25 - task_total_delay_router_router7_task26 - task_total_delay_router_router7_task27 - task_total_delay_router_router7_task28 - task_total_delay_router_router7_task29 - task_total_delay_router_router7_task3 - task_total_delay_router_router7_task30 - task_total_delay_router_router7_task31 - task_total_delay_router_router7_task32 - task_total_delay_router_router7_task33 - task_total_delay_router_router7_task34 - task_total_delay_router_router7_task35 - task_total_delay_router_router7_task36 - task_total_delay_router_router7_task37 - task_total_delay_router_router7_task38 - task_total_delay_router_router7_task39 - task_total_delay_router_router7_task4 - task_total_delay_router_router7_task40 - task_total_delay_router_router7_task41 - task_total_delay_router_router7_task42 - task_total_delay_router_router7_task43 - task_total_delay_router_router7_task44 - task_total_delay_router_router7_task45 - task_total_delay_router_router7_task46 - task_total_delay_router_router7_task47 - task_total_delay_router_router7_task48 - task_total_delay_router_router7_task49 - task_total_delay_router_router7_task5 - task_total_delay_router_router7_task50 - task_total_delay_router_router7_task51 - task_total_delay_router_router7_task52 - task_total_delay_router_router7_task53 - task_total_delay_router_router7_task54 - task_total_delay_router_router7_task55 - task_total_delay_router_router7_task56 - task_total_delay_router_router7_task57 - task_total_delay_router_router7_task58 - task_total_delay_router_router7_task59 - task_total_delay_router_router7_task6 - task_total_delay_router_router7_task60 - task_total_delay_router_router7_task61 - task_total_delay_router_router7_task62 - task_total_delay_router_router7_task63 - task_total_delay_router_router7_task64 - task_total_delay_router_router7_task65 - task_total_delay_router_router7_task66 - task_total_delay_router_router7_task67 - task_total_delay_router_router7_task68 - task_total_delay_router_router7_task69 - task_total_delay_router_router7_task7 - task_total_delay_router_router7_task8 - task_total_delay_router_router7_task9 >= -0.0\n", + "_C121360: PE7_total_memory - task_total_memory_router_router7_task0 - task_total_memory_router_router7_task1 - task_total_memory_router_router7_task10 - task_total_memory_router_router7_task11 - task_total_memory_router_router7_task12 - task_total_memory_router_router7_task13 - task_total_memory_router_router7_task14 - task_total_memory_router_router7_task15 - task_total_memory_router_router7_task16 - task_total_memory_router_router7_task17 - task_total_memory_router_router7_task18 - task_total_memory_router_router7_task19 - task_total_memory_router_router7_task2 - task_total_memory_router_router7_task20 - task_total_memory_router_router7_task21 - task_total_memory_router_router7_task22 - task_total_memory_router_router7_task23 - task_total_memory_router_router7_task24 - task_total_memory_router_router7_task25 - task_total_memory_router_router7_task26 - task_total_memory_router_router7_task27 - task_total_memory_router_router7_task28 - task_total_memory_router_router7_task29 - task_total_memory_router_router7_task3 - task_total_memory_router_router7_task30 - task_total_memory_router_router7_task31 - task_total_memory_router_router7_task32 - task_total_memory_router_router7_task33 - task_total_memory_router_router7_task34 - task_total_memory_router_router7_task35 - task_total_memory_router_router7_task36 - task_total_memory_router_router7_task37 - task_total_memory_router_router7_task38 - task_total_memory_router_router7_task39 - task_total_memory_router_router7_task4 - task_total_memory_router_router7_task40 - task_total_memory_router_router7_task41 - task_total_memory_router_router7_task42 - task_total_memory_router_router7_task43 - task_total_memory_router_router7_task44 - task_total_memory_router_router7_task45 - task_total_memory_router_router7_task46 - task_total_memory_router_router7_task47 - task_total_memory_router_router7_task48 - task_total_memory_router_router7_task49 - task_total_memory_router_router7_task5 - task_total_memory_router_router7_task50 - task_total_memory_router_router7_task51 - task_total_memory_router_router7_task52 - task_total_memory_router_router7_task53 - task_total_memory_router_router7_task54 - task_total_memory_router_router7_task55 - task_total_memory_router_router7_task56 - task_total_memory_router_router7_task57 - task_total_memory_router_router7_task58 - task_total_memory_router_router7_task59 - task_total_memory_router_router7_task6 - task_total_memory_router_router7_task60 - task_total_memory_router_router7_task61 - task_total_memory_router_router7_task62 - task_total_memory_router_router7_task63 - task_total_memory_router_router7_task64 - task_total_memory_router_router7_task65 - task_total_memory_router_router7_task66 - task_total_memory_router_router7_task67 - task_total_memory_router_router7_task68 - task_total_memory_router_router7_task69 - 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task_total_memory_router_router8_task26 - task_total_memory_router_router8_task27 - task_total_memory_router_router8_task28 - task_total_memory_router_router8_task29 - task_total_memory_router_router8_task3 - task_total_memory_router_router8_task30 - task_total_memory_router_router8_task31 - task_total_memory_router_router8_task32 - task_total_memory_router_router8_task33 - task_total_memory_router_router8_task34 - task_total_memory_router_router8_task35 - task_total_memory_router_router8_task36 - task_total_memory_router_router8_task37 - task_total_memory_router_router8_task38 - task_total_memory_router_router8_task39 - task_total_memory_router_router8_task4 - task_total_memory_router_router8_task40 - task_total_memory_router_router8_task41 - task_total_memory_router_router8_task42 - task_total_memory_router_router8_task43 - task_total_memory_router_router8_task44 - task_total_memory_router_router8_task45 - task_total_memory_router_router8_task46 - task_total_memory_router_router8_task47 - task_total_memory_router_router8_task48 - task_total_memory_router_router8_task49 - task_total_memory_router_router8_task5 - task_total_memory_router_router8_task50 - task_total_memory_router_router8_task51 - task_total_memory_router_router8_task52 - task_total_memory_router_router8_task53 - task_total_memory_router_router8_task54 - task_total_memory_router_router8_task55 - task_total_memory_router_router8_task56 - task_total_memory_router_router8_task57 - task_total_memory_router_router8_task58 - task_total_memory_router_router8_task59 - task_total_memory_router_router8_task6 - task_total_memory_router_router8_task60 - task_total_memory_router_router8_task61 - task_total_memory_router_router8_task62 - task_total_memory_router_router8_task63 - task_total_memory_router_router8_task64 - task_total_memory_router_router8_task65 - task_total_memory_router_router8_task66 - task_total_memory_router_router8_task67 - task_total_memory_router_router8_task68 - task_total_memory_router_router8_task69 - task_total_memory_router_router8_task7 - task_total_memory_router_router8_task8 - task_total_memory_router_router8_task9 >= -0.0\n", + "_C121645: PE8_total_delay - task_total_delay_router_router8_task0 - task_total_delay_router_router8_task1 - task_total_delay_router_router8_task10 - task_total_delay_router_router8_task11 - task_total_delay_router_router8_task12 - task_total_delay_router_router8_task13 - task_total_delay_router_router8_task14 - task_total_delay_router_router8_task15 - task_total_delay_router_router8_task16 - task_total_delay_router_router8_task17 - task_total_delay_router_router8_task18 - task_total_delay_router_router8_task19 - task_total_delay_router_router8_task2 - task_total_delay_router_router8_task20 - task_total_delay_router_router8_task21 - task_total_delay_router_router8_task22 - task_total_delay_router_router8_task23 - task_total_delay_router_router8_task24 - task_total_delay_router_router8_task25 - task_total_delay_router_router8_task26 - task_total_delay_router_router8_task27 - task_total_delay_router_router8_task28 - task_total_delay_router_router8_task29 - task_total_delay_router_router8_task3 - task_total_delay_router_router8_task30 - task_total_delay_router_router8_task31 - task_total_delay_router_router8_task32 - task_total_delay_router_router8_task33 - task_total_delay_router_router8_task34 - task_total_delay_router_router8_task35 - task_total_delay_router_router8_task36 - task_total_delay_router_router8_task37 - task_total_delay_router_router8_task38 - task_total_delay_router_router8_task39 - task_total_delay_router_router8_task4 - task_total_delay_router_router8_task40 - task_total_delay_router_router8_task41 - task_total_delay_router_router8_task42 - task_total_delay_router_router8_task43 - task_total_delay_router_router8_task44 - task_total_delay_router_router8_task45 - task_total_delay_router_router8_task46 - task_total_delay_router_router8_task47 - task_total_delay_router_router8_task48 - task_total_delay_router_router8_task49 - task_total_delay_router_router8_task5 - task_total_delay_router_router8_task50 - task_total_delay_router_router8_task51 - task_total_delay_router_router8_task52 - task_total_delay_router_router8_task53 - task_total_delay_router_router8_task54 - task_total_delay_router_router8_task55 - task_total_delay_router_router8_task56 - task_total_delay_router_router8_task57 - task_total_delay_router_router8_task58 - task_total_delay_router_router8_task59 - task_total_delay_router_router8_task6 - task_total_delay_router_router8_task60 - task_total_delay_router_router8_task61 - task_total_delay_router_router8_task62 - task_total_delay_router_router8_task63 - task_total_delay_router_router8_task64 - task_total_delay_router_router8_task65 - task_total_delay_router_router8_task66 - task_total_delay_router_router8_task67 - task_total_delay_router_router8_task68 - task_total_delay_router_router8_task69 - task_total_delay_router_router8_task7 - task_total_delay_router_router8_task8 - task_total_delay_router_router8_task9 >= -0.0\n", + "_C121646: PE8_total_memory - task_total_memory_router_router8_task0 - task_total_memory_router_router8_task1 - task_total_memory_router_router8_task10 - task_total_memory_router_router8_task11 - task_total_memory_router_router8_task12 - task_total_memory_router_router8_task13 - task_total_memory_router_router8_task14 - task_total_memory_router_router8_task15 - task_total_memory_router_router8_task16 - task_total_memory_router_router8_task17 - task_total_memory_router_router8_task18 - task_total_memory_router_router8_task19 - task_total_memory_router_router8_task2 - task_total_memory_router_router8_task20 - task_total_memory_router_router8_task21 - task_total_memory_router_router8_task22 - task_total_memory_router_router8_task23 - task_total_memory_router_router8_task24 - task_total_memory_router_router8_task25 - task_total_memory_router_router8_task26 - task_total_memory_router_router8_task27 - task_total_memory_router_router8_task28 - task_total_memory_router_router8_task29 - task_total_memory_router_router8_task3 - task_total_memory_router_router8_task30 - task_total_memory_router_router8_task31 - task_total_memory_router_router8_task32 - task_total_memory_router_router8_task33 - task_total_memory_router_router8_task34 - task_total_memory_router_router8_task35 - task_total_memory_router_router8_task36 - task_total_memory_router_router8_task37 - task_total_memory_router_router8_task38 - task_total_memory_router_router8_task39 - task_total_memory_router_router8_task4 - task_total_memory_router_router8_task40 - task_total_memory_router_router8_task41 - task_total_memory_router_router8_task42 - task_total_memory_router_router8_task43 - task_total_memory_router_router8_task44 - task_total_memory_router_router8_task45 - task_total_memory_router_router8_task46 - task_total_memory_router_router8_task47 - task_total_memory_router_router8_task48 - task_total_memory_router_router8_task49 - task_total_memory_router_router8_task5 - task_total_memory_router_router8_task50 - task_total_memory_router_router8_task51 - task_total_memory_router_router8_task52 - task_total_memory_router_router8_task53 - task_total_memory_router_router8_task54 - task_total_memory_router_router8_task55 - task_total_memory_router_router8_task56 - task_total_memory_router_router8_task57 - task_total_memory_router_router8_task58 - task_total_memory_router_router8_task59 - task_total_memory_router_router8_task6 - task_total_memory_router_router8_task60 - task_total_memory_router_router8_task61 - task_total_memory_router_router8_task62 - task_total_memory_router_router8_task63 - task_total_memory_router_router8_task64 - task_total_memory_router_router8_task65 - task_total_memory_router_router8_task66 - task_total_memory_router_router8_task67 - 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task_total_memory_router_router9_task23 - task_total_memory_router_router9_task24 - task_total_memory_router_router9_task25 - task_total_memory_router_router9_task26 - task_total_memory_router_router9_task27 - task_total_memory_router_router9_task28 - task_total_memory_router_router9_task29 - task_total_memory_router_router9_task3 - task_total_memory_router_router9_task30 - task_total_memory_router_router9_task31 - task_total_memory_router_router9_task32 - task_total_memory_router_router9_task33 - task_total_memory_router_router9_task34 - task_total_memory_router_router9_task35 - task_total_memory_router_router9_task36 - task_total_memory_router_router9_task37 - task_total_memory_router_router9_task38 - task_total_memory_router_router9_task39 - task_total_memory_router_router9_task4 - task_total_memory_router_router9_task40 - task_total_memory_router_router9_task41 - task_total_memory_router_router9_task42 - task_total_memory_router_router9_task43 - task_total_memory_router_router9_task44 - task_total_memory_router_router9_task45 - task_total_memory_router_router9_task46 - task_total_memory_router_router9_task47 - task_total_memory_router_router9_task48 - task_total_memory_router_router9_task49 - task_total_memory_router_router9_task5 - task_total_memory_router_router9_task50 - task_total_memory_router_router9_task51 - task_total_memory_router_router9_task52 - task_total_memory_router_router9_task53 - task_total_memory_router_router9_task54 - task_total_memory_router_router9_task55 - task_total_memory_router_router9_task56 - task_total_memory_router_router9_task57 - task_total_memory_router_router9_task58 - task_total_memory_router_router9_task59 - task_total_memory_router_router9_task6 - task_total_memory_router_router9_task60 - task_total_memory_router_router9_task61 - task_total_memory_router_router9_task62 - task_total_memory_router_router9_task63 - task_total_memory_router_router9_task64 - task_total_memory_router_router9_task65 - task_total_memory_router_router9_task66 - task_total_memory_router_router9_task67 - task_total_memory_router_router9_task68 - task_total_memory_router_router9_task69 - task_total_memory_router_router9_task7 - task_total_memory_router_router9_task8 - task_total_memory_router_router9_task9 >= -0.0\n", + "_C121931: PE9_total_delay - task_total_delay_router_router9_task0 - task_total_delay_router_router9_task1 - task_total_delay_router_router9_task10 - task_total_delay_router_router9_task11 - task_total_delay_router_router9_task12 - task_total_delay_router_router9_task13 - task_total_delay_router_router9_task14 - task_total_delay_router_router9_task15 - task_total_delay_router_router9_task16 - task_total_delay_router_router9_task17 - task_total_delay_router_router9_task18 - task_total_delay_router_router9_task19 - task_total_delay_router_router9_task2 - task_total_delay_router_router9_task20 - task_total_delay_router_router9_task21 - task_total_delay_router_router9_task22 - task_total_delay_router_router9_task23 - task_total_delay_router_router9_task24 - task_total_delay_router_router9_task25 - task_total_delay_router_router9_task26 - task_total_delay_router_router9_task27 - task_total_delay_router_router9_task28 - task_total_delay_router_router9_task29 - task_total_delay_router_router9_task3 - task_total_delay_router_router9_task30 - task_total_delay_router_router9_task31 - task_total_delay_router_router9_task32 - task_total_delay_router_router9_task33 - task_total_delay_router_router9_task34 - task_total_delay_router_router9_task35 - task_total_delay_router_router9_task36 - task_total_delay_router_router9_task37 - task_total_delay_router_router9_task38 - task_total_delay_router_router9_task39 - task_total_delay_router_router9_task4 - task_total_delay_router_router9_task40 - task_total_delay_router_router9_task41 - task_total_delay_router_router9_task42 - task_total_delay_router_router9_task43 - task_total_delay_router_router9_task44 - task_total_delay_router_router9_task45 - task_total_delay_router_router9_task46 - task_total_delay_router_router9_task47 - task_total_delay_router_router9_task48 - task_total_delay_router_router9_task49 - task_total_delay_router_router9_task5 - task_total_delay_router_router9_task50 - task_total_delay_router_router9_task51 - task_total_delay_router_router9_task52 - task_total_delay_router_router9_task53 - task_total_delay_router_router9_task54 - task_total_delay_router_router9_task55 - task_total_delay_router_router9_task56 - task_total_delay_router_router9_task57 - task_total_delay_router_router9_task58 - task_total_delay_router_router9_task59 - task_total_delay_router_router9_task6 - task_total_delay_router_router9_task60 - task_total_delay_router_router9_task61 - task_total_delay_router_router9_task62 - task_total_delay_router_router9_task63 - task_total_delay_router_router9_task64 - task_total_delay_router_router9_task65 - task_total_delay_router_router9_task66 - task_total_delay_router_router9_task67 - task_total_delay_router_router9_task68 - task_total_delay_router_router9_task69 - task_total_delay_router_router9_task7 - task_total_delay_router_router9_task8 - task_total_delay_router_router9_task9 >= -0.0\n", + "_C121932: PE9_total_memory - task_total_memory_router_router9_task0 - task_total_memory_router_router9_task1 - task_total_memory_router_router9_task10 - task_total_memory_router_router9_task11 - task_total_memory_router_router9_task12 - task_total_memory_router_router9_task13 - task_total_memory_router_router9_task14 - task_total_memory_router_router9_task15 - task_total_memory_router_router9_task16 - task_total_memory_router_router9_task17 - task_total_memory_router_router9_task18 - task_total_memory_router_router9_task19 - task_total_memory_router_router9_task2 - task_total_memory_router_router9_task20 - task_total_memory_router_router9_task21 - task_total_memory_router_router9_task22 - task_total_memory_router_router9_task23 - task_total_memory_router_router9_task24 - task_total_memory_router_router9_task25 - task_total_memory_router_router9_task26 - task_total_memory_router_router9_task27 - task_total_memory_router_router9_task28 - task_total_memory_router_router9_task29 - task_total_memory_router_router9_task3 - task_total_memory_router_router9_task30 - task_total_memory_router_router9_task31 - task_total_memory_router_router9_task32 - task_total_memory_router_router9_task33 - task_total_memory_router_router9_task34 - task_total_memory_router_router9_task35 - task_total_memory_router_router9_task36 - task_total_memory_router_router9_task37 - task_total_memory_router_router9_task38 - task_total_memory_router_router9_task39 - task_total_memory_router_router9_task4 - task_total_memory_router_router9_task40 - task_total_memory_router_router9_task41 - task_total_memory_router_router9_task42 - task_total_memory_router_router9_task43 - task_total_memory_router_router9_task44 - task_total_memory_router_router9_task45 - task_total_memory_router_router9_task46 - task_total_memory_router_router9_task47 - task_total_memory_router_router9_task48 - task_total_memory_router_router9_task49 - task_total_memory_router_router9_task5 - task_total_memory_router_router9_task50 - task_total_memory_router_router9_task51 - task_total_memory_router_router9_task52 - task_total_memory_router_router9_task53 - task_total_memory_router_router9_task54 - task_total_memory_router_router9_task55 - task_total_memory_router_router9_task56 - task_total_memory_router_router9_task57 - task_total_memory_router_router9_task58 - task_total_memory_router_router9_task59 - task_total_memory_router_router9_task6 - task_total_memory_router_router9_task60 - task_total_memory_router_router9_task61 - task_total_memory_router_router9_task62 - task_total_memory_router_router9_task63 - task_total_memory_router_router9_task64 - task_total_memory_router_router9_task65 - task_total_memory_router_router9_task66 - task_total_memory_router_router9_task67 - task_total_memory_router_router9_task68 - task_total_memory_router_router9_task69 - task_total_memory_router_router9_task7 - task_total_memory_router_router9_task8 - task_total_memory_router_router9_task9 >= -0.0\n", + "_C121933: -PE_mem_overflow9 + max_memory_overflow >= 0\n", + "_C121934: PE9_time_delay_max - t0_end_ - 250000.0*t_0_map_9 >= -250000.0\n", + "_C121935: PE9_time_delay_min - t0_start + 250000.0*t_0_map_9 <= 250000.0\n", + "_C121936: PE9_time_delay_max - t1_end_ - 250000.0*t_1_map_9 >= -250000.0\n", + "_C121937: PE9_time_delay_min - t1_start + 250000.0*t_1_map_9 <= 250000.0\n", + "_C121938: PE9_time_delay_max - t2_end_ - 250000.0*t_2_map_9 >= -250000.0\n", + "_C121939: PE9_time_delay_min - t2_start + 250000.0*t_2_map_9 <= 250000.0\n", + "_C121940: PE9_time_delay_max - t3_end_ - 250000.0*t_3_map_9 >= -250000.0\n", + "_C121941: PE9_time_delay_min - 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250000.0\n", + "_C121954: PE9_time_delay_max - t10_end_ - 250000.0*t_10_map_9 >= -250000.0\n", + "_C121955: PE9_time_delay_min - t10_start + 250000.0*t_10_map_9 <= 250000.0\n", + "_C121956: PE9_time_delay_max - t11_end_ - 250000.0*t_11_map_9 >= -250000.0\n", + "_C121957: PE9_time_delay_min - t11_start + 250000.0*t_11_map_9 <= 250000.0\n", + "_C121958: PE9_time_delay_max - t12_end_ - 250000.0*t_12_map_9 >= -250000.0\n", + "_C121959: PE9_time_delay_min - t12_start + 250000.0*t_12_map_9 <= 250000.0\n", + "_C121960: PE9_time_delay_max - t13_end_ - 250000.0*t_13_map_9 >= -250000.0\n", + "_C121961: PE9_time_delay_min - t13_start + 250000.0*t_13_map_9 <= 250000.0\n", + "_C121962: PE9_time_delay_max - t14_end_ - 250000.0*t_14_map_9 >= -250000.0\n", + "_C121963: PE9_time_delay_min - t14_start + 250000.0*t_14_map_9 <= 250000.0\n", + "_C121964: PE9_time_delay_max - t15_end_ - 250000.0*t_15_map_9 >= -250000.0\n", + "_C121965: PE9_time_delay_min - t15_start + 250000.0*t_15_map_9 <= 250000.0\n", + 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PE9_time_delay_max - t34_end_ - 250000.0*t_34_map_9 >= -250000.0\n", + "_C122003: PE9_time_delay_min - t34_start + 250000.0*t_34_map_9 <= 250000.0\n", + "_C122004: PE9_time_delay_max - t35_end_ - 250000.0*t_35_map_9 >= -250000.0\n", + "_C122005: PE9_time_delay_min - t35_start + 250000.0*t_35_map_9 <= 250000.0\n", + "_C122006: PE9_time_delay_max - t36_end_ - 250000.0*t_36_map_9 >= -250000.0\n", + "_C122007: PE9_time_delay_min - t36_start + 250000.0*t_36_map_9 <= 250000.0\n", + "_C122008: PE9_time_delay_max - t37_end_ - 250000.0*t_37_map_9 >= -250000.0\n", + "_C122009: PE9_time_delay_min - t37_start + 250000.0*t_37_map_9 <= 250000.0\n", + "_C122010: PE9_time_delay_max - t38_end_ - 250000.0*t_38_map_9 >= -250000.0\n", + "_C122011: PE9_time_delay_min - t38_start + 250000.0*t_38_map_9 <= 250000.0\n", + "_C122012: PE9_time_delay_max - t39_end_ - 250000.0*t_39_map_9 >= -250000.0\n", + "_C122013: PE9_time_delay_min - t39_start + 250000.0*t_39_map_9 <= 250000.0\n", + "_C122014: PE9_time_delay_max - t40_end_ - 250000.0*t_40_map_9 >= -250000.0\n", + "_C122015: PE9_time_delay_min - t40_start + 250000.0*t_40_map_9 <= 250000.0\n", + "_C122016: PE9_time_delay_max - t41_end_ - 250000.0*t_41_map_9 >= -250000.0\n", + "_C122017: PE9_time_delay_min - t41_start + 250000.0*t_41_map_9 <= 250000.0\n", + "_C122018: PE9_time_delay_max - t42_end_ - 250000.0*t_42_map_9 >= -250000.0\n", + "_C122019: PE9_time_delay_min - t42_start + 250000.0*t_42_map_9 <= 250000.0\n", + "_C122020: PE9_time_delay_max - t43_end_ - 250000.0*t_43_map_9 >= -250000.0\n", + "_C122021: PE9_time_delay_min - t43_start + 250000.0*t_43_map_9 <= 250000.0\n", + "_C122022: PE9_time_delay_max - t44_end_ - 250000.0*t_44_map_9 >= -250000.0\n", + "_C122023: PE9_time_delay_min - t44_start + 250000.0*t_44_map_9 <= 250000.0\n", + "_C122024: PE9_time_delay_max - t45_end_ - 250000.0*t_45_map_9 >= -250000.0\n", + "_C122025: PE9_time_delay_min - t45_start + 250000.0*t_45_map_9 <= 250000.0\n", + "_C122026: 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"_C122143: -250000.0*t_33_map_10 - t_mem_33 + task_total_memory_router_router10_task33 >= -250000.0\n", + "_C122144: -t34_end_ + t34_start - 250000.0*t_34_map_10 - t_send_34 + task_total_delay_router_router10_task34 >= -250000.0\n", + "_C122145: -250000.0*t_34_map_10 - t_mem_34 + task_total_memory_router_router10_task34 >= -250000.0\n", + "_C122146: -t35_end_ + t35_start - 250000.0*t_35_map_10 - t_send_35 + task_total_delay_router_router10_task35 >= -250000.0\n", + "_C122147: -250000.0*t_35_map_10 - t_mem_35 + task_total_memory_router_router10_task35 >= -250000.0\n", + "_C122148: -t36_end_ + t36_start - 250000.0*t_36_map_10 - t_send_36 + task_total_delay_router_router10_task36 >= -250000.0\n", + "_C122149: -250000.0*t_36_map_10 - t_mem_36 + task_total_memory_router_router10_task36 >= -250000.0\n", + "_C122150: -t37_end_ + t37_start - 250000.0*t_37_map_10 - t_send_37 + task_total_delay_router_router10_task37 >= -250000.0\n", + "_C122151: -250000.0*t_37_map_10 - t_mem_37 + task_total_memory_router_router10_task37 >= -250000.0\n", + "_C122152: -t38_end_ + t38_start - 250000.0*t_38_map_10 - t_send_38 + task_total_delay_router_router10_task38 >= -250000.0\n", + "_C122153: -250000.0*t_38_map_10 - t_mem_38 + task_total_memory_router_router10_task38 >= -250000.0\n", + "_C122154: -t39_end_ + t39_start - 250000.0*t_39_map_10 - t_send_39 + task_total_delay_router_router10_task39 >= -250000.0\n", + "_C122155: -250000.0*t_39_map_10 - t_mem_39 + task_total_memory_router_router10_task39 >= -250000.0\n", + "_C122156: -t40_end_ + t40_start - 250000.0*t_40_map_10 - t_send_40 + task_total_delay_router_router10_task40 >= -250000.0\n", + "_C122157: -250000.0*t_40_map_10 - t_mem_40 + task_total_memory_router_router10_task40 >= -250000.0\n", + "_C122158: -t41_end_ + t41_start - 250000.0*t_41_map_10 - t_send_41 + task_total_delay_router_router10_task41 >= -250000.0\n", + "_C122159: -250000.0*t_41_map_10 - t_mem_41 + task_total_memory_router_router10_task41 >= -250000.0\n", + "_C122160: -t42_end_ + t42_start - 250000.0*t_42_map_10 - t_send_42 + task_total_delay_router_router10_task42 >= -250000.0\n", + "_C122161: -250000.0*t_42_map_10 - t_mem_42 + task_total_memory_router_router10_task42 >= -250000.0\n", + "_C122162: -t43_end_ + t43_start - 250000.0*t_43_map_10 - t_send_43 + task_total_delay_router_router10_task43 >= -250000.0\n", + "_C122163: -250000.0*t_43_map_10 - t_mem_43 + task_total_memory_router_router10_task43 >= -250000.0\n", + "_C122164: -t44_end_ + t44_start - 250000.0*t_44_map_10 - t_send_44 + task_total_delay_router_router10_task44 >= -250000.0\n", + "_C122165: -250000.0*t_44_map_10 - t_mem_44 + task_total_memory_router_router10_task44 >= -250000.0\n", + "_C122166: -t45_end_ + t45_start - 250000.0*t_45_map_10 - t_send_45 + task_total_delay_router_router10_task45 >= -250000.0\n", + "_C122167: -250000.0*t_45_map_10 - t_mem_45 + task_total_memory_router_router10_task45 >= -250000.0\n", + "_C122168: -t46_end_ + t46_start - 250000.0*t_46_map_10 - 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+ "_C122194: -t59_end_ + t59_start - 250000.0*t_59_map_10 - t_send_59 + task_total_delay_router_router10_task59 >= -250000.0\n", + "_C122195: -250000.0*t_59_map_10 - t_mem_59 + task_total_memory_router_router10_task59 >= -250000.0\n", + "_C122196: -t60_end_ + t60_start - 250000.0*t_60_map_10 - t_send_60 + task_total_delay_router_router10_task60 >= -250000.0\n", + "_C122197: -250000.0*t_60_map_10 - t_mem_60 + task_total_memory_router_router10_task60 >= -250000.0\n", + "_C122198: -t61_end_ + t61_start - 250000.0*t_61_map_10 - t_send_61 + task_total_delay_router_router10_task61 >= -250000.0\n", + "_C122199: -250000.0*t_61_map_10 - t_mem_61 + task_total_memory_router_router10_task61 >= -250000.0\n", + "_C122200: -t62_end_ + t62_start - 250000.0*t_62_map_10 - t_send_62 + task_total_delay_router_router10_task62 >= -250000.0\n", + "_C122201: -250000.0*t_62_map_10 - t_mem_62 + task_total_memory_router_router10_task62 >= -250000.0\n", + "_C122202: -t63_end_ + t63_start - 250000.0*t_63_map_10 - 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task_total_memory_router_router10_task16 - task_total_memory_router_router10_task17 - task_total_memory_router_router10_task18 - task_total_memory_router_router10_task19 - task_total_memory_router_router10_task2 - task_total_memory_router_router10_task20 - task_total_memory_router_router10_task21 - task_total_memory_router_router10_task22 - task_total_memory_router_router10_task23 - task_total_memory_router_router10_task24 - task_total_memory_router_router10_task25 - task_total_memory_router_router10_task26 - task_total_memory_router_router10_task27 - task_total_memory_router_router10_task28 - task_total_memory_router_router10_task29 - task_total_memory_router_router10_task3 - task_total_memory_router_router10_task30 - task_total_memory_router_router10_task31 - task_total_memory_router_router10_task32 - task_total_memory_router_router10_task33 - task_total_memory_router_router10_task34 - task_total_memory_router_router10_task35 - task_total_memory_router_router10_task36 - task_total_memory_router_router10_task37 - task_total_memory_router_router10_task38 - task_total_memory_router_router10_task39 - task_total_memory_router_router10_task4 - task_total_memory_router_router10_task40 - task_total_memory_router_router10_task41 - task_total_memory_router_router10_task42 - task_total_memory_router_router10_task43 - task_total_memory_router_router10_task44 - task_total_memory_router_router10_task45 - task_total_memory_router_router10_task46 - task_total_memory_router_router10_task47 - task_total_memory_router_router10_task48 - task_total_memory_router_router10_task49 - task_total_memory_router_router10_task5 - task_total_memory_router_router10_task50 - task_total_memory_router_router10_task51 - task_total_memory_router_router10_task52 - task_total_memory_router_router10_task53 - task_total_memory_router_router10_task54 - task_total_memory_router_router10_task55 - task_total_memory_router_router10_task56 - task_total_memory_router_router10_task57 - task_total_memory_router_router10_task58 - task_total_memory_router_router10_task59 - task_total_memory_router_router10_task6 - task_total_memory_router_router10_task60 - task_total_memory_router_router10_task61 - task_total_memory_router_router10_task62 - task_total_memory_router_router10_task63 - task_total_memory_router_router10_task64 - task_total_memory_router_router10_task65 - task_total_memory_router_router10_task66 - task_total_memory_router_router10_task67 - task_total_memory_router_router10_task68 - task_total_memory_router_router10_task69 - task_total_memory_router_router10_task7 - task_total_memory_router_router10_task8 - task_total_memory_router_router10_task9 >= -0.0\n", + "_C122217: PE10_total_delay - task_total_delay_router_router10_task0 - task_total_delay_router_router10_task1 - task_total_delay_router_router10_task10 - task_total_delay_router_router10_task11 - task_total_delay_router_router10_task12 - task_total_delay_router_router10_task13 - task_total_delay_router_router10_task14 - task_total_delay_router_router10_task15 - task_total_delay_router_router10_task16 - task_total_delay_router_router10_task17 - task_total_delay_router_router10_task18 - task_total_delay_router_router10_task19 - task_total_delay_router_router10_task2 - task_total_delay_router_router10_task20 - task_total_delay_router_router10_task21 - task_total_delay_router_router10_task22 - task_total_delay_router_router10_task23 - task_total_delay_router_router10_task24 - task_total_delay_router_router10_task25 - task_total_delay_router_router10_task26 - task_total_delay_router_router10_task27 - task_total_delay_router_router10_task28 - task_total_delay_router_router10_task29 - task_total_delay_router_router10_task3 - task_total_delay_router_router10_task30 - task_total_delay_router_router10_task31 - task_total_delay_router_router10_task32 - task_total_delay_router_router10_task33 - task_total_delay_router_router10_task34 - task_total_delay_router_router10_task35 - task_total_delay_router_router10_task36 - task_total_delay_router_router10_task37 - task_total_delay_router_router10_task38 - task_total_delay_router_router10_task39 - task_total_delay_router_router10_task4 - task_total_delay_router_router10_task40 - task_total_delay_router_router10_task41 - task_total_delay_router_router10_task42 - task_total_delay_router_router10_task43 - task_total_delay_router_router10_task44 - task_total_delay_router_router10_task45 - task_total_delay_router_router10_task46 - task_total_delay_router_router10_task47 - task_total_delay_router_router10_task48 - task_total_delay_router_router10_task49 - task_total_delay_router_router10_task5 - task_total_delay_router_router10_task50 - task_total_delay_router_router10_task51 - task_total_delay_router_router10_task52 - task_total_delay_router_router10_task53 - task_total_delay_router_router10_task54 - task_total_delay_router_router10_task55 - task_total_delay_router_router10_task56 - task_total_delay_router_router10_task57 - task_total_delay_router_router10_task58 - task_total_delay_router_router10_task59 - task_total_delay_router_router10_task6 - task_total_delay_router_router10_task60 - task_total_delay_router_router10_task61 - task_total_delay_router_router10_task62 - task_total_delay_router_router10_task63 - task_total_delay_router_router10_task64 - task_total_delay_router_router10_task65 - task_total_delay_router_router10_task66 - task_total_delay_router_router10_task67 - task_total_delay_router_router10_task68 - task_total_delay_router_router10_task69 - task_total_delay_router_router10_task7 - task_total_delay_router_router10_task8 - task_total_delay_router_router10_task9 >= -0.0\n", + "_C122218: PE10_total_memory - task_total_memory_router_router10_task0 - task_total_memory_router_router10_task1 - task_total_memory_router_router10_task10 - task_total_memory_router_router10_task11 - task_total_memory_router_router10_task12 - task_total_memory_router_router10_task13 - task_total_memory_router_router10_task14 - task_total_memory_router_router10_task15 - task_total_memory_router_router10_task16 - task_total_memory_router_router10_task17 - task_total_memory_router_router10_task18 - task_total_memory_router_router10_task19 - task_total_memory_router_router10_task2 - task_total_memory_router_router10_task20 - task_total_memory_router_router10_task21 - task_total_memory_router_router10_task22 - task_total_memory_router_router10_task23 - task_total_memory_router_router10_task24 - task_total_memory_router_router10_task25 - task_total_memory_router_router10_task26 - task_total_memory_router_router10_task27 - task_total_memory_router_router10_task28 - task_total_memory_router_router10_task29 - task_total_memory_router_router10_task3 - task_total_memory_router_router10_task30 - task_total_memory_router_router10_task31 - task_total_memory_router_router10_task32 - task_total_memory_router_router10_task33 - task_total_memory_router_router10_task34 - task_total_memory_router_router10_task35 - task_total_memory_router_router10_task36 - task_total_memory_router_router10_task37 - task_total_memory_router_router10_task38 - task_total_memory_router_router10_task39 - task_total_memory_router_router10_task4 - task_total_memory_router_router10_task40 - task_total_memory_router_router10_task41 - task_total_memory_router_router10_task42 - task_total_memory_router_router10_task43 - task_total_memory_router_router10_task44 - task_total_memory_router_router10_task45 - task_total_memory_router_router10_task46 - task_total_memory_router_router10_task47 - task_total_memory_router_router10_task48 - task_total_memory_router_router10_task49 - task_total_memory_router_router10_task5 - task_total_memory_router_router10_task50 - task_total_memory_router_router10_task51 - task_total_memory_router_router10_task52 - task_total_memory_router_router10_task53 - task_total_memory_router_router10_task54 - task_total_memory_router_router10_task55 - task_total_memory_router_router10_task56 - task_total_memory_router_router10_task57 - task_total_memory_router_router10_task58 - task_total_memory_router_router10_task59 - task_total_memory_router_router10_task6 - task_total_memory_router_router10_task60 - task_total_memory_router_router10_task61 - task_total_memory_router_router10_task62 - task_total_memory_router_router10_task63 - task_total_memory_router_router10_task64 - task_total_memory_router_router10_task65 - task_total_memory_router_router10_task66 - task_total_memory_router_router10_task67 - task_total_memory_router_router10_task68 - task_total_memory_router_router10_task69 - task_total_memory_router_router10_task7 - task_total_memory_router_router10_task8 - task_total_memory_router_router10_task9 >= -0.0\n", + "_C122219: -PE_mem_overflow10 + max_memory_overflow >= 0\n", + "_C122220: PE10_time_delay_max - t0_end_ - 250000.0*t_0_map_10 >= 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+ "_C122482: -t60_end_ + t60_start - 250000.0*t_60_map_11 - t_send_60 + task_total_delay_router_router11_task60 >= -250000.0\n", + "_C122483: -250000.0*t_60_map_11 - t_mem_60 + task_total_memory_router_router11_task60 >= -250000.0\n", + "_C122484: -t61_end_ + t61_start - 250000.0*t_61_map_11 - t_send_61 + task_total_delay_router_router11_task61 >= -250000.0\n", + "_C122485: -250000.0*t_61_map_11 - t_mem_61 + task_total_memory_router_router11_task61 >= -250000.0\n", + "_C122486: -t62_end_ + t62_start - 250000.0*t_62_map_11 - t_send_62 + task_total_delay_router_router11_task62 >= -250000.0\n", + "_C122487: -250000.0*t_62_map_11 - t_mem_62 + task_total_memory_router_router11_task62 >= -250000.0\n", + "_C122488: -t63_end_ + t63_start - 250000.0*t_63_map_11 - t_send_63 + task_total_delay_router_router11_task63 >= -250000.0\n", + "_C122489: -250000.0*t_63_map_11 - t_mem_63 + task_total_memory_router_router11_task63 >= -250000.0\n", + "_C122490: -t64_end_ + t64_start - 250000.0*t_64_map_11 - t_send_64 + task_total_delay_router_router11_task64 >= -250000.0\n", + "_C122491: -250000.0*t_64_map_11 - t_mem_64 + task_total_memory_router_router11_task64 >= -250000.0\n", + "_C122492: -t65_end_ + t65_start - 250000.0*t_65_map_11 - t_send_65 + task_total_delay_router_router11_task65 >= -250000.0\n", + "_C122493: -250000.0*t_65_map_11 - t_mem_65 + task_total_memory_router_router11_task65 >= -250000.0\n", + "_C122494: -t66_end_ + t66_start - 250000.0*t_66_map_11 - t_send_66 + task_total_delay_router_router11_task66 >= -250000.0\n", + "_C122495: -250000.0*t_66_map_11 - t_mem_66 + task_total_memory_router_router11_task66 >= -250000.0\n", + "_C122496: -t67_end_ + t67_start - 250000.0*t_67_map_11 - t_send_67 + task_total_delay_router_router11_task67 >= -250000.0\n", + "_C122497: -250000.0*t_67_map_11 - t_mem_67 + task_total_memory_router_router11_task67 >= -250000.0\n", + "_C122498: -t68_end_ + t68_start - 250000.0*t_68_map_11 - t_send_68 + task_total_delay_router_router11_task68 >= 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task_total_memory_router_router11_task21 - task_total_memory_router_router11_task22 - task_total_memory_router_router11_task23 - task_total_memory_router_router11_task24 - task_total_memory_router_router11_task25 - task_total_memory_router_router11_task26 - task_total_memory_router_router11_task27 - task_total_memory_router_router11_task28 - task_total_memory_router_router11_task29 - task_total_memory_router_router11_task3 - task_total_memory_router_router11_task30 - task_total_memory_router_router11_task31 - task_total_memory_router_router11_task32 - task_total_memory_router_router11_task33 - task_total_memory_router_router11_task34 - task_total_memory_router_router11_task35 - task_total_memory_router_router11_task36 - task_total_memory_router_router11_task37 - task_total_memory_router_router11_task38 - task_total_memory_router_router11_task39 - task_total_memory_router_router11_task4 - task_total_memory_router_router11_task40 - task_total_memory_router_router11_task41 - task_total_memory_router_router11_task42 - task_total_memory_router_router11_task43 - task_total_memory_router_router11_task44 - task_total_memory_router_router11_task45 - task_total_memory_router_router11_task46 - task_total_memory_router_router11_task47 - task_total_memory_router_router11_task48 - task_total_memory_router_router11_task49 - task_total_memory_router_router11_task5 - task_total_memory_router_router11_task50 - task_total_memory_router_router11_task51 - task_total_memory_router_router11_task52 - task_total_memory_router_router11_task53 - task_total_memory_router_router11_task54 - task_total_memory_router_router11_task55 - task_total_memory_router_router11_task56 - task_total_memory_router_router11_task57 - task_total_memory_router_router11_task58 - task_total_memory_router_router11_task59 - task_total_memory_router_router11_task6 - task_total_memory_router_router11_task60 - task_total_memory_router_router11_task61 - task_total_memory_router_router11_task62 - task_total_memory_router_router11_task63 - task_total_memory_router_router11_task64 - task_total_memory_router_router11_task65 - task_total_memory_router_router11_task66 - task_total_memory_router_router11_task67 - task_total_memory_router_router11_task68 - task_total_memory_router_router11_task69 - task_total_memory_router_router11_task7 - task_total_memory_router_router11_task8 - task_total_memory_router_router11_task9 >= -0.0\n", + "_C122503: PE11_total_delay - task_total_delay_router_router11_task0 - task_total_delay_router_router11_task1 - task_total_delay_router_router11_task10 - task_total_delay_router_router11_task11 - task_total_delay_router_router11_task12 - task_total_delay_router_router11_task13 - task_total_delay_router_router11_task14 - task_total_delay_router_router11_task15 - task_total_delay_router_router11_task16 - task_total_delay_router_router11_task17 - task_total_delay_router_router11_task18 - task_total_delay_router_router11_task19 - task_total_delay_router_router11_task2 - task_total_delay_router_router11_task20 - task_total_delay_router_router11_task21 - task_total_delay_router_router11_task22 - task_total_delay_router_router11_task23 - task_total_delay_router_router11_task24 - task_total_delay_router_router11_task25 - task_total_delay_router_router11_task26 - task_total_delay_router_router11_task27 - task_total_delay_router_router11_task28 - task_total_delay_router_router11_task29 - task_total_delay_router_router11_task3 - task_total_delay_router_router11_task30 - task_total_delay_router_router11_task31 - task_total_delay_router_router11_task32 - task_total_delay_router_router11_task33 - task_total_delay_router_router11_task34 - task_total_delay_router_router11_task35 - task_total_delay_router_router11_task36 - task_total_delay_router_router11_task37 - task_total_delay_router_router11_task38 - task_total_delay_router_router11_task39 - task_total_delay_router_router11_task4 - task_total_delay_router_router11_task40 - task_total_delay_router_router11_task41 - task_total_delay_router_router11_task42 - task_total_delay_router_router11_task43 - task_total_delay_router_router11_task44 - task_total_delay_router_router11_task45 - task_total_delay_router_router11_task46 - task_total_delay_router_router11_task47 - task_total_delay_router_router11_task48 - task_total_delay_router_router11_task49 - task_total_delay_router_router11_task5 - task_total_delay_router_router11_task50 - task_total_delay_router_router11_task51 - task_total_delay_router_router11_task52 - task_total_delay_router_router11_task53 - task_total_delay_router_router11_task54 - task_total_delay_router_router11_task55 - task_total_delay_router_router11_task56 - task_total_delay_router_router11_task57 - task_total_delay_router_router11_task58 - task_total_delay_router_router11_task59 - task_total_delay_router_router11_task6 - task_total_delay_router_router11_task60 - task_total_delay_router_router11_task61 - task_total_delay_router_router11_task62 - task_total_delay_router_router11_task63 - task_total_delay_router_router11_task64 - task_total_delay_router_router11_task65 - task_total_delay_router_router11_task66 - task_total_delay_router_router11_task67 - task_total_delay_router_router11_task68 - task_total_delay_router_router11_task69 - task_total_delay_router_router11_task7 - task_total_delay_router_router11_task8 - task_total_delay_router_router11_task9 >= -0.0\n", + "_C122504: PE11_total_memory - task_total_memory_router_router11_task0 - task_total_memory_router_router11_task1 - task_total_memory_router_router11_task10 - task_total_memory_router_router11_task11 - task_total_memory_router_router11_task12 - task_total_memory_router_router11_task13 - task_total_memory_router_router11_task14 - task_total_memory_router_router11_task15 - task_total_memory_router_router11_task16 - task_total_memory_router_router11_task17 - task_total_memory_router_router11_task18 - task_total_memory_router_router11_task19 - task_total_memory_router_router11_task2 - task_total_memory_router_router11_task20 - task_total_memory_router_router11_task21 - task_total_memory_router_router11_task22 - task_total_memory_router_router11_task23 - task_total_memory_router_router11_task24 - task_total_memory_router_router11_task25 - task_total_memory_router_router11_task26 - task_total_memory_router_router11_task27 - task_total_memory_router_router11_task28 - task_total_memory_router_router11_task29 - task_total_memory_router_router11_task3 - task_total_memory_router_router11_task30 - task_total_memory_router_router11_task31 - task_total_memory_router_router11_task32 - task_total_memory_router_router11_task33 - task_total_memory_router_router11_task34 - task_total_memory_router_router11_task35 - task_total_memory_router_router11_task36 - task_total_memory_router_router11_task37 - task_total_memory_router_router11_task38 - task_total_memory_router_router11_task39 - task_total_memory_router_router11_task4 - task_total_memory_router_router11_task40 - task_total_memory_router_router11_task41 - task_total_memory_router_router11_task42 - task_total_memory_router_router11_task43 - task_total_memory_router_router11_task44 - task_total_memory_router_router11_task45 - task_total_memory_router_router11_task46 - task_total_memory_router_router11_task47 - task_total_memory_router_router11_task48 - task_total_memory_router_router11_task49 - task_total_memory_router_router11_task5 - task_total_memory_router_router11_task50 - task_total_memory_router_router11_task51 - task_total_memory_router_router11_task52 - task_total_memory_router_router11_task53 - task_total_memory_router_router11_task54 - task_total_memory_router_router11_task55 - task_total_memory_router_router11_task56 - task_total_memory_router_router11_task57 - task_total_memory_router_router11_task58 - task_total_memory_router_router11_task59 - task_total_memory_router_router11_task6 - task_total_memory_router_router11_task60 - task_total_memory_router_router11_task61 - task_total_memory_router_router11_task62 - task_total_memory_router_router11_task63 - task_total_memory_router_router11_task64 - task_total_memory_router_router11_task65 - task_total_memory_router_router11_task66 - task_total_memory_router_router11_task67 - task_total_memory_router_router11_task68 - task_total_memory_router_router11_task69 - task_total_memory_router_router11_task7 - task_total_memory_router_router11_task8 - task_total_memory_router_router11_task9 >= -0.0\n", + "_C122505: -PE_mem_overflow11 + max_memory_overflow >= 0\n", + "_C122506: PE11_time_delay_max - t0_end_ - 250000.0*t_0_map_11 >= -250000.0\n", + "_C122507: PE11_time_delay_min - t0_start + 250000.0*t_0_map_11 <= 250000.0\n", + "_C122508: PE11_time_delay_max - t1_end_ - 250000.0*t_1_map_11 >= -250000.0\n", + "_C122509: PE11_time_delay_min - t1_start + 250000.0*t_1_map_11 <= 250000.0\n", + 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250000.0\n", + "_C122558: PE11_time_delay_max - t26_end_ - 250000.0*t_26_map_11 >= -250000.0\n", + "_C122559: PE11_time_delay_min - t26_start + 250000.0*t_26_map_11 <= 250000.0\n", + "_C122560: PE11_time_delay_max - t27_end_ - 250000.0*t_27_map_11 >= -250000.0\n", + "_C122561: PE11_time_delay_min - t27_start + 250000.0*t_27_map_11 <= 250000.0\n", + "_C122562: PE11_time_delay_max - t28_end_ - 250000.0*t_28_map_11 >= -250000.0\n", + "_C122563: PE11_time_delay_min - t28_start + 250000.0*t_28_map_11 <= 250000.0\n", + "_C122564: PE11_time_delay_max - t29_end_ - 250000.0*t_29_map_11 >= -250000.0\n", + "_C122565: PE11_time_delay_min - t29_start + 250000.0*t_29_map_11 <= 250000.0\n", + "_C122566: PE11_time_delay_max - t30_end_ - 250000.0*t_30_map_11 >= -250000.0\n", + "_C122567: PE11_time_delay_min - t30_start + 250000.0*t_30_map_11 <= 250000.0\n", + "_C122568: PE11_time_delay_max - t31_end_ - 250000.0*t_31_map_11 >= -250000.0\n", + "_C122569: PE11_time_delay_min - t31_start + 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t37_start + 250000.0*t_37_map_11 <= 250000.0\n", + "_C122582: PE11_time_delay_max - t38_end_ - 250000.0*t_38_map_11 >= -250000.0\n", + "_C122583: PE11_time_delay_min - t38_start + 250000.0*t_38_map_11 <= 250000.0\n", + "_C122584: PE11_time_delay_max - t39_end_ - 250000.0*t_39_map_11 >= -250000.0\n", + "_C122585: PE11_time_delay_min - t39_start + 250000.0*t_39_map_11 <= 250000.0\n", + "_C122586: PE11_time_delay_max - t40_end_ - 250000.0*t_40_map_11 >= -250000.0\n", + "_C122587: PE11_time_delay_min - t40_start + 250000.0*t_40_map_11 <= 250000.0\n", + "_C122588: PE11_time_delay_max - t41_end_ - 250000.0*t_41_map_11 >= -250000.0\n", + "_C122589: PE11_time_delay_min - t41_start + 250000.0*t_41_map_11 <= 250000.0\n", + "_C122590: PE11_time_delay_max - t42_end_ - 250000.0*t_42_map_11 >= -250000.0\n", + "_C122591: PE11_time_delay_min - t42_start + 250000.0*t_42_map_11 <= 250000.0\n", + "_C122592: PE11_time_delay_max - t43_end_ - 250000.0*t_43_map_11 >= -250000.0\n", + "_C122593: PE11_time_delay_min - t43_start + 250000.0*t_43_map_11 <= 250000.0\n", + "_C122594: PE11_time_delay_max - t44_end_ - 250000.0*t_44_map_11 >= -250000.0\n", + "_C122595: PE11_time_delay_min - t44_start + 250000.0*t_44_map_11 <= 250000.0\n", + "_C122596: PE11_time_delay_max - t45_end_ - 250000.0*t_45_map_11 >= -250000.0\n", + "_C122597: PE11_time_delay_min - t45_start + 250000.0*t_45_map_11 <= 250000.0\n", + "_C122598: PE11_time_delay_max - t46_end_ - 250000.0*t_46_map_11 >= -250000.0\n", + "_C122599: PE11_time_delay_min - t46_start + 250000.0*t_46_map_11 <= 250000.0\n", + "_C122600: PE11_time_delay_max - t47_end_ - 250000.0*t_47_map_11 >= -250000.0\n", + "_C122601: PE11_time_delay_min - t47_start + 250000.0*t_47_map_11 <= 250000.0\n", + "_C122602: PE11_time_delay_max - t48_end_ - 250000.0*t_48_map_11 >= -250000.0\n", + "_C122603: PE11_time_delay_min - t48_start + 250000.0*t_48_map_11 <= 250000.0\n", + "_C122604: PE11_time_delay_max - t49_end_ - 250000.0*t_49_map_11 >= -250000.0\n", + "_C122605: PE11_time_delay_min - t49_start + 250000.0*t_49_map_11 <= 250000.0\n", + "_C122606: PE11_time_delay_max - t50_end_ - 250000.0*t_50_map_11 >= -250000.0\n", + "_C122607: PE11_time_delay_min - t50_start + 250000.0*t_50_map_11 <= 250000.0\n", + "_C122608: PE11_time_delay_max - t51_end_ - 250000.0*t_51_map_11 >= -250000.0\n", + "_C122609: PE11_time_delay_min - t51_start + 250000.0*t_51_map_11 <= 250000.0\n", + "_C122610: PE11_time_delay_max - t52_end_ - 250000.0*t_52_map_11 >= -250000.0\n", + "_C122611: PE11_time_delay_min - t52_start + 250000.0*t_52_map_11 <= 250000.0\n", + "_C122612: PE11_time_delay_max - t53_end_ - 250000.0*t_53_map_11 >= -250000.0\n", + "_C122613: PE11_time_delay_min - t53_start + 250000.0*t_53_map_11 <= 250000.0\n", + "_C122614: PE11_time_delay_max - t54_end_ - 250000.0*t_54_map_11 >= -250000.0\n", + "_C122615: PE11_time_delay_min - t54_start + 250000.0*t_54_map_11 <= 250000.0\n", + "_C122616: PE11_time_delay_max - t55_end_ - 250000.0*t_55_map_11 >= 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250000.0*t_61_map_11 >= -250000.0\n", + "_C122629: PE11_time_delay_min - t61_start + 250000.0*t_61_map_11 <= 250000.0\n", + "_C122630: PE11_time_delay_max - t62_end_ - 250000.0*t_62_map_11 >= -250000.0\n", + "_C122631: PE11_time_delay_min - t62_start + 250000.0*t_62_map_11 <= 250000.0\n", + "_C122632: PE11_time_delay_max - t63_end_ - 250000.0*t_63_map_11 >= -250000.0\n", + "_C122633: PE11_time_delay_min - t63_start + 250000.0*t_63_map_11 <= 250000.0\n", + "_C122634: PE11_time_delay_max - t64_end_ - 250000.0*t_64_map_11 >= -250000.0\n", + "_C122635: PE11_time_delay_min - t64_start + 250000.0*t_64_map_11 <= 250000.0\n", + "_C122636: PE11_time_delay_max - t65_end_ - 250000.0*t_65_map_11 >= -250000.0\n", + "_C122637: PE11_time_delay_min - t65_start + 250000.0*t_65_map_11 <= 250000.0\n", + "_C122638: PE11_time_delay_max - t66_end_ - 250000.0*t_66_map_11 >= -250000.0\n", + "_C122639: PE11_time_delay_min - t66_start + 250000.0*t_66_map_11 <= 250000.0\n", + "_C122640: PE11_time_delay_max - 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+ task_total_memory_router_router12_task52 >= -250000.0\n", + "_C122754: -t53_end_ + t53_start - 250000.0*t_53_map_12 - t_send_53 + task_total_delay_router_router12_task53 >= -250000.0\n", + "_C122755: -250000.0*t_53_map_12 - t_mem_53 + task_total_memory_router_router12_task53 >= -250000.0\n", + "_C122756: -t54_end_ + t54_start - 250000.0*t_54_map_12 - t_send_54 + task_total_delay_router_router12_task54 >= -250000.0\n", + "_C122757: -250000.0*t_54_map_12 - t_mem_54 + task_total_memory_router_router12_task54 >= -250000.0\n", + "_C122758: -t55_end_ + t55_start - 250000.0*t_55_map_12 - t_send_55 + task_total_delay_router_router12_task55 >= -250000.0\n", + "_C122759: -250000.0*t_55_map_12 - t_mem_55 + task_total_memory_router_router12_task55 >= -250000.0\n", + "_C122760: -t56_end_ + t56_start - 250000.0*t_56_map_12 - t_send_56 + task_total_delay_router_router12_task56 >= -250000.0\n", + "_C122761: -250000.0*t_56_map_12 - t_mem_56 + task_total_memory_router_router12_task56 >= -250000.0\n", + "_C122762: -t57_end_ + t57_start - 250000.0*t_57_map_12 - t_send_57 + task_total_delay_router_router12_task57 >= -250000.0\n", + "_C122763: -250000.0*t_57_map_12 - t_mem_57 + task_total_memory_router_router12_task57 >= -250000.0\n", + "_C122764: -t58_end_ + t58_start - 250000.0*t_58_map_12 - t_send_58 + task_total_delay_router_router12_task58 >= -250000.0\n", + "_C122765: -250000.0*t_58_map_12 - t_mem_58 + task_total_memory_router_router12_task58 >= -250000.0\n", + "_C122766: -t59_end_ + t59_start - 250000.0*t_59_map_12 - t_send_59 + task_total_delay_router_router12_task59 >= -250000.0\n", + "_C122767: -250000.0*t_59_map_12 - t_mem_59 + task_total_memory_router_router12_task59 >= -250000.0\n", + "_C122768: -t60_end_ + t60_start - 250000.0*t_60_map_12 - t_send_60 + task_total_delay_router_router12_task60 >= -250000.0\n", + "_C122769: -250000.0*t_60_map_12 - t_mem_60 + task_total_memory_router_router12_task60 >= -250000.0\n", + "_C122770: -t61_end_ + t61_start - 250000.0*t_61_map_12 - t_send_61 + task_total_delay_router_router12_task61 >= -250000.0\n", + "_C122771: -250000.0*t_61_map_12 - t_mem_61 + task_total_memory_router_router12_task61 >= -250000.0\n", + "_C122772: -t62_end_ + t62_start - 250000.0*t_62_map_12 - t_send_62 + task_total_delay_router_router12_task62 >= -250000.0\n", + "_C122773: -250000.0*t_62_map_12 - t_mem_62 + task_total_memory_router_router12_task62 >= -250000.0\n", + "_C122774: -t63_end_ + t63_start - 250000.0*t_63_map_12 - t_send_63 + task_total_delay_router_router12_task63 >= -250000.0\n", + "_C122775: -250000.0*t_63_map_12 - t_mem_63 + task_total_memory_router_router12_task63 >= -250000.0\n", + "_C122776: -t64_end_ + t64_start - 250000.0*t_64_map_12 - t_send_64 + task_total_delay_router_router12_task64 >= -250000.0\n", + "_C122777: -250000.0*t_64_map_12 - t_mem_64 + task_total_memory_router_router12_task64 >= -250000.0\n", + "_C122778: -t65_end_ + t65_start - 250000.0*t_65_map_12 - t_send_65 + task_total_delay_router_router12_task65 >= 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+ task_total_memory_router_router12_task69 >= -250000.0\n", + "_C122788: PE_mem_overflow12 - task_total_memory_router_router12_task0 - task_total_memory_router_router12_task1 - task_total_memory_router_router12_task10 - task_total_memory_router_router12_task11 - task_total_memory_router_router12_task12 - task_total_memory_router_router12_task13 - task_total_memory_router_router12_task14 - task_total_memory_router_router12_task15 - task_total_memory_router_router12_task16 - task_total_memory_router_router12_task17 - task_total_memory_router_router12_task18 - task_total_memory_router_router12_task19 - task_total_memory_router_router12_task2 - task_total_memory_router_router12_task20 - task_total_memory_router_router12_task21 - task_total_memory_router_router12_task22 - task_total_memory_router_router12_task23 - task_total_memory_router_router12_task24 - task_total_memory_router_router12_task25 - task_total_memory_router_router12_task26 - task_total_memory_router_router12_task27 - task_total_memory_router_router12_task28 - task_total_memory_router_router12_task29 - task_total_memory_router_router12_task3 - task_total_memory_router_router12_task30 - task_total_memory_router_router12_task31 - task_total_memory_router_router12_task32 - task_total_memory_router_router12_task33 - task_total_memory_router_router12_task34 - task_total_memory_router_router12_task35 - task_total_memory_router_router12_task36 - task_total_memory_router_router12_task37 - task_total_memory_router_router12_task38 - task_total_memory_router_router12_task39 - task_total_memory_router_router12_task4 - task_total_memory_router_router12_task40 - task_total_memory_router_router12_task41 - task_total_memory_router_router12_task42 - task_total_memory_router_router12_task43 - task_total_memory_router_router12_task44 - task_total_memory_router_router12_task45 - task_total_memory_router_router12_task46 - task_total_memory_router_router12_task47 - task_total_memory_router_router12_task48 - task_total_memory_router_router12_task49 - task_total_memory_router_router12_task5 - task_total_memory_router_router12_task50 - task_total_memory_router_router12_task51 - task_total_memory_router_router12_task52 - task_total_memory_router_router12_task53 - task_total_memory_router_router12_task54 - task_total_memory_router_router12_task55 - task_total_memory_router_router12_task56 - task_total_memory_router_router12_task57 - task_total_memory_router_router12_task58 - task_total_memory_router_router12_task59 - task_total_memory_router_router12_task6 - task_total_memory_router_router12_task60 - task_total_memory_router_router12_task61 - task_total_memory_router_router12_task62 - task_total_memory_router_router12_task63 - task_total_memory_router_router12_task64 - task_total_memory_router_router12_task65 - task_total_memory_router_router12_task66 - task_total_memory_router_router12_task67 - task_total_memory_router_router12_task68 - task_total_memory_router_router12_task69 - task_total_memory_router_router12_task7 - task_total_memory_router_router12_task8 - task_total_memory_router_router12_task9 >= -0.0\n", + "_C122789: PE12_total_delay - task_total_delay_router_router12_task0 - task_total_delay_router_router12_task1 - task_total_delay_router_router12_task10 - task_total_delay_router_router12_task11 - task_total_delay_router_router12_task12 - task_total_delay_router_router12_task13 - task_total_delay_router_router12_task14 - task_total_delay_router_router12_task15 - task_total_delay_router_router12_task16 - task_total_delay_router_router12_task17 - task_total_delay_router_router12_task18 - task_total_delay_router_router12_task19 - task_total_delay_router_router12_task2 - task_total_delay_router_router12_task20 - task_total_delay_router_router12_task21 - task_total_delay_router_router12_task22 - task_total_delay_router_router12_task23 - task_total_delay_router_router12_task24 - task_total_delay_router_router12_task25 - task_total_delay_router_router12_task26 - task_total_delay_router_router12_task27 - task_total_delay_router_router12_task28 - task_total_delay_router_router12_task29 - task_total_delay_router_router12_task3 - task_total_delay_router_router12_task30 - task_total_delay_router_router12_task31 - task_total_delay_router_router12_task32 - task_total_delay_router_router12_task33 - task_total_delay_router_router12_task34 - task_total_delay_router_router12_task35 - task_total_delay_router_router12_task36 - task_total_delay_router_router12_task37 - task_total_delay_router_router12_task38 - task_total_delay_router_router12_task39 - task_total_delay_router_router12_task4 - task_total_delay_router_router12_task40 - task_total_delay_router_router12_task41 - task_total_delay_router_router12_task42 - task_total_delay_router_router12_task43 - task_total_delay_router_router12_task44 - task_total_delay_router_router12_task45 - task_total_delay_router_router12_task46 - task_total_delay_router_router12_task47 - task_total_delay_router_router12_task48 - task_total_delay_router_router12_task49 - task_total_delay_router_router12_task5 - task_total_delay_router_router12_task50 - task_total_delay_router_router12_task51 - task_total_delay_router_router12_task52 - task_total_delay_router_router12_task53 - task_total_delay_router_router12_task54 - task_total_delay_router_router12_task55 - task_total_delay_router_router12_task56 - task_total_delay_router_router12_task57 - task_total_delay_router_router12_task58 - task_total_delay_router_router12_task59 - task_total_delay_router_router12_task6 - task_total_delay_router_router12_task60 - task_total_delay_router_router12_task61 - task_total_delay_router_router12_task62 - task_total_delay_router_router12_task63 - task_total_delay_router_router12_task64 - task_total_delay_router_router12_task65 - task_total_delay_router_router12_task66 - task_total_delay_router_router12_task67 - task_total_delay_router_router12_task68 - task_total_delay_router_router12_task69 - task_total_delay_router_router12_task7 - task_total_delay_router_router12_task8 - task_total_delay_router_router12_task9 >= -0.0\n", + "_C122790: PE12_total_memory - task_total_memory_router_router12_task0 - task_total_memory_router_router12_task1 - task_total_memory_router_router12_task10 - task_total_memory_router_router12_task11 - task_total_memory_router_router12_task12 - task_total_memory_router_router12_task13 - task_total_memory_router_router12_task14 - task_total_memory_router_router12_task15 - task_total_memory_router_router12_task16 - task_total_memory_router_router12_task17 - task_total_memory_router_router12_task18 - task_total_memory_router_router12_task19 - task_total_memory_router_router12_task2 - task_total_memory_router_router12_task20 - task_total_memory_router_router12_task21 - task_total_memory_router_router12_task22 - task_total_memory_router_router12_task23 - task_total_memory_router_router12_task24 - task_total_memory_router_router12_task25 - task_total_memory_router_router12_task26 - task_total_memory_router_router12_task27 - task_total_memory_router_router12_task28 - task_total_memory_router_router12_task29 - task_total_memory_router_router12_task3 - task_total_memory_router_router12_task30 - task_total_memory_router_router12_task31 - task_total_memory_router_router12_task32 - task_total_memory_router_router12_task33 - task_total_memory_router_router12_task34 - task_total_memory_router_router12_task35 - task_total_memory_router_router12_task36 - task_total_memory_router_router12_task37 - task_total_memory_router_router12_task38 - task_total_memory_router_router12_task39 - task_total_memory_router_router12_task4 - task_total_memory_router_router12_task40 - task_total_memory_router_router12_task41 - task_total_memory_router_router12_task42 - task_total_memory_router_router12_task43 - task_total_memory_router_router12_task44 - task_total_memory_router_router12_task45 - task_total_memory_router_router12_task46 - task_total_memory_router_router12_task47 - task_total_memory_router_router12_task48 - task_total_memory_router_router12_task49 - task_total_memory_router_router12_task5 - task_total_memory_router_router12_task50 - task_total_memory_router_router12_task51 - task_total_memory_router_router12_task52 - task_total_memory_router_router12_task53 - task_total_memory_router_router12_task54 - task_total_memory_router_router12_task55 - task_total_memory_router_router12_task56 - task_total_memory_router_router12_task57 - task_total_memory_router_router12_task58 - task_total_memory_router_router12_task59 - task_total_memory_router_router12_task6 - task_total_memory_router_router12_task60 - task_total_memory_router_router12_task61 - task_total_memory_router_router12_task62 - task_total_memory_router_router12_task63 - task_total_memory_router_router12_task64 - task_total_memory_router_router12_task65 - task_total_memory_router_router12_task66 - task_total_memory_router_router12_task67 - task_total_memory_router_router12_task68 - task_total_memory_router_router12_task69 - task_total_memory_router_router12_task7 - task_total_memory_router_router12_task8 - task_total_memory_router_router12_task9 >= -0.0\n", + "_C122791: -PE_mem_overflow12 + max_memory_overflow >= 0\n", + "_C122792: PE12_time_delay_max - t0_end_ - 250000.0*t_0_map_12 >= -250000.0\n", + "_C122793: PE12_time_delay_min - t0_start + 250000.0*t_0_map_12 <= 250000.0\n", + "_C122794: PE12_time_delay_max - t1_end_ - 250000.0*t_1_map_12 >= -250000.0\n", + "_C122795: PE12_time_delay_min - t1_start + 250000.0*t_1_map_12 <= 250000.0\n", + "_C122796: PE12_time_delay_max - t2_end_ - 250000.0*t_2_map_12 >= -250000.0\n", + "_C122797: PE12_time_delay_min - t2_start + 250000.0*t_2_map_12 <= 250000.0\n", + "_C122798: PE12_time_delay_max - t3_end_ - 250000.0*t_3_map_12 >= -250000.0\n", + "_C122799: PE12_time_delay_min - t3_start + 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"_C122906: PE12_time_delay_max - t57_end_ - 250000.0*t_57_map_12 >= -250000.0\n", + "_C122907: PE12_time_delay_min - t57_start + 250000.0*t_57_map_12 <= 250000.0\n", + "_C122908: PE12_time_delay_max - t58_end_ - 250000.0*t_58_map_12 >= -250000.0\n", + "_C122909: PE12_time_delay_min - t58_start + 250000.0*t_58_map_12 <= 250000.0\n", + "_C122910: PE12_time_delay_max - t59_end_ - 250000.0*t_59_map_12 >= -250000.0\n", + "_C122911: PE12_time_delay_min - t59_start + 250000.0*t_59_map_12 <= 250000.0\n", + "_C122912: PE12_time_delay_max - t60_end_ - 250000.0*t_60_map_12 >= -250000.0\n", + "_C122913: PE12_time_delay_min - t60_start + 250000.0*t_60_map_12 <= 250000.0\n", + "_C122914: PE12_time_delay_max - t61_end_ - 250000.0*t_61_map_12 >= -250000.0\n", + "_C122915: PE12_time_delay_min - t61_start + 250000.0*t_61_map_12 <= 250000.0\n", + "_C122916: PE12_time_delay_max - t62_end_ - 250000.0*t_62_map_12 >= -250000.0\n", + "_C122917: PE12_time_delay_min - t62_start + 250000.0*t_62_map_12 <= 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task_total_memory_router_router13_task12 - task_total_memory_router_router13_task13 - task_total_memory_router_router13_task14 - task_total_memory_router_router13_task15 - task_total_memory_router_router13_task16 - task_total_memory_router_router13_task17 - task_total_memory_router_router13_task18 - task_total_memory_router_router13_task19 - task_total_memory_router_router13_task2 - task_total_memory_router_router13_task20 - task_total_memory_router_router13_task21 - task_total_memory_router_router13_task22 - task_total_memory_router_router13_task23 - task_total_memory_router_router13_task24 - task_total_memory_router_router13_task25 - task_total_memory_router_router13_task26 - task_total_memory_router_router13_task27 - task_total_memory_router_router13_task28 - task_total_memory_router_router13_task29 - task_total_memory_router_router13_task3 - task_total_memory_router_router13_task30 - task_total_memory_router_router13_task31 - task_total_memory_router_router13_task32 - task_total_memory_router_router13_task33 - task_total_memory_router_router13_task34 - task_total_memory_router_router13_task35 - task_total_memory_router_router13_task36 - task_total_memory_router_router13_task37 - task_total_memory_router_router13_task38 - task_total_memory_router_router13_task39 - task_total_memory_router_router13_task4 - task_total_memory_router_router13_task40 - task_total_memory_router_router13_task41 - task_total_memory_router_router13_task42 - task_total_memory_router_router13_task43 - task_total_memory_router_router13_task44 - task_total_memory_router_router13_task45 - task_total_memory_router_router13_task46 - task_total_memory_router_router13_task47 - task_total_memory_router_router13_task48 - task_total_memory_router_router13_task49 - task_total_memory_router_router13_task5 - task_total_memory_router_router13_task50 - task_total_memory_router_router13_task51 - task_total_memory_router_router13_task52 - task_total_memory_router_router13_task53 - task_total_memory_router_router13_task54 - task_total_memory_router_router13_task55 - task_total_memory_router_router13_task56 - task_total_memory_router_router13_task57 - task_total_memory_router_router13_task58 - task_total_memory_router_router13_task59 - task_total_memory_router_router13_task6 - task_total_memory_router_router13_task60 - task_total_memory_router_router13_task61 - task_total_memory_router_router13_task62 - task_total_memory_router_router13_task63 - task_total_memory_router_router13_task64 - task_total_memory_router_router13_task65 - task_total_memory_router_router13_task66 - task_total_memory_router_router13_task67 - task_total_memory_router_router13_task68 - task_total_memory_router_router13_task69 - task_total_memory_router_router13_task7 - task_total_memory_router_router13_task8 - task_total_memory_router_router13_task9 >= -0.0\n", + "_C123075: PE13_total_delay - task_total_delay_router_router13_task0 - task_total_delay_router_router13_task1 - task_total_delay_router_router13_task10 - task_total_delay_router_router13_task11 - task_total_delay_router_router13_task12 - task_total_delay_router_router13_task13 - task_total_delay_router_router13_task14 - task_total_delay_router_router13_task15 - task_total_delay_router_router13_task16 - task_total_delay_router_router13_task17 - task_total_delay_router_router13_task18 - task_total_delay_router_router13_task19 - task_total_delay_router_router13_task2 - task_total_delay_router_router13_task20 - task_total_delay_router_router13_task21 - task_total_delay_router_router13_task22 - task_total_delay_router_router13_task23 - task_total_delay_router_router13_task24 - task_total_delay_router_router13_task25 - task_total_delay_router_router13_task26 - task_total_delay_router_router13_task27 - task_total_delay_router_router13_task28 - task_total_delay_router_router13_task29 - task_total_delay_router_router13_task3 - task_total_delay_router_router13_task30 - task_total_delay_router_router13_task31 - task_total_delay_router_router13_task32 - task_total_delay_router_router13_task33 - task_total_delay_router_router13_task34 - task_total_delay_router_router13_task35 - task_total_delay_router_router13_task36 - task_total_delay_router_router13_task37 - task_total_delay_router_router13_task38 - task_total_delay_router_router13_task39 - task_total_delay_router_router13_task4 - task_total_delay_router_router13_task40 - task_total_delay_router_router13_task41 - task_total_delay_router_router13_task42 - task_total_delay_router_router13_task43 - task_total_delay_router_router13_task44 - task_total_delay_router_router13_task45 - task_total_delay_router_router13_task46 - task_total_delay_router_router13_task47 - task_total_delay_router_router13_task48 - task_total_delay_router_router13_task49 - task_total_delay_router_router13_task5 - task_total_delay_router_router13_task50 - task_total_delay_router_router13_task51 - task_total_delay_router_router13_task52 - task_total_delay_router_router13_task53 - task_total_delay_router_router13_task54 - task_total_delay_router_router13_task55 - task_total_delay_router_router13_task56 - task_total_delay_router_router13_task57 - task_total_delay_router_router13_task58 - task_total_delay_router_router13_task59 - task_total_delay_router_router13_task6 - task_total_delay_router_router13_task60 - task_total_delay_router_router13_task61 - task_total_delay_router_router13_task62 - task_total_delay_router_router13_task63 - task_total_delay_router_router13_task64 - task_total_delay_router_router13_task65 - task_total_delay_router_router13_task66 - task_total_delay_router_router13_task67 - task_total_delay_router_router13_task68 - task_total_delay_router_router13_task69 - task_total_delay_router_router13_task7 - task_total_delay_router_router13_task8 - task_total_delay_router_router13_task9 >= -0.0\n", + "_C123076: PE13_total_memory - task_total_memory_router_router13_task0 - task_total_memory_router_router13_task1 - task_total_memory_router_router13_task10 - task_total_memory_router_router13_task11 - task_total_memory_router_router13_task12 - task_total_memory_router_router13_task13 - task_total_memory_router_router13_task14 - task_total_memory_router_router13_task15 - task_total_memory_router_router13_task16 - task_total_memory_router_router13_task17 - task_total_memory_router_router13_task18 - task_total_memory_router_router13_task19 - task_total_memory_router_router13_task2 - task_total_memory_router_router13_task20 - task_total_memory_router_router13_task21 - task_total_memory_router_router13_task22 - task_total_memory_router_router13_task23 - task_total_memory_router_router13_task24 - task_total_memory_router_router13_task25 - task_total_memory_router_router13_task26 - task_total_memory_router_router13_task27 - task_total_memory_router_router13_task28 - task_total_memory_router_router13_task29 - task_total_memory_router_router13_task3 - task_total_memory_router_router13_task30 - task_total_memory_router_router13_task31 - task_total_memory_router_router13_task32 - task_total_memory_router_router13_task33 - task_total_memory_router_router13_task34 - task_total_memory_router_router13_task35 - task_total_memory_router_router13_task36 - task_total_memory_router_router13_task37 - task_total_memory_router_router13_task38 - task_total_memory_router_router13_task39 - task_total_memory_router_router13_task4 - task_total_memory_router_router13_task40 - task_total_memory_router_router13_task41 - task_total_memory_router_router13_task42 - task_total_memory_router_router13_task43 - task_total_memory_router_router13_task44 - task_total_memory_router_router13_task45 - task_total_memory_router_router13_task46 - task_total_memory_router_router13_task47 - task_total_memory_router_router13_task48 - task_total_memory_router_router13_task49 - task_total_memory_router_router13_task5 - task_total_memory_router_router13_task50 - task_total_memory_router_router13_task51 - task_total_memory_router_router13_task52 - task_total_memory_router_router13_task53 - task_total_memory_router_router13_task54 - task_total_memory_router_router13_task55 - task_total_memory_router_router13_task56 - task_total_memory_router_router13_task57 - task_total_memory_router_router13_task58 - task_total_memory_router_router13_task59 - task_total_memory_router_router13_task6 - task_total_memory_router_router13_task60 - task_total_memory_router_router13_task61 - task_total_memory_router_router13_task62 - task_total_memory_router_router13_task63 - task_total_memory_router_router13_task64 - task_total_memory_router_router13_task65 - task_total_memory_router_router13_task66 - task_total_memory_router_router13_task67 - task_total_memory_router_router13_task68 - task_total_memory_router_router13_task69 - task_total_memory_router_router13_task7 - task_total_memory_router_router13_task8 - 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t_send_59 + task_total_delay_router_router14_task59 >= -250000.0\n", + "_C123339: -250000.0*t_59_map_14 - t_mem_59 + task_total_memory_router_router14_task59 >= -250000.0\n", + "_C123340: -t60_end_ + t60_start - 250000.0*t_60_map_14 - t_send_60 + task_total_delay_router_router14_task60 >= -250000.0\n", + "_C123341: -250000.0*t_60_map_14 - t_mem_60 + task_total_memory_router_router14_task60 >= -250000.0\n", + "_C123342: -t61_end_ + t61_start - 250000.0*t_61_map_14 - t_send_61 + task_total_delay_router_router14_task61 >= -250000.0\n", + "_C123343: -250000.0*t_61_map_14 - t_mem_61 + task_total_memory_router_router14_task61 >= -250000.0\n", + "_C123344: -t62_end_ + t62_start - 250000.0*t_62_map_14 - t_send_62 + task_total_delay_router_router14_task62 >= -250000.0\n", + "_C123345: -250000.0*t_62_map_14 - t_mem_62 + task_total_memory_router_router14_task62 >= -250000.0\n", + "_C123346: -t63_end_ + t63_start - 250000.0*t_63_map_14 - t_send_63 + task_total_delay_router_router14_task63 >= 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+ task_total_memory_router_router14_task67 >= -250000.0\n", + "_C123356: -t68_end_ + t68_start - 250000.0*t_68_map_14 - t_send_68 + task_total_delay_router_router14_task68 >= -250000.0\n", + "_C123357: -250000.0*t_68_map_14 - t_mem_68 + task_total_memory_router_router14_task68 >= -250000.0\n", + "_C123358: -t69_end_ + t69_start - 250000.0*t_69_map_14 - t_send_69 + task_total_delay_router_router14_task69 >= -250000.0\n", + "_C123359: -250000.0*t_69_map_14 - t_mem_69 + task_total_memory_router_router14_task69 >= -250000.0\n", + "_C123360: PE_mem_overflow14 - task_total_memory_router_router14_task0 - task_total_memory_router_router14_task1 - task_total_memory_router_router14_task10 - task_total_memory_router_router14_task11 - task_total_memory_router_router14_task12 - task_total_memory_router_router14_task13 - task_total_memory_router_router14_task14 - task_total_memory_router_router14_task15 - task_total_memory_router_router14_task16 - task_total_memory_router_router14_task17 - task_total_memory_router_router14_task18 - task_total_memory_router_router14_task19 - task_total_memory_router_router14_task2 - task_total_memory_router_router14_task20 - task_total_memory_router_router14_task21 - task_total_memory_router_router14_task22 - task_total_memory_router_router14_task23 - task_total_memory_router_router14_task24 - task_total_memory_router_router14_task25 - task_total_memory_router_router14_task26 - task_total_memory_router_router14_task27 - task_total_memory_router_router14_task28 - task_total_memory_router_router14_task29 - task_total_memory_router_router14_task3 - task_total_memory_router_router14_task30 - task_total_memory_router_router14_task31 - task_total_memory_router_router14_task32 - task_total_memory_router_router14_task33 - task_total_memory_router_router14_task34 - task_total_memory_router_router14_task35 - task_total_memory_router_router14_task36 - task_total_memory_router_router14_task37 - task_total_memory_router_router14_task38 - task_total_memory_router_router14_task39 - task_total_memory_router_router14_task4 - task_total_memory_router_router14_task40 - task_total_memory_router_router14_task41 - task_total_memory_router_router14_task42 - task_total_memory_router_router14_task43 - task_total_memory_router_router14_task44 - task_total_memory_router_router14_task45 - task_total_memory_router_router14_task46 - task_total_memory_router_router14_task47 - task_total_memory_router_router14_task48 - task_total_memory_router_router14_task49 - task_total_memory_router_router14_task5 - task_total_memory_router_router14_task50 - task_total_memory_router_router14_task51 - task_total_memory_router_router14_task52 - task_total_memory_router_router14_task53 - task_total_memory_router_router14_task54 - task_total_memory_router_router14_task55 - task_total_memory_router_router14_task56 - task_total_memory_router_router14_task57 - task_total_memory_router_router14_task58 - task_total_memory_router_router14_task59 - task_total_memory_router_router14_task6 - task_total_memory_router_router14_task60 - task_total_memory_router_router14_task61 - task_total_memory_router_router14_task62 - task_total_memory_router_router14_task63 - task_total_memory_router_router14_task64 - task_total_memory_router_router14_task65 - task_total_memory_router_router14_task66 - task_total_memory_router_router14_task67 - task_total_memory_router_router14_task68 - task_total_memory_router_router14_task69 - task_total_memory_router_router14_task7 - task_total_memory_router_router14_task8 - task_total_memory_router_router14_task9 >= -0.0\n", + "_C123361: PE14_total_delay - task_total_delay_router_router14_task0 - task_total_delay_router_router14_task1 - task_total_delay_router_router14_task10 - task_total_delay_router_router14_task11 - task_total_delay_router_router14_task12 - task_total_delay_router_router14_task13 - task_total_delay_router_router14_task14 - task_total_delay_router_router14_task15 - task_total_delay_router_router14_task16 - task_total_delay_router_router14_task17 - task_total_delay_router_router14_task18 - task_total_delay_router_router14_task19 - task_total_delay_router_router14_task2 - task_total_delay_router_router14_task20 - task_total_delay_router_router14_task21 - task_total_delay_router_router14_task22 - task_total_delay_router_router14_task23 - task_total_delay_router_router14_task24 - task_total_delay_router_router14_task25 - task_total_delay_router_router14_task26 - task_total_delay_router_router14_task27 - task_total_delay_router_router14_task28 - task_total_delay_router_router14_task29 - task_total_delay_router_router14_task3 - task_total_delay_router_router14_task30 - task_total_delay_router_router14_task31 - task_total_delay_router_router14_task32 - task_total_delay_router_router14_task33 - task_total_delay_router_router14_task34 - task_total_delay_router_router14_task35 - task_total_delay_router_router14_task36 - task_total_delay_router_router14_task37 - task_total_delay_router_router14_task38 - task_total_delay_router_router14_task39 - task_total_delay_router_router14_task4 - task_total_delay_router_router14_task40 - task_total_delay_router_router14_task41 - task_total_delay_router_router14_task42 - task_total_delay_router_router14_task43 - task_total_delay_router_router14_task44 - task_total_delay_router_router14_task45 - task_total_delay_router_router14_task46 - task_total_delay_router_router14_task47 - task_total_delay_router_router14_task48 - task_total_delay_router_router14_task49 - task_total_delay_router_router14_task5 - task_total_delay_router_router14_task50 - task_total_delay_router_router14_task51 - task_total_delay_router_router14_task52 - task_total_delay_router_router14_task53 - task_total_delay_router_router14_task54 - task_total_delay_router_router14_task55 - task_total_delay_router_router14_task56 - task_total_delay_router_router14_task57 - task_total_delay_router_router14_task58 - task_total_delay_router_router14_task59 - task_total_delay_router_router14_task6 - task_total_delay_router_router14_task60 - task_total_delay_router_router14_task61 - task_total_delay_router_router14_task62 - task_total_delay_router_router14_task63 - task_total_delay_router_router14_task64 - task_total_delay_router_router14_task65 - task_total_delay_router_router14_task66 - task_total_delay_router_router14_task67 - task_total_delay_router_router14_task68 - task_total_delay_router_router14_task69 - task_total_delay_router_router14_task7 - task_total_delay_router_router14_task8 - task_total_delay_router_router14_task9 >= -0.0\n", + "_C123362: PE14_total_memory - task_total_memory_router_router14_task0 - task_total_memory_router_router14_task1 - task_total_memory_router_router14_task10 - task_total_memory_router_router14_task11 - task_total_memory_router_router14_task12 - task_total_memory_router_router14_task13 - task_total_memory_router_router14_task14 - task_total_memory_router_router14_task15 - task_total_memory_router_router14_task16 - task_total_memory_router_router14_task17 - task_total_memory_router_router14_task18 - task_total_memory_router_router14_task19 - task_total_memory_router_router14_task2 - task_total_memory_router_router14_task20 - task_total_memory_router_router14_task21 - task_total_memory_router_router14_task22 - task_total_memory_router_router14_task23 - task_total_memory_router_router14_task24 - task_total_memory_router_router14_task25 - task_total_memory_router_router14_task26 - task_total_memory_router_router14_task27 - task_total_memory_router_router14_task28 - task_total_memory_router_router14_task29 - task_total_memory_router_router14_task3 - task_total_memory_router_router14_task30 - task_total_memory_router_router14_task31 - task_total_memory_router_router14_task32 - task_total_memory_router_router14_task33 - task_total_memory_router_router14_task34 - task_total_memory_router_router14_task35 - task_total_memory_router_router14_task36 - task_total_memory_router_router14_task37 - task_total_memory_router_router14_task38 - task_total_memory_router_router14_task39 - task_total_memory_router_router14_task4 - task_total_memory_router_router14_task40 - task_total_memory_router_router14_task41 - task_total_memory_router_router14_task42 - task_total_memory_router_router14_task43 - task_total_memory_router_router14_task44 - task_total_memory_router_router14_task45 - task_total_memory_router_router14_task46 - task_total_memory_router_router14_task47 - task_total_memory_router_router14_task48 - task_total_memory_router_router14_task49 - task_total_memory_router_router14_task5 - task_total_memory_router_router14_task50 - task_total_memory_router_router14_task51 - task_total_memory_router_router14_task52 - task_total_memory_router_router14_task53 - task_total_memory_router_router14_task54 - task_total_memory_router_router14_task55 - task_total_memory_router_router14_task56 - task_total_memory_router_router14_task57 - task_total_memory_router_router14_task58 - task_total_memory_router_router14_task59 - task_total_memory_router_router14_task6 - task_total_memory_router_router14_task60 - task_total_memory_router_router14_task61 - task_total_memory_router_router14_task62 - task_total_memory_router_router14_task63 - task_total_memory_router_router14_task64 - task_total_memory_router_router14_task65 - task_total_memory_router_router14_task66 - task_total_memory_router_router14_task67 - task_total_memory_router_router14_task68 - task_total_memory_router_router14_task69 - task_total_memory_router_router14_task7 - task_total_memory_router_router14_task8 - task_total_memory_router_router14_task9 >= -0.0\n", + "_C123363: -PE_mem_overflow14 + max_memory_overflow >= 0\n", + "_C123364: PE14_time_delay_max - t0_end_ - 250000.0*t_0_map_14 >= -250000.0\n", + "_C123365: PE14_time_delay_min - t0_start + 250000.0*t_0_map_14 <= 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"_C123390: PE14_time_delay_max - t13_end_ - 250000.0*t_13_map_14 >= -250000.0\n", + "_C123391: PE14_time_delay_min - t13_start + 250000.0*t_13_map_14 <= 250000.0\n", + "_C123392: PE14_time_delay_max - t14_end_ - 250000.0*t_14_map_14 >= -250000.0\n", + "_C123393: PE14_time_delay_min - t14_start + 250000.0*t_14_map_14 <= 250000.0\n", + "_C123394: PE14_time_delay_max - t15_end_ - 250000.0*t_15_map_14 >= -250000.0\n", + "_C123395: PE14_time_delay_min - t15_start + 250000.0*t_15_map_14 <= 250000.0\n", + "_C123396: PE14_time_delay_max - t16_end_ - 250000.0*t_16_map_14 >= -250000.0\n", + "_C123397: PE14_time_delay_min - t16_start + 250000.0*t_16_map_14 <= 250000.0\n", + "_C123398: PE14_time_delay_max - t17_end_ - 250000.0*t_17_map_14 >= -250000.0\n", + "_C123399: PE14_time_delay_min - t17_start + 250000.0*t_17_map_14 <= 250000.0\n", + "_C123400: PE14_time_delay_max - t18_end_ - 250000.0*t_18_map_14 >= -250000.0\n", + "_C123401: PE14_time_delay_min - t18_start + 250000.0*t_18_map_14 <= 250000.0\n", + "_C123402: PE14_time_delay_max - t19_end_ - 250000.0*t_19_map_14 >= -250000.0\n", + "_C123403: PE14_time_delay_min - t19_start + 250000.0*t_19_map_14 <= 250000.0\n", + "_C123404: PE14_time_delay_max - t20_end_ - 250000.0*t_20_map_14 >= -250000.0\n", + "_C123405: PE14_time_delay_min - t20_start + 250000.0*t_20_map_14 <= 250000.0\n", + "_C123406: PE14_time_delay_max - t21_end_ - 250000.0*t_21_map_14 >= -250000.0\n", + "_C123407: PE14_time_delay_min - t21_start + 250000.0*t_21_map_14 <= 250000.0\n", + "_C123408: PE14_time_delay_max - t22_end_ - 250000.0*t_22_map_14 >= -250000.0\n", + "_C123409: PE14_time_delay_min - t22_start + 250000.0*t_22_map_14 <= 250000.0\n", + "_C123410: PE14_time_delay_max - t23_end_ - 250000.0*t_23_map_14 >= -250000.0\n", + "_C123411: PE14_time_delay_min - t23_start + 250000.0*t_23_map_14 <= 250000.0\n", + "_C123412: PE14_time_delay_max - t24_end_ - 250000.0*t_24_map_14 >= -250000.0\n", + "_C123413: PE14_time_delay_min - t24_start + 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PE14_time_delay_min - t36_start + 250000.0*t_36_map_14 <= 250000.0\n", + "_C123438: PE14_time_delay_max - t37_end_ - 250000.0*t_37_map_14 >= -250000.0\n", + "_C123439: PE14_time_delay_min - t37_start + 250000.0*t_37_map_14 <= 250000.0\n", + "_C123440: PE14_time_delay_max - t38_end_ - 250000.0*t_38_map_14 >= -250000.0\n", + "_C123441: PE14_time_delay_min - t38_start + 250000.0*t_38_map_14 <= 250000.0\n", + "_C123442: PE14_time_delay_max - t39_end_ - 250000.0*t_39_map_14 >= -250000.0\n", + "_C123443: PE14_time_delay_min - t39_start + 250000.0*t_39_map_14 <= 250000.0\n", + "_C123444: PE14_time_delay_max - t40_end_ - 250000.0*t_40_map_14 >= -250000.0\n", + "_C123445: PE14_time_delay_min - t40_start + 250000.0*t_40_map_14 <= 250000.0\n", + "_C123446: PE14_time_delay_max - t41_end_ - 250000.0*t_41_map_14 >= -250000.0\n", + "_C123447: PE14_time_delay_min - t41_start + 250000.0*t_41_map_14 <= 250000.0\n", + "_C123448: PE14_time_delay_max - t42_end_ - 250000.0*t_42_map_14 >= -250000.0\n", + "_C123449: PE14_time_delay_min - t42_start + 250000.0*t_42_map_14 <= 250000.0\n", + "_C123450: PE14_time_delay_max - t43_end_ - 250000.0*t_43_map_14 >= -250000.0\n", + "_C123451: PE14_time_delay_min - t43_start + 250000.0*t_43_map_14 <= 250000.0\n", + "_C123452: PE14_time_delay_max - t44_end_ - 250000.0*t_44_map_14 >= -250000.0\n", + "_C123453: PE14_time_delay_min - t44_start + 250000.0*t_44_map_14 <= 250000.0\n", + "_C123454: PE14_time_delay_max - t45_end_ - 250000.0*t_45_map_14 >= -250000.0\n", + "_C123455: PE14_time_delay_min - t45_start + 250000.0*t_45_map_14 <= 250000.0\n", + "_C123456: PE14_time_delay_max - t46_end_ - 250000.0*t_46_map_14 >= -250000.0\n", + "_C123457: PE14_time_delay_min - t46_start + 250000.0*t_46_map_14 <= 250000.0\n", + "_C123458: PE14_time_delay_max - t47_end_ - 250000.0*t_47_map_14 >= -250000.0\n", + "_C123459: PE14_time_delay_min - t47_start + 250000.0*t_47_map_14 <= 250000.0\n", + "_C123460: PE14_time_delay_max - t48_end_ - 250000.0*t_48_map_14 >= 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250000.0*t_54_map_14 >= -250000.0\n", + "_C123473: PE14_time_delay_min - t54_start + 250000.0*t_54_map_14 <= 250000.0\n", + "_C123474: PE14_time_delay_max - t55_end_ - 250000.0*t_55_map_14 >= -250000.0\n", + "_C123475: PE14_time_delay_min - t55_start + 250000.0*t_55_map_14 <= 250000.0\n", + "_C123476: PE14_time_delay_max - t56_end_ - 250000.0*t_56_map_14 >= -250000.0\n", + "_C123477: PE14_time_delay_min - t56_start + 250000.0*t_56_map_14 <= 250000.0\n", + "_C123478: PE14_time_delay_max - t57_end_ - 250000.0*t_57_map_14 >= -250000.0\n", + "_C123479: PE14_time_delay_min - t57_start + 250000.0*t_57_map_14 <= 250000.0\n", + "_C123480: PE14_time_delay_max - t58_end_ - 250000.0*t_58_map_14 >= -250000.0\n", + "_C123481: PE14_time_delay_min - t58_start + 250000.0*t_58_map_14 <= 250000.0\n", + "_C123482: PE14_time_delay_max - t59_end_ - 250000.0*t_59_map_14 >= -250000.0\n", + "_C123483: PE14_time_delay_min - t59_start + 250000.0*t_59_map_14 <= 250000.0\n", + "_C123484: PE14_time_delay_max - t60_end_ - 250000.0*t_60_map_14 >= -250000.0\n", + "_C123485: PE14_time_delay_min - t60_start + 250000.0*t_60_map_14 <= 250000.0\n", + "_C123486: PE14_time_delay_max - t61_end_ - 250000.0*t_61_map_14 >= -250000.0\n", + "_C123487: PE14_time_delay_min - t61_start + 250000.0*t_61_map_14 <= 250000.0\n", + "_C123488: PE14_time_delay_max - t62_end_ - 250000.0*t_62_map_14 >= -250000.0\n", + "_C123489: PE14_time_delay_min - t62_start + 250000.0*t_62_map_14 <= 250000.0\n", + "_C123490: PE14_time_delay_max - t63_end_ - 250000.0*t_63_map_14 >= -250000.0\n", + "_C123491: PE14_time_delay_min - t63_start + 250000.0*t_63_map_14 <= 250000.0\n", + "_C123492: PE14_time_delay_max - t64_end_ - 250000.0*t_64_map_14 >= -250000.0\n", + "_C123493: PE14_time_delay_min - t64_start + 250000.0*t_64_map_14 <= 250000.0\n", + "_C123494: PE14_time_delay_max - t65_end_ - 250000.0*t_65_map_14 >= -250000.0\n", + "_C123495: PE14_time_delay_min - t65_start + 250000.0*t_65_map_14 <= 250000.0\n", + "_C123496: PE14_time_delay_max - t66_end_ - 250000.0*t_66_map_14 >= -250000.0\n", + "_C123497: PE14_time_delay_min - t66_start + 250000.0*t_66_map_14 <= 250000.0\n", + "_C123498: PE14_time_delay_max - t67_end_ - 250000.0*t_67_map_14 >= -250000.0\n", + "_C123499: PE14_time_delay_min - t67_start + 250000.0*t_67_map_14 <= 250000.0\n", + "_C123500: PE14_time_delay_max - t68_end_ - 250000.0*t_68_map_14 >= -250000.0\n", + "_C123501: PE14_time_delay_min - t68_start + 250000.0*t_68_map_14 <= 250000.0\n", + "_C123502: PE14_time_delay_max - t69_end_ - 250000.0*t_69_map_14 >= -250000.0\n", + "_C123503: PE14_time_delay_min - t69_start + 250000.0*t_69_map_14 <= 250000.0\n", + "_C123504: -PE14_time_delay_max + PE14_time_delay_min + PE14_total_time_delay = 0\n", + "_C123505: -PE14_total_time_delay + max_router_delay >= 0\n", + "_C123506: -t0_end_ + t0_start - 250000.0*t_0_map_15 - t_send_0 + task_total_delay_router_router15_task0 >= -250000.0\n", + "_C123507: -250000.0*t_0_map_15 - t_mem_0 + task_total_memory_router_router15_task0 >= -250000.0\n", + "_C123508: -t1_end_ + t1_start - 250000.0*t_1_map_15 - t_send_1 + task_total_delay_router_router15_task1 >= -250000.0\n", + "_C123509: -250000.0*t_1_map_15 - t_mem_1 + task_total_memory_router_router15_task1 >= -250000.0\n", + "_C123510: -t2_end_ + t2_start - 250000.0*t_2_map_15 - t_send_2 + task_total_delay_router_router15_task2 >= -250000.0\n", + "_C123511: -250000.0*t_2_map_15 - t_mem_2 + task_total_memory_router_router15_task2 >= -250000.0\n", + "_C123512: -t3_end_ + t3_start - 250000.0*t_3_map_15 - t_send_3 + task_total_delay_router_router15_task3 >= -250000.0\n", + "_C123513: -250000.0*t_3_map_15 - t_mem_3 + task_total_memory_router_router15_task3 >= -250000.0\n", + "_C123514: -t4_end_ + t4_start - 250000.0*t_4_map_15 - t_send_4 + task_total_delay_router_router15_task4 >= -250000.0\n", + "_C123515: -250000.0*t_4_map_15 - t_mem_4 + task_total_memory_router_router15_task4 >= -250000.0\n", + "_C123516: -t5_end_ + t5_start - 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+ "_C123644: -t69_end_ + t69_start - 250000.0*t_69_map_15 - t_send_69 + task_total_delay_router_router15_task69 >= -250000.0\n", + "_C123645: -250000.0*t_69_map_15 - t_mem_69 + task_total_memory_router_router15_task69 >= -250000.0\n", + "_C123646: PE_mem_overflow15 - task_total_memory_router_router15_task0 - task_total_memory_router_router15_task1 - task_total_memory_router_router15_task10 - task_total_memory_router_router15_task11 - task_total_memory_router_router15_task12 - task_total_memory_router_router15_task13 - task_total_memory_router_router15_task14 - task_total_memory_router_router15_task15 - task_total_memory_router_router15_task16 - task_total_memory_router_router15_task17 - task_total_memory_router_router15_task18 - task_total_memory_router_router15_task19 - task_total_memory_router_router15_task2 - task_total_memory_router_router15_task20 - task_total_memory_router_router15_task21 - task_total_memory_router_router15_task22 - task_total_memory_router_router15_task23 - task_total_memory_router_router15_task24 - task_total_memory_router_router15_task25 - task_total_memory_router_router15_task26 - task_total_memory_router_router15_task27 - task_total_memory_router_router15_task28 - task_total_memory_router_router15_task29 - task_total_memory_router_router15_task3 - task_total_memory_router_router15_task30 - task_total_memory_router_router15_task31 - task_total_memory_router_router15_task32 - task_total_memory_router_router15_task33 - task_total_memory_router_router15_task34 - task_total_memory_router_router15_task35 - task_total_memory_router_router15_task36 - task_total_memory_router_router15_task37 - task_total_memory_router_router15_task38 - task_total_memory_router_router15_task39 - task_total_memory_router_router15_task4 - task_total_memory_router_router15_task40 - task_total_memory_router_router15_task41 - task_total_memory_router_router15_task42 - task_total_memory_router_router15_task43 - task_total_memory_router_router15_task44 - task_total_memory_router_router15_task45 - task_total_memory_router_router15_task46 - task_total_memory_router_router15_task47 - task_total_memory_router_router15_task48 - task_total_memory_router_router15_task49 - task_total_memory_router_router15_task5 - task_total_memory_router_router15_task50 - task_total_memory_router_router15_task51 - task_total_memory_router_router15_task52 - task_total_memory_router_router15_task53 - task_total_memory_router_router15_task54 - task_total_memory_router_router15_task55 - task_total_memory_router_router15_task56 - task_total_memory_router_router15_task57 - task_total_memory_router_router15_task58 - task_total_memory_router_router15_task59 - task_total_memory_router_router15_task6 - task_total_memory_router_router15_task60 - task_total_memory_router_router15_task61 - task_total_memory_router_router15_task62 - task_total_memory_router_router15_task63 - task_total_memory_router_router15_task64 - task_total_memory_router_router15_task65 - task_total_memory_router_router15_task66 - task_total_memory_router_router15_task67 - task_total_memory_router_router15_task68 - task_total_memory_router_router15_task69 - task_total_memory_router_router15_task7 - task_total_memory_router_router15_task8 - task_total_memory_router_router15_task9 >= -0.0\n", + "_C123647: PE15_total_delay - task_total_delay_router_router15_task0 - task_total_delay_router_router15_task1 - task_total_delay_router_router15_task10 - task_total_delay_router_router15_task11 - task_total_delay_router_router15_task12 - task_total_delay_router_router15_task13 - task_total_delay_router_router15_task14 - task_total_delay_router_router15_task15 - task_total_delay_router_router15_task16 - task_total_delay_router_router15_task17 - task_total_delay_router_router15_task18 - task_total_delay_router_router15_task19 - task_total_delay_router_router15_task2 - task_total_delay_router_router15_task20 - task_total_delay_router_router15_task21 - task_total_delay_router_router15_task22 - task_total_delay_router_router15_task23 - task_total_delay_router_router15_task24 - task_total_delay_router_router15_task25 - task_total_delay_router_router15_task26 - task_total_delay_router_router15_task27 - task_total_delay_router_router15_task28 - task_total_delay_router_router15_task29 - task_total_delay_router_router15_task3 - task_total_delay_router_router15_task30 - task_total_delay_router_router15_task31 - task_total_delay_router_router15_task32 - task_total_delay_router_router15_task33 - task_total_delay_router_router15_task34 - task_total_delay_router_router15_task35 - task_total_delay_router_router15_task36 - task_total_delay_router_router15_task37 - task_total_delay_router_router15_task38 - task_total_delay_router_router15_task39 - task_total_delay_router_router15_task4 - task_total_delay_router_router15_task40 - task_total_delay_router_router15_task41 - task_total_delay_router_router15_task42 - task_total_delay_router_router15_task43 - task_total_delay_router_router15_task44 - task_total_delay_router_router15_task45 - task_total_delay_router_router15_task46 - task_total_delay_router_router15_task47 - task_total_delay_router_router15_task48 - task_total_delay_router_router15_task49 - task_total_delay_router_router15_task5 - task_total_delay_router_router15_task50 - task_total_delay_router_router15_task51 - task_total_delay_router_router15_task52 - task_total_delay_router_router15_task53 - task_total_delay_router_router15_task54 - task_total_delay_router_router15_task55 - task_total_delay_router_router15_task56 - task_total_delay_router_router15_task57 - task_total_delay_router_router15_task58 - task_total_delay_router_router15_task59 - task_total_delay_router_router15_task6 - task_total_delay_router_router15_task60 - task_total_delay_router_router15_task61 - task_total_delay_router_router15_task62 - task_total_delay_router_router15_task63 - task_total_delay_router_router15_task64 - task_total_delay_router_router15_task65 - task_total_delay_router_router15_task66 - task_total_delay_router_router15_task67 - task_total_delay_router_router15_task68 - task_total_delay_router_router15_task69 - task_total_delay_router_router15_task7 - task_total_delay_router_router15_task8 - task_total_delay_router_router15_task9 >= -0.0\n", + "_C123648: PE15_total_memory - task_total_memory_router_router15_task0 - task_total_memory_router_router15_task1 - task_total_memory_router_router15_task10 - task_total_memory_router_router15_task11 - task_total_memory_router_router15_task12 - task_total_memory_router_router15_task13 - task_total_memory_router_router15_task14 - task_total_memory_router_router15_task15 - task_total_memory_router_router15_task16 - task_total_memory_router_router15_task17 - task_total_memory_router_router15_task18 - task_total_memory_router_router15_task19 - task_total_memory_router_router15_task2 - task_total_memory_router_router15_task20 - task_total_memory_router_router15_task21 - task_total_memory_router_router15_task22 - task_total_memory_router_router15_task23 - task_total_memory_router_router15_task24 - task_total_memory_router_router15_task25 - task_total_memory_router_router15_task26 - task_total_memory_router_router15_task27 - task_total_memory_router_router15_task28 - task_total_memory_router_router15_task29 - task_total_memory_router_router15_task3 - task_total_memory_router_router15_task30 - task_total_memory_router_router15_task31 - task_total_memory_router_router15_task32 - task_total_memory_router_router15_task33 - task_total_memory_router_router15_task34 - task_total_memory_router_router15_task35 - task_total_memory_router_router15_task36 - task_total_memory_router_router15_task37 - task_total_memory_router_router15_task38 - task_total_memory_router_router15_task39 - task_total_memory_router_router15_task4 - task_total_memory_router_router15_task40 - task_total_memory_router_router15_task41 - task_total_memory_router_router15_task42 - task_total_memory_router_router15_task43 - task_total_memory_router_router15_task44 - task_total_memory_router_router15_task45 - task_total_memory_router_router15_task46 - task_total_memory_router_router15_task47 - task_total_memory_router_router15_task48 - task_total_memory_router_router15_task49 - task_total_memory_router_router15_task5 - task_total_memory_router_router15_task50 - task_total_memory_router_router15_task51 - task_total_memory_router_router15_task52 - task_total_memory_router_router15_task53 - task_total_memory_router_router15_task54 - task_total_memory_router_router15_task55 - task_total_memory_router_router15_task56 - task_total_memory_router_router15_task57 - task_total_memory_router_router15_task58 - task_total_memory_router_router15_task59 - task_total_memory_router_router15_task6 - task_total_memory_router_router15_task60 - task_total_memory_router_router15_task61 - task_total_memory_router_router15_task62 - task_total_memory_router_router15_task63 - task_total_memory_router_router15_task64 - task_total_memory_router_router15_task65 - task_total_memory_router_router15_task66 - task_total_memory_router_router15_task67 - task_total_memory_router_router15_task68 - task_total_memory_router_router15_task69 - task_total_memory_router_router15_task7 - task_total_memory_router_router15_task8 - task_total_memory_router_router15_task9 >= -0.0\n", + "_C123649: -PE_mem_overflow15 + max_memory_overflow >= 0\n", + "_C123650: PE15_time_delay_max - t0_end_ - 250000.0*t_0_map_15 >= -250000.0\n", + "_C123651: PE15_time_delay_min - t0_start + 250000.0*t_0_map_15 <= 250000.0\n", + "_C123652: PE15_time_delay_max - t1_end_ - 250000.0*t_1_map_15 >= -250000.0\n", + "_C123653: PE15_time_delay_min - t1_start + 250000.0*t_1_map_15 <= 250000.0\n", + "_C123654: PE15_time_delay_max - t2_end_ - 250000.0*t_2_map_15 >= -250000.0\n", + "_C123655: PE15_time_delay_min - t2_start + 250000.0*t_2_map_15 <= 250000.0\n", + "_C123656: PE15_time_delay_max - t3_end_ - 250000.0*t_3_map_15 >= -250000.0\n", + "_C123657: PE15_time_delay_min - t3_start + 250000.0*t_3_map_15 <= 250000.0\n", + "_C123658: PE15_time_delay_max - t4_end_ - 250000.0*t_4_map_15 >= -250000.0\n", + "_C123659: PE15_time_delay_min - t4_start + 250000.0*t_4_map_15 <= 250000.0\n", + "_C123660: PE15_time_delay_max - t5_end_ - 250000.0*t_5_map_15 >= -250000.0\n", + "_C123661: PE15_time_delay_min - t5_start + 250000.0*t_5_map_15 <= 250000.0\n", + "_C123662: PE15_time_delay_max - t6_end_ - 250000.0*t_6_map_15 >= -250000.0\n", + "_C123663: PE15_time_delay_min - t6_start + 250000.0*t_6_map_15 <= 250000.0\n", + "_C123664: PE15_time_delay_max - t7_end_ - 250000.0*t_7_map_15 >= -250000.0\n", + "_C123665: PE15_time_delay_min - t7_start + 250000.0*t_7_map_15 <= 250000.0\n", + "_C123666: PE15_time_delay_max - t8_end_ - 250000.0*t_8_map_15 >= -250000.0\n", + "_C123667: PE15_time_delay_min - t8_start + 250000.0*t_8_map_15 <= 250000.0\n", + "_C123668: PE15_time_delay_max - t9_end_ - 250000.0*t_9_map_15 >= -250000.0\n", + "_C123669: PE15_time_delay_min - t9_start + 250000.0*t_9_map_15 <= 250000.0\n", + "_C123670: PE15_time_delay_max - t10_end_ - 250000.0*t_10_map_15 >= -250000.0\n", + "_C123671: PE15_time_delay_min - t10_start + 250000.0*t_10_map_15 <= 250000.0\n", + "_C123672: PE15_time_delay_max - t11_end_ - 250000.0*t_11_map_15 >= -250000.0\n", + "_C123673: PE15_time_delay_min - t11_start + 250000.0*t_11_map_15 <= 250000.0\n", + "_C123674: PE15_time_delay_max - t12_end_ - 250000.0*t_12_map_15 >= -250000.0\n", + "_C123675: PE15_time_delay_min - t12_start + 250000.0*t_12_map_15 <= 250000.0\n", + "_C123676: PE15_time_delay_max - t13_end_ - 250000.0*t_13_map_15 >= -250000.0\n", + "_C123677: PE15_time_delay_min - t13_start + 250000.0*t_13_map_15 <= 250000.0\n", + "_C123678: PE15_time_delay_max - t14_end_ - 250000.0*t_14_map_15 >= -250000.0\n", + "_C123679: PE15_time_delay_min - t14_start + 250000.0*t_14_map_15 <= 250000.0\n", + "_C123680: PE15_time_delay_max - t15_end_ - 250000.0*t_15_map_15 >= -250000.0\n", + "_C123681: PE15_time_delay_min - t15_start + 250000.0*t_15_map_15 <= 250000.0\n", + "_C123682: PE15_time_delay_max - t16_end_ - 250000.0*t_16_map_15 >= -250000.0\n", + "_C123683: PE15_time_delay_min - t16_start + 250000.0*t_16_map_15 <= 250000.0\n", + "_C123684: PE15_time_delay_max - t17_end_ - 250000.0*t_17_map_15 >= -250000.0\n", + "_C123685: PE15_time_delay_min - t17_start + 250000.0*t_17_map_15 <= 250000.0\n", + "_C123686: PE15_time_delay_max - t18_end_ - 250000.0*t_18_map_15 >= -250000.0\n", + "_C123687: PE15_time_delay_min - t18_start + 250000.0*t_18_map_15 <= 250000.0\n", + "_C123688: PE15_time_delay_max - t19_end_ - 250000.0*t_19_map_15 >= -250000.0\n", + "_C123689: PE15_time_delay_min - t19_start + 250000.0*t_19_map_15 <= 250000.0\n", + "_C123690: PE15_time_delay_max - t20_end_ - 250000.0*t_20_map_15 >= -250000.0\n", + "_C123691: PE15_time_delay_min - t20_start + 250000.0*t_20_map_15 <= 250000.0\n", + "_C123692: PE15_time_delay_max - t21_end_ - 250000.0*t_21_map_15 >= -250000.0\n", + "_C123693: PE15_time_delay_min - t21_start + 250000.0*t_21_map_15 <= 250000.0\n", + "_C123694: PE15_time_delay_max - t22_end_ - 250000.0*t_22_map_15 >= -250000.0\n", + "_C123695: PE15_time_delay_min - t22_start + 250000.0*t_22_map_15 <= 250000.0\n", + "_C123696: PE15_time_delay_max - t23_end_ - 250000.0*t_23_map_15 >= -250000.0\n", + "_C123697: PE15_time_delay_min - t23_start + 250000.0*t_23_map_15 <= 250000.0\n", + "_C123698: PE15_time_delay_max - t24_end_ - 250000.0*t_24_map_15 >= -250000.0\n", + "_C123699: PE15_time_delay_min - t24_start + 250000.0*t_24_map_15 <= 250000.0\n", + "_C123700: PE15_time_delay_max - t25_end_ - 250000.0*t_25_map_15 >= -250000.0\n", + "_C123701: PE15_time_delay_min - t25_start + 250000.0*t_25_map_15 <= 250000.0\n", + "_C123702: PE15_time_delay_max - t26_end_ - 250000.0*t_26_map_15 >= -250000.0\n", + "_C123703: PE15_time_delay_min - t26_start + 250000.0*t_26_map_15 <= 250000.0\n", + "_C123704: PE15_time_delay_max - t27_end_ - 250000.0*t_27_map_15 >= -250000.0\n", + "_C123705: PE15_time_delay_min - t27_start + 250000.0*t_27_map_15 <= 250000.0\n", + "_C123706: PE15_time_delay_max - t28_end_ - 250000.0*t_28_map_15 >= -250000.0\n", + "_C123707: PE15_time_delay_min - t28_start + 250000.0*t_28_map_15 <= 250000.0\n", + "_C123708: PE15_time_delay_max - t29_end_ - 250000.0*t_29_map_15 >= -250000.0\n", + "_C123709: PE15_time_delay_min - t29_start + 250000.0*t_29_map_15 <= 250000.0\n", + "_C123710: PE15_time_delay_max - t30_end_ - 250000.0*t_30_map_15 >= -250000.0\n", + "_C123711: PE15_time_delay_min - t30_start + 250000.0*t_30_map_15 <= 250000.0\n", + "_C123712: PE15_time_delay_max - t31_end_ - 250000.0*t_31_map_15 >= -250000.0\n", + "_C123713: PE15_time_delay_min - t31_start + 250000.0*t_31_map_15 <= 250000.0\n", + "_C123714: PE15_time_delay_max - t32_end_ - 250000.0*t_32_map_15 >= -250000.0\n", + "_C123715: PE15_time_delay_min - t32_start + 250000.0*t_32_map_15 <= 250000.0\n", + "_C123716: PE15_time_delay_max - t33_end_ - 250000.0*t_33_map_15 >= -250000.0\n", + "_C123717: PE15_time_delay_min - t33_start + 250000.0*t_33_map_15 <= 250000.0\n", + "_C123718: PE15_time_delay_max - t34_end_ - 250000.0*t_34_map_15 >= -250000.0\n", + "_C123719: PE15_time_delay_min - t34_start + 250000.0*t_34_map_15 <= 250000.0\n", + "_C123720: PE15_time_delay_max - t35_end_ - 250000.0*t_35_map_15 >= -250000.0\n", + "_C123721: PE15_time_delay_min - t35_start + 250000.0*t_35_map_15 <= 250000.0\n", + "_C123722: PE15_time_delay_max - t36_end_ - 250000.0*t_36_map_15 >= -250000.0\n", + "_C123723: PE15_time_delay_min - t36_start + 250000.0*t_36_map_15 <= 250000.0\n", + "_C123724: PE15_time_delay_max - t37_end_ - 250000.0*t_37_map_15 >= -250000.0\n", + "_C123725: PE15_time_delay_min - t37_start + 250000.0*t_37_map_15 <= 250000.0\n", + "_C123726: PE15_time_delay_max - t38_end_ - 250000.0*t_38_map_15 >= -250000.0\n", + "_C123727: PE15_time_delay_min - t38_start + 250000.0*t_38_map_15 <= 250000.0\n", + "_C123728: PE15_time_delay_max - t39_end_ - 250000.0*t_39_map_15 >= -250000.0\n", + "_C123729: PE15_time_delay_min - t39_start + 250000.0*t_39_map_15 <= 250000.0\n", + "_C123730: PE15_time_delay_max - t40_end_ - 250000.0*t_40_map_15 >= -250000.0\n", + "_C123731: PE15_time_delay_min - t40_start + 250000.0*t_40_map_15 <= 250000.0\n", + "_C123732: PE15_time_delay_max - t41_end_ - 250000.0*t_41_map_15 >= -250000.0\n", + "_C123733: PE15_time_delay_min - t41_start + 250000.0*t_41_map_15 <= 250000.0\n", + "_C123734: PE15_time_delay_max - t42_end_ - 250000.0*t_42_map_15 >= -250000.0\n", + "_C123735: PE15_time_delay_min - t42_start + 250000.0*t_42_map_15 <= 250000.0\n", + "_C123736: PE15_time_delay_max - t43_end_ - 250000.0*t_43_map_15 >= -250000.0\n", + "_C123737: PE15_time_delay_min - t43_start + 250000.0*t_43_map_15 <= 250000.0\n", + "_C123738: PE15_time_delay_max - t44_end_ - 250000.0*t_44_map_15 >= -250000.0\n", + "_C123739: PE15_time_delay_min - t44_start + 250000.0*t_44_map_15 <= 250000.0\n", + "_C123740: PE15_time_delay_max - t45_end_ - 250000.0*t_45_map_15 >= -250000.0\n", + "_C123741: PE15_time_delay_min - t45_start + 250000.0*t_45_map_15 <= 250000.0\n", + "_C123742: PE15_time_delay_max - t46_end_ - 250000.0*t_46_map_15 >= -250000.0\n", + "_C123743: PE15_time_delay_min - t46_start + 250000.0*t_46_map_15 <= 250000.0\n", + "_C123744: PE15_time_delay_max - t47_end_ - 250000.0*t_47_map_15 >= -250000.0\n", + "_C123745: PE15_time_delay_min - t47_start + 250000.0*t_47_map_15 <= 250000.0\n", + "_C123746: PE15_time_delay_max - t48_end_ - 250000.0*t_48_map_15 >= -250000.0\n", + "_C123747: PE15_time_delay_min - t48_start + 250000.0*t_48_map_15 <= 250000.0\n", + "_C123748: PE15_time_delay_max - t49_end_ - 250000.0*t_49_map_15 >= -250000.0\n", + "_C123749: PE15_time_delay_min - t49_start + 250000.0*t_49_map_15 <= 250000.0\n", + "_C123750: PE15_time_delay_max - t50_end_ - 250000.0*t_50_map_15 >= -250000.0\n", + "_C123751: PE15_time_delay_min - t50_start + 250000.0*t_50_map_15 <= 250000.0\n", + "_C123752: PE15_time_delay_max - t51_end_ - 250000.0*t_51_map_15 >= -250000.0\n", + "_C123753: PE15_time_delay_min - t51_start + 250000.0*t_51_map_15 <= 250000.0\n", + "_C123754: PE15_time_delay_max - t52_end_ - 250000.0*t_52_map_15 >= -250000.0\n", + "_C123755: PE15_time_delay_min - t52_start + 250000.0*t_52_map_15 <= 250000.0\n", + "_C123756: PE15_time_delay_max - t53_end_ - 250000.0*t_53_map_15 >= -250000.0\n", + "_C123757: PE15_time_delay_min - t53_start + 250000.0*t_53_map_15 <= 250000.0\n", + "_C123758: PE15_time_delay_max - t54_end_ - 250000.0*t_54_map_15 >= -250000.0\n", + "_C123759: PE15_time_delay_min - t54_start + 250000.0*t_54_map_15 <= 250000.0\n", + "_C123760: PE15_time_delay_max - t55_end_ - 250000.0*t_55_map_15 >= -250000.0\n", + "_C123761: PE15_time_delay_min - t55_start + 250000.0*t_55_map_15 <= 250000.0\n", + "_C123762: PE15_time_delay_max - t56_end_ - 250000.0*t_56_map_15 >= -250000.0\n", + "_C123763: PE15_time_delay_min - t56_start + 250000.0*t_56_map_15 <= 250000.0\n", + "_C123764: PE15_time_delay_max - t57_end_ - 250000.0*t_57_map_15 >= -250000.0\n", + "_C123765: PE15_time_delay_min - t57_start + 250000.0*t_57_map_15 <= 250000.0\n", + "_C123766: PE15_time_delay_max - t58_end_ - 250000.0*t_58_map_15 >= -250000.0\n", + "_C123767: PE15_time_delay_min - t58_start + 250000.0*t_58_map_15 <= 250000.0\n", + "_C123768: PE15_time_delay_max - t59_end_ - 250000.0*t_59_map_15 >= -250000.0\n", + "_C123769: PE15_time_delay_min - t59_start + 250000.0*t_59_map_15 <= 250000.0\n", + "_C123770: PE15_time_delay_max - t60_end_ - 250000.0*t_60_map_15 >= -250000.0\n", + "_C123771: PE15_time_delay_min - t60_start + 250000.0*t_60_map_15 <= 250000.0\n", + "_C123772: PE15_time_delay_max - t61_end_ - 250000.0*t_61_map_15 >= -250000.0\n", + "_C123773: PE15_time_delay_min - t61_start + 250000.0*t_61_map_15 <= 250000.0\n", + "_C123774: PE15_time_delay_max - t62_end_ - 250000.0*t_62_map_15 >= -250000.0\n", + "_C123775: PE15_time_delay_min - t62_start + 250000.0*t_62_map_15 <= 250000.0\n", + "_C123776: PE15_time_delay_max - t63_end_ - 250000.0*t_63_map_15 >= -250000.0\n", + "_C123777: PE15_time_delay_min - t63_start + 250000.0*t_63_map_15 <= 250000.0\n", + "_C123778: PE15_time_delay_max - t64_end_ - 250000.0*t_64_map_15 >= -250000.0\n", + "_C123779: PE15_time_delay_min - t64_start + 250000.0*t_64_map_15 <= 250000.0\n", + "_C123780: PE15_time_delay_max - t65_end_ - 250000.0*t_65_map_15 >= -250000.0\n", + "_C123781: PE15_time_delay_min - t65_start + 250000.0*t_65_map_15 <= 250000.0\n", + "_C123782: PE15_time_delay_max - t66_end_ - 250000.0*t_66_map_15 >= -250000.0\n", + "_C123783: PE15_time_delay_min - t66_start + 250000.0*t_66_map_15 <= 250000.0\n", + "_C123784: PE15_time_delay_max - t67_end_ - 250000.0*t_67_map_15 >= -250000.0\n", + "_C123785: PE15_time_delay_min - t67_start + 250000.0*t_67_map_15 <= 250000.0\n", + "_C123786: PE15_time_delay_max - t68_end_ - 250000.0*t_68_map_15 >= -250000.0\n", + "_C123787: PE15_time_delay_min - t68_start + 250000.0*t_68_map_15 <= 250000.0\n", + "_C123788: PE15_time_delay_max - t69_end_ - 250000.0*t_69_map_15 >= -250000.0\n", + "_C123789: PE15_time_delay_min - t69_start + 250000.0*t_69_map_15 <= 250000.0\n", + "_C123790: -PE15_time_delay_max + PE15_time_delay_min + PE15_total_time_delay = 0\n", + "_C123791: -PE15_total_time_delay + max_router_delay >= 0\n", + "Debug: Found max_router_delay variable with value 238.0\n", + "Debug: Found mapping variable t_0_map_0 with value 1.0\n", + "Debug: Split parts: ['t', '0', 'map', '0']\n", + "Debug: Mapping task 0 to PE 0\n", + "Debug: reverse_mapping[0] now [0]\n", + "Debug: Found mapping variable t_10_map_1 with value 1.0\n", + "Debug: Split parts: ['t', '10', 'map', '1']\n", + "Debug: Mapping task 10 to PE 1\n", + "Debug: reverse_mapping[1] now [10]\n", + "Debug: Found mapping variable t_11_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '11', 'map', '2']\n", + "Debug: Mapping task 11 to PE 2\n", + "Debug: reverse_mapping[2] now [11]\n", + "Debug: Found mapping variable t_12_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '12', 'map', '2']\n", + "Debug: Mapping task 12 to PE 2\n", + "Debug: reverse_mapping[2] now [11, 12]\n", + "Debug: Found mapping variable t_13_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '13', 'map', '2']\n", + "Debug: Mapping task 13 to PE 2\n", + "Debug: reverse_mapping[2] now [11, 12, 13]\n", + "Debug: Found mapping variable t_14_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '14', 'map', '2']\n", + "Debug: Mapping task 14 to PE 2\n", + "Debug: reverse_mapping[2] now [11, 12, 13, 14]\n", + "Debug: Found mapping variable t_15_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '15', 'map', '2']\n", + "Debug: Mapping task 15 to PE 2\n", + "Debug: reverse_mapping[2] now [11, 12, 13, 14, 15]\n", + "Debug: Found mapping variable t_16_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '16', 'map', '2']\n", + "Debug: Mapping task 16 to PE 2\n", + "Debug: reverse_mapping[2] now [11, 12, 13, 14, 15, 16]\n", + "Debug: Found mapping variable t_17_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '17', 'map', '3']\n", + "Debug: Mapping task 17 to PE 3\n", + "Debug: reverse_mapping[3] now [17]\n", + "Debug: Found mapping variable t_18_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '18', 'map', '3']\n", + "Debug: Mapping task 18 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18]\n", + "Debug: Found mapping variable t_19_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '19', 'map', '3']\n", + "Debug: Mapping task 19 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19]\n", + "Debug: Found mapping variable t_1_map_0 with value 1.0\n", + "Debug: Split parts: ['t', '1', 'map', '0']\n", + "Debug: Mapping task 1 to PE 0\n", + "Debug: reverse_mapping[0] now [0, 1]\n", + "Debug: Found mapping variable t_20_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '20', 'map', '3']\n", + "Debug: Mapping task 20 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20]\n", + "Debug: Found mapping variable t_21_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '21', 'map', '3']\n", + "Debug: Mapping task 21 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21]\n", + "Debug: Found mapping variable t_22_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '22', 'map', '3']\n", + "Debug: Mapping task 22 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22]\n", + "Debug: Found mapping variable t_23_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '23', 'map', '3']\n", + "Debug: Mapping task 23 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23]\n", + "Debug: Found mapping variable t_24_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '24', 'map', '3']\n", + "Debug: Mapping task 24 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24]\n", + "Debug: Found mapping variable t_25_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '25', 'map', '3']\n", + "Debug: Mapping task 25 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25]\n", + "Debug: Found mapping variable t_26_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '26', 'map', '3']\n", + "Debug: Mapping task 26 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26]\n", + "Debug: Found mapping variable t_27_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '27', 'map', '3']\n", + "Debug: Mapping task 27 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]\n", + "Debug: Found mapping variable t_28_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '28', 'map', '3']\n", + "Debug: Mapping task 28 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]\n", + "Debug: Found mapping variable t_29_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '29', 'map', '3']\n", + "Debug: Mapping task 29 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29]\n", + "Debug: Found mapping variable t_2_map_0 with value 1.0\n", + "Debug: Split parts: ['t', '2', 'map', '0']\n", + "Debug: Mapping task 2 to PE 0\n", + "Debug: reverse_mapping[0] now [0, 1, 2]\n", + "Debug: Found mapping variable t_30_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '30', 'map', '3']\n", + "Debug: Mapping task 30 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]\n", + "Debug: Found mapping variable t_31_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '31', 'map', '3']\n", + "Debug: Mapping task 31 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]\n", + "Debug: Found mapping variable t_32_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '32', 'map', '3']\n", + "Debug: Mapping task 32 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32]\n", + "Debug: Found mapping variable t_33_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '33', 'map', '3']\n", + "Debug: Mapping task 33 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33]\n", + "Debug: Found mapping variable t_34_map_3 with value 1.0\n", + "Debug: Split parts: ['t', '34', 'map', '3']\n", + "Debug: Mapping task 34 to PE 3\n", + "Debug: reverse_mapping[3] now [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34]\n", + "Debug: Found mapping variable t_35_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '35', 'map', '4']\n", + "Debug: Mapping task 35 to PE 4\n", + "Debug: reverse_mapping[4] now [35]\n", + "Debug: Found mapping variable t_36_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '36', 'map', '4']\n", + "Debug: Mapping task 36 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36]\n", + "Debug: Found mapping variable t_37_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '37', 'map', '4']\n", + "Debug: Mapping task 37 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37]\n", + "Debug: Found mapping variable t_38_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '38', 'map', '4']\n", + "Debug: Mapping task 38 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38]\n", + "Debug: Found mapping variable t_39_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '39', 'map', '4']\n", + "Debug: Mapping task 39 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39]\n", + "Debug: Found mapping variable t_3_map_0 with value 1.0\n", + "Debug: Split parts: ['t', '3', 'map', '0']\n", + "Debug: Mapping task 3 to PE 0\n", + "Debug: reverse_mapping[0] now [0, 1, 2, 3]\n", + "Debug: Found mapping variable t_40_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '40', 'map', '4']\n", + "Debug: Mapping task 40 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40]\n", + "Debug: Found mapping variable t_41_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '41', 'map', '4']\n", + "Debug: Mapping task 41 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41]\n", + "Debug: Found mapping variable t_42_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '42', 'map', '4']\n", + "Debug: Mapping task 42 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42]\n", + "Debug: Found mapping variable t_43_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '43', 'map', '4']\n", + "Debug: Mapping task 43 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43]\n", + "Debug: Found mapping variable t_44_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '44', 'map', '4']\n", + "Debug: Mapping task 44 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44]\n", + "Debug: Found mapping variable t_45_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '45', 'map', '4']\n", + "Debug: Mapping task 45 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]\n", + "Debug: Found mapping variable t_46_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '46', 'map', '4']\n", + "Debug: Mapping task 46 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]\n", + "Debug: Found mapping variable t_47_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '47', 'map', '4']\n", + "Debug: Mapping task 47 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47]\n", + "Debug: Found mapping variable t_48_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '48', 'map', '4']\n", + "Debug: Mapping task 48 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48]\n", + "Debug: Found mapping variable t_49_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '49', 'map', '4']\n", + "Debug: Mapping task 49 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49]\n", + "Debug: Found mapping variable t_4_map_5 with value 1.0\n", + "Debug: Split parts: ['t', '4', 'map', '5']\n", + "Debug: Mapping task 4 to PE 5\n", + "Debug: reverse_mapping[5] now [4]\n", + "Debug: Found mapping variable t_50_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '50', 'map', '4']\n", + "Debug: Mapping task 50 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]\n", + "Debug: Found mapping variable t_51_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '51', 'map', '4']\n", + "Debug: Mapping task 51 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51]\n", + "Debug: Found mapping variable t_52_map_4 with value 1.0\n", + "Debug: Split parts: ['t', '52', 'map', '4']\n", + "Debug: Mapping task 52 to PE 4\n", + "Debug: reverse_mapping[4] now [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52]\n", + "Debug: Found mapping variable t_53_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '53', 'map', '6']\n", + "Debug: Mapping task 53 to PE 6\n", + "Debug: reverse_mapping[6] now [53]\n", + "Debug: Found mapping variable t_54_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '54', 'map', '6']\n", + "Debug: Mapping task 54 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54]\n", + "Debug: Found mapping variable t_55_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '55', 'map', '6']\n", + "Debug: Mapping task 55 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55]\n", + "Debug: Found mapping variable t_56_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '56', 'map', '6']\n", + "Debug: Mapping task 56 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56]\n", + "Debug: Found mapping variable t_57_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '57', 'map', '6']\n", + "Debug: Mapping task 57 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57]\n", + "Debug: Found mapping variable t_58_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '58', 'map', '6']\n", + "Debug: Mapping task 58 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58]\n", + "Debug: Found mapping variable t_59_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '59', 'map', '6']\n", + "Debug: Mapping task 59 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59]\n", + "Debug: Found mapping variable t_5_map_5 with value 1.0\n", + "Debug: Split parts: ['t', '5', 'map', '5']\n", + "Debug: Mapping task 5 to PE 5\n", + "Debug: reverse_mapping[5] now [4, 5]\n", + "Debug: Found mapping variable t_60_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '60', 'map', '6']\n", + "Debug: Mapping task 60 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60]\n", + "Debug: Found mapping variable t_61_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '61', 'map', '6']\n", + "Debug: Mapping task 61 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60, 61]\n", + "Debug: Found mapping variable t_62_map_7 with value 1.0\n", + "Debug: Split parts: ['t', '62', 'map', '7']\n", + "Debug: Mapping task 62 to PE 7\n", + "Debug: reverse_mapping[7] now [62]\n", + "Debug: Found mapping variable t_63_map_7 with value 1.0\n", + "Debug: Split parts: ['t', '63', 'map', '7']\n", + "Debug: Mapping task 63 to PE 7\n", + "Debug: reverse_mapping[7] now [62, 63]\n", + "Debug: Found mapping variable t_64_map_7 with value 1.0\n", + "Debug: Split parts: ['t', '64', 'map', '7']\n", + "Debug: Mapping task 64 to PE 7\n", + "Debug: reverse_mapping[7] now [62, 63, 64]\n", + "Debug: Found mapping variable t_65_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '65', 'map', '6']\n", + "Debug: Mapping task 65 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60, 61, 65]\n", + "Debug: Found mapping variable t_66_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '66', 'map', '6']\n", + "Debug: Mapping task 66 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66]\n", + "Debug: Found mapping variable t_67_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '67', 'map', '6']\n", + "Debug: Mapping task 67 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67]\n", + "Debug: Found mapping variable t_68_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '68', 'map', '6']\n", + "Debug: Mapping task 68 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68]\n", + "Debug: Found mapping variable t_69_map_6 with value 1.0\n", + "Debug: Split parts: ['t', '69', 'map', '6']\n", + "Debug: Mapping task 69 to PE 6\n", + "Debug: reverse_mapping[6] now [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69]\n", + "Debug: Found mapping variable t_6_map_5 with value 1.0\n", + "Debug: Split parts: ['t', '6', 'map', '5']\n", + "Debug: Mapping task 6 to PE 5\n", + "Debug: reverse_mapping[5] now [4, 5, 6]\n", + "Debug: Found mapping variable t_7_map_2 with value 1.0\n", + "Debug: Split parts: ['t', '7', 'map', '2']\n", + "Debug: Mapping task 7 to PE 2\n", + "Debug: reverse_mapping[2] now [11, 12, 13, 14, 15, 16, 7]\n", + "Debug: Found mapping variable t_8_map_1 with value 1.0\n", + "Debug: Split parts: ['t', '8', 'map', '1']\n", + "Debug: Mapping task 8 to PE 1\n", + "Debug: reverse_mapping[1] now [10, 8]\n", + "Debug: Found mapping variable t_9_map_1 with value 1.0\n", + "Debug: Split parts: ['t', '9', 'map', '1']\n", + "Debug: Mapping task 9 to PE 1\n", + "Debug: reverse_mapping[1] now [10, 8, 9]\n", + "Reverse mapping: {0: [0, 1, 2, 3], 1: [10, 8, 9], 2: [11, 12, 13, 14, 15, 16, 7], 3: [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], 4: [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], 5: [4, 5, 6], 6: [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69], 7: [62, 63, 64]}\n", + "0 [0, 1, 2, 3]\n", + "1 [10, 8, 9]\n", + "2 [11, 12, 13, 14, 15, 16, 7]\n", + "3 [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34]\n", + "4 [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52]\n", + "5 [4, 5, 6]\n", + "6 [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69]\n", + "7 [62, 63, 64]\n", + "Combined mapping: {0: ([0, 1, 2, 3], 1191), 10: ([10, 8, 9], 274), 11: ([11, 12, 13, 14, 15, 16, 7], 1924), 17: ([17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], 2554), 35: ([35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], 7716), 4: ([4, 5, 6], 265), 53: ([53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69], 12630), 62: ([62, 63, 64], 3028)}\n", + "Debug: Checking end time for pe=0, task=0, v.name=t0_end_, v.varValue=4.0, current delay_max=0\n", + "Debug: Updated delay_max[0] to 4.0\n", + "Debug: Checking start time for pe=0, task=0, v.name=t0_start, v.varValue=0.0, current delay_min=inf\n", + "Debug: Updated delay_min[0] to 0.0\n", + "Debug: found t_comp pe=0, task=0, v.name=t_comp_0, v.varValue=4.0 new total comp=4\n", + "Debug: Checking end time for pe=0, task=1, v.name=t1_end_, v.varValue=38.0, current delay_max=4.0\n", + "Debug: Updated delay_max[0] to 38.0\n", + "Debug: Checking start time for pe=0, task=1, v.name=t1_start, v.varValue=4.0, current delay_min=0.0\n", + "Debug: found t_comp pe=0, task=1, v.name=t_comp_1, v.varValue=34.0 new total comp=38\n", + "Debug: Checking end time for pe=0, task=2, v.name=t2_end_, v.varValue=105.0, current delay_max=38.0\n", + "Debug: Updated delay_max[0] to 105.0\n", + "Debug: Checking start time for pe=0, task=2, v.name=t2_start, v.varValue=38.0, current delay_min=0.0\n", + "Debug: found t_comp pe=0, task=2, v.name=t_comp_2, v.varValue=67.0 new total comp=105\n", + "Debug: Checking end time for pe=0, task=3, v.name=t3_end_, v.varValue=120.0, current delay_max=105.0\n", + "Debug: Updated delay_max[0] to 120.0\n", + "Debug: Checking start time for pe=0, task=3, v.name=t3_start, v.varValue=105.0, current delay_min=0.0\n", + "Debug: found t_comp pe=0, task=3, v.name=t_comp_3, v.varValue=1.0 new total comp=106\n", + "Debug: Checking end time for pe=1, task=10, v.name=t10_end_, v.varValue=231.0, current delay_max=0\n", + "Debug: Updated delay_max[1] to 231.0\n", + "Debug: Checking start time for pe=1, task=10, v.name=t10_start, v.varValue=191.0, current delay_min=inf\n", + "Debug: Updated delay_min[1] to 191.0\n", + "Debug: found t_comp pe=1, task=10, v.name=t_comp_10, v.varValue=26.0 new total comp=26\n", + "Debug: Checking end time for pe=1, task=8, v.name=t8_end_, v.varValue=165.0, current delay_max=231.0\n", + "Debug: Checking start time for pe=1, task=8, v.name=t8_start, v.varValue=155.0, current delay_min=191.0\n", + "Debug: Updated delay_min[1] to 155.0\n", + "Debug: found t_comp pe=1, task=8, v.name=t_comp_8, v.varValue=10.0 new total comp=36\n", + "Debug: Checking end time for pe=1, task=9, v.name=t9_end_, v.varValue=191.0, current delay_max=231.0\n", + "Debug: Checking start time for pe=1, task=9, v.name=t9_start, v.varValue=165.0, current delay_min=155.0\n", + "Debug: found t_comp pe=1, task=9, v.name=t_comp_9, v.varValue=26.0 new total comp=62\n", + "Debug: Checking end time for pe=2, task=11, v.name=t11_end_, v.varValue=278.0, current delay_max=0\n", + "Debug: Updated delay_max[2] to 278.0\n", + "Debug: Checking start time for pe=2, task=11, v.name=t11_start, v.varValue=231.0, current delay_min=inf\n", + "Debug: Updated delay_min[2] to 231.0\n", + "Debug: found t_comp pe=2, task=11, v.name=t_comp_11, v.varValue=47.0 new total comp=47\n", + "Debug: Checking end time for pe=2, task=12, v.name=t12_end_, v.varValue=278.0, current delay_max=278.0\n", + "Debug: Checking start time for pe=2, task=12, v.name=t12_start, v.varValue=278.0, current delay_min=231.0\n", + "Debug: found t_comp pe=2, task=12, v.name=t_comp_12, v.varValue=0.0 new total comp=47\n", + "Debug: Checking end time for pe=2, task=13, v.name=t13_end_, v.varValue=347.0, current delay_max=278.0\n", + "Debug: Updated delay_max[2] to 347.0\n", + "Debug: Checking start time for pe=2, task=13, v.name=t13_start, v.varValue=278.0, current delay_min=231.0\n", + "Debug: found t_comp pe=2, task=13, v.name=t_comp_13, v.varValue=69.0 new total comp=116\n", + "Debug: Checking end time for pe=2, task=14, v.name=t14_end_, v.varValue=348.0, current delay_max=347.0\n", + "Debug: Updated delay_max[2] to 348.0\n", + "Debug: Checking start time for pe=2, task=14, v.name=t14_start, v.varValue=347.0, current delay_min=231.0\n", + "Debug: found t_comp pe=2, task=14, v.name=t_comp_14, v.varValue=1.0 new total comp=117\n", + "Debug: Checking end time for pe=2, task=15, v.name=t15_end_, v.varValue=348.0, current delay_max=348.0\n", + "Debug: Checking start time for pe=2, task=15, v.name=t15_start, v.varValue=348.0, current delay_min=231.0\n", + "Debug: found t_comp pe=2, task=15, v.name=t_comp_15, v.varValue=0.0 new total comp=117\n", + "Debug: Checking end time for pe=2, task=16, v.name=t16_end_, v.varValue=361.0, current delay_max=348.0\n", + "Debug: Updated delay_max[2] to 361.0\n", + "Debug: Checking start time for pe=2, task=16, v.name=t16_start, v.varValue=348.0, current delay_min=231.0\n", + "Debug: found t_comp pe=2, task=16, v.name=t_comp_16, v.varValue=8.0 new total comp=125\n", + "Debug: Checking end time for pe=2, task=7, v.name=t7_end_, v.varValue=226.0, current delay_max=361.0\n", + "Debug: Checking start time for pe=2, task=7, v.name=t7_start, v.varValue=179.0, current delay_min=231.0\n", + "Debug: Updated delay_min[2] to 179.0\n", + "Debug: found t_comp pe=2, task=7, v.name=t_comp_7, v.varValue=47.0 new total comp=172\n", + "Debug: Checking end time for pe=3, task=17, v.name=t17_end_, v.varValue=361.0, current delay_max=0\n", + "Debug: Updated delay_max[3] to 361.0\n", + "Debug: Checking start time for pe=3, task=17, v.name=t17_start, v.varValue=355.0, current delay_min=inf\n", + "Debug: Updated delay_min[3] to 355.0\n", + "Debug: found t_comp pe=3, task=17, v.name=t_comp_17, v.varValue=6.0 new total comp=6\n", + "Debug: Checking end time for pe=3, task=18, v.name=t18_end_, v.varValue=411.0, current delay_max=361.0\n", + "Debug: Updated delay_max[3] to 411.0\n", + "Debug: Checking start time for pe=3, task=18, v.name=t18_start, v.varValue=399.0, current delay_min=355.0\n", + "Debug: found t_comp pe=3, task=18, v.name=t_comp_18, v.varValue=12.0 new total comp=18\n", + "Debug: Checking end time for pe=3, task=19, v.name=t19_end_, v.varValue=355.0, current delay_max=411.0\n", + "Debug: Checking start time for pe=3, task=19, v.name=t19_start, v.varValue=349.0, current delay_min=355.0\n", + "Debug: Updated delay_min[3] to 349.0\n", + "Debug: found t_comp pe=3, task=19, v.name=t_comp_19, v.varValue=6.0 new total comp=24\n", + "Debug: Checking end time for pe=3, task=20, v.name=t20_end_, v.varValue=381.0, current delay_max=411.0\n", + "Debug: Checking start time for pe=3, task=20, v.name=t20_start, v.varValue=369.0, current delay_min=349.0\n", + "Debug: found t_comp pe=3, task=20, v.name=t_comp_20, v.varValue=12.0 new total comp=36\n", + "Debug: Checking end time for pe=3, task=21, v.name=t21_end_, v.varValue=399.0, current delay_max=411.0\n", + "Debug: Checking start time for pe=3, task=21, v.name=t21_start, v.varValue=381.0, current delay_min=349.0\n", + "Debug: found t_comp pe=3, task=21, v.name=t_comp_21, v.varValue=18.0 new total comp=54\n", + "Debug: Checking end time for pe=3, task=22, v.name=t22_end_, v.varValue=349.0, current delay_max=411.0\n", + "Debug: Checking start time for pe=3, task=22, v.name=t22_start, v.varValue=348.0, current delay_min=349.0\n", + "Debug: Updated delay_min[3] to 348.0\n", + "Debug: found t_comp pe=3, task=22, v.name=t_comp_22, v.varValue=1.0 new total comp=55\n", + "Debug: Checking end time for pe=3, task=23, v.name=t23_end_, v.varValue=369.0, current delay_max=411.0\n", + "Debug: Checking start time for pe=3, task=23, v.name=t23_start, v.varValue=361.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=23, v.name=t_comp_23, v.varValue=8.0 new total comp=63\n", + "Debug: Checking end time for pe=3, task=24, v.name=t24_end_, v.varValue=411.0, current delay_max=411.0\n", + "Debug: Checking start time for pe=3, task=24, v.name=t24_start, v.varValue=411.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=24, v.name=t_comp_24, v.varValue=0.0 new total comp=63\n", + "Debug: Checking end time for pe=3, task=25, v.name=t25_end_, v.varValue=437.0, current delay_max=411.0\n", + "Debug: Updated delay_max[3] to 437.0\n", + "Debug: Checking start time for pe=3, task=25, v.name=t25_start, v.varValue=429.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=25, v.name=t_comp_25, v.varValue=8.0 new total comp=71\n", + "Debug: Checking end time for pe=3, task=26, v.name=t26_end_, v.varValue=444.0, current delay_max=437.0\n", + "Debug: Updated delay_max[3] to 444.0\n", + "Debug: Checking start time for pe=3, task=26, v.name=t26_start, v.varValue=438.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=26, v.name=t_comp_26, v.varValue=6.0 new total comp=77\n", + "Debug: Checking end time for pe=3, task=27, v.name=t27_end_, v.varValue=456.0, current delay_max=444.0\n", + "Debug: Updated delay_max[3] to 456.0\n", + "Debug: Checking start time for pe=3, task=27, v.name=t27_start, v.varValue=444.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=27, v.name=t_comp_27, v.varValue=12.0 new total comp=89\n", + "Debug: Checking end time for pe=3, task=28, v.name=t28_end_, v.varValue=417.0, current delay_max=456.0\n", + "Debug: Checking start time for pe=3, task=28, v.name=t28_start, v.varValue=411.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=28, v.name=t_comp_28, v.varValue=6.0 new total comp=95\n", + "Debug: Checking end time for pe=3, task=29, v.name=t29_end_, v.varValue=429.0, current delay_max=456.0\n", + "Debug: Checking start time for pe=3, task=29, v.name=t29_start, v.varValue=417.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=29, v.name=t_comp_29, v.varValue=12.0 new total comp=107\n", + "Debug: Checking end time for pe=3, task=30, v.name=t30_end_, v.varValue=482.0, current delay_max=456.0\n", + "Debug: Updated delay_max[3] to 482.0\n", + "Debug: Checking start time for pe=3, task=30, v.name=t30_start, v.varValue=464.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=30, v.name=t_comp_30, v.varValue=18.0 new total comp=125\n", + "Debug: Checking end time for pe=3, task=31, v.name=t31_end_, v.varValue=438.0, current delay_max=482.0\n", + "Debug: Checking start time for pe=3, task=31, v.name=t31_start, v.varValue=437.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=31, v.name=t_comp_31, v.varValue=1.0 new total comp=126\n", + "Debug: Checking end time for pe=3, task=32, v.name=t32_end_, v.varValue=464.0, current delay_max=482.0\n", + "Debug: Checking start time for pe=3, task=32, v.name=t32_start, v.varValue=456.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=32, v.name=t_comp_32, v.varValue=8.0 new total comp=134\n", + "Debug: Checking end time for pe=3, task=33, v.name=t33_end_, v.varValue=482.0, current delay_max=482.0\n", + "Debug: Checking start time for pe=3, task=33, v.name=t33_start, v.varValue=482.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=33, v.name=t_comp_33, v.varValue=0.0 new total comp=134\n", + "Debug: Checking end time for pe=3, task=34, v.name=t34_end_, v.varValue=495.0, current delay_max=482.0\n", + "Debug: Updated delay_max[3] to 495.0\n", + "Debug: Checking start time for pe=3, task=34, v.name=t34_start, v.varValue=482.0, current delay_min=348.0\n", + "Debug: found t_comp pe=3, task=34, v.name=t_comp_34, v.varValue=8.0 new total comp=142\n", + "Debug: Checking end time for pe=4, task=35, v.name=t35_end_, v.varValue=524.0, current delay_max=0\n", + "Debug: Updated delay_max[4] to 524.0\n", + "Debug: Checking start time for pe=4, task=35, v.name=t35_start, v.varValue=518.0, current delay_min=inf\n", + "Debug: Updated delay_min[4] to 518.0\n", + "Debug: found t_comp pe=4, task=35, v.name=t_comp_35, v.varValue=6.0 new total comp=6\n", + "Debug: Checking end time for pe=4, task=36, v.name=t36_end_, v.varValue=545.0, current delay_max=524.0\n", + "Debug: Updated delay_max[4] to 545.0\n", + "Debug: Checking start time for pe=4, task=36, v.name=t36_start, v.varValue=533.0, current delay_min=518.0\n", + "Debug: found t_comp pe=4, task=36, v.name=t_comp_36, v.varValue=12.0 new total comp=18\n", + "Debug: Checking end time for pe=4, task=37, v.name=t37_end_, v.varValue=488.0, current delay_max=545.0\n", + "Debug: Checking start time for pe=4, task=37, v.name=t37_start, v.varValue=482.0, current delay_min=518.0\n", + "Debug: Updated delay_min[4] to 482.0\n", + "Debug: found t_comp pe=4, task=37, v.name=t_comp_37, v.varValue=6.0 new total comp=24\n", + "Debug: Checking end time for pe=4, task=38, v.name=t38_end_, v.varValue=500.0, current delay_max=545.0\n", + "Debug: Checking start time for pe=4, task=38, v.name=t38_start, v.varValue=488.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=38, v.name=t_comp_38, v.varValue=12.0 new total comp=36\n", + "Debug: Checking end time for pe=4, task=39, v.name=t39_end_, v.varValue=518.0, current delay_max=545.0\n", + "Debug: Checking start time for pe=4, task=39, v.name=t39_start, v.varValue=500.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=39, v.name=t_comp_39, v.varValue=18.0 new total comp=54\n", + "Debug: Checking end time for pe=4, task=40, v.name=t40_end_, v.varValue=525.0, current delay_max=545.0\n", + "Debug: Checking start time for pe=4, task=40, v.name=t40_start, v.varValue=524.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=40, v.name=t_comp_40, v.varValue=1.0 new total comp=55\n", + "Debug: Checking end time for pe=4, task=41, v.name=t41_end_, v.varValue=533.0, current delay_max=545.0\n", + "Debug: Checking start time for pe=4, task=41, v.name=t41_start, v.varValue=525.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=41, v.name=t_comp_41, v.varValue=8.0 new total comp=63\n", + "Debug: Checking end time for pe=4, task=42, v.name=t42_end_, v.varValue=545.0, current delay_max=545.0\n", + "Debug: Checking start time for pe=4, task=42, v.name=t42_start, v.varValue=545.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=42, v.name=t_comp_42, v.varValue=0.0 new total comp=63\n", + "Debug: Checking end time for pe=4, task=43, v.name=t43_end_, v.varValue=553.0, current delay_max=545.0\n", + "Debug: Updated delay_max[4] to 553.0\n", + "Debug: Checking start time for pe=4, task=43, v.name=t43_start, v.varValue=545.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=43, v.name=t_comp_43, v.varValue=8.0 new total comp=71\n", + "Debug: Checking end time for pe=4, task=44, v.name=t44_end_, v.varValue=559.0, current delay_max=553.0\n", + "Debug: Updated delay_max[4] to 559.0\n", + "Debug: Checking start time for pe=4, task=44, v.name=t44_start, v.varValue=553.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=44, v.name=t_comp_44, v.varValue=6.0 new total comp=77\n", + "Debug: Checking end time for pe=4, task=45, v.name=t45_end_, v.varValue=608.0, current delay_max=559.0\n", + "Debug: Updated delay_max[4] to 608.0\n", + "Debug: Checking start time for pe=4, task=45, v.name=t45_start, v.varValue=596.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=45, v.name=t_comp_45, v.varValue=12.0 new total comp=89\n", + "Debug: Checking end time for pe=4, task=46, v.name=t46_end_, v.varValue=565.0, current delay_max=608.0\n", + "Debug: Checking start time for pe=4, task=46, v.name=t46_start, v.varValue=559.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=46, v.name=t_comp_46, v.varValue=6.0 new total comp=95\n", + "Debug: Checking end time for pe=4, task=47, v.name=t47_end_, v.varValue=577.0, current delay_max=608.0\n", + "Debug: Checking start time for pe=4, task=47, v.name=t47_start, v.varValue=565.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=47, v.name=t_comp_47, v.varValue=12.0 new total comp=107\n", + "Debug: Checking end time for pe=4, task=48, v.name=t48_end_, v.varValue=596.0, current delay_max=608.0\n", + "Debug: Checking start time for pe=4, task=48, v.name=t48_start, v.varValue=578.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=48, v.name=t_comp_48, v.varValue=18.0 new total comp=125\n", + "Debug: Checking end time for pe=4, task=49, v.name=t49_end_, v.varValue=578.0, current delay_max=608.0\n", + "Debug: Checking start time for pe=4, task=49, v.name=t49_start, v.varValue=577.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=49, v.name=t_comp_49, v.varValue=1.0 new total comp=126\n", + "Debug: Checking end time for pe=4, task=50, v.name=t50_end_, v.varValue=616.0, current delay_max=608.0\n", + "Debug: Updated delay_max[4] to 616.0\n", + "Debug: Checking start time for pe=4, task=50, v.name=t50_start, v.varValue=608.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=50, v.name=t_comp_50, v.varValue=8.0 new total comp=134\n", + "Debug: Checking end time for pe=4, task=51, v.name=t51_end_, v.varValue=616.0, current delay_max=616.0\n", + "Debug: Checking start time for pe=4, task=51, v.name=t51_start, v.varValue=616.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=51, v.name=t_comp_51, v.varValue=0.0 new total comp=134\n", + "Debug: Checking end time for pe=4, task=52, v.name=t52_end_, v.varValue=686.0, current delay_max=616.0\n", + "Debug: Updated delay_max[4] to 686.0\n", + "Debug: Checking start time for pe=4, task=52, v.name=t52_start, v.varValue=616.0, current delay_min=482.0\n", + "Debug: found t_comp pe=4, task=52, v.name=t_comp_52, v.varValue=65.0 new total comp=199\n", + "Debug: Checking end time for pe=5, task=4, v.name=t4_end_, v.varValue=155.0, current delay_max=0\n", + "Debug: Updated delay_max[5] to 155.0\n", + "Debug: Checking start time for pe=5, task=4, v.name=t4_start, v.varValue=105.0, current delay_min=inf\n", + "Debug: Updated delay_min[5] to 105.0\n", + "Debug: found t_comp pe=5, task=4, v.name=t_comp_4, v.varValue=50.0 new total comp=50\n", + "Debug: Checking end time for pe=5, task=5, v.name=t5_end_, v.varValue=155.0, current delay_max=155.0\n", + "Debug: Checking start time for pe=5, task=5, v.name=t5_start, v.varValue=155.0, current delay_min=105.0\n", + "Debug: found t_comp pe=5, task=5, v.name=t_comp_5, v.varValue=0.0 new total comp=50\n", + "Debug: Checking end time for pe=5, task=6, v.name=t6_end_, v.varValue=179.0, current delay_max=155.0\n", + "Debug: Updated delay_max[5] to 179.0\n", + "Debug: Checking start time for pe=5, task=6, v.name=t6_start, v.varValue=155.0, current delay_min=105.0\n", + "Debug: found t_comp pe=5, task=6, v.name=t_comp_6, v.varValue=10.0 new total comp=60\n", + "Debug: Checking end time for pe=6, task=53, v.name=t53_end_, v.varValue=632.0, current delay_max=0\n", + "Debug: Updated delay_max[6] to 632.0\n", + "Debug: Checking start time for pe=6, task=53, v.name=t53_start, v.varValue=616.0, current delay_min=inf\n", + "Debug: Updated delay_min[6] to 616.0\n", + "Debug: found t_comp pe=6, task=53, v.name=t_comp_53, v.varValue=16.0 new total comp=16\n", + "Debug: Checking end time for pe=6, task=54, v.name=t54_end_, v.varValue=712.0, current delay_max=632.0\n", + "Debug: Updated delay_max[6] to 712.0\n", + "Debug: Checking start time for pe=6, task=54, v.name=t54_start, v.varValue=632.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=54, v.name=t_comp_54, v.varValue=80.0 new total comp=96\n", + "Debug: Checking end time for pe=6, task=55, v.name=t55_end_, v.varValue=737.0, current delay_max=712.0\n", + "Debug: Updated delay_max[6] to 737.0\n", + "Debug: Checking start time for pe=6, task=55, v.name=t55_start, v.varValue=712.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=55, v.name=t_comp_55, v.varValue=25.0 new total comp=121\n", + "Debug: Checking end time for pe=6, task=56, v.name=t56_end_, v.varValue=617.0, current delay_max=737.0\n", + "Debug: Checking start time for pe=6, task=56, v.name=t56_start, v.varValue=616.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=56, v.name=t_comp_56, v.varValue=1.0 new total comp=122\n", + "Debug: Checking end time for pe=6, task=57, v.name=t57_end_, v.varValue=737.0, current delay_max=737.0\n", + "Debug: Checking start time for pe=6, task=57, v.name=t57_start, v.varValue=737.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=57, v.name=t_comp_57, v.varValue=0.0 new total comp=122\n", + "Debug: Checking end time for pe=6, task=58, v.name=t58_end_, v.varValue=757.0, current delay_max=737.0\n", + "Debug: Updated delay_max[6] to 757.0\n", + "Debug: Checking start time for pe=6, task=58, v.name=t58_start, v.varValue=737.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=58, v.name=t_comp_58, v.varValue=20.0 new total comp=142\n", + "Debug: Checking end time for pe=6, task=59, v.name=t59_end_, v.varValue=767.0, current delay_max=757.0\n", + "Debug: Updated delay_max[6] to 767.0\n", + "Debug: Checking start time for pe=6, task=59, v.name=t59_start, v.varValue=757.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=59, v.name=t_comp_59, v.varValue=10.0 new total comp=152\n", + "Debug: Checking end time for pe=6, task=60, v.name=t60_end_, v.varValue=782.0, current delay_max=767.0\n", + "Debug: Updated delay_max[6] to 782.0\n", + "Debug: Checking start time for pe=6, task=60, v.name=t60_start, v.varValue=767.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=60, v.name=t_comp_60, v.varValue=15.0 new total comp=167\n", + "Debug: Checking end time for pe=6, task=61, v.name=t61_end_, v.varValue=820.0, current delay_max=782.0\n", + "Debug: Updated delay_max[6] to 820.0\n", + "Debug: Checking start time for pe=6, task=61, v.name=t61_start, v.varValue=800.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=61, v.name=t_comp_61, v.varValue=20.0 new total comp=187\n", + "Debug: Checking end time for pe=6, task=65, v.name=t65_end_, v.varValue=800.0, current delay_max=820.0\n", + "Debug: Checking start time for pe=6, task=65, v.name=t65_start, v.varValue=782.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=65, v.name=t_comp_65, v.varValue=18.0 new total comp=205\n", + "Debug: Checking end time for pe=6, task=66, v.name=t66_end_, v.varValue=840.0, current delay_max=820.0\n", + "Debug: Updated delay_max[6] to 840.0\n", + "Debug: Checking start time for pe=6, task=66, v.name=t66_start, v.varValue=820.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=66, v.name=t_comp_66, v.varValue=20.0 new total comp=225\n", + "Debug: Checking end time for pe=6, task=67, v.name=t67_end_, v.varValue=820.0, current delay_max=840.0\n", + "Debug: Checking start time for pe=6, task=67, v.name=t67_start, v.varValue=819.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=67, v.name=t_comp_67, v.varValue=1.0 new total comp=226\n", + "Debug: Checking end time for pe=6, task=68, v.name=t68_end_, v.varValue=847.0, current delay_max=840.0\n", + "Debug: Updated delay_max[6] to 847.0\n", + "Debug: Checking start time for pe=6, task=68, v.name=t68_start, v.varValue=840.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=68, v.name=t_comp_68, v.varValue=7.0 new total comp=233\n", + "Debug: Checking end time for pe=6, task=69, v.name=t69_end_, v.varValue=854.0, current delay_max=847.0\n", + "Debug: Updated delay_max[6] to 854.0\n", + "Debug: Checking start time for pe=6, task=69, v.name=t69_start, v.varValue=847.0, current delay_min=616.0\n", + "Debug: found t_comp pe=6, task=69, v.name=t_comp_69, v.varValue=7.0 new total comp=240\n", + "Debug: Checking end time for pe=7, task=62, v.name=t62_end_, v.varValue=747.0, current delay_max=0\n", + "Debug: Updated delay_max[7] to 747.0\n", + "Debug: Checking start time for pe=7, task=62, v.name=t62_start, v.varValue=737.0, current delay_min=inf\n", + "Debug: Updated delay_min[7] to 737.0\n", + "Debug: found t_comp pe=7, task=62, v.name=t_comp_62, v.varValue=10.0 new total comp=10\n", + "Debug: Checking end time for pe=7, task=63, v.name=t63_end_, v.varValue=760.0, current delay_max=747.0\n", + "Debug: Updated delay_max[7] to 760.0\n", + "Debug: Checking start time for pe=7, task=63, v.name=t63_start, v.varValue=747.0, current delay_min=737.0\n", + "Debug: found t_comp pe=7, task=63, v.name=t_comp_63, v.varValue=13.0 new total comp=23\n", + "Debug: Checking end time for pe=7, task=64, v.name=t64_end_, v.varValue=778.0, current delay_max=760.0\n", + "Debug: Updated delay_max[7] to 778.0\n", + "Debug: Checking start time for pe=7, task=64, v.name=t64_start, v.varValue=760.0, current delay_min=737.0\n", + "Debug: found t_comp pe=7, task=64, v.name=t_comp_64, v.varValue=15.0 new total comp=38\n", + "Reverse mapping: {0: [0, 1, 2, 3], 1: [10, 8, 9], 2: [11, 12, 13, 14, 15, 16, 7], 3: [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], 4: [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], 5: [4, 5, 6], 6: [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69], 7: [62, 63, 64]}\n", + "total_comp: {0: 106, 1: 62, 2: 172, 3: 142, 4: 199, 5: 60, 6: 240, 7: 38}\n", + "total_sending: {0: 14.0, 1: 14.0, 2: 5.0, 3: 5.0, 4: 5.0, 5: 14.0, 6: 0.0, 7: 3.0}\n", + "total_memory: {0: 1191.0, 1: 274.0, 2: 1924.0, 3: 2554.0, 4: 7716.0, 5: 265.0, 6: 12630.0, 7: 3028.0}\n", + "delay_max: {0: 120.0, 1: 231.0, 2: 361.0, 3: 495.0, 4: 686.0, 5: 179.0, 6: 854.0, 7: 778.0}\n", + "delay_min: {0: 0.0, 1: 155.0, 2: 179.0, 3: 348.0, 4: 482.0, 5: 105.0, 6: 616.0, 7: 737.0}\n", + "delay_duration: {0: 120.0, 1: 76.0, 2: 182.0, 3: 147.0, 4: 204.0, 5: 74.0, 6: 238.0, 7: 41.0}\n", "order_choose_13_14 = 1.0\n", "order_choose_16_17 = 0.0\n", "order_choose_16_18 = 0.0\n", @@ -124382,37 +124372,37 @@ "order_choose_16_22 = 0.0\n", "order_choose_16_23 = 0.0\n", "order_choose_17_19 = 0.0\n", - "order_choose_17_20 = 0.0\n", + "order_choose_17_20 = 1.0\n", "order_choose_17_21 = 1.0\n", "order_choose_17_22 = 0.0\n", "order_choose_17_23 = 1.0\n", "order_choose_18_19 = 0.0\n", "order_choose_18_20 = 0.0\n", - "order_choose_18_21 = 1.0\n", + "order_choose_18_21 = 0.0\n", "order_choose_18_22 = 0.0\n", "order_choose_18_23 = 0.0\n", - "order_choose_19_22 = 1.0\n", + "order_choose_19_22 = 0.0\n", "order_choose_19_23 = 1.0\n", "order_choose_20_22 = 0.0\n", - "order_choose_20_23 = 1.0\n", + "order_choose_20_23 = 0.0\n", "order_choose_21_22 = 0.0\n", "order_choose_21_23 = 0.0\n", - "order_choose_25_26 = 0.0\n", - "order_choose_25_27 = 0.0\n", + "order_choose_25_26 = 1.0\n", + "order_choose_25_27 = 1.0\n", "order_choose_25_28 = 0.0\n", "order_choose_25_29 = 0.0\n", - "order_choose_25_30 = 0.0\n", - "order_choose_25_31 = 0.0\n", - "order_choose_25_32 = 0.0\n", - "order_choose_26_28 = 1.0\n", - "order_choose_26_29 = 1.0\n", + "order_choose_25_30 = 1.0\n", + "order_choose_25_31 = 1.0\n", + "order_choose_25_32 = 1.0\n", + "order_choose_26_28 = 0.0\n", + "order_choose_26_29 = 0.0\n", "order_choose_26_30 = 1.0\n", - "order_choose_26_31 = 1.0\n", + "order_choose_26_31 = 0.0\n", "order_choose_26_32 = 1.0\n", "order_choose_27_28 = 0.0\n", "order_choose_27_29 = 0.0\n", "order_choose_27_30 = 1.0\n", - "order_choose_27_31 = 1.0\n", + "order_choose_27_31 = 0.0\n", "order_choose_27_32 = 1.0\n", "order_choose_28_31 = 1.0\n", "order_choose_28_32 = 1.0\n", @@ -124420,73 +124410,73 @@ "order_choose_29_32 = 1.0\n", "order_choose_30_31 = 0.0\n", "order_choose_30_32 = 0.0\n", - "order_choose_34_35 = 1.0\n", - "order_choose_34_36 = 1.0\n", + "order_choose_34_35 = 0.0\n", + "order_choose_34_36 = 0.0\n", "order_choose_34_37 = 0.0\n", - "order_choose_34_38 = 1.0\n", - "order_choose_34_39 = 1.0\n", - "order_choose_34_40 = 1.0\n", - "order_choose_34_41 = 1.0\n", + "order_choose_34_38 = 0.0\n", + "order_choose_34_39 = 0.0\n", + "order_choose_34_40 = 0.0\n", + "order_choose_34_41 = 0.0\n", "order_choose_35_37 = 0.0\n", - "order_choose_35_38 = 1.0\n", - "order_choose_35_39 = 1.0\n", - "order_choose_35_40 = 0.0\n", + "order_choose_35_38 = 0.0\n", + "order_choose_35_39 = 0.0\n", + "order_choose_35_40 = 1.0\n", "order_choose_35_41 = 1.0\n", "order_choose_36_37 = 0.0\n", "order_choose_36_38 = 0.0\n", - "order_choose_36_39 = 1.0\n", + "order_choose_36_39 = 0.0\n", "order_choose_36_40 = 0.0\n", "order_choose_36_41 = 0.0\n", "order_choose_37_40 = 1.0\n", "order_choose_37_41 = 1.0\n", - "order_choose_38_40 = 0.0\n", + "order_choose_38_40 = 1.0\n", "order_choose_38_41 = 1.0\n", - "order_choose_39_40 = 0.0\n", - "order_choose_39_41 = 0.0\n", + "order_choose_39_40 = 1.0\n", + "order_choose_39_41 = 1.0\n", "order_choose_3_4 = 0.0\n", - "order_choose_43_44 = 0.0\n", - "order_choose_43_45 = 0.0\n", - "order_choose_43_46 = 0.0\n", - "order_choose_43_47 = 0.0\n", - "order_choose_43_48 = 0.0\n", - "order_choose_43_49 = 0.0\n", - "order_choose_43_50 = 0.0\n", - "order_choose_44_46 = 0.0\n", + "order_choose_43_44 = 1.0\n", + "order_choose_43_45 = 1.0\n", + "order_choose_43_46 = 1.0\n", + "order_choose_43_47 = 1.0\n", + "order_choose_43_48 = 1.0\n", + "order_choose_43_49 = 1.0\n", + "order_choose_43_50 = 1.0\n", + "order_choose_44_46 = 1.0\n", "order_choose_44_47 = 1.0\n", "order_choose_44_48 = 1.0\n", - "order_choose_44_49 = 0.0\n", - "order_choose_44_50 = 0.0\n", + "order_choose_44_49 = 1.0\n", + "order_choose_44_50 = 1.0\n", "order_choose_45_46 = 0.0\n", - "order_choose_45_47 = 1.0\n", - "order_choose_45_48 = 1.0\n", + "order_choose_45_47 = 0.0\n", + "order_choose_45_48 = 0.0\n", "order_choose_45_49 = 0.0\n", - "order_choose_45_50 = 0.0\n", - "order_choose_46_49 = 0.0\n", - "order_choose_46_50 = 0.0\n", - "order_choose_47_49 = 0.0\n", - "order_choose_47_50 = 0.0\n", + "order_choose_45_50 = 1.0\n", + "order_choose_46_49 = 1.0\n", + "order_choose_46_50 = 1.0\n", + "order_choose_47_49 = 1.0\n", + "order_choose_47_50 = 1.0\n", "order_choose_48_49 = 0.0\n", - "order_choose_48_50 = 0.0\n", + "order_choose_48_50 = 1.0\n", "order_choose_52_53 = 0.0\n", "order_choose_52_54 = 0.0\n", "order_choose_52_55 = 0.0\n", "order_choose_52_56 = 0.0\n", - "order_choose_53_56 = 0.0\n", + "order_choose_53_56 = 3.99999999e-06\n", "order_choose_54_56 = 0.0\n", "order_choose_55_56 = 0.0\n", - "order_choose_58_59 = 0.0\n", + "order_choose_58_59 = 1.0\n", "order_choose_58_60 = 1.0\n", "order_choose_58_61 = 1.0\n", "order_choose_58_62 = 0.0\n", - "order_choose_58_63 = 1.0\n", - "order_choose_58_64 = 1.0\n", + "order_choose_58_63 = 0.0\n", + "order_choose_58_64 = 0.0\n", "order_choose_58_65 = 1.0\n", "order_choose_58_66 = 1.0\n", - "order_choose_58_67 = 0.0\n", + "order_choose_58_67 = 1.0\n", "order_choose_58_68 = 1.0\n", - "order_choose_59_62 = 1.0\n", - "order_choose_59_63 = 1.0\n", - "order_choose_59_64 = 1.0\n", + "order_choose_59_62 = 0.0\n", + "order_choose_59_63 = 0.0\n", + "order_choose_59_64 = 0.0\n", "order_choose_59_65 = 1.0\n", "order_choose_59_66 = 1.0\n", "order_choose_59_67 = 1.0\n", @@ -124496,31 +124486,31 @@ "order_choose_60_64 = 0.0\n", "order_choose_60_65 = 1.0\n", "order_choose_60_66 = 1.0\n", - "order_choose_60_67 = 0.0\n", + "order_choose_60_67 = 1.0\n", "order_choose_60_68 = 1.0\n", "order_choose_61_62 = 0.0\n", "order_choose_61_63 = 0.0\n", "order_choose_61_64 = 0.0\n", "order_choose_61_65 = 0.0\n", - "order_choose_61_66 = 0.0\n", - "order_choose_61_67 = 0.0\n", - "order_choose_61_68 = 0.0\n", - "order_choose_62_67 = 1.0\n", - "order_choose_62_68 = 1.0\n", + "order_choose_61_66 = 1.0\n", + "order_choose_61_67 = 0.99999600000001\n", + "order_choose_61_68 = 1.0\n", + "order_choose_62_67 = 0.0\n", + "order_choose_62_68 = 0.0\n", "order_choose_63_67 = 0.0\n", - "order_choose_63_68 = 1.0\n", + "order_choose_63_68 = 0.0\n", "order_choose_64_67 = 0.0\n", - "order_choose_64_68 = 1.0\n", - "order_choose_65_67 = 0.0\n", + "order_choose_64_68 = 0.0\n", + "order_choose_65_67 = 1.0\n", "order_choose_65_68 = 1.0\n", "order_choose_66_67 = 0.0\n", - "order_choose_66_68 = 0.0\n", + "order_choose_66_68 = 1.0\n", "order_choose_6_10 = 0.0\n", "order_choose_6_11 = 0.0\n", "order_choose_6_8 = 0.0\n", "order_choose_6_9 = 0.0\n", "order_choose_7_10 = 0.0\n", - "order_choose_7_11 = 0.0\n", + "order_choose_7_11 = 1.0\n", "order_choose_7_8 = 0.0\n", "order_choose_7_9 = 0.0\n", "same_0_0 = 1.0\n", @@ -124695,11 +124685,11 @@ "same_0_19_and_7 = 0.0\n", "same_0_19_and_8 = 0.0\n", "same_0_19_and_9 = 0.0\n", - "same_0_1_and_0 = 0.0\n", + "same_0_1_and_0 = 1.0\n", "same_0_1_and_1 = 0.0\n", "same_0_1_and_10 = 0.0\n", "same_0_1_and_11 = 0.0\n", - "same_0_1_and_12 = 1.0\n", + "same_0_1_and_12 = 0.0\n", "same_0_1_and_13 = 0.0\n", "same_0_1_and_14 = 0.0\n", "same_0_1_and_15 = 0.0\n", @@ -124882,11 +124872,11 @@ "same_0_29_and_7 = 0.0\n", "same_0_29_and_8 = 0.0\n", "same_0_29_and_9 = 0.0\n", - "same_0_2_and_0 = 0.0\n", + "same_0_2_and_0 = 1.0\n", "same_0_2_and_1 = 0.0\n", "same_0_2_and_10 = 0.0\n", "same_0_2_and_11 = 0.0\n", - "same_0_2_and_12 = 1.0\n", + "same_0_2_and_12 = 0.0\n", "same_0_2_and_13 = 0.0\n", "same_0_2_and_14 = 0.0\n", "same_0_2_and_15 = 0.0\n", @@ -125069,11 +125059,11 @@ "same_0_39_and_7 = 0.0\n", "same_0_39_and_8 = 0.0\n", "same_0_39_and_9 = 0.0\n", - "same_0_3_and_0 = 0.0\n", + "same_0_3_and_0 = 1.0\n", "same_0_3_and_1 = 0.0\n", "same_0_3_and_10 = 0.0\n", "same_0_3_and_11 = 0.0\n", - "same_0_3_and_12 = 1.0\n", + "same_0_3_and_12 = 0.0\n", "same_0_3_and_13 = 0.0\n", "same_0_3_and_14 = 0.0\n", "same_0_3_and_15 = 0.0\n", @@ -125085,7 +125075,7 @@ "same_0_3_and_7 = 0.0\n", "same_0_3_and_8 = 0.0\n", "same_0_3_and_9 = 0.0\n", - "same_0_4 = 1.0\n", + "same_0_4 = 0.0\n", "same_0_40 = 0.0\n", "same_0_40_and_0 = 0.0\n", "same_0_40_and_1 = 0.0\n", @@ -125260,7 +125250,7 @@ "same_0_4_and_1 = 0.0\n", "same_0_4_and_10 = 0.0\n", "same_0_4_and_11 = 0.0\n", - "same_0_4_and_12 = 1.0\n", + "same_0_4_and_12 = 0.0\n", "same_0_4_and_13 = 0.0\n", "same_0_4_and_14 = 0.0\n", "same_0_4_and_15 = 0.0\n", @@ -125272,7 +125262,7 @@ "same_0_4_and_7 = 0.0\n", "same_0_4_and_8 = 0.0\n", "same_0_4_and_9 = 0.0\n", - "same_0_5 = 1.0\n", + "same_0_5 = 0.0\n", "same_0_50 = 0.0\n", "same_0_50_and_0 = 0.0\n", "same_0_50_and_1 = 0.0\n", @@ -125447,7 +125437,7 @@ "same_0_5_and_1 = 0.0\n", "same_0_5_and_10 = 0.0\n", "same_0_5_and_11 = 0.0\n", - "same_0_5_and_12 = 1.0\n", + "same_0_5_and_12 = 0.0\n", "same_0_5_and_13 = 0.0\n", "same_0_5_and_14 = 0.0\n", "same_0_5_and_15 = 0.0\n", @@ -125459,7 +125449,7 @@ "same_0_5_and_7 = 0.0\n", "same_0_5_and_8 = 0.0\n", "same_0_5_and_9 = 0.0\n", - "same_0_6 = 1.0\n", + "same_0_6 = 0.0\n", "same_0_60 = 0.0\n", "same_0_60_and_0 = 0.0\n", "same_0_60_and_1 = 0.0\n", @@ -125634,7 +125624,7 @@ "same_0_6_and_1 = 0.0\n", "same_0_6_and_10 = 0.0\n", "same_0_6_and_11 = 0.0\n", - "same_0_6_and_12 = 1.0\n", + "same_0_6_and_12 = 0.0\n", "same_0_6_and_13 = 0.0\n", "same_0_6_and_14 = 0.0\n", "same_0_6_and_15 = 0.0\n", @@ -126706,12 +126696,12 @@ "same_11_12_and_0 = 0.0\n", "same_11_12_and_1 = 0.0\n", "same_11_12_and_10 = 0.0\n", - "same_11_12_and_11 = 1.0\n", + "same_11_12_and_11 = 0.0\n", "same_11_12_and_12 = 0.0\n", "same_11_12_and_13 = 0.0\n", "same_11_12_and_14 = 0.0\n", "same_11_12_and_15 = 0.0\n", - "same_11_12_and_2 = 0.0\n", + "same_11_12_and_2 = 1.0\n", "same_11_12_and_3 = 0.0\n", "same_11_12_and_4 = 0.0\n", "same_11_12_and_5 = 0.0\n", @@ -126723,12 +126713,12 @@ "same_11_13_and_0 = 0.0\n", "same_11_13_and_1 = 0.0\n", "same_11_13_and_10 = 0.0\n", - "same_11_13_and_11 = 1.0\n", + "same_11_13_and_11 = 0.0\n", "same_11_13_and_12 = 0.0\n", "same_11_13_and_13 = 0.0\n", "same_11_13_and_14 = 0.0\n", "same_11_13_and_15 = 0.0\n", - "same_11_13_and_2 = 0.0\n", + "same_11_13_and_2 = 1.0\n", "same_11_13_and_3 = 0.0\n", "same_11_13_and_4 = 0.0\n", "same_11_13_and_5 = 0.0\n", @@ -126736,7 +126726,7 @@ "same_11_13_and_7 = 0.0\n", "same_11_13_and_8 = 0.0\n", "same_11_13_and_9 = 0.0\n", - "same_11_14 = 0.0\n", + "same_11_14 = 1.0\n", "same_11_14_and_0 = 0.0\n", "same_11_14_and_1 = 0.0\n", "same_11_14_and_10 = 0.0\n", @@ -126745,7 +126735,7 @@ "same_11_14_and_13 = 0.0\n", "same_11_14_and_14 = 0.0\n", "same_11_14_and_15 = 0.0\n", - "same_11_14_and_2 = 0.0\n", + "same_11_14_and_2 = 1.0\n", "same_11_14_and_3 = 0.0\n", "same_11_14_and_4 = 0.0\n", "same_11_14_and_5 = 0.0\n", @@ -126753,7 +126743,7 @@ "same_11_14_and_7 = 0.0\n", "same_11_14_and_8 = 0.0\n", "same_11_14_and_9 = 0.0\n", - "same_11_15 = 0.0\n", + "same_11_15 = 1.0\n", "same_11_15_and_0 = 0.0\n", "same_11_15_and_1 = 0.0\n", "same_11_15_and_10 = 0.0\n", @@ -126762,7 +126752,7 @@ "same_11_15_and_13 = 0.0\n", "same_11_15_and_14 = 0.0\n", "same_11_15_and_15 = 0.0\n", - "same_11_15_and_2 = 0.0\n", + "same_11_15_and_2 = 1.0\n", "same_11_15_and_3 = 0.0\n", "same_11_15_and_4 = 0.0\n", "same_11_15_and_5 = 0.0\n", @@ -126770,7 +126760,7 @@ "same_11_15_and_7 = 0.0\n", "same_11_15_and_8 = 0.0\n", "same_11_15_and_9 = 0.0\n", - "same_11_16 = 0.0\n", + "same_11_16 = 1.0\n", "same_11_16_and_0 = 0.0\n", "same_11_16_and_1 = 0.0\n", "same_11_16_and_10 = 0.0\n", @@ -126779,7 +126769,7 @@ "same_11_16_and_13 = 0.0\n", "same_11_16_and_14 = 0.0\n", "same_11_16_and_15 = 0.0\n", - "same_11_16_and_2 = 0.0\n", + "same_11_16_and_2 = 1.0\n", "same_11_16_and_3 = 0.0\n", "same_11_16_and_4 = 0.0\n", "same_11_16_and_5 = 0.0\n", @@ -127693,12 +127683,12 @@ "same_12_13_and_0 = 0.0\n", "same_12_13_and_1 = 0.0\n", "same_12_13_and_10 = 0.0\n", - "same_12_13_and_11 = 1.0\n", + "same_12_13_and_11 = 0.0\n", "same_12_13_and_12 = 0.0\n", "same_12_13_and_13 = 0.0\n", "same_12_13_and_14 = 0.0\n", "same_12_13_and_15 = 0.0\n", - "same_12_13_and_2 = 0.0\n", + "same_12_13_and_2 = 1.0\n", "same_12_13_and_3 = 0.0\n", "same_12_13_and_4 = 0.0\n", "same_12_13_and_5 = 0.0\n", @@ -127706,7 +127696,7 @@ "same_12_13_and_7 = 0.0\n", "same_12_13_and_8 = 0.0\n", "same_12_13_and_9 = 0.0\n", - "same_12_14 = 0.0\n", + "same_12_14 = 1.0\n", "same_12_14_and_0 = 0.0\n", "same_12_14_and_1 = 0.0\n", "same_12_14_and_10 = 0.0\n", @@ -127715,7 +127705,7 @@ "same_12_14_and_13 = 0.0\n", "same_12_14_and_14 = 0.0\n", "same_12_14_and_15 = 0.0\n", - "same_12_14_and_2 = 0.0\n", + "same_12_14_and_2 = 1.0\n", "same_12_14_and_3 = 0.0\n", "same_12_14_and_4 = 0.0\n", "same_12_14_and_5 = 0.0\n", @@ -127723,7 +127713,7 @@ "same_12_14_and_7 = 0.0\n", "same_12_14_and_8 = 0.0\n", "same_12_14_and_9 = 0.0\n", - "same_12_15 = 0.0\n", + "same_12_15 = 1.0\n", "same_12_15_and_0 = 0.0\n", "same_12_15_and_1 = 0.0\n", "same_12_15_and_10 = 0.0\n", @@ -127732,7 +127722,7 @@ "same_12_15_and_13 = 0.0\n", "same_12_15_and_14 = 0.0\n", "same_12_15_and_15 = 0.0\n", - "same_12_15_and_2 = 0.0\n", + "same_12_15_and_2 = 1.0\n", "same_12_15_and_3 = 0.0\n", "same_12_15_and_4 = 0.0\n", "same_12_15_and_5 = 0.0\n", @@ -127740,7 +127730,7 @@ "same_12_15_and_7 = 0.0\n", "same_12_15_and_8 = 0.0\n", "same_12_15_and_9 = 0.0\n", - "same_12_16 = 0.0\n", + "same_12_16 = 1.0\n", "same_12_16_and_0 = 0.0\n", "same_12_16_and_1 = 0.0\n", "same_12_16_and_10 = 0.0\n", @@ -127749,7 +127739,7 @@ "same_12_16_and_13 = 0.0\n", "same_12_16_and_14 = 0.0\n", "same_12_16_and_15 = 0.0\n", - "same_12_16_and_2 = 0.0\n", + "same_12_16_and_2 = 1.0\n", "same_12_16_and_3 = 0.0\n", "same_12_16_and_4 = 0.0\n", "same_12_16_and_5 = 0.0\n", @@ -128659,7 +128649,7 @@ "same_12_69_and_8 = 0.0\n", "same_12_69_and_9 = 0.0\n", "same_13_13 = 1.0\n", - "same_13_14 = 0.0\n", + "same_13_14 = 1.0\n", "same_13_14_and_0 = 0.0\n", "same_13_14_and_1 = 0.0\n", "same_13_14_and_10 = 0.0\n", @@ -128668,7 +128658,7 @@ "same_13_14_and_13 = 0.0\n", "same_13_14_and_14 = 0.0\n", "same_13_14_and_15 = 0.0\n", - "same_13_14_and_2 = 0.0\n", + "same_13_14_and_2 = 1.0\n", "same_13_14_and_3 = 0.0\n", "same_13_14_and_4 = 0.0\n", "same_13_14_and_5 = 0.0\n", @@ -128676,7 +128666,7 @@ "same_13_14_and_7 = 0.0\n", "same_13_14_and_8 = 0.0\n", "same_13_14_and_9 = 0.0\n", - "same_13_15 = 0.0\n", + "same_13_15 = 1.0\n", "same_13_15_and_0 = 0.0\n", "same_13_15_and_1 = 0.0\n", "same_13_15_and_10 = 0.0\n", @@ -128685,7 +128675,7 @@ "same_13_15_and_13 = 0.0\n", "same_13_15_and_14 = 0.0\n", "same_13_15_and_15 = 0.0\n", - "same_13_15_and_2 = 0.0\n", + "same_13_15_and_2 = 1.0\n", "same_13_15_and_3 = 0.0\n", "same_13_15_and_4 = 0.0\n", "same_13_15_and_5 = 0.0\n", @@ -128693,7 +128683,7 @@ "same_13_15_and_7 = 0.0\n", "same_13_15_and_8 = 0.0\n", "same_13_15_and_9 = 0.0\n", - "same_13_16 = 0.0\n", + "same_13_16 = 1.0\n", "same_13_16_and_0 = 0.0\n", "same_13_16_and_1 = 0.0\n", "same_13_16_and_10 = 0.0\n", @@ -128702,7 +128692,7 @@ "same_13_16_and_13 = 0.0\n", "same_13_16_and_14 = 0.0\n", "same_13_16_and_15 = 0.0\n", - "same_13_16_and_2 = 0.0\n", + "same_13_16_and_2 = 1.0\n", "same_13_16_and_3 = 0.0\n", "same_13_16_and_4 = 0.0\n", "same_13_16_and_5 = 0.0\n", @@ -129618,10 +129608,10 @@ "same_14_15_and_10 = 0.0\n", "same_14_15_and_11 = 0.0\n", "same_14_15_and_12 = 0.0\n", - "same_14_15_and_13 = 1.0\n", + "same_14_15_and_13 = 0.0\n", "same_14_15_and_14 = 0.0\n", "same_14_15_and_15 = 0.0\n", - "same_14_15_and_2 = 0.0\n", + "same_14_15_and_2 = 1.0\n", "same_14_15_and_3 = 0.0\n", "same_14_15_and_4 = 0.0\n", "same_14_15_and_5 = 0.0\n", @@ -129635,10 +129625,10 @@ "same_14_16_and_10 = 0.0\n", "same_14_16_and_11 = 0.0\n", "same_14_16_and_12 = 0.0\n", - "same_14_16_and_13 = 1.0\n", + "same_14_16_and_13 = 0.0\n", "same_14_16_and_14 = 0.0\n", "same_14_16_and_15 = 0.0\n", - "same_14_16_and_2 = 0.0\n", + "same_14_16_and_2 = 1.0\n", "same_14_16_and_3 = 0.0\n", "same_14_16_and_4 = 0.0\n", "same_14_16_and_5 = 0.0\n", @@ -129646,13 +129636,13 @@ "same_14_16_and_7 = 0.0\n", "same_14_16_and_8 = 0.0\n", "same_14_16_and_9 = 0.0\n", - "same_14_17 = 1.0\n", + "same_14_17 = 0.0\n", "same_14_17_and_0 = 0.0\n", "same_14_17_and_1 = 0.0\n", "same_14_17_and_10 = 0.0\n", "same_14_17_and_11 = 0.0\n", "same_14_17_and_12 = 0.0\n", - "same_14_17_and_13 = 1.0\n", + "same_14_17_and_13 = 0.0\n", "same_14_17_and_14 = 0.0\n", "same_14_17_and_15 = 0.0\n", "same_14_17_and_2 = 0.0\n", @@ -129663,13 +129653,13 @@ "same_14_17_and_7 = 0.0\n", "same_14_17_and_8 = 0.0\n", "same_14_17_and_9 = 0.0\n", - "same_14_18 = 1.0\n", + "same_14_18 = 0.0\n", "same_14_18_and_0 = 0.0\n", "same_14_18_and_1 = 0.0\n", "same_14_18_and_10 = 0.0\n", "same_14_18_and_11 = 0.0\n", "same_14_18_and_12 = 0.0\n", - "same_14_18_and_13 = 1.0\n", + "same_14_18_and_13 = 0.0\n", "same_14_18_and_14 = 0.0\n", "same_14_18_and_15 = 0.0\n", "same_14_18_and_2 = 0.0\n", @@ -129680,13 +129670,13 @@ "same_14_18_and_7 = 0.0\n", "same_14_18_and_8 = 0.0\n", "same_14_18_and_9 = 0.0\n", - "same_14_19 = 1.0\n", + "same_14_19 = 0.0\n", "same_14_19_and_0 = 0.0\n", "same_14_19_and_1 = 0.0\n", "same_14_19_and_10 = 0.0\n", "same_14_19_and_11 = 0.0\n", "same_14_19_and_12 = 0.0\n", - "same_14_19_and_13 = 1.0\n", + "same_14_19_and_13 = 0.0\n", "same_14_19_and_14 = 0.0\n", "same_14_19_and_15 = 0.0\n", "same_14_19_and_2 = 0.0\n", @@ -129697,13 +129687,13 @@ "same_14_19_and_7 = 0.0\n", "same_14_19_and_8 = 0.0\n", "same_14_19_and_9 = 0.0\n", - "same_14_20 = 1.0\n", + "same_14_20 = 0.0\n", "same_14_20_and_0 = 0.0\n", "same_14_20_and_1 = 0.0\n", "same_14_20_and_10 = 0.0\n", "same_14_20_and_11 = 0.0\n", "same_14_20_and_12 = 0.0\n", - "same_14_20_and_13 = 1.0\n", + "same_14_20_and_13 = 0.0\n", "same_14_20_and_14 = 0.0\n", "same_14_20_and_15 = 0.0\n", "same_14_20_and_2 = 0.0\n", @@ -129714,13 +129704,13 @@ "same_14_20_and_7 = 0.0\n", "same_14_20_and_8 = 0.0\n", "same_14_20_and_9 = 0.0\n", - "same_14_21 = 1.0\n", + "same_14_21 = 0.0\n", "same_14_21_and_0 = 0.0\n", "same_14_21_and_1 = 0.0\n", "same_14_21_and_10 = 0.0\n", "same_14_21_and_11 = 0.0\n", "same_14_21_and_12 = 0.0\n", - "same_14_21_and_13 = 1.0\n", + "same_14_21_and_13 = 0.0\n", "same_14_21_and_14 = 0.0\n", "same_14_21_and_15 = 0.0\n", "same_14_21_and_2 = 0.0\n", @@ -129731,13 +129721,13 @@ "same_14_21_and_7 = 0.0\n", "same_14_21_and_8 = 0.0\n", "same_14_21_and_9 = 0.0\n", - "same_14_22 = 1.0\n", + "same_14_22 = 0.0\n", "same_14_22_and_0 = 0.0\n", "same_14_22_and_1 = 0.0\n", "same_14_22_and_10 = 0.0\n", "same_14_22_and_11 = 0.0\n", "same_14_22_and_12 = 0.0\n", - "same_14_22_and_13 = 1.0\n", + "same_14_22_and_13 = 0.0\n", "same_14_22_and_14 = 0.0\n", "same_14_22_and_15 = 0.0\n", "same_14_22_and_2 = 0.0\n", @@ -129748,13 +129738,13 @@ "same_14_22_and_7 = 0.0\n", "same_14_22_and_8 = 0.0\n", "same_14_22_and_9 = 0.0\n", - "same_14_23 = 1.0\n", + "same_14_23 = 0.0\n", "same_14_23_and_0 = 0.0\n", "same_14_23_and_1 = 0.0\n", "same_14_23_and_10 = 0.0\n", "same_14_23_and_11 = 0.0\n", "same_14_23_and_12 = 0.0\n", - "same_14_23_and_13 = 1.0\n", + "same_14_23_and_13 = 0.0\n", "same_14_23_and_14 = 0.0\n", "same_14_23_and_15 = 0.0\n", "same_14_23_and_2 = 0.0\n", @@ -129765,13 +129755,13 @@ "same_14_23_and_7 = 0.0\n", "same_14_23_and_8 = 0.0\n", "same_14_23_and_9 = 0.0\n", - "same_14_24 = 1.0\n", + "same_14_24 = 0.0\n", "same_14_24_and_0 = 0.0\n", "same_14_24_and_1 = 0.0\n", "same_14_24_and_10 = 0.0\n", "same_14_24_and_11 = 0.0\n", "same_14_24_and_12 = 0.0\n", - "same_14_24_and_13 = 1.0\n", + "same_14_24_and_13 = 0.0\n", "same_14_24_and_14 = 0.0\n", "same_14_24_and_15 = 0.0\n", "same_14_24_and_2 = 0.0\n", @@ -129782,13 +129772,13 @@ "same_14_24_and_7 = 0.0\n", "same_14_24_and_8 = 0.0\n", "same_14_24_and_9 = 0.0\n", - "same_14_25 = 1.0\n", + "same_14_25 = 0.0\n", "same_14_25_and_0 = 0.0\n", "same_14_25_and_1 = 0.0\n", "same_14_25_and_10 = 0.0\n", "same_14_25_and_11 = 0.0\n", "same_14_25_and_12 = 0.0\n", - "same_14_25_and_13 = 1.0\n", + "same_14_25_and_13 = 0.0\n", "same_14_25_and_14 = 0.0\n", "same_14_25_and_15 = 0.0\n", "same_14_25_and_2 = 0.0\n", @@ -130554,10 +130544,10 @@ "same_15_16_and_10 = 0.0\n", "same_15_16_and_11 = 0.0\n", "same_15_16_and_12 = 0.0\n", - "same_15_16_and_13 = 1.0\n", + "same_15_16_and_13 = 0.0\n", "same_15_16_and_14 = 0.0\n", "same_15_16_and_15 = 0.0\n", - "same_15_16_and_2 = 0.0\n", + "same_15_16_and_2 = 1.0\n", "same_15_16_and_3 = 0.0\n", "same_15_16_and_4 = 0.0\n", "same_15_16_and_5 = 0.0\n", @@ -130565,13 +130555,13 @@ "same_15_16_and_7 = 0.0\n", "same_15_16_and_8 = 0.0\n", "same_15_16_and_9 = 0.0\n", - "same_15_17 = 1.0\n", + "same_15_17 = 0.0\n", "same_15_17_and_0 = 0.0\n", "same_15_17_and_1 = 0.0\n", "same_15_17_and_10 = 0.0\n", "same_15_17_and_11 = 0.0\n", "same_15_17_and_12 = 0.0\n", - "same_15_17_and_13 = 1.0\n", + "same_15_17_and_13 = 0.0\n", "same_15_17_and_14 = 0.0\n", "same_15_17_and_15 = 0.0\n", "same_15_17_and_2 = 0.0\n", @@ -130582,13 +130572,13 @@ "same_15_17_and_7 = 0.0\n", "same_15_17_and_8 = 0.0\n", "same_15_17_and_9 = 0.0\n", - "same_15_18 = 1.0\n", + "same_15_18 = 0.0\n", "same_15_18_and_0 = 0.0\n", "same_15_18_and_1 = 0.0\n", "same_15_18_and_10 = 0.0\n", "same_15_18_and_11 = 0.0\n", "same_15_18_and_12 = 0.0\n", - "same_15_18_and_13 = 1.0\n", + "same_15_18_and_13 = 0.0\n", "same_15_18_and_14 = 0.0\n", "same_15_18_and_15 = 0.0\n", "same_15_18_and_2 = 0.0\n", @@ -130599,13 +130589,13 @@ "same_15_18_and_7 = 0.0\n", "same_15_18_and_8 = 0.0\n", "same_15_18_and_9 = 0.0\n", - "same_15_19 = 1.0\n", + "same_15_19 = 0.0\n", "same_15_19_and_0 = 0.0\n", "same_15_19_and_1 = 0.0\n", "same_15_19_and_10 = 0.0\n", "same_15_19_and_11 = 0.0\n", "same_15_19_and_12 = 0.0\n", - "same_15_19_and_13 = 1.0\n", + "same_15_19_and_13 = 0.0\n", "same_15_19_and_14 = 0.0\n", "same_15_19_and_15 = 0.0\n", "same_15_19_and_2 = 0.0\n", @@ -130616,13 +130606,13 @@ "same_15_19_and_7 = 0.0\n", "same_15_19_and_8 = 0.0\n", "same_15_19_and_9 = 0.0\n", - "same_15_20 = 1.0\n", + "same_15_20 = 0.0\n", "same_15_20_and_0 = 0.0\n", "same_15_20_and_1 = 0.0\n", "same_15_20_and_10 = 0.0\n", "same_15_20_and_11 = 0.0\n", "same_15_20_and_12 = 0.0\n", - "same_15_20_and_13 = 1.0\n", + "same_15_20_and_13 = 0.0\n", "same_15_20_and_14 = 0.0\n", "same_15_20_and_15 = 0.0\n", "same_15_20_and_2 = 0.0\n", @@ -130633,13 +130623,13 @@ "same_15_20_and_7 = 0.0\n", "same_15_20_and_8 = 0.0\n", "same_15_20_and_9 = 0.0\n", - "same_15_21 = 1.0\n", + "same_15_21 = 0.0\n", "same_15_21_and_0 = 0.0\n", "same_15_21_and_1 = 0.0\n", "same_15_21_and_10 = 0.0\n", "same_15_21_and_11 = 0.0\n", "same_15_21_and_12 = 0.0\n", - "same_15_21_and_13 = 1.0\n", + "same_15_21_and_13 = 0.0\n", "same_15_21_and_14 = 0.0\n", "same_15_21_and_15 = 0.0\n", "same_15_21_and_2 = 0.0\n", @@ -130650,13 +130640,13 @@ "same_15_21_and_7 = 0.0\n", "same_15_21_and_8 = 0.0\n", "same_15_21_and_9 = 0.0\n", - "same_15_22 = 1.0\n", + "same_15_22 = 0.0\n", "same_15_22_and_0 = 0.0\n", "same_15_22_and_1 = 0.0\n", "same_15_22_and_10 = 0.0\n", "same_15_22_and_11 = 0.0\n", "same_15_22_and_12 = 0.0\n", - "same_15_22_and_13 = 1.0\n", + "same_15_22_and_13 = 0.0\n", "same_15_22_and_14 = 0.0\n", "same_15_22_and_15 = 0.0\n", "same_15_22_and_2 = 0.0\n", @@ -130667,13 +130657,13 @@ "same_15_22_and_7 = 0.0\n", "same_15_22_and_8 = 0.0\n", "same_15_22_and_9 = 0.0\n", - "same_15_23 = 1.0\n", + "same_15_23 = 0.0\n", "same_15_23_and_0 = 0.0\n", "same_15_23_and_1 = 0.0\n", "same_15_23_and_10 = 0.0\n", "same_15_23_and_11 = 0.0\n", "same_15_23_and_12 = 0.0\n", - "same_15_23_and_13 = 1.0\n", + "same_15_23_and_13 = 0.0\n", "same_15_23_and_14 = 0.0\n", "same_15_23_and_15 = 0.0\n", "same_15_23_and_2 = 0.0\n", @@ -130684,13 +130674,13 @@ "same_15_23_and_7 = 0.0\n", "same_15_23_and_8 = 0.0\n", "same_15_23_and_9 = 0.0\n", - "same_15_24 = 1.0\n", + "same_15_24 = 0.0\n", "same_15_24_and_0 = 0.0\n", "same_15_24_and_1 = 0.0\n", "same_15_24_and_10 = 0.0\n", "same_15_24_and_11 = 0.0\n", "same_15_24_and_12 = 0.0\n", - "same_15_24_and_13 = 1.0\n", + "same_15_24_and_13 = 0.0\n", "same_15_24_and_14 = 0.0\n", "same_15_24_and_15 = 0.0\n", "same_15_24_and_2 = 0.0\n", @@ -130701,13 +130691,13 @@ "same_15_24_and_7 = 0.0\n", "same_15_24_and_8 = 0.0\n", "same_15_24_and_9 = 0.0\n", - "same_15_25 = 1.0\n", + "same_15_25 = 0.0\n", "same_15_25_and_0 = 0.0\n", "same_15_25_and_1 = 0.0\n", "same_15_25_and_10 = 0.0\n", "same_15_25_and_11 = 0.0\n", "same_15_25_and_12 = 0.0\n", - "same_15_25_and_13 = 1.0\n", + "same_15_25_and_13 = 0.0\n", "same_15_25_and_14 = 0.0\n", "same_15_25_and_15 = 0.0\n", "same_15_25_and_2 = 0.0\n", @@ -131467,13 +131457,13 @@ "same_15_69_and_8 = 0.0\n", "same_15_69_and_9 = 0.0\n", "same_16_16 = 1.0\n", - "same_16_17 = 1.0\n", + "same_16_17 = 0.0\n", "same_16_17_and_0 = 0.0\n", "same_16_17_and_1 = 0.0\n", "same_16_17_and_10 = 0.0\n", "same_16_17_and_11 = 0.0\n", "same_16_17_and_12 = 0.0\n", - "same_16_17_and_13 = 1.0\n", + "same_16_17_and_13 = 0.0\n", "same_16_17_and_14 = 0.0\n", "same_16_17_and_15 = 0.0\n", "same_16_17_and_2 = 0.0\n", @@ -131484,13 +131474,13 @@ "same_16_17_and_7 = 0.0\n", "same_16_17_and_8 = 0.0\n", "same_16_17_and_9 = 0.0\n", - "same_16_18 = 1.0\n", + "same_16_18 = 0.0\n", "same_16_18_and_0 = 0.0\n", "same_16_18_and_1 = 0.0\n", "same_16_18_and_10 = 0.0\n", "same_16_18_and_11 = 0.0\n", "same_16_18_and_12 = 0.0\n", - "same_16_18_and_13 = 1.0\n", + "same_16_18_and_13 = 0.0\n", "same_16_18_and_14 = 0.0\n", "same_16_18_and_15 = 0.0\n", "same_16_18_and_2 = 0.0\n", @@ -131501,13 +131491,13 @@ "same_16_18_and_7 = 0.0\n", "same_16_18_and_8 = 0.0\n", "same_16_18_and_9 = 0.0\n", - "same_16_19 = 1.0\n", + "same_16_19 = 0.0\n", "same_16_19_and_0 = 0.0\n", "same_16_19_and_1 = 0.0\n", "same_16_19_and_10 = 0.0\n", "same_16_19_and_11 = 0.0\n", "same_16_19_and_12 = 0.0\n", - "same_16_19_and_13 = 1.0\n", + "same_16_19_and_13 = 0.0\n", "same_16_19_and_14 = 0.0\n", "same_16_19_and_15 = 0.0\n", "same_16_19_and_2 = 0.0\n", @@ -131518,13 +131508,13 @@ "same_16_19_and_7 = 0.0\n", "same_16_19_and_8 = 0.0\n", "same_16_19_and_9 = 0.0\n", - "same_16_20 = 1.0\n", + "same_16_20 = 0.0\n", "same_16_20_and_0 = 0.0\n", "same_16_20_and_1 = 0.0\n", "same_16_20_and_10 = 0.0\n", "same_16_20_and_11 = 0.0\n", "same_16_20_and_12 = 0.0\n", - "same_16_20_and_13 = 1.0\n", + "same_16_20_and_13 = 0.0\n", "same_16_20_and_14 = 0.0\n", "same_16_20_and_15 = 0.0\n", "same_16_20_and_2 = 0.0\n", @@ -131535,13 +131525,13 @@ "same_16_20_and_7 = 0.0\n", "same_16_20_and_8 = 0.0\n", "same_16_20_and_9 = 0.0\n", - "same_16_21 = 1.0\n", + "same_16_21 = 0.0\n", "same_16_21_and_0 = 0.0\n", "same_16_21_and_1 = 0.0\n", "same_16_21_and_10 = 0.0\n", "same_16_21_and_11 = 0.0\n", "same_16_21_and_12 = 0.0\n", - "same_16_21_and_13 = 1.0\n", + "same_16_21_and_13 = 0.0\n", "same_16_21_and_14 = 0.0\n", "same_16_21_and_15 = 0.0\n", "same_16_21_and_2 = 0.0\n", @@ -131552,13 +131542,13 @@ "same_16_21_and_7 = 0.0\n", "same_16_21_and_8 = 0.0\n", "same_16_21_and_9 = 0.0\n", - "same_16_22 = 1.0\n", + "same_16_22 = 0.0\n", "same_16_22_and_0 = 0.0\n", "same_16_22_and_1 = 0.0\n", "same_16_22_and_10 = 0.0\n", "same_16_22_and_11 = 0.0\n", "same_16_22_and_12 = 0.0\n", - "same_16_22_and_13 = 1.0\n", + "same_16_22_and_13 = 0.0\n", "same_16_22_and_14 = 0.0\n", "same_16_22_and_15 = 0.0\n", "same_16_22_and_2 = 0.0\n", @@ -131569,13 +131559,13 @@ "same_16_22_and_7 = 0.0\n", "same_16_22_and_8 = 0.0\n", "same_16_22_and_9 = 0.0\n", - "same_16_23 = 1.0\n", + "same_16_23 = 0.0\n", "same_16_23_and_0 = 0.0\n", "same_16_23_and_1 = 0.0\n", "same_16_23_and_10 = 0.0\n", "same_16_23_and_11 = 0.0\n", "same_16_23_and_12 = 0.0\n", - "same_16_23_and_13 = 1.0\n", + "same_16_23_and_13 = 0.0\n", "same_16_23_and_14 = 0.0\n", "same_16_23_and_15 = 0.0\n", "same_16_23_and_2 = 0.0\n", @@ -131586,13 +131576,13 @@ "same_16_23_and_7 = 0.0\n", "same_16_23_and_8 = 0.0\n", "same_16_23_and_9 = 0.0\n", - "same_16_24 = 1.0\n", + "same_16_24 = 0.0\n", "same_16_24_and_0 = 0.0\n", "same_16_24_and_1 = 0.0\n", "same_16_24_and_10 = 0.0\n", "same_16_24_and_11 = 0.0\n", "same_16_24_and_12 = 0.0\n", - "same_16_24_and_13 = 1.0\n", + "same_16_24_and_13 = 0.0\n", "same_16_24_and_14 = 0.0\n", "same_16_24_and_15 = 0.0\n", "same_16_24_and_2 = 0.0\n", @@ -131603,13 +131593,13 @@ "same_16_24_and_7 = 0.0\n", "same_16_24_and_8 = 0.0\n", "same_16_24_and_9 = 0.0\n", - "same_16_25 = 1.0\n", + "same_16_25 = 0.0\n", "same_16_25_and_0 = 0.0\n", "same_16_25_and_1 = 0.0\n", "same_16_25_and_10 = 0.0\n", "same_16_25_and_11 = 0.0\n", "same_16_25_and_12 = 0.0\n", - "same_16_25_and_13 = 1.0\n", + "same_16_25_and_13 = 0.0\n", "same_16_25_and_14 = 0.0\n", "same_16_25_and_15 = 0.0\n", "same_16_25_and_2 = 0.0\n", @@ -132375,11 +132365,11 @@ "same_17_18_and_10 = 0.0\n", "same_17_18_and_11 = 0.0\n", "same_17_18_and_12 = 0.0\n", - "same_17_18_and_13 = 1.0\n", + "same_17_18_and_13 = 0.0\n", "same_17_18_and_14 = 0.0\n", "same_17_18_and_15 = 0.0\n", "same_17_18_and_2 = 0.0\n", - "same_17_18_and_3 = 0.0\n", + "same_17_18_and_3 = 1.0\n", "same_17_18_and_4 = 0.0\n", "same_17_18_and_5 = 0.0\n", "same_17_18_and_6 = 0.0\n", @@ -132392,11 +132382,11 @@ "same_17_19_and_10 = 0.0\n", "same_17_19_and_11 = 0.0\n", "same_17_19_and_12 = 0.0\n", - "same_17_19_and_13 = 1.0\n", + "same_17_19_and_13 = 0.0\n", "same_17_19_and_14 = 0.0\n", "same_17_19_and_15 = 0.0\n", "same_17_19_and_2 = 0.0\n", - "same_17_19_and_3 = 0.0\n", + "same_17_19_and_3 = 1.0\n", "same_17_19_and_4 = 0.0\n", "same_17_19_and_5 = 0.0\n", "same_17_19_and_6 = 0.0\n", @@ -132409,11 +132399,11 @@ "same_17_20_and_10 = 0.0\n", "same_17_20_and_11 = 0.0\n", "same_17_20_and_12 = 0.0\n", - "same_17_20_and_13 = 1.0\n", + "same_17_20_and_13 = 0.0\n", "same_17_20_and_14 = 0.0\n", "same_17_20_and_15 = 0.0\n", "same_17_20_and_2 = 0.0\n", - "same_17_20_and_3 = 0.0\n", + "same_17_20_and_3 = 1.0\n", "same_17_20_and_4 = 0.0\n", "same_17_20_and_5 = 0.0\n", "same_17_20_and_6 = 0.0\n", @@ -132426,11 +132416,11 @@ "same_17_21_and_10 = 0.0\n", "same_17_21_and_11 = 0.0\n", "same_17_21_and_12 = 0.0\n", - "same_17_21_and_13 = 1.0\n", + "same_17_21_and_13 = 0.0\n", "same_17_21_and_14 = 0.0\n", "same_17_21_and_15 = 0.0\n", "same_17_21_and_2 = 0.0\n", - "same_17_21_and_3 = 0.0\n", + "same_17_21_and_3 = 1.0\n", "same_17_21_and_4 = 0.0\n", "same_17_21_and_5 = 0.0\n", "same_17_21_and_6 = 0.0\n", @@ -132443,11 +132433,11 @@ "same_17_22_and_10 = 0.0\n", "same_17_22_and_11 = 0.0\n", "same_17_22_and_12 = 0.0\n", - "same_17_22_and_13 = 1.0\n", + "same_17_22_and_13 = 0.0\n", "same_17_22_and_14 = 0.0\n", "same_17_22_and_15 = 0.0\n", "same_17_22_and_2 = 0.0\n", - "same_17_22_and_3 = 0.0\n", + "same_17_22_and_3 = 1.0\n", "same_17_22_and_4 = 0.0\n", "same_17_22_and_5 = 0.0\n", "same_17_22_and_6 = 0.0\n", @@ -132460,11 +132450,11 @@ "same_17_23_and_10 = 0.0\n", "same_17_23_and_11 = 0.0\n", "same_17_23_and_12 = 0.0\n", - "same_17_23_and_13 = 1.0\n", + "same_17_23_and_13 = 0.0\n", "same_17_23_and_14 = 0.0\n", "same_17_23_and_15 = 0.0\n", "same_17_23_and_2 = 0.0\n", - "same_17_23_and_3 = 0.0\n", + "same_17_23_and_3 = 1.0\n", "same_17_23_and_4 = 0.0\n", "same_17_23_and_5 = 0.0\n", "same_17_23_and_6 = 0.0\n", @@ -132477,11 +132467,11 @@ "same_17_24_and_10 = 0.0\n", "same_17_24_and_11 = 0.0\n", "same_17_24_and_12 = 0.0\n", - "same_17_24_and_13 = 1.0\n", + "same_17_24_and_13 = 0.0\n", "same_17_24_and_14 = 0.0\n", "same_17_24_and_15 = 0.0\n", "same_17_24_and_2 = 0.0\n", - "same_17_24_and_3 = 0.0\n", + "same_17_24_and_3 = 1.0\n", "same_17_24_and_4 = 0.0\n", "same_17_24_and_5 = 0.0\n", "same_17_24_and_6 = 0.0\n", @@ -132494,18 +132484,18 @@ "same_17_25_and_10 = 0.0\n", "same_17_25_and_11 = 0.0\n", "same_17_25_and_12 = 0.0\n", - "same_17_25_and_13 = 1.0\n", + "same_17_25_and_13 = 0.0\n", "same_17_25_and_14 = 0.0\n", "same_17_25_and_15 = 0.0\n", "same_17_25_and_2 = 0.0\n", - "same_17_25_and_3 = 0.0\n", + "same_17_25_and_3 = 1.0\n", "same_17_25_and_4 = 0.0\n", "same_17_25_and_5 = 0.0\n", "same_17_25_and_6 = 0.0\n", "same_17_25_and_7 = 0.0\n", "same_17_25_and_8 = 0.0\n", "same_17_25_and_9 = 0.0\n", - "same_17_26 = 0.0\n", + "same_17_26 = 1.0\n", "same_17_26_and_0 = 0.0\n", "same_17_26_and_1 = 0.0\n", "same_17_26_and_10 = 0.0\n", @@ -132515,14 +132505,14 @@ "same_17_26_and_14 = 0.0\n", "same_17_26_and_15 = 0.0\n", "same_17_26_and_2 = 0.0\n", - "same_17_26_and_3 = 0.0\n", + "same_17_26_and_3 = 1.0\n", "same_17_26_and_4 = 0.0\n", "same_17_26_and_5 = 0.0\n", "same_17_26_and_6 = 0.0\n", "same_17_26_and_7 = 0.0\n", "same_17_26_and_8 = 0.0\n", "same_17_26_and_9 = 0.0\n", - "same_17_27 = 0.0\n", + "same_17_27 = 1.0\n", "same_17_27_and_0 = 0.0\n", "same_17_27_and_1 = 0.0\n", "same_17_27_and_10 = 0.0\n", @@ -132532,14 +132522,14 @@ "same_17_27_and_14 = 0.0\n", "same_17_27_and_15 = 0.0\n", "same_17_27_and_2 = 0.0\n", - "same_17_27_and_3 = 0.0\n", + "same_17_27_and_3 = 1.0\n", "same_17_27_and_4 = 0.0\n", "same_17_27_and_5 = 0.0\n", "same_17_27_and_6 = 0.0\n", "same_17_27_and_7 = 0.0\n", "same_17_27_and_8 = 0.0\n", "same_17_27_and_9 = 0.0\n", - "same_17_28 = 0.0\n", + "same_17_28 = 1.0\n", "same_17_28_and_0 = 0.0\n", "same_17_28_and_1 = 0.0\n", "same_17_28_and_10 = 0.0\n", @@ -132549,14 +132539,14 @@ "same_17_28_and_14 = 0.0\n", "same_17_28_and_15 = 0.0\n", "same_17_28_and_2 = 0.0\n", - "same_17_28_and_3 = 0.0\n", + "same_17_28_and_3 = 1.0\n", "same_17_28_and_4 = 0.0\n", "same_17_28_and_5 = 0.0\n", "same_17_28_and_6 = 0.0\n", "same_17_28_and_7 = 0.0\n", "same_17_28_and_8 = 0.0\n", "same_17_28_and_9 = 0.0\n", - "same_17_29 = 0.0\n", + "same_17_29 = 1.0\n", "same_17_29_and_0 = 0.0\n", "same_17_29_and_1 = 0.0\n", "same_17_29_and_10 = 0.0\n", @@ -132566,14 +132556,14 @@ "same_17_29_and_14 = 0.0\n", "same_17_29_and_15 = 0.0\n", "same_17_29_and_2 = 0.0\n", - "same_17_29_and_3 = 0.0\n", + "same_17_29_and_3 = 1.0\n", "same_17_29_and_4 = 0.0\n", "same_17_29_and_5 = 0.0\n", "same_17_29_and_6 = 0.0\n", "same_17_29_and_7 = 0.0\n", "same_17_29_and_8 = 0.0\n", "same_17_29_and_9 = 0.0\n", - "same_17_30 = 0.0\n", + "same_17_30 = 1.0\n", "same_17_30_and_0 = 0.0\n", "same_17_30_and_1 = 0.0\n", "same_17_30_and_10 = 0.0\n", @@ -132583,14 +132573,14 @@ "same_17_30_and_14 = 0.0\n", "same_17_30_and_15 = 0.0\n", "same_17_30_and_2 = 0.0\n", - "same_17_30_and_3 = 0.0\n", + "same_17_30_and_3 = 1.0\n", "same_17_30_and_4 = 0.0\n", "same_17_30_and_5 = 0.0\n", "same_17_30_and_6 = 0.0\n", "same_17_30_and_7 = 0.0\n", "same_17_30_and_8 = 0.0\n", "same_17_30_and_9 = 0.0\n", - "same_17_31 = 0.0\n", + "same_17_31 = 1.0\n", "same_17_31_and_0 = 0.0\n", "same_17_31_and_1 = 0.0\n", "same_17_31_and_10 = 0.0\n", @@ -132600,14 +132590,14 @@ "same_17_31_and_14 = 0.0\n", "same_17_31_and_15 = 0.0\n", "same_17_31_and_2 = 0.0\n", - "same_17_31_and_3 = 0.0\n", + "same_17_31_and_3 = 1.0\n", "same_17_31_and_4 = 0.0\n", "same_17_31_and_5 = 0.0\n", "same_17_31_and_6 = 0.0\n", "same_17_31_and_7 = 0.0\n", "same_17_31_and_8 = 0.0\n", "same_17_31_and_9 = 0.0\n", - "same_17_32 = 0.0\n", + "same_17_32 = 1.0\n", "same_17_32_and_0 = 0.0\n", "same_17_32_and_1 = 0.0\n", "same_17_32_and_10 = 0.0\n", @@ -132617,14 +132607,14 @@ "same_17_32_and_14 = 0.0\n", "same_17_32_and_15 = 0.0\n", "same_17_32_and_2 = 0.0\n", - "same_17_32_and_3 = 0.0\n", + "same_17_32_and_3 = 1.0\n", "same_17_32_and_4 = 0.0\n", "same_17_32_and_5 = 0.0\n", "same_17_32_and_6 = 0.0\n", "same_17_32_and_7 = 0.0\n", "same_17_32_and_8 = 0.0\n", "same_17_32_and_9 = 0.0\n", - "same_17_33 = 0.0\n", + "same_17_33 = 1.0\n", "same_17_33_and_0 = 0.0\n", "same_17_33_and_1 = 0.0\n", "same_17_33_and_10 = 0.0\n", @@ -132634,14 +132624,14 @@ "same_17_33_and_14 = 0.0\n", "same_17_33_and_15 = 0.0\n", "same_17_33_and_2 = 0.0\n", - "same_17_33_and_3 = 0.0\n", + "same_17_33_and_3 = 1.0\n", "same_17_33_and_4 = 0.0\n", "same_17_33_and_5 = 0.0\n", "same_17_33_and_6 = 0.0\n", "same_17_33_and_7 = 0.0\n", "same_17_33_and_8 = 0.0\n", "same_17_33_and_9 = 0.0\n", - "same_17_34 = 0.0\n", + "same_17_34 = 1.0\n", "same_17_34_and_0 = 0.0\n", "same_17_34_and_1 = 0.0\n", "same_17_34_and_10 = 0.0\n", @@ -132651,7 +132641,7 @@ "same_17_34_and_14 = 0.0\n", "same_17_34_and_15 = 0.0\n", "same_17_34_and_2 = 0.0\n", - "same_17_34_and_3 = 0.0\n", + "same_17_34_and_3 = 1.0\n", "same_17_34_and_4 = 0.0\n", "same_17_34_and_5 = 0.0\n", "same_17_34_and_6 = 0.0\n", @@ -133260,11 +133250,11 @@ "same_18_19_and_10 = 0.0\n", "same_18_19_and_11 = 0.0\n", "same_18_19_and_12 = 0.0\n", - "same_18_19_and_13 = 1.0\n", + "same_18_19_and_13 = 0.0\n", "same_18_19_and_14 = 0.0\n", "same_18_19_and_15 = 0.0\n", "same_18_19_and_2 = 0.0\n", - "same_18_19_and_3 = 0.0\n", + "same_18_19_and_3 = 1.0\n", "same_18_19_and_4 = 0.0\n", "same_18_19_and_5 = 0.0\n", "same_18_19_and_6 = 0.0\n", @@ -133277,11 +133267,11 @@ "same_18_20_and_10 = 0.0\n", "same_18_20_and_11 = 0.0\n", "same_18_20_and_12 = 0.0\n", - "same_18_20_and_13 = 1.0\n", + "same_18_20_and_13 = 0.0\n", "same_18_20_and_14 = 0.0\n", "same_18_20_and_15 = 0.0\n", "same_18_20_and_2 = 0.0\n", - "same_18_20_and_3 = 0.0\n", + "same_18_20_and_3 = 1.0\n", "same_18_20_and_4 = 0.0\n", "same_18_20_and_5 = 0.0\n", "same_18_20_and_6 = 0.0\n", @@ -133294,11 +133284,11 @@ "same_18_21_and_10 = 0.0\n", "same_18_21_and_11 = 0.0\n", "same_18_21_and_12 = 0.0\n", - "same_18_21_and_13 = 1.0\n", + "same_18_21_and_13 = 0.0\n", "same_18_21_and_14 = 0.0\n", "same_18_21_and_15 = 0.0\n", "same_18_21_and_2 = 0.0\n", - "same_18_21_and_3 = 0.0\n", + "same_18_21_and_3 = 1.0\n", "same_18_21_and_4 = 0.0\n", "same_18_21_and_5 = 0.0\n", "same_18_21_and_6 = 0.0\n", @@ -133311,11 +133301,11 @@ "same_18_22_and_10 = 0.0\n", "same_18_22_and_11 = 0.0\n", "same_18_22_and_12 = 0.0\n", - "same_18_22_and_13 = 1.0\n", + "same_18_22_and_13 = 0.0\n", "same_18_22_and_14 = 0.0\n", "same_18_22_and_15 = 0.0\n", "same_18_22_and_2 = 0.0\n", - "same_18_22_and_3 = 0.0\n", + "same_18_22_and_3 = 1.0\n", "same_18_22_and_4 = 0.0\n", "same_18_22_and_5 = 0.0\n", "same_18_22_and_6 = 0.0\n", @@ -133328,11 +133318,11 @@ "same_18_23_and_10 = 0.0\n", "same_18_23_and_11 = 0.0\n", "same_18_23_and_12 = 0.0\n", - "same_18_23_and_13 = 1.0\n", + "same_18_23_and_13 = 0.0\n", "same_18_23_and_14 = 0.0\n", "same_18_23_and_15 = 0.0\n", "same_18_23_and_2 = 0.0\n", - "same_18_23_and_3 = 0.0\n", + "same_18_23_and_3 = 1.0\n", "same_18_23_and_4 = 0.0\n", "same_18_23_and_5 = 0.0\n", "same_18_23_and_6 = 0.0\n", @@ -133345,11 +133335,11 @@ "same_18_24_and_10 = 0.0\n", "same_18_24_and_11 = 0.0\n", "same_18_24_and_12 = 0.0\n", - "same_18_24_and_13 = 1.0\n", + "same_18_24_and_13 = 0.0\n", "same_18_24_and_14 = 0.0\n", "same_18_24_and_15 = 0.0\n", "same_18_24_and_2 = 0.0\n", - "same_18_24_and_3 = 0.0\n", + "same_18_24_and_3 = 1.0\n", "same_18_24_and_4 = 0.0\n", "same_18_24_and_5 = 0.0\n", "same_18_24_and_6 = 0.0\n", @@ -133362,18 +133352,18 @@ "same_18_25_and_10 = 0.0\n", "same_18_25_and_11 = 0.0\n", "same_18_25_and_12 = 0.0\n", - "same_18_25_and_13 = 1.0\n", + "same_18_25_and_13 = 0.0\n", "same_18_25_and_14 = 0.0\n", "same_18_25_and_15 = 0.0\n", "same_18_25_and_2 = 0.0\n", - "same_18_25_and_3 = 0.0\n", + "same_18_25_and_3 = 1.0\n", "same_18_25_and_4 = 0.0\n", "same_18_25_and_5 = 0.0\n", "same_18_25_and_6 = 0.0\n", "same_18_25_and_7 = 0.0\n", "same_18_25_and_8 = 0.0\n", "same_18_25_and_9 = 0.0\n", - "same_18_26 = 0.0\n", + "same_18_26 = 1.0\n", "same_18_26_and_0 = 0.0\n", "same_18_26_and_1 = 0.0\n", "same_18_26_and_10 = 0.0\n", @@ -133383,14 +133373,14 @@ "same_18_26_and_14 = 0.0\n", "same_18_26_and_15 = 0.0\n", "same_18_26_and_2 = 0.0\n", - "same_18_26_and_3 = 0.0\n", + "same_18_26_and_3 = 1.0\n", "same_18_26_and_4 = 0.0\n", "same_18_26_and_5 = 0.0\n", "same_18_26_and_6 = 0.0\n", "same_18_26_and_7 = 0.0\n", "same_18_26_and_8 = 0.0\n", "same_18_26_and_9 = 0.0\n", - "same_18_27 = 0.0\n", + "same_18_27 = 1.0\n", "same_18_27_and_0 = 0.0\n", "same_18_27_and_1 = 0.0\n", "same_18_27_and_10 = 0.0\n", @@ -133400,14 +133390,14 @@ "same_18_27_and_14 = 0.0\n", "same_18_27_and_15 = 0.0\n", "same_18_27_and_2 = 0.0\n", - "same_18_27_and_3 = 0.0\n", + "same_18_27_and_3 = 1.0\n", "same_18_27_and_4 = 0.0\n", "same_18_27_and_5 = 0.0\n", "same_18_27_and_6 = 0.0\n", "same_18_27_and_7 = 0.0\n", "same_18_27_and_8 = 0.0\n", "same_18_27_and_9 = 0.0\n", - "same_18_28 = 0.0\n", + "same_18_28 = 1.0\n", "same_18_28_and_0 = 0.0\n", "same_18_28_and_1 = 0.0\n", "same_18_28_and_10 = 0.0\n", @@ -133417,14 +133407,14 @@ "same_18_28_and_14 = 0.0\n", "same_18_28_and_15 = 0.0\n", "same_18_28_and_2 = 0.0\n", - "same_18_28_and_3 = 0.0\n", + "same_18_28_and_3 = 1.0\n", "same_18_28_and_4 = 0.0\n", "same_18_28_and_5 = 0.0\n", "same_18_28_and_6 = 0.0\n", "same_18_28_and_7 = 0.0\n", "same_18_28_and_8 = 0.0\n", "same_18_28_and_9 = 0.0\n", - "same_18_29 = 0.0\n", + "same_18_29 = 1.0\n", "same_18_29_and_0 = 0.0\n", "same_18_29_and_1 = 0.0\n", "same_18_29_and_10 = 0.0\n", @@ -133434,14 +133424,14 @@ "same_18_29_and_14 = 0.0\n", "same_18_29_and_15 = 0.0\n", "same_18_29_and_2 = 0.0\n", - "same_18_29_and_3 = 0.0\n", + "same_18_29_and_3 = 1.0\n", "same_18_29_and_4 = 0.0\n", "same_18_29_and_5 = 0.0\n", "same_18_29_and_6 = 0.0\n", "same_18_29_and_7 = 0.0\n", "same_18_29_and_8 = 0.0\n", "same_18_29_and_9 = 0.0\n", - "same_18_30 = 0.0\n", + "same_18_30 = 1.0\n", "same_18_30_and_0 = 0.0\n", "same_18_30_and_1 = 0.0\n", "same_18_30_and_10 = 0.0\n", @@ -133451,14 +133441,14 @@ "same_18_30_and_14 = 0.0\n", "same_18_30_and_15 = 0.0\n", "same_18_30_and_2 = 0.0\n", - "same_18_30_and_3 = 0.0\n", + "same_18_30_and_3 = 1.0\n", "same_18_30_and_4 = 0.0\n", "same_18_30_and_5 = 0.0\n", "same_18_30_and_6 = 0.0\n", "same_18_30_and_7 = 0.0\n", "same_18_30_and_8 = 0.0\n", "same_18_30_and_9 = 0.0\n", - "same_18_31 = 0.0\n", + "same_18_31 = 1.0\n", "same_18_31_and_0 = 0.0\n", "same_18_31_and_1 = 0.0\n", "same_18_31_and_10 = 0.0\n", @@ -133468,14 +133458,14 @@ "same_18_31_and_14 = 0.0\n", "same_18_31_and_15 = 0.0\n", "same_18_31_and_2 = 0.0\n", - "same_18_31_and_3 = 0.0\n", + "same_18_31_and_3 = 1.0\n", "same_18_31_and_4 = 0.0\n", "same_18_31_and_5 = 0.0\n", "same_18_31_and_6 = 0.0\n", "same_18_31_and_7 = 0.0\n", "same_18_31_and_8 = 0.0\n", "same_18_31_and_9 = 0.0\n", - "same_18_32 = 0.0\n", + "same_18_32 = 1.0\n", "same_18_32_and_0 = 0.0\n", "same_18_32_and_1 = 0.0\n", "same_18_32_and_10 = 0.0\n", @@ -133485,14 +133475,14 @@ "same_18_32_and_14 = 0.0\n", "same_18_32_and_15 = 0.0\n", "same_18_32_and_2 = 0.0\n", - "same_18_32_and_3 = 0.0\n", + "same_18_32_and_3 = 1.0\n", "same_18_32_and_4 = 0.0\n", "same_18_32_and_5 = 0.0\n", "same_18_32_and_6 = 0.0\n", "same_18_32_and_7 = 0.0\n", "same_18_32_and_8 = 0.0\n", "same_18_32_and_9 = 0.0\n", - "same_18_33 = 0.0\n", + "same_18_33 = 1.0\n", "same_18_33_and_0 = 0.0\n", "same_18_33_and_1 = 0.0\n", "same_18_33_and_10 = 0.0\n", @@ -133502,14 +133492,14 @@ "same_18_33_and_14 = 0.0\n", "same_18_33_and_15 = 0.0\n", "same_18_33_and_2 = 0.0\n", - "same_18_33_and_3 = 0.0\n", + "same_18_33_and_3 = 1.0\n", "same_18_33_and_4 = 0.0\n", "same_18_33_and_5 = 0.0\n", "same_18_33_and_6 = 0.0\n", "same_18_33_and_7 = 0.0\n", "same_18_33_and_8 = 0.0\n", "same_18_33_and_9 = 0.0\n", - "same_18_34 = 0.0\n", + "same_18_34 = 1.0\n", "same_18_34_and_0 = 0.0\n", "same_18_34_and_1 = 0.0\n", "same_18_34_and_10 = 0.0\n", @@ -133519,7 +133509,7 @@ "same_18_34_and_14 = 0.0\n", "same_18_34_and_15 = 0.0\n", "same_18_34_and_2 = 0.0\n", - "same_18_34_and_3 = 0.0\n", + "same_18_34_and_3 = 1.0\n", "same_18_34_and_4 = 0.0\n", "same_18_34_and_5 = 0.0\n", "same_18_34_and_6 = 0.0\n", @@ -134128,11 +134118,11 @@ "same_19_20_and_10 = 0.0\n", "same_19_20_and_11 = 0.0\n", "same_19_20_and_12 = 0.0\n", - "same_19_20_and_13 = 1.0\n", + "same_19_20_and_13 = 0.0\n", "same_19_20_and_14 = 0.0\n", "same_19_20_and_15 = 0.0\n", "same_19_20_and_2 = 0.0\n", - "same_19_20_and_3 = 0.0\n", + "same_19_20_and_3 = 1.0\n", "same_19_20_and_4 = 0.0\n", "same_19_20_and_5 = 0.0\n", "same_19_20_and_6 = 0.0\n", @@ -134145,11 +134135,11 @@ "same_19_21_and_10 = 0.0\n", "same_19_21_and_11 = 0.0\n", "same_19_21_and_12 = 0.0\n", - "same_19_21_and_13 = 1.0\n", + "same_19_21_and_13 = 0.0\n", "same_19_21_and_14 = 0.0\n", "same_19_21_and_15 = 0.0\n", "same_19_21_and_2 = 0.0\n", - "same_19_21_and_3 = 0.0\n", + "same_19_21_and_3 = 1.0\n", "same_19_21_and_4 = 0.0\n", "same_19_21_and_5 = 0.0\n", "same_19_21_and_6 = 0.0\n", @@ -134162,11 +134152,11 @@ "same_19_22_and_10 = 0.0\n", "same_19_22_and_11 = 0.0\n", "same_19_22_and_12 = 0.0\n", - "same_19_22_and_13 = 1.0\n", + "same_19_22_and_13 = 0.0\n", "same_19_22_and_14 = 0.0\n", "same_19_22_and_15 = 0.0\n", "same_19_22_and_2 = 0.0\n", - "same_19_22_and_3 = 0.0\n", + "same_19_22_and_3 = 1.0\n", "same_19_22_and_4 = 0.0\n", "same_19_22_and_5 = 0.0\n", "same_19_22_and_6 = 0.0\n", @@ -134179,11 +134169,11 @@ "same_19_23_and_10 = 0.0\n", "same_19_23_and_11 = 0.0\n", "same_19_23_and_12 = 0.0\n", - "same_19_23_and_13 = 1.0\n", + "same_19_23_and_13 = 0.0\n", "same_19_23_and_14 = 0.0\n", "same_19_23_and_15 = 0.0\n", "same_19_23_and_2 = 0.0\n", - "same_19_23_and_3 = 0.0\n", + "same_19_23_and_3 = 1.0\n", "same_19_23_and_4 = 0.0\n", "same_19_23_and_5 = 0.0\n", "same_19_23_and_6 = 0.0\n", @@ -134196,11 +134186,11 @@ "same_19_24_and_10 = 0.0\n", "same_19_24_and_11 = 0.0\n", "same_19_24_and_12 = 0.0\n", - "same_19_24_and_13 = 1.0\n", + "same_19_24_and_13 = 0.0\n", "same_19_24_and_14 = 0.0\n", "same_19_24_and_15 = 0.0\n", "same_19_24_and_2 = 0.0\n", - "same_19_24_and_3 = 0.0\n", + "same_19_24_and_3 = 1.0\n", "same_19_24_and_4 = 0.0\n", "same_19_24_and_5 = 0.0\n", "same_19_24_and_6 = 0.0\n", @@ -134213,18 +134203,18 @@ "same_19_25_and_10 = 0.0\n", "same_19_25_and_11 = 0.0\n", "same_19_25_and_12 = 0.0\n", - "same_19_25_and_13 = 1.0\n", + "same_19_25_and_13 = 0.0\n", "same_19_25_and_14 = 0.0\n", "same_19_25_and_15 = 0.0\n", "same_19_25_and_2 = 0.0\n", - "same_19_25_and_3 = 0.0\n", + "same_19_25_and_3 = 1.0\n", "same_19_25_and_4 = 0.0\n", "same_19_25_and_5 = 0.0\n", "same_19_25_and_6 = 0.0\n", "same_19_25_and_7 = 0.0\n", "same_19_25_and_8 = 0.0\n", "same_19_25_and_9 = 0.0\n", - "same_19_26 = 0.0\n", + "same_19_26 = 1.0\n", "same_19_26_and_0 = 0.0\n", "same_19_26_and_1 = 0.0\n", "same_19_26_and_10 = 0.0\n", @@ -134234,14 +134224,14 @@ "same_19_26_and_14 = 0.0\n", "same_19_26_and_15 = 0.0\n", "same_19_26_and_2 = 0.0\n", - "same_19_26_and_3 = 0.0\n", + "same_19_26_and_3 = 1.0\n", "same_19_26_and_4 = 0.0\n", "same_19_26_and_5 = 0.0\n", "same_19_26_and_6 = 0.0\n", "same_19_26_and_7 = 0.0\n", "same_19_26_and_8 = 0.0\n", "same_19_26_and_9 = 0.0\n", - "same_19_27 = 0.0\n", + "same_19_27 = 1.0\n", "same_19_27_and_0 = 0.0\n", "same_19_27_and_1 = 0.0\n", "same_19_27_and_10 = 0.0\n", @@ -134251,14 +134241,14 @@ "same_19_27_and_14 = 0.0\n", "same_19_27_and_15 = 0.0\n", "same_19_27_and_2 = 0.0\n", - "same_19_27_and_3 = 0.0\n", + "same_19_27_and_3 = 1.0\n", "same_19_27_and_4 = 0.0\n", "same_19_27_and_5 = 0.0\n", "same_19_27_and_6 = 0.0\n", "same_19_27_and_7 = 0.0\n", "same_19_27_and_8 = 0.0\n", "same_19_27_and_9 = 0.0\n", - "same_19_28 = 0.0\n", + "same_19_28 = 1.0\n", "same_19_28_and_0 = 0.0\n", "same_19_28_and_1 = 0.0\n", "same_19_28_and_10 = 0.0\n", @@ -134268,14 +134258,14 @@ "same_19_28_and_14 = 0.0\n", "same_19_28_and_15 = 0.0\n", "same_19_28_and_2 = 0.0\n", - "same_19_28_and_3 = 0.0\n", + "same_19_28_and_3 = 1.0\n", "same_19_28_and_4 = 0.0\n", "same_19_28_and_5 = 0.0\n", "same_19_28_and_6 = 0.0\n", "same_19_28_and_7 = 0.0\n", "same_19_28_and_8 = 0.0\n", "same_19_28_and_9 = 0.0\n", - "same_19_29 = 0.0\n", + "same_19_29 = 1.0\n", "same_19_29_and_0 = 0.0\n", "same_19_29_and_1 = 0.0\n", "same_19_29_and_10 = 0.0\n", @@ -134285,14 +134275,14 @@ "same_19_29_and_14 = 0.0\n", "same_19_29_and_15 = 0.0\n", "same_19_29_and_2 = 0.0\n", - "same_19_29_and_3 = 0.0\n", + "same_19_29_and_3 = 1.0\n", "same_19_29_and_4 = 0.0\n", "same_19_29_and_5 = 0.0\n", "same_19_29_and_6 = 0.0\n", "same_19_29_and_7 = 0.0\n", "same_19_29_and_8 = 0.0\n", "same_19_29_and_9 = 0.0\n", - "same_19_30 = 0.0\n", + "same_19_30 = 1.0\n", "same_19_30_and_0 = 0.0\n", "same_19_30_and_1 = 0.0\n", "same_19_30_and_10 = 0.0\n", @@ -134302,14 +134292,14 @@ "same_19_30_and_14 = 0.0\n", "same_19_30_and_15 = 0.0\n", "same_19_30_and_2 = 0.0\n", - "same_19_30_and_3 = 0.0\n", + "same_19_30_and_3 = 1.0\n", "same_19_30_and_4 = 0.0\n", "same_19_30_and_5 = 0.0\n", "same_19_30_and_6 = 0.0\n", "same_19_30_and_7 = 0.0\n", "same_19_30_and_8 = 0.0\n", "same_19_30_and_9 = 0.0\n", - "same_19_31 = 0.0\n", + "same_19_31 = 1.0\n", "same_19_31_and_0 = 0.0\n", "same_19_31_and_1 = 0.0\n", "same_19_31_and_10 = 0.0\n", @@ -134319,14 +134309,14 @@ "same_19_31_and_14 = 0.0\n", "same_19_31_and_15 = 0.0\n", "same_19_31_and_2 = 0.0\n", - "same_19_31_and_3 = 0.0\n", + "same_19_31_and_3 = 1.0\n", "same_19_31_and_4 = 0.0\n", "same_19_31_and_5 = 0.0\n", "same_19_31_and_6 = 0.0\n", "same_19_31_and_7 = 0.0\n", "same_19_31_and_8 = 0.0\n", "same_19_31_and_9 = 0.0\n", - "same_19_32 = 0.0\n", + "same_19_32 = 1.0\n", "same_19_32_and_0 = 0.0\n", "same_19_32_and_1 = 0.0\n", "same_19_32_and_10 = 0.0\n", @@ -134336,14 +134326,14 @@ "same_19_32_and_14 = 0.0\n", "same_19_32_and_15 = 0.0\n", "same_19_32_and_2 = 0.0\n", - "same_19_32_and_3 = 0.0\n", + "same_19_32_and_3 = 1.0\n", "same_19_32_and_4 = 0.0\n", "same_19_32_and_5 = 0.0\n", "same_19_32_and_6 = 0.0\n", "same_19_32_and_7 = 0.0\n", "same_19_32_and_8 = 0.0\n", "same_19_32_and_9 = 0.0\n", - "same_19_33 = 0.0\n", + "same_19_33 = 1.0\n", "same_19_33_and_0 = 0.0\n", "same_19_33_and_1 = 0.0\n", "same_19_33_and_10 = 0.0\n", @@ -134353,14 +134343,14 @@ "same_19_33_and_14 = 0.0\n", "same_19_33_and_15 = 0.0\n", "same_19_33_and_2 = 0.0\n", - "same_19_33_and_3 = 0.0\n", + "same_19_33_and_3 = 1.0\n", "same_19_33_and_4 = 0.0\n", "same_19_33_and_5 = 0.0\n", "same_19_33_and_6 = 0.0\n", "same_19_33_and_7 = 0.0\n", "same_19_33_and_8 = 0.0\n", "same_19_33_and_9 = 0.0\n", - "same_19_34 = 0.0\n", + "same_19_34 = 1.0\n", "same_19_34_and_0 = 0.0\n", "same_19_34_and_1 = 0.0\n", "same_19_34_and_10 = 0.0\n", @@ -134370,7 +134360,7 @@ "same_19_34_and_14 = 0.0\n", "same_19_34_and_15 = 0.0\n", "same_19_34_and_2 = 0.0\n", - "same_19_34_and_3 = 0.0\n", + "same_19_34_and_3 = 1.0\n", "same_19_34_and_4 = 0.0\n", "same_19_34_and_5 = 0.0\n", "same_19_34_and_6 = 0.0\n", @@ -135314,11 +135304,11 @@ "same_1_29_and_7 = 0.0\n", "same_1_29_and_8 = 0.0\n", "same_1_29_and_9 = 0.0\n", - "same_1_2_and_0 = 0.0\n", + "same_1_2_and_0 = 1.0\n", "same_1_2_and_1 = 0.0\n", "same_1_2_and_10 = 0.0\n", "same_1_2_and_11 = 0.0\n", - "same_1_2_and_12 = 1.0\n", + "same_1_2_and_12 = 0.0\n", "same_1_2_and_13 = 0.0\n", "same_1_2_and_14 = 0.0\n", "same_1_2_and_15 = 0.0\n", @@ -135501,11 +135491,11 @@ "same_1_39_and_7 = 0.0\n", "same_1_39_and_8 = 0.0\n", "same_1_39_and_9 = 0.0\n", - "same_1_3_and_0 = 0.0\n", + "same_1_3_and_0 = 1.0\n", "same_1_3_and_1 = 0.0\n", "same_1_3_and_10 = 0.0\n", "same_1_3_and_11 = 0.0\n", - "same_1_3_and_12 = 1.0\n", + "same_1_3_and_12 = 0.0\n", "same_1_3_and_13 = 0.0\n", "same_1_3_and_14 = 0.0\n", "same_1_3_and_15 = 0.0\n", @@ -135517,7 +135507,7 @@ "same_1_3_and_7 = 0.0\n", "same_1_3_and_8 = 0.0\n", "same_1_3_and_9 = 0.0\n", - "same_1_4 = 1.0\n", + "same_1_4 = 0.0\n", "same_1_40 = 0.0\n", "same_1_40_and_0 = 0.0\n", "same_1_40_and_1 = 0.0\n", @@ -135692,7 +135682,7 @@ "same_1_4_and_1 = 0.0\n", "same_1_4_and_10 = 0.0\n", "same_1_4_and_11 = 0.0\n", - "same_1_4_and_12 = 1.0\n", + "same_1_4_and_12 = 0.0\n", "same_1_4_and_13 = 0.0\n", "same_1_4_and_14 = 0.0\n", "same_1_4_and_15 = 0.0\n", @@ -135704,7 +135694,7 @@ "same_1_4_and_7 = 0.0\n", "same_1_4_and_8 = 0.0\n", "same_1_4_and_9 = 0.0\n", - "same_1_5 = 1.0\n", + "same_1_5 = 0.0\n", "same_1_50 = 0.0\n", "same_1_50_and_0 = 0.0\n", "same_1_50_and_1 = 0.0\n", @@ -135879,7 +135869,7 @@ "same_1_5_and_1 = 0.0\n", "same_1_5_and_10 = 0.0\n", "same_1_5_and_11 = 0.0\n", - "same_1_5_and_12 = 1.0\n", + "same_1_5_and_12 = 0.0\n", "same_1_5_and_13 = 0.0\n", "same_1_5_and_14 = 0.0\n", "same_1_5_and_15 = 0.0\n", @@ -135891,7 +135881,7 @@ "same_1_5_and_7 = 0.0\n", "same_1_5_and_8 = 0.0\n", "same_1_5_and_9 = 0.0\n", - "same_1_6 = 1.0\n", + "same_1_6 = 0.0\n", "same_1_60 = 0.0\n", "same_1_60_and_0 = 0.0\n", "same_1_60_and_1 = 0.0\n", @@ -136066,7 +136056,7 @@ "same_1_6_and_1 = 0.0\n", "same_1_6_and_10 = 0.0\n", "same_1_6_and_11 = 0.0\n", - "same_1_6_and_12 = 1.0\n", + "same_1_6_and_12 = 0.0\n", "same_1_6_and_13 = 0.0\n", "same_1_6_and_14 = 0.0\n", "same_1_6_and_15 = 0.0\n", @@ -136136,11 +136126,11 @@ "same_20_21_and_10 = 0.0\n", "same_20_21_and_11 = 0.0\n", "same_20_21_and_12 = 0.0\n", - "same_20_21_and_13 = 1.0\n", + "same_20_21_and_13 = 0.0\n", "same_20_21_and_14 = 0.0\n", "same_20_21_and_15 = 0.0\n", "same_20_21_and_2 = 0.0\n", - "same_20_21_and_3 = 0.0\n", + "same_20_21_and_3 = 1.0\n", "same_20_21_and_4 = 0.0\n", "same_20_21_and_5 = 0.0\n", "same_20_21_and_6 = 0.0\n", @@ -136153,11 +136143,11 @@ "same_20_22_and_10 = 0.0\n", "same_20_22_and_11 = 0.0\n", "same_20_22_and_12 = 0.0\n", - "same_20_22_and_13 = 1.0\n", + "same_20_22_and_13 = 0.0\n", "same_20_22_and_14 = 0.0\n", "same_20_22_and_15 = 0.0\n", "same_20_22_and_2 = 0.0\n", - "same_20_22_and_3 = 0.0\n", + "same_20_22_and_3 = 1.0\n", "same_20_22_and_4 = 0.0\n", "same_20_22_and_5 = 0.0\n", "same_20_22_and_6 = 0.0\n", @@ -136170,11 +136160,11 @@ "same_20_23_and_10 = 0.0\n", "same_20_23_and_11 = 0.0\n", "same_20_23_and_12 = 0.0\n", - "same_20_23_and_13 = 1.0\n", + "same_20_23_and_13 = 0.0\n", "same_20_23_and_14 = 0.0\n", "same_20_23_and_15 = 0.0\n", "same_20_23_and_2 = 0.0\n", - "same_20_23_and_3 = 0.0\n", + "same_20_23_and_3 = 1.0\n", "same_20_23_and_4 = 0.0\n", "same_20_23_and_5 = 0.0\n", "same_20_23_and_6 = 0.0\n", @@ -136187,11 +136177,11 @@ "same_20_24_and_10 = 0.0\n", "same_20_24_and_11 = 0.0\n", "same_20_24_and_12 = 0.0\n", - "same_20_24_and_13 = 1.0\n", + "same_20_24_and_13 = 0.0\n", "same_20_24_and_14 = 0.0\n", "same_20_24_and_15 = 0.0\n", "same_20_24_and_2 = 0.0\n", - "same_20_24_and_3 = 0.0\n", + "same_20_24_and_3 = 1.0\n", "same_20_24_and_4 = 0.0\n", "same_20_24_and_5 = 0.0\n", "same_20_24_and_6 = 0.0\n", @@ -136204,18 +136194,18 @@ "same_20_25_and_10 = 0.0\n", "same_20_25_and_11 = 0.0\n", "same_20_25_and_12 = 0.0\n", - "same_20_25_and_13 = 1.0\n", + "same_20_25_and_13 = 0.0\n", "same_20_25_and_14 = 0.0\n", "same_20_25_and_15 = 0.0\n", "same_20_25_and_2 = 0.0\n", - "same_20_25_and_3 = 0.0\n", + "same_20_25_and_3 = 1.0\n", "same_20_25_and_4 = 0.0\n", "same_20_25_and_5 = 0.0\n", "same_20_25_and_6 = 0.0\n", "same_20_25_and_7 = 0.0\n", "same_20_25_and_8 = 0.0\n", "same_20_25_and_9 = 0.0\n", - "same_20_26 = 0.0\n", + "same_20_26 = 1.0\n", "same_20_26_and_0 = 0.0\n", "same_20_26_and_1 = 0.0\n", "same_20_26_and_10 = 0.0\n", @@ -136225,14 +136215,14 @@ "same_20_26_and_14 = 0.0\n", "same_20_26_and_15 = 0.0\n", "same_20_26_and_2 = 0.0\n", - "same_20_26_and_3 = 0.0\n", + "same_20_26_and_3 = 1.0\n", "same_20_26_and_4 = 0.0\n", "same_20_26_and_5 = 0.0\n", "same_20_26_and_6 = 0.0\n", "same_20_26_and_7 = 0.0\n", "same_20_26_and_8 = 0.0\n", "same_20_26_and_9 = 0.0\n", - "same_20_27 = 0.0\n", + "same_20_27 = 1.0\n", "same_20_27_and_0 = 0.0\n", "same_20_27_and_1 = 0.0\n", "same_20_27_and_10 = 0.0\n", @@ -136242,14 +136232,14 @@ "same_20_27_and_14 = 0.0\n", "same_20_27_and_15 = 0.0\n", "same_20_27_and_2 = 0.0\n", - "same_20_27_and_3 = 0.0\n", + "same_20_27_and_3 = 1.0\n", "same_20_27_and_4 = 0.0\n", "same_20_27_and_5 = 0.0\n", "same_20_27_and_6 = 0.0\n", "same_20_27_and_7 = 0.0\n", "same_20_27_and_8 = 0.0\n", "same_20_27_and_9 = 0.0\n", - "same_20_28 = 0.0\n", + "same_20_28 = 1.0\n", "same_20_28_and_0 = 0.0\n", "same_20_28_and_1 = 0.0\n", "same_20_28_and_10 = 0.0\n", @@ -136259,14 +136249,14 @@ "same_20_28_and_14 = 0.0\n", "same_20_28_and_15 = 0.0\n", "same_20_28_and_2 = 0.0\n", - "same_20_28_and_3 = 0.0\n", + "same_20_28_and_3 = 1.0\n", "same_20_28_and_4 = 0.0\n", "same_20_28_and_5 = 0.0\n", "same_20_28_and_6 = 0.0\n", "same_20_28_and_7 = 0.0\n", "same_20_28_and_8 = 0.0\n", "same_20_28_and_9 = 0.0\n", - "same_20_29 = 0.0\n", + "same_20_29 = 1.0\n", "same_20_29_and_0 = 0.0\n", "same_20_29_and_1 = 0.0\n", "same_20_29_and_10 = 0.0\n", @@ -136276,14 +136266,14 @@ "same_20_29_and_14 = 0.0\n", "same_20_29_and_15 = 0.0\n", "same_20_29_and_2 = 0.0\n", - "same_20_29_and_3 = 0.0\n", + "same_20_29_and_3 = 1.0\n", "same_20_29_and_4 = 0.0\n", "same_20_29_and_5 = 0.0\n", "same_20_29_and_6 = 0.0\n", "same_20_29_and_7 = 0.0\n", "same_20_29_and_8 = 0.0\n", "same_20_29_and_9 = 0.0\n", - "same_20_30 = 0.0\n", + "same_20_30 = 1.0\n", "same_20_30_and_0 = 0.0\n", "same_20_30_and_1 = 0.0\n", "same_20_30_and_10 = 0.0\n", @@ -136293,14 +136283,14 @@ "same_20_30_and_14 = 0.0\n", "same_20_30_and_15 = 0.0\n", "same_20_30_and_2 = 0.0\n", - "same_20_30_and_3 = 0.0\n", + "same_20_30_and_3 = 1.0\n", "same_20_30_and_4 = 0.0\n", "same_20_30_and_5 = 0.0\n", "same_20_30_and_6 = 0.0\n", "same_20_30_and_7 = 0.0\n", "same_20_30_and_8 = 0.0\n", "same_20_30_and_9 = 0.0\n", - "same_20_31 = 0.0\n", + "same_20_31 = 1.0\n", "same_20_31_and_0 = 0.0\n", "same_20_31_and_1 = 0.0\n", "same_20_31_and_10 = 0.0\n", @@ -136310,14 +136300,14 @@ "same_20_31_and_14 = 0.0\n", "same_20_31_and_15 = 0.0\n", "same_20_31_and_2 = 0.0\n", - "same_20_31_and_3 = 0.0\n", + "same_20_31_and_3 = 1.0\n", "same_20_31_and_4 = 0.0\n", "same_20_31_and_5 = 0.0\n", "same_20_31_and_6 = 0.0\n", "same_20_31_and_7 = 0.0\n", "same_20_31_and_8 = 0.0\n", "same_20_31_and_9 = 0.0\n", - "same_20_32 = 0.0\n", + "same_20_32 = 1.0\n", "same_20_32_and_0 = 0.0\n", "same_20_32_and_1 = 0.0\n", "same_20_32_and_10 = 0.0\n", @@ -136327,14 +136317,14 @@ "same_20_32_and_14 = 0.0\n", "same_20_32_and_15 = 0.0\n", "same_20_32_and_2 = 0.0\n", - "same_20_32_and_3 = 0.0\n", + "same_20_32_and_3 = 1.0\n", "same_20_32_and_4 = 0.0\n", "same_20_32_and_5 = 0.0\n", "same_20_32_and_6 = 0.0\n", "same_20_32_and_7 = 0.0\n", "same_20_32_and_8 = 0.0\n", "same_20_32_and_9 = 0.0\n", - "same_20_33 = 0.0\n", + "same_20_33 = 1.0\n", "same_20_33_and_0 = 0.0\n", "same_20_33_and_1 = 0.0\n", "same_20_33_and_10 = 0.0\n", @@ -136344,14 +136334,14 @@ "same_20_33_and_14 = 0.0\n", "same_20_33_and_15 = 0.0\n", "same_20_33_and_2 = 0.0\n", - "same_20_33_and_3 = 0.0\n", + "same_20_33_and_3 = 1.0\n", "same_20_33_and_4 = 0.0\n", "same_20_33_and_5 = 0.0\n", "same_20_33_and_6 = 0.0\n", "same_20_33_and_7 = 0.0\n", "same_20_33_and_8 = 0.0\n", "same_20_33_and_9 = 0.0\n", - "same_20_34 = 0.0\n", + "same_20_34 = 1.0\n", "same_20_34_and_0 = 0.0\n", "same_20_34_and_1 = 0.0\n", "same_20_34_and_10 = 0.0\n", @@ -136361,7 +136351,7 @@ "same_20_34_and_14 = 0.0\n", "same_20_34_and_15 = 0.0\n", "same_20_34_and_2 = 0.0\n", - "same_20_34_and_3 = 0.0\n", + "same_20_34_and_3 = 1.0\n", "same_20_34_and_4 = 0.0\n", "same_20_34_and_5 = 0.0\n", "same_20_34_and_6 = 0.0\n", @@ -136970,11 +136960,11 @@ "same_21_22_and_10 = 0.0\n", "same_21_22_and_11 = 0.0\n", "same_21_22_and_12 = 0.0\n", - "same_21_22_and_13 = 1.0\n", + "same_21_22_and_13 = 0.0\n", "same_21_22_and_14 = 0.0\n", "same_21_22_and_15 = 0.0\n", "same_21_22_and_2 = 0.0\n", - "same_21_22_and_3 = 0.0\n", + "same_21_22_and_3 = 1.0\n", "same_21_22_and_4 = 0.0\n", "same_21_22_and_5 = 0.0\n", "same_21_22_and_6 = 0.0\n", @@ -136987,11 +136977,11 @@ "same_21_23_and_10 = 0.0\n", "same_21_23_and_11 = 0.0\n", "same_21_23_and_12 = 0.0\n", - "same_21_23_and_13 = 1.0\n", + "same_21_23_and_13 = 0.0\n", "same_21_23_and_14 = 0.0\n", "same_21_23_and_15 = 0.0\n", "same_21_23_and_2 = 0.0\n", - "same_21_23_and_3 = 0.0\n", + "same_21_23_and_3 = 1.0\n", "same_21_23_and_4 = 0.0\n", "same_21_23_and_5 = 0.0\n", "same_21_23_and_6 = 0.0\n", @@ -137004,11 +136994,11 @@ "same_21_24_and_10 = 0.0\n", "same_21_24_and_11 = 0.0\n", "same_21_24_and_12 = 0.0\n", - "same_21_24_and_13 = 1.0\n", + "same_21_24_and_13 = 0.0\n", "same_21_24_and_14 = 0.0\n", "same_21_24_and_15 = 0.0\n", "same_21_24_and_2 = 0.0\n", - "same_21_24_and_3 = 0.0\n", + "same_21_24_and_3 = 1.0\n", "same_21_24_and_4 = 0.0\n", "same_21_24_and_5 = 0.0\n", "same_21_24_and_6 = 0.0\n", @@ -137021,18 +137011,18 @@ "same_21_25_and_10 = 0.0\n", "same_21_25_and_11 = 0.0\n", "same_21_25_and_12 = 0.0\n", - "same_21_25_and_13 = 1.0\n", + "same_21_25_and_13 = 0.0\n", "same_21_25_and_14 = 0.0\n", "same_21_25_and_15 = 0.0\n", "same_21_25_and_2 = 0.0\n", - "same_21_25_and_3 = 0.0\n", + "same_21_25_and_3 = 1.0\n", "same_21_25_and_4 = 0.0\n", "same_21_25_and_5 = 0.0\n", "same_21_25_and_6 = 0.0\n", "same_21_25_and_7 = 0.0\n", "same_21_25_and_8 = 0.0\n", "same_21_25_and_9 = 0.0\n", - "same_21_26 = 0.0\n", + "same_21_26 = 1.0\n", "same_21_26_and_0 = 0.0\n", "same_21_26_and_1 = 0.0\n", "same_21_26_and_10 = 0.0\n", @@ -137042,14 +137032,14 @@ "same_21_26_and_14 = 0.0\n", "same_21_26_and_15 = 0.0\n", "same_21_26_and_2 = 0.0\n", - "same_21_26_and_3 = 0.0\n", + "same_21_26_and_3 = 1.0\n", "same_21_26_and_4 = 0.0\n", "same_21_26_and_5 = 0.0\n", "same_21_26_and_6 = 0.0\n", "same_21_26_and_7 = 0.0\n", "same_21_26_and_8 = 0.0\n", "same_21_26_and_9 = 0.0\n", - "same_21_27 = 0.0\n", + "same_21_27 = 1.0\n", "same_21_27_and_0 = 0.0\n", "same_21_27_and_1 = 0.0\n", "same_21_27_and_10 = 0.0\n", @@ -137059,14 +137049,14 @@ "same_21_27_and_14 = 0.0\n", "same_21_27_and_15 = 0.0\n", "same_21_27_and_2 = 0.0\n", - "same_21_27_and_3 = 0.0\n", + "same_21_27_and_3 = 1.0\n", "same_21_27_and_4 = 0.0\n", "same_21_27_and_5 = 0.0\n", "same_21_27_and_6 = 0.0\n", "same_21_27_and_7 = 0.0\n", "same_21_27_and_8 = 0.0\n", "same_21_27_and_9 = 0.0\n", - "same_21_28 = 0.0\n", + "same_21_28 = 1.0\n", "same_21_28_and_0 = 0.0\n", "same_21_28_and_1 = 0.0\n", "same_21_28_and_10 = 0.0\n", @@ -137076,14 +137066,14 @@ "same_21_28_and_14 = 0.0\n", "same_21_28_and_15 = 0.0\n", "same_21_28_and_2 = 0.0\n", - "same_21_28_and_3 = 0.0\n", + "same_21_28_and_3 = 1.0\n", "same_21_28_and_4 = 0.0\n", "same_21_28_and_5 = 0.0\n", "same_21_28_and_6 = 0.0\n", "same_21_28_and_7 = 0.0\n", "same_21_28_and_8 = 0.0\n", "same_21_28_and_9 = 0.0\n", - "same_21_29 = 0.0\n", + "same_21_29 = 1.0\n", "same_21_29_and_0 = 0.0\n", "same_21_29_and_1 = 0.0\n", "same_21_29_and_10 = 0.0\n", @@ -137093,14 +137083,14 @@ "same_21_29_and_14 = 0.0\n", "same_21_29_and_15 = 0.0\n", "same_21_29_and_2 = 0.0\n", - "same_21_29_and_3 = 0.0\n", + "same_21_29_and_3 = 1.0\n", "same_21_29_and_4 = 0.0\n", "same_21_29_and_5 = 0.0\n", "same_21_29_and_6 = 0.0\n", "same_21_29_and_7 = 0.0\n", "same_21_29_and_8 = 0.0\n", "same_21_29_and_9 = 0.0\n", - "same_21_30 = 0.0\n", + "same_21_30 = 1.0\n", "same_21_30_and_0 = 0.0\n", "same_21_30_and_1 = 0.0\n", "same_21_30_and_10 = 0.0\n", @@ -137110,14 +137100,14 @@ "same_21_30_and_14 = 0.0\n", "same_21_30_and_15 = 0.0\n", "same_21_30_and_2 = 0.0\n", - "same_21_30_and_3 = 0.0\n", + "same_21_30_and_3 = 1.0\n", "same_21_30_and_4 = 0.0\n", "same_21_30_and_5 = 0.0\n", "same_21_30_and_6 = 0.0\n", "same_21_30_and_7 = 0.0\n", "same_21_30_and_8 = 0.0\n", "same_21_30_and_9 = 0.0\n", - "same_21_31 = 0.0\n", + "same_21_31 = 1.0\n", "same_21_31_and_0 = 0.0\n", "same_21_31_and_1 = 0.0\n", "same_21_31_and_10 = 0.0\n", @@ -137127,14 +137117,14 @@ "same_21_31_and_14 = 0.0\n", "same_21_31_and_15 = 0.0\n", "same_21_31_and_2 = 0.0\n", - "same_21_31_and_3 = 0.0\n", + "same_21_31_and_3 = 1.0\n", "same_21_31_and_4 = 0.0\n", "same_21_31_and_5 = 0.0\n", "same_21_31_and_6 = 0.0\n", "same_21_31_and_7 = 0.0\n", "same_21_31_and_8 = 0.0\n", "same_21_31_and_9 = 0.0\n", - "same_21_32 = 0.0\n", + "same_21_32 = 1.0\n", "same_21_32_and_0 = 0.0\n", "same_21_32_and_1 = 0.0\n", "same_21_32_and_10 = 0.0\n", @@ -137144,14 +137134,14 @@ "same_21_32_and_14 = 0.0\n", "same_21_32_and_15 = 0.0\n", "same_21_32_and_2 = 0.0\n", - "same_21_32_and_3 = 0.0\n", + "same_21_32_and_3 = 1.0\n", "same_21_32_and_4 = 0.0\n", "same_21_32_and_5 = 0.0\n", "same_21_32_and_6 = 0.0\n", "same_21_32_and_7 = 0.0\n", "same_21_32_and_8 = 0.0\n", "same_21_32_and_9 = 0.0\n", - "same_21_33 = 0.0\n", + "same_21_33 = 1.0\n", "same_21_33_and_0 = 0.0\n", "same_21_33_and_1 = 0.0\n", "same_21_33_and_10 = 0.0\n", @@ -137161,14 +137151,14 @@ "same_21_33_and_14 = 0.0\n", "same_21_33_and_15 = 0.0\n", "same_21_33_and_2 = 0.0\n", - "same_21_33_and_3 = 0.0\n", + "same_21_33_and_3 = 1.0\n", "same_21_33_and_4 = 0.0\n", "same_21_33_and_5 = 0.0\n", "same_21_33_and_6 = 0.0\n", "same_21_33_and_7 = 0.0\n", "same_21_33_and_8 = 0.0\n", "same_21_33_and_9 = 0.0\n", - "same_21_34 = 0.0\n", + "same_21_34 = 1.0\n", "same_21_34_and_0 = 0.0\n", "same_21_34_and_1 = 0.0\n", "same_21_34_and_10 = 0.0\n", @@ -137178,7 +137168,7 @@ "same_21_34_and_14 = 0.0\n", "same_21_34_and_15 = 0.0\n", "same_21_34_and_2 = 0.0\n", - "same_21_34_and_3 = 0.0\n", + "same_21_34_and_3 = 1.0\n", "same_21_34_and_4 = 0.0\n", "same_21_34_and_5 = 0.0\n", "same_21_34_and_6 = 0.0\n", @@ -137787,11 +137777,11 @@ "same_22_23_and_10 = 0.0\n", "same_22_23_and_11 = 0.0\n", "same_22_23_and_12 = 0.0\n", - "same_22_23_and_13 = 1.0\n", + "same_22_23_and_13 = 0.0\n", "same_22_23_and_14 = 0.0\n", "same_22_23_and_15 = 0.0\n", "same_22_23_and_2 = 0.0\n", - "same_22_23_and_3 = 0.0\n", + "same_22_23_and_3 = 1.0\n", "same_22_23_and_4 = 0.0\n", "same_22_23_and_5 = 0.0\n", "same_22_23_and_6 = 0.0\n", @@ -137804,11 +137794,11 @@ "same_22_24_and_10 = 0.0\n", "same_22_24_and_11 = 0.0\n", "same_22_24_and_12 = 0.0\n", - "same_22_24_and_13 = 1.0\n", + "same_22_24_and_13 = 0.0\n", "same_22_24_and_14 = 0.0\n", "same_22_24_and_15 = 0.0\n", "same_22_24_and_2 = 0.0\n", - "same_22_24_and_3 = 0.0\n", + "same_22_24_and_3 = 1.0\n", "same_22_24_and_4 = 0.0\n", "same_22_24_and_5 = 0.0\n", "same_22_24_and_6 = 0.0\n", @@ -137821,18 +137811,18 @@ "same_22_25_and_10 = 0.0\n", "same_22_25_and_11 = 0.0\n", "same_22_25_and_12 = 0.0\n", - "same_22_25_and_13 = 1.0\n", + "same_22_25_and_13 = 0.0\n", "same_22_25_and_14 = 0.0\n", "same_22_25_and_15 = 0.0\n", "same_22_25_and_2 = 0.0\n", - "same_22_25_and_3 = 0.0\n", + "same_22_25_and_3 = 1.0\n", "same_22_25_and_4 = 0.0\n", "same_22_25_and_5 = 0.0\n", "same_22_25_and_6 = 0.0\n", "same_22_25_and_7 = 0.0\n", "same_22_25_and_8 = 0.0\n", "same_22_25_and_9 = 0.0\n", - "same_22_26 = 0.0\n", + "same_22_26 = 1.0\n", "same_22_26_and_0 = 0.0\n", "same_22_26_and_1 = 0.0\n", "same_22_26_and_10 = 0.0\n", @@ -137842,14 +137832,14 @@ "same_22_26_and_14 = 0.0\n", "same_22_26_and_15 = 0.0\n", "same_22_26_and_2 = 0.0\n", - "same_22_26_and_3 = 0.0\n", + "same_22_26_and_3 = 1.0\n", "same_22_26_and_4 = 0.0\n", "same_22_26_and_5 = 0.0\n", "same_22_26_and_6 = 0.0\n", "same_22_26_and_7 = 0.0\n", "same_22_26_and_8 = 0.0\n", "same_22_26_and_9 = 0.0\n", - "same_22_27 = 0.0\n", + "same_22_27 = 1.0\n", "same_22_27_and_0 = 0.0\n", "same_22_27_and_1 = 0.0\n", "same_22_27_and_10 = 0.0\n", @@ -137859,14 +137849,14 @@ "same_22_27_and_14 = 0.0\n", "same_22_27_and_15 = 0.0\n", "same_22_27_and_2 = 0.0\n", - "same_22_27_and_3 = 0.0\n", + "same_22_27_and_3 = 1.0\n", "same_22_27_and_4 = 0.0\n", "same_22_27_and_5 = 0.0\n", "same_22_27_and_6 = 0.0\n", "same_22_27_and_7 = 0.0\n", "same_22_27_and_8 = 0.0\n", "same_22_27_and_9 = 0.0\n", - "same_22_28 = 0.0\n", + "same_22_28 = 1.0\n", "same_22_28_and_0 = 0.0\n", "same_22_28_and_1 = 0.0\n", "same_22_28_and_10 = 0.0\n", @@ -137876,14 +137866,14 @@ "same_22_28_and_14 = 0.0\n", "same_22_28_and_15 = 0.0\n", "same_22_28_and_2 = 0.0\n", - "same_22_28_and_3 = 0.0\n", + "same_22_28_and_3 = 1.0\n", "same_22_28_and_4 = 0.0\n", "same_22_28_and_5 = 0.0\n", "same_22_28_and_6 = 0.0\n", "same_22_28_and_7 = 0.0\n", "same_22_28_and_8 = 0.0\n", "same_22_28_and_9 = 0.0\n", - "same_22_29 = 0.0\n", + "same_22_29 = 1.0\n", "same_22_29_and_0 = 0.0\n", "same_22_29_and_1 = 0.0\n", "same_22_29_and_10 = 0.0\n", @@ -137893,14 +137883,14 @@ "same_22_29_and_14 = 0.0\n", "same_22_29_and_15 = 0.0\n", "same_22_29_and_2 = 0.0\n", - "same_22_29_and_3 = 0.0\n", + "same_22_29_and_3 = 1.0\n", "same_22_29_and_4 = 0.0\n", "same_22_29_and_5 = 0.0\n", "same_22_29_and_6 = 0.0\n", "same_22_29_and_7 = 0.0\n", "same_22_29_and_8 = 0.0\n", "same_22_29_and_9 = 0.0\n", - "same_22_30 = 0.0\n", + "same_22_30 = 1.0\n", "same_22_30_and_0 = 0.0\n", "same_22_30_and_1 = 0.0\n", "same_22_30_and_10 = 0.0\n", @@ -137910,14 +137900,14 @@ "same_22_30_and_14 = 0.0\n", "same_22_30_and_15 = 0.0\n", "same_22_30_and_2 = 0.0\n", - "same_22_30_and_3 = 0.0\n", + "same_22_30_and_3 = 1.0\n", "same_22_30_and_4 = 0.0\n", "same_22_30_and_5 = 0.0\n", "same_22_30_and_6 = 0.0\n", "same_22_30_and_7 = 0.0\n", "same_22_30_and_8 = 0.0\n", "same_22_30_and_9 = 0.0\n", - "same_22_31 = 0.0\n", + "same_22_31 = 1.0\n", "same_22_31_and_0 = 0.0\n", "same_22_31_and_1 = 0.0\n", "same_22_31_and_10 = 0.0\n", @@ -137927,14 +137917,14 @@ "same_22_31_and_14 = 0.0\n", "same_22_31_and_15 = 0.0\n", "same_22_31_and_2 = 0.0\n", - "same_22_31_and_3 = 0.0\n", + "same_22_31_and_3 = 1.0\n", "same_22_31_and_4 = 0.0\n", "same_22_31_and_5 = 0.0\n", "same_22_31_and_6 = 0.0\n", "same_22_31_and_7 = 0.0\n", "same_22_31_and_8 = 0.0\n", "same_22_31_and_9 = 0.0\n", - "same_22_32 = 0.0\n", + "same_22_32 = 1.0\n", "same_22_32_and_0 = 0.0\n", "same_22_32_and_1 = 0.0\n", "same_22_32_and_10 = 0.0\n", @@ -137944,14 +137934,14 @@ "same_22_32_and_14 = 0.0\n", "same_22_32_and_15 = 0.0\n", "same_22_32_and_2 = 0.0\n", - "same_22_32_and_3 = 0.0\n", + "same_22_32_and_3 = 1.0\n", "same_22_32_and_4 = 0.0\n", "same_22_32_and_5 = 0.0\n", "same_22_32_and_6 = 0.0\n", "same_22_32_and_7 = 0.0\n", "same_22_32_and_8 = 0.0\n", "same_22_32_and_9 = 0.0\n", - "same_22_33 = 0.0\n", + "same_22_33 = 1.0\n", "same_22_33_and_0 = 0.0\n", "same_22_33_and_1 = 0.0\n", "same_22_33_and_10 = 0.0\n", @@ -137961,14 +137951,14 @@ "same_22_33_and_14 = 0.0\n", "same_22_33_and_15 = 0.0\n", "same_22_33_and_2 = 0.0\n", - "same_22_33_and_3 = 0.0\n", + "same_22_33_and_3 = 1.0\n", "same_22_33_and_4 = 0.0\n", "same_22_33_and_5 = 0.0\n", "same_22_33_and_6 = 0.0\n", "same_22_33_and_7 = 0.0\n", "same_22_33_and_8 = 0.0\n", "same_22_33_and_9 = 0.0\n", - "same_22_34 = 0.0\n", + "same_22_34 = 1.0\n", "same_22_34_and_0 = 0.0\n", "same_22_34_and_1 = 0.0\n", "same_22_34_and_10 = 0.0\n", @@ -137978,7 +137968,7 @@ "same_22_34_and_14 = 0.0\n", "same_22_34_and_15 = 0.0\n", "same_22_34_and_2 = 0.0\n", - "same_22_34_and_3 = 0.0\n", + "same_22_34_and_3 = 1.0\n", "same_22_34_and_4 = 0.0\n", "same_22_34_and_5 = 0.0\n", "same_22_34_and_6 = 0.0\n", @@ -138587,11 +138577,11 @@ "same_23_24_and_10 = 0.0\n", "same_23_24_and_11 = 0.0\n", "same_23_24_and_12 = 0.0\n", - "same_23_24_and_13 = 1.0\n", + "same_23_24_and_13 = 0.0\n", "same_23_24_and_14 = 0.0\n", "same_23_24_and_15 = 0.0\n", "same_23_24_and_2 = 0.0\n", - "same_23_24_and_3 = 0.0\n", + "same_23_24_and_3 = 1.0\n", "same_23_24_and_4 = 0.0\n", "same_23_24_and_5 = 0.0\n", "same_23_24_and_6 = 0.0\n", @@ -138604,18 +138594,18 @@ "same_23_25_and_10 = 0.0\n", "same_23_25_and_11 = 0.0\n", "same_23_25_and_12 = 0.0\n", - "same_23_25_and_13 = 1.0\n", + "same_23_25_and_13 = 0.0\n", "same_23_25_and_14 = 0.0\n", "same_23_25_and_15 = 0.0\n", "same_23_25_and_2 = 0.0\n", - "same_23_25_and_3 = 0.0\n", + "same_23_25_and_3 = 1.0\n", "same_23_25_and_4 = 0.0\n", "same_23_25_and_5 = 0.0\n", "same_23_25_and_6 = 0.0\n", "same_23_25_and_7 = 0.0\n", "same_23_25_and_8 = 0.0\n", "same_23_25_and_9 = 0.0\n", - "same_23_26 = 0.0\n", + "same_23_26 = 1.0\n", "same_23_26_and_0 = 0.0\n", "same_23_26_and_1 = 0.0\n", "same_23_26_and_10 = 0.0\n", @@ -138625,14 +138615,14 @@ "same_23_26_and_14 = 0.0\n", "same_23_26_and_15 = 0.0\n", "same_23_26_and_2 = 0.0\n", - "same_23_26_and_3 = 0.0\n", + "same_23_26_and_3 = 1.0\n", "same_23_26_and_4 = 0.0\n", "same_23_26_and_5 = 0.0\n", "same_23_26_and_6 = 0.0\n", "same_23_26_and_7 = 0.0\n", "same_23_26_and_8 = 0.0\n", "same_23_26_and_9 = 0.0\n", - "same_23_27 = 0.0\n", + "same_23_27 = 1.0\n", "same_23_27_and_0 = 0.0\n", "same_23_27_and_1 = 0.0\n", "same_23_27_and_10 = 0.0\n", @@ -138642,14 +138632,14 @@ "same_23_27_and_14 = 0.0\n", "same_23_27_and_15 = 0.0\n", "same_23_27_and_2 = 0.0\n", - "same_23_27_and_3 = 0.0\n", + "same_23_27_and_3 = 1.0\n", "same_23_27_and_4 = 0.0\n", "same_23_27_and_5 = 0.0\n", "same_23_27_and_6 = 0.0\n", "same_23_27_and_7 = 0.0\n", "same_23_27_and_8 = 0.0\n", "same_23_27_and_9 = 0.0\n", - "same_23_28 = 0.0\n", + "same_23_28 = 1.0\n", "same_23_28_and_0 = 0.0\n", "same_23_28_and_1 = 0.0\n", "same_23_28_and_10 = 0.0\n", @@ -138659,14 +138649,14 @@ "same_23_28_and_14 = 0.0\n", "same_23_28_and_15 = 0.0\n", "same_23_28_and_2 = 0.0\n", - "same_23_28_and_3 = 0.0\n", + "same_23_28_and_3 = 1.0\n", "same_23_28_and_4 = 0.0\n", "same_23_28_and_5 = 0.0\n", "same_23_28_and_6 = 0.0\n", "same_23_28_and_7 = 0.0\n", "same_23_28_and_8 = 0.0\n", "same_23_28_and_9 = 0.0\n", - "same_23_29 = 0.0\n", + "same_23_29 = 1.0\n", "same_23_29_and_0 = 0.0\n", "same_23_29_and_1 = 0.0\n", "same_23_29_and_10 = 0.0\n", @@ -138676,14 +138666,14 @@ "same_23_29_and_14 = 0.0\n", "same_23_29_and_15 = 0.0\n", "same_23_29_and_2 = 0.0\n", - "same_23_29_and_3 = 0.0\n", + "same_23_29_and_3 = 1.0\n", "same_23_29_and_4 = 0.0\n", "same_23_29_and_5 = 0.0\n", "same_23_29_and_6 = 0.0\n", "same_23_29_and_7 = 0.0\n", "same_23_29_and_8 = 0.0\n", "same_23_29_and_9 = 0.0\n", - "same_23_30 = 0.0\n", + "same_23_30 = 1.0\n", "same_23_30_and_0 = 0.0\n", "same_23_30_and_1 = 0.0\n", "same_23_30_and_10 = 0.0\n", @@ -138693,14 +138683,14 @@ "same_23_30_and_14 = 0.0\n", "same_23_30_and_15 = 0.0\n", "same_23_30_and_2 = 0.0\n", - "same_23_30_and_3 = 0.0\n", + "same_23_30_and_3 = 1.0\n", "same_23_30_and_4 = 0.0\n", "same_23_30_and_5 = 0.0\n", "same_23_30_and_6 = 0.0\n", "same_23_30_and_7 = 0.0\n", "same_23_30_and_8 = 0.0\n", "same_23_30_and_9 = 0.0\n", - "same_23_31 = 0.0\n", + "same_23_31 = 1.0\n", "same_23_31_and_0 = 0.0\n", "same_23_31_and_1 = 0.0\n", "same_23_31_and_10 = 0.0\n", @@ -138710,14 +138700,14 @@ "same_23_31_and_14 = 0.0\n", "same_23_31_and_15 = 0.0\n", "same_23_31_and_2 = 0.0\n", - "same_23_31_and_3 = 0.0\n", + "same_23_31_and_3 = 1.0\n", "same_23_31_and_4 = 0.0\n", "same_23_31_and_5 = 0.0\n", "same_23_31_and_6 = 0.0\n", "same_23_31_and_7 = 0.0\n", "same_23_31_and_8 = 0.0\n", "same_23_31_and_9 = 0.0\n", - "same_23_32 = 0.0\n", + "same_23_32 = 1.0\n", "same_23_32_and_0 = 0.0\n", "same_23_32_and_1 = 0.0\n", "same_23_32_and_10 = 0.0\n", @@ -138727,14 +138717,14 @@ "same_23_32_and_14 = 0.0\n", "same_23_32_and_15 = 0.0\n", "same_23_32_and_2 = 0.0\n", - "same_23_32_and_3 = 0.0\n", + "same_23_32_and_3 = 1.0\n", "same_23_32_and_4 = 0.0\n", "same_23_32_and_5 = 0.0\n", "same_23_32_and_6 = 0.0\n", "same_23_32_and_7 = 0.0\n", "same_23_32_and_8 = 0.0\n", "same_23_32_and_9 = 0.0\n", - "same_23_33 = 0.0\n", + "same_23_33 = 1.0\n", "same_23_33_and_0 = 0.0\n", "same_23_33_and_1 = 0.0\n", "same_23_33_and_10 = 0.0\n", @@ -138744,14 +138734,14 @@ "same_23_33_and_14 = 0.0\n", "same_23_33_and_15 = 0.0\n", "same_23_33_and_2 = 0.0\n", - "same_23_33_and_3 = 0.0\n", + "same_23_33_and_3 = 1.0\n", "same_23_33_and_4 = 0.0\n", "same_23_33_and_5 = 0.0\n", "same_23_33_and_6 = 0.0\n", "same_23_33_and_7 = 0.0\n", "same_23_33_and_8 = 0.0\n", "same_23_33_and_9 = 0.0\n", - "same_23_34 = 0.0\n", + "same_23_34 = 1.0\n", "same_23_34_and_0 = 0.0\n", "same_23_34_and_1 = 0.0\n", "same_23_34_and_10 = 0.0\n", @@ -138761,7 +138751,7 @@ "same_23_34_and_14 = 0.0\n", "same_23_34_and_15 = 0.0\n", "same_23_34_and_2 = 0.0\n", - "same_23_34_and_3 = 0.0\n", + "same_23_34_and_3 = 1.0\n", "same_23_34_and_4 = 0.0\n", "same_23_34_and_5 = 0.0\n", "same_23_34_and_6 = 0.0\n", @@ -139370,18 +139360,18 @@ "same_24_25_and_10 = 0.0\n", "same_24_25_and_11 = 0.0\n", "same_24_25_and_12 = 0.0\n", - "same_24_25_and_13 = 1.0\n", + "same_24_25_and_13 = 0.0\n", "same_24_25_and_14 = 0.0\n", "same_24_25_and_15 = 0.0\n", "same_24_25_and_2 = 0.0\n", - "same_24_25_and_3 = 0.0\n", + "same_24_25_and_3 = 1.0\n", "same_24_25_and_4 = 0.0\n", "same_24_25_and_5 = 0.0\n", "same_24_25_and_6 = 0.0\n", "same_24_25_and_7 = 0.0\n", "same_24_25_and_8 = 0.0\n", "same_24_25_and_9 = 0.0\n", - "same_24_26 = 0.0\n", + "same_24_26 = 1.0\n", "same_24_26_and_0 = 0.0\n", "same_24_26_and_1 = 0.0\n", "same_24_26_and_10 = 0.0\n", @@ -139391,14 +139381,14 @@ "same_24_26_and_14 = 0.0\n", "same_24_26_and_15 = 0.0\n", "same_24_26_and_2 = 0.0\n", - "same_24_26_and_3 = 0.0\n", + "same_24_26_and_3 = 1.0\n", "same_24_26_and_4 = 0.0\n", "same_24_26_and_5 = 0.0\n", "same_24_26_and_6 = 0.0\n", "same_24_26_and_7 = 0.0\n", "same_24_26_and_8 = 0.0\n", "same_24_26_and_9 = 0.0\n", - "same_24_27 = 0.0\n", + "same_24_27 = 1.0\n", "same_24_27_and_0 = 0.0\n", "same_24_27_and_1 = 0.0\n", "same_24_27_and_10 = 0.0\n", @@ -139408,14 +139398,14 @@ "same_24_27_and_14 = 0.0\n", "same_24_27_and_15 = 0.0\n", "same_24_27_and_2 = 0.0\n", - "same_24_27_and_3 = 0.0\n", + "same_24_27_and_3 = 1.0\n", "same_24_27_and_4 = 0.0\n", "same_24_27_and_5 = 0.0\n", "same_24_27_and_6 = 0.0\n", "same_24_27_and_7 = 0.0\n", "same_24_27_and_8 = 0.0\n", "same_24_27_and_9 = 0.0\n", - "same_24_28 = 0.0\n", + "same_24_28 = 1.0\n", "same_24_28_and_0 = 0.0\n", "same_24_28_and_1 = 0.0\n", "same_24_28_and_10 = 0.0\n", @@ -139425,14 +139415,14 @@ "same_24_28_and_14 = 0.0\n", "same_24_28_and_15 = 0.0\n", "same_24_28_and_2 = 0.0\n", - "same_24_28_and_3 = 0.0\n", + "same_24_28_and_3 = 1.0\n", "same_24_28_and_4 = 0.0\n", "same_24_28_and_5 = 0.0\n", "same_24_28_and_6 = 0.0\n", "same_24_28_and_7 = 0.0\n", "same_24_28_and_8 = 0.0\n", "same_24_28_and_9 = 0.0\n", - "same_24_29 = 0.0\n", + "same_24_29 = 1.0\n", "same_24_29_and_0 = 0.0\n", "same_24_29_and_1 = 0.0\n", "same_24_29_and_10 = 0.0\n", @@ -139442,14 +139432,14 @@ "same_24_29_and_14 = 0.0\n", "same_24_29_and_15 = 0.0\n", "same_24_29_and_2 = 0.0\n", - "same_24_29_and_3 = 0.0\n", + "same_24_29_and_3 = 1.0\n", "same_24_29_and_4 = 0.0\n", "same_24_29_and_5 = 0.0\n", "same_24_29_and_6 = 0.0\n", "same_24_29_and_7 = 0.0\n", "same_24_29_and_8 = 0.0\n", "same_24_29_and_9 = 0.0\n", - "same_24_30 = 0.0\n", + "same_24_30 = 1.0\n", "same_24_30_and_0 = 0.0\n", "same_24_30_and_1 = 0.0\n", "same_24_30_and_10 = 0.0\n", @@ -139459,14 +139449,14 @@ "same_24_30_and_14 = 0.0\n", "same_24_30_and_15 = 0.0\n", "same_24_30_and_2 = 0.0\n", - "same_24_30_and_3 = 0.0\n", + "same_24_30_and_3 = 1.0\n", "same_24_30_and_4 = 0.0\n", "same_24_30_and_5 = 0.0\n", "same_24_30_and_6 = 0.0\n", "same_24_30_and_7 = 0.0\n", "same_24_30_and_8 = 0.0\n", "same_24_30_and_9 = 0.0\n", - "same_24_31 = 0.0\n", + "same_24_31 = 1.0\n", "same_24_31_and_0 = 0.0\n", "same_24_31_and_1 = 0.0\n", "same_24_31_and_10 = 0.0\n", @@ -139476,14 +139466,14 @@ "same_24_31_and_14 = 0.0\n", "same_24_31_and_15 = 0.0\n", "same_24_31_and_2 = 0.0\n", - "same_24_31_and_3 = 0.0\n", + "same_24_31_and_3 = 1.0\n", "same_24_31_and_4 = 0.0\n", "same_24_31_and_5 = 0.0\n", "same_24_31_and_6 = 0.0\n", "same_24_31_and_7 = 0.0\n", "same_24_31_and_8 = 0.0\n", "same_24_31_and_9 = 0.0\n", - "same_24_32 = 0.0\n", + "same_24_32 = 1.0\n", "same_24_32_and_0 = 0.0\n", "same_24_32_and_1 = 0.0\n", "same_24_32_and_10 = 0.0\n", @@ -139493,14 +139483,14 @@ "same_24_32_and_14 = 0.0\n", "same_24_32_and_15 = 0.0\n", "same_24_32_and_2 = 0.0\n", - "same_24_32_and_3 = 0.0\n", + "same_24_32_and_3 = 1.0\n", "same_24_32_and_4 = 0.0\n", "same_24_32_and_5 = 0.0\n", "same_24_32_and_6 = 0.0\n", "same_24_32_and_7 = 0.0\n", "same_24_32_and_8 = 0.0\n", "same_24_32_and_9 = 0.0\n", - "same_24_33 = 0.0\n", + "same_24_33 = 1.0\n", "same_24_33_and_0 = 0.0\n", "same_24_33_and_1 = 0.0\n", "same_24_33_and_10 = 0.0\n", @@ -139510,14 +139500,14 @@ "same_24_33_and_14 = 0.0\n", "same_24_33_and_15 = 0.0\n", "same_24_33_and_2 = 0.0\n", - "same_24_33_and_3 = 0.0\n", + "same_24_33_and_3 = 1.0\n", "same_24_33_and_4 = 0.0\n", "same_24_33_and_5 = 0.0\n", "same_24_33_and_6 = 0.0\n", "same_24_33_and_7 = 0.0\n", "same_24_33_and_8 = 0.0\n", "same_24_33_and_9 = 0.0\n", - "same_24_34 = 0.0\n", + "same_24_34 = 1.0\n", "same_24_34_and_0 = 0.0\n", "same_24_34_and_1 = 0.0\n", "same_24_34_and_10 = 0.0\n", @@ -139527,7 +139517,7 @@ "same_24_34_and_14 = 0.0\n", "same_24_34_and_15 = 0.0\n", "same_24_34_and_2 = 0.0\n", - "same_24_34_and_3 = 0.0\n", + "same_24_34_and_3 = 1.0\n", "same_24_34_and_4 = 0.0\n", "same_24_34_and_5 = 0.0\n", "same_24_34_and_6 = 0.0\n", @@ -140130,7 +140120,7 @@ "same_24_69_and_8 = 0.0\n", "same_24_69_and_9 = 0.0\n", "same_25_25 = 1.0\n", - "same_25_26 = 0.0\n", + "same_25_26 = 1.0\n", "same_25_26_and_0 = 0.0\n", "same_25_26_and_1 = 0.0\n", "same_25_26_and_10 = 0.0\n", @@ -140140,14 +140130,14 @@ "same_25_26_and_14 = 0.0\n", "same_25_26_and_15 = 0.0\n", "same_25_26_and_2 = 0.0\n", - "same_25_26_and_3 = 0.0\n", + "same_25_26_and_3 = 1.0\n", "same_25_26_and_4 = 0.0\n", "same_25_26_and_5 = 0.0\n", "same_25_26_and_6 = 0.0\n", "same_25_26_and_7 = 0.0\n", "same_25_26_and_8 = 0.0\n", "same_25_26_and_9 = 0.0\n", - "same_25_27 = 0.0\n", + "same_25_27 = 1.0\n", "same_25_27_and_0 = 0.0\n", "same_25_27_and_1 = 0.0\n", "same_25_27_and_10 = 0.0\n", @@ -140157,14 +140147,14 @@ "same_25_27_and_14 = 0.0\n", "same_25_27_and_15 = 0.0\n", "same_25_27_and_2 = 0.0\n", - "same_25_27_and_3 = 0.0\n", + "same_25_27_and_3 = 1.0\n", "same_25_27_and_4 = 0.0\n", "same_25_27_and_5 = 0.0\n", "same_25_27_and_6 = 0.0\n", "same_25_27_and_7 = 0.0\n", "same_25_27_and_8 = 0.0\n", "same_25_27_and_9 = 0.0\n", - "same_25_28 = 0.0\n", + "same_25_28 = 1.0\n", "same_25_28_and_0 = 0.0\n", "same_25_28_and_1 = 0.0\n", "same_25_28_and_10 = 0.0\n", @@ -140174,14 +140164,14 @@ "same_25_28_and_14 = 0.0\n", "same_25_28_and_15 = 0.0\n", "same_25_28_and_2 = 0.0\n", - "same_25_28_and_3 = 0.0\n", + "same_25_28_and_3 = 1.0\n", "same_25_28_and_4 = 0.0\n", "same_25_28_and_5 = 0.0\n", "same_25_28_and_6 = 0.0\n", "same_25_28_and_7 = 0.0\n", "same_25_28_and_8 = 0.0\n", "same_25_28_and_9 = 0.0\n", - "same_25_29 = 0.0\n", + "same_25_29 = 1.0\n", "same_25_29_and_0 = 0.0\n", "same_25_29_and_1 = 0.0\n", "same_25_29_and_10 = 0.0\n", @@ -140191,14 +140181,14 @@ "same_25_29_and_14 = 0.0\n", "same_25_29_and_15 = 0.0\n", "same_25_29_and_2 = 0.0\n", - "same_25_29_and_3 = 0.0\n", + "same_25_29_and_3 = 1.0\n", "same_25_29_and_4 = 0.0\n", "same_25_29_and_5 = 0.0\n", "same_25_29_and_6 = 0.0\n", "same_25_29_and_7 = 0.0\n", "same_25_29_and_8 = 0.0\n", "same_25_29_and_9 = 0.0\n", - "same_25_30 = 0.0\n", + "same_25_30 = 1.0\n", "same_25_30_and_0 = 0.0\n", "same_25_30_and_1 = 0.0\n", "same_25_30_and_10 = 0.0\n", @@ -140208,14 +140198,14 @@ "same_25_30_and_14 = 0.0\n", "same_25_30_and_15 = 0.0\n", "same_25_30_and_2 = 0.0\n", - "same_25_30_and_3 = 0.0\n", + "same_25_30_and_3 = 1.0\n", "same_25_30_and_4 = 0.0\n", "same_25_30_and_5 = 0.0\n", "same_25_30_and_6 = 0.0\n", "same_25_30_and_7 = 0.0\n", "same_25_30_and_8 = 0.0\n", "same_25_30_and_9 = 0.0\n", - "same_25_31 = 0.0\n", + "same_25_31 = 1.0\n", "same_25_31_and_0 = 0.0\n", "same_25_31_and_1 = 0.0\n", "same_25_31_and_10 = 0.0\n", @@ -140225,14 +140215,14 @@ "same_25_31_and_14 = 0.0\n", "same_25_31_and_15 = 0.0\n", "same_25_31_and_2 = 0.0\n", - "same_25_31_and_3 = 0.0\n", + "same_25_31_and_3 = 1.0\n", "same_25_31_and_4 = 0.0\n", "same_25_31_and_5 = 0.0\n", "same_25_31_and_6 = 0.0\n", "same_25_31_and_7 = 0.0\n", "same_25_31_and_8 = 0.0\n", "same_25_31_and_9 = 0.0\n", - "same_25_32 = 0.0\n", + "same_25_32 = 1.0\n", "same_25_32_and_0 = 0.0\n", "same_25_32_and_1 = 0.0\n", "same_25_32_and_10 = 0.0\n", @@ -140242,14 +140232,14 @@ "same_25_32_and_14 = 0.0\n", "same_25_32_and_15 = 0.0\n", "same_25_32_and_2 = 0.0\n", - "same_25_32_and_3 = 0.0\n", + "same_25_32_and_3 = 1.0\n", "same_25_32_and_4 = 0.0\n", "same_25_32_and_5 = 0.0\n", "same_25_32_and_6 = 0.0\n", "same_25_32_and_7 = 0.0\n", "same_25_32_and_8 = 0.0\n", "same_25_32_and_9 = 0.0\n", - "same_25_33 = 0.0\n", + "same_25_33 = 1.0\n", "same_25_33_and_0 = 0.0\n", "same_25_33_and_1 = 0.0\n", "same_25_33_and_10 = 0.0\n", @@ -140259,14 +140249,14 @@ "same_25_33_and_14 = 0.0\n", "same_25_33_and_15 = 0.0\n", "same_25_33_and_2 = 0.0\n", - "same_25_33_and_3 = 0.0\n", + "same_25_33_and_3 = 1.0\n", "same_25_33_and_4 = 0.0\n", "same_25_33_and_5 = 0.0\n", "same_25_33_and_6 = 0.0\n", "same_25_33_and_7 = 0.0\n", "same_25_33_and_8 = 0.0\n", "same_25_33_and_9 = 0.0\n", - "same_25_34 = 0.0\n", + "same_25_34 = 1.0\n", "same_25_34_and_0 = 0.0\n", "same_25_34_and_1 = 0.0\n", "same_25_34_and_10 = 0.0\n", @@ -140276,7 +140266,7 @@ "same_25_34_and_14 = 0.0\n", "same_25_34_and_15 = 0.0\n", "same_25_34_and_2 = 0.0\n", - "same_25_34_and_3 = 0.0\n", + "same_25_34_and_3 = 1.0\n", "same_25_34_and_4 = 0.0\n", "same_25_34_and_5 = 0.0\n", "same_25_34_and_6 = 0.0\n", @@ -140889,9 +140879,9 @@ "same_26_27_and_14 = 0.0\n", "same_26_27_and_15 = 0.0\n", "same_26_27_and_2 = 0.0\n", - "same_26_27_and_3 = 0.0\n", + "same_26_27_and_3 = 1.0\n", "same_26_27_and_4 = 0.0\n", - "same_26_27_and_5 = 1.0\n", + "same_26_27_and_5 = 0.0\n", "same_26_27_and_6 = 0.0\n", "same_26_27_and_7 = 0.0\n", "same_26_27_and_8 = 0.0\n", @@ -140906,9 +140896,9 @@ "same_26_28_and_14 = 0.0\n", "same_26_28_and_15 = 0.0\n", "same_26_28_and_2 = 0.0\n", - "same_26_28_and_3 = 0.0\n", + "same_26_28_and_3 = 1.0\n", "same_26_28_and_4 = 0.0\n", - "same_26_28_and_5 = 1.0\n", + "same_26_28_and_5 = 0.0\n", "same_26_28_and_6 = 0.0\n", "same_26_28_and_7 = 0.0\n", "same_26_28_and_8 = 0.0\n", @@ -140923,9 +140913,9 @@ "same_26_29_and_14 = 0.0\n", "same_26_29_and_15 = 0.0\n", "same_26_29_and_2 = 0.0\n", - "same_26_29_and_3 = 0.0\n", + "same_26_29_and_3 = 1.0\n", "same_26_29_and_4 = 0.0\n", - "same_26_29_and_5 = 1.0\n", + "same_26_29_and_5 = 0.0\n", "same_26_29_and_6 = 0.0\n", "same_26_29_and_7 = 0.0\n", "same_26_29_and_8 = 0.0\n", @@ -140940,9 +140930,9 @@ "same_26_30_and_14 = 0.0\n", "same_26_30_and_15 = 0.0\n", "same_26_30_and_2 = 0.0\n", - "same_26_30_and_3 = 0.0\n", + "same_26_30_and_3 = 1.0\n", "same_26_30_and_4 = 0.0\n", - "same_26_30_and_5 = 1.0\n", + "same_26_30_and_5 = 0.0\n", "same_26_30_and_6 = 0.0\n", "same_26_30_and_7 = 0.0\n", "same_26_30_and_8 = 0.0\n", @@ -140957,9 +140947,9 @@ "same_26_31_and_14 = 0.0\n", "same_26_31_and_15 = 0.0\n", "same_26_31_and_2 = 0.0\n", - "same_26_31_and_3 = 0.0\n", + "same_26_31_and_3 = 1.0\n", "same_26_31_and_4 = 0.0\n", - "same_26_31_and_5 = 1.0\n", + "same_26_31_and_5 = 0.0\n", "same_26_31_and_6 = 0.0\n", "same_26_31_and_7 = 0.0\n", "same_26_31_and_8 = 0.0\n", @@ -140974,9 +140964,9 @@ "same_26_32_and_14 = 0.0\n", "same_26_32_and_15 = 0.0\n", "same_26_32_and_2 = 0.0\n", - "same_26_32_and_3 = 0.0\n", + "same_26_32_and_3 = 1.0\n", "same_26_32_and_4 = 0.0\n", - "same_26_32_and_5 = 1.0\n", + "same_26_32_and_5 = 0.0\n", "same_26_32_and_6 = 0.0\n", "same_26_32_and_7 = 0.0\n", "same_26_32_and_8 = 0.0\n", @@ -140991,9 +140981,9 @@ "same_26_33_and_14 = 0.0\n", "same_26_33_and_15 = 0.0\n", "same_26_33_and_2 = 0.0\n", - "same_26_33_and_3 = 0.0\n", + "same_26_33_and_3 = 1.0\n", "same_26_33_and_4 = 0.0\n", - "same_26_33_and_5 = 1.0\n", + "same_26_33_and_5 = 0.0\n", "same_26_33_and_6 = 0.0\n", "same_26_33_and_7 = 0.0\n", "same_26_33_and_8 = 0.0\n", @@ -141008,14 +140998,14 @@ "same_26_34_and_14 = 0.0\n", "same_26_34_and_15 = 0.0\n", "same_26_34_and_2 = 0.0\n", - "same_26_34_and_3 = 0.0\n", + "same_26_34_and_3 = 1.0\n", "same_26_34_and_4 = 0.0\n", - "same_26_34_and_5 = 1.0\n", + "same_26_34_and_5 = 0.0\n", "same_26_34_and_6 = 0.0\n", "same_26_34_and_7 = 0.0\n", "same_26_34_and_8 = 0.0\n", "same_26_34_and_9 = 0.0\n", - "same_26_35 = 1.0\n", + "same_26_35 = 0.0\n", "same_26_35_and_0 = 0.0\n", "same_26_35_and_1 = 0.0\n", "same_26_35_and_10 = 0.0\n", @@ -141027,12 +141017,12 @@ "same_26_35_and_2 = 0.0\n", "same_26_35_and_3 = 0.0\n", "same_26_35_and_4 = 0.0\n", - "same_26_35_and_5 = 1.0\n", + "same_26_35_and_5 = 0.0\n", "same_26_35_and_6 = 0.0\n", "same_26_35_and_7 = 0.0\n", "same_26_35_and_8 = 0.0\n", "same_26_35_and_9 = 0.0\n", - "same_26_36 = 1.0\n", + "same_26_36 = 0.0\n", "same_26_36_and_0 = 0.0\n", "same_26_36_and_1 = 0.0\n", "same_26_36_and_10 = 0.0\n", @@ -141044,12 +141034,12 @@ "same_26_36_and_2 = 0.0\n", "same_26_36_and_3 = 0.0\n", "same_26_36_and_4 = 0.0\n", - "same_26_36_and_5 = 1.0\n", + "same_26_36_and_5 = 0.0\n", "same_26_36_and_6 = 0.0\n", "same_26_36_and_7 = 0.0\n", "same_26_36_and_8 = 0.0\n", "same_26_36_and_9 = 0.0\n", - "same_26_37 = 1.0\n", + "same_26_37 = 0.0\n", "same_26_37_and_0 = 0.0\n", "same_26_37_and_1 = 0.0\n", "same_26_37_and_10 = 0.0\n", @@ -141061,12 +141051,12 @@ "same_26_37_and_2 = 0.0\n", "same_26_37_and_3 = 0.0\n", "same_26_37_and_4 = 0.0\n", - "same_26_37_and_5 = 1.0\n", + "same_26_37_and_5 = 0.0\n", "same_26_37_and_6 = 0.0\n", "same_26_37_and_7 = 0.0\n", "same_26_37_and_8 = 0.0\n", "same_26_37_and_9 = 0.0\n", - "same_26_38 = 1.0\n", + "same_26_38 = 0.0\n", "same_26_38_and_0 = 0.0\n", "same_26_38_and_1 = 0.0\n", "same_26_38_and_10 = 0.0\n", @@ -141078,12 +141068,12 @@ "same_26_38_and_2 = 0.0\n", "same_26_38_and_3 = 0.0\n", "same_26_38_and_4 = 0.0\n", - "same_26_38_and_5 = 1.0\n", + "same_26_38_and_5 = 0.0\n", "same_26_38_and_6 = 0.0\n", "same_26_38_and_7 = 0.0\n", "same_26_38_and_8 = 0.0\n", "same_26_38_and_9 = 0.0\n", - "same_26_39 = 1.0\n", + "same_26_39 = 0.0\n", "same_26_39_and_0 = 0.0\n", "same_26_39_and_1 = 0.0\n", "same_26_39_and_10 = 0.0\n", @@ -141095,12 +141085,12 @@ "same_26_39_and_2 = 0.0\n", "same_26_39_and_3 = 0.0\n", "same_26_39_and_4 = 0.0\n", - "same_26_39_and_5 = 1.0\n", + "same_26_39_and_5 = 0.0\n", "same_26_39_and_6 = 0.0\n", "same_26_39_and_7 = 0.0\n", "same_26_39_and_8 = 0.0\n", "same_26_39_and_9 = 0.0\n", - "same_26_40 = 1.0\n", + "same_26_40 = 0.0\n", "same_26_40_and_0 = 0.0\n", "same_26_40_and_1 = 0.0\n", "same_26_40_and_10 = 0.0\n", @@ -141112,12 +141102,12 @@ "same_26_40_and_2 = 0.0\n", "same_26_40_and_3 = 0.0\n", "same_26_40_and_4 = 0.0\n", - "same_26_40_and_5 = 1.0\n", + "same_26_40_and_5 = 0.0\n", "same_26_40_and_6 = 0.0\n", "same_26_40_and_7 = 0.0\n", "same_26_40_and_8 = 0.0\n", "same_26_40_and_9 = 0.0\n", - "same_26_41 = 1.0\n", + "same_26_41 = 0.0\n", "same_26_41_and_0 = 0.0\n", "same_26_41_and_1 = 0.0\n", "same_26_41_and_10 = 0.0\n", @@ -141129,12 +141119,12 @@ "same_26_41_and_2 = 0.0\n", "same_26_41_and_3 = 0.0\n", "same_26_41_and_4 = 0.0\n", - "same_26_41_and_5 = 1.0\n", + "same_26_41_and_5 = 0.0\n", "same_26_41_and_6 = 0.0\n", "same_26_41_and_7 = 0.0\n", "same_26_41_and_8 = 0.0\n", "same_26_41_and_9 = 0.0\n", - "same_26_42 = 1.0\n", + "same_26_42 = 0.0\n", "same_26_42_and_0 = 0.0\n", "same_26_42_and_1 = 0.0\n", "same_26_42_and_10 = 0.0\n", @@ -141146,12 +141136,12 @@ "same_26_42_and_2 = 0.0\n", "same_26_42_and_3 = 0.0\n", "same_26_42_and_4 = 0.0\n", - "same_26_42_and_5 = 1.0\n", + "same_26_42_and_5 = 0.0\n", "same_26_42_and_6 = 0.0\n", "same_26_42_and_7 = 0.0\n", "same_26_42_and_8 = 0.0\n", "same_26_42_and_9 = 0.0\n", - "same_26_43 = 1.0\n", + "same_26_43 = 0.0\n", "same_26_43_and_0 = 0.0\n", "same_26_43_and_1 = 0.0\n", "same_26_43_and_10 = 0.0\n", @@ -141163,7 +141153,7 @@ "same_26_43_and_2 = 0.0\n", "same_26_43_and_3 = 0.0\n", "same_26_43_and_4 = 0.0\n", - "same_26_43_and_5 = 1.0\n", + "same_26_43_and_5 = 0.0\n", "same_26_43_and_6 = 0.0\n", "same_26_43_and_7 = 0.0\n", "same_26_43_and_8 = 0.0\n", @@ -141621,9 +141611,9 @@ "same_27_28_and_14 = 0.0\n", "same_27_28_and_15 = 0.0\n", "same_27_28_and_2 = 0.0\n", - "same_27_28_and_3 = 0.0\n", + "same_27_28_and_3 = 1.0\n", "same_27_28_and_4 = 0.0\n", - "same_27_28_and_5 = 1.0\n", + "same_27_28_and_5 = 0.0\n", "same_27_28_and_6 = 0.0\n", "same_27_28_and_7 = 0.0\n", "same_27_28_and_8 = 0.0\n", @@ -141638,9 +141628,9 @@ "same_27_29_and_14 = 0.0\n", "same_27_29_and_15 = 0.0\n", "same_27_29_and_2 = 0.0\n", - "same_27_29_and_3 = 0.0\n", + "same_27_29_and_3 = 1.0\n", "same_27_29_and_4 = 0.0\n", - "same_27_29_and_5 = 1.0\n", + "same_27_29_and_5 = 0.0\n", "same_27_29_and_6 = 0.0\n", "same_27_29_and_7 = 0.0\n", "same_27_29_and_8 = 0.0\n", @@ -141655,9 +141645,9 @@ "same_27_30_and_14 = 0.0\n", "same_27_30_and_15 = 0.0\n", "same_27_30_and_2 = 0.0\n", - "same_27_30_and_3 = 0.0\n", + "same_27_30_and_3 = 1.0\n", "same_27_30_and_4 = 0.0\n", - "same_27_30_and_5 = 1.0\n", + "same_27_30_and_5 = 0.0\n", "same_27_30_and_6 = 0.0\n", "same_27_30_and_7 = 0.0\n", "same_27_30_and_8 = 0.0\n", @@ -141672,9 +141662,9 @@ "same_27_31_and_14 = 0.0\n", "same_27_31_and_15 = 0.0\n", "same_27_31_and_2 = 0.0\n", - "same_27_31_and_3 = 0.0\n", + "same_27_31_and_3 = 1.0\n", "same_27_31_and_4 = 0.0\n", - "same_27_31_and_5 = 1.0\n", + "same_27_31_and_5 = 0.0\n", "same_27_31_and_6 = 0.0\n", "same_27_31_and_7 = 0.0\n", "same_27_31_and_8 = 0.0\n", @@ -141689,9 +141679,9 @@ "same_27_32_and_14 = 0.0\n", "same_27_32_and_15 = 0.0\n", "same_27_32_and_2 = 0.0\n", - "same_27_32_and_3 = 0.0\n", + "same_27_32_and_3 = 1.0\n", "same_27_32_and_4 = 0.0\n", - "same_27_32_and_5 = 1.0\n", + "same_27_32_and_5 = 0.0\n", "same_27_32_and_6 = 0.0\n", "same_27_32_and_7 = 0.0\n", "same_27_32_and_8 = 0.0\n", @@ -141706,9 +141696,9 @@ "same_27_33_and_14 = 0.0\n", "same_27_33_and_15 = 0.0\n", "same_27_33_and_2 = 0.0\n", - "same_27_33_and_3 = 0.0\n", + "same_27_33_and_3 = 1.0\n", "same_27_33_and_4 = 0.0\n", - "same_27_33_and_5 = 1.0\n", + "same_27_33_and_5 = 0.0\n", "same_27_33_and_6 = 0.0\n", "same_27_33_and_7 = 0.0\n", "same_27_33_and_8 = 0.0\n", @@ -141723,14 +141713,14 @@ "same_27_34_and_14 = 0.0\n", "same_27_34_and_15 = 0.0\n", "same_27_34_and_2 = 0.0\n", - "same_27_34_and_3 = 0.0\n", + "same_27_34_and_3 = 1.0\n", "same_27_34_and_4 = 0.0\n", - "same_27_34_and_5 = 1.0\n", + "same_27_34_and_5 = 0.0\n", "same_27_34_and_6 = 0.0\n", "same_27_34_and_7 = 0.0\n", "same_27_34_and_8 = 0.0\n", "same_27_34_and_9 = 0.0\n", - "same_27_35 = 1.0\n", + "same_27_35 = 0.0\n", "same_27_35_and_0 = 0.0\n", "same_27_35_and_1 = 0.0\n", "same_27_35_and_10 = 0.0\n", @@ -141742,12 +141732,12 @@ "same_27_35_and_2 = 0.0\n", "same_27_35_and_3 = 0.0\n", "same_27_35_and_4 = 0.0\n", - "same_27_35_and_5 = 1.0\n", + "same_27_35_and_5 = 0.0\n", "same_27_35_and_6 = 0.0\n", "same_27_35_and_7 = 0.0\n", "same_27_35_and_8 = 0.0\n", "same_27_35_and_9 = 0.0\n", - "same_27_36 = 1.0\n", + "same_27_36 = 0.0\n", "same_27_36_and_0 = 0.0\n", "same_27_36_and_1 = 0.0\n", "same_27_36_and_10 = 0.0\n", @@ -141759,12 +141749,12 @@ "same_27_36_and_2 = 0.0\n", "same_27_36_and_3 = 0.0\n", "same_27_36_and_4 = 0.0\n", - "same_27_36_and_5 = 1.0\n", + "same_27_36_and_5 = 0.0\n", "same_27_36_and_6 = 0.0\n", "same_27_36_and_7 = 0.0\n", "same_27_36_and_8 = 0.0\n", "same_27_36_and_9 = 0.0\n", - "same_27_37 = 1.0\n", + "same_27_37 = 0.0\n", "same_27_37_and_0 = 0.0\n", "same_27_37_and_1 = 0.0\n", "same_27_37_and_10 = 0.0\n", @@ -141776,12 +141766,12 @@ "same_27_37_and_2 = 0.0\n", "same_27_37_and_3 = 0.0\n", "same_27_37_and_4 = 0.0\n", - "same_27_37_and_5 = 1.0\n", + "same_27_37_and_5 = 0.0\n", "same_27_37_and_6 = 0.0\n", "same_27_37_and_7 = 0.0\n", "same_27_37_and_8 = 0.0\n", "same_27_37_and_9 = 0.0\n", - "same_27_38 = 1.0\n", + "same_27_38 = 0.0\n", "same_27_38_and_0 = 0.0\n", "same_27_38_and_1 = 0.0\n", "same_27_38_and_10 = 0.0\n", @@ -141793,12 +141783,12 @@ "same_27_38_and_2 = 0.0\n", "same_27_38_and_3 = 0.0\n", "same_27_38_and_4 = 0.0\n", - "same_27_38_and_5 = 1.0\n", + "same_27_38_and_5 = 0.0\n", "same_27_38_and_6 = 0.0\n", "same_27_38_and_7 = 0.0\n", "same_27_38_and_8 = 0.0\n", "same_27_38_and_9 = 0.0\n", - "same_27_39 = 1.0\n", + "same_27_39 = 0.0\n", "same_27_39_and_0 = 0.0\n", "same_27_39_and_1 = 0.0\n", "same_27_39_and_10 = 0.0\n", @@ -141810,12 +141800,12 @@ "same_27_39_and_2 = 0.0\n", "same_27_39_and_3 = 0.0\n", "same_27_39_and_4 = 0.0\n", - "same_27_39_and_5 = 1.0\n", + "same_27_39_and_5 = 0.0\n", "same_27_39_and_6 = 0.0\n", "same_27_39_and_7 = 0.0\n", "same_27_39_and_8 = 0.0\n", "same_27_39_and_9 = 0.0\n", - "same_27_40 = 1.0\n", + "same_27_40 = 0.0\n", "same_27_40_and_0 = 0.0\n", "same_27_40_and_1 = 0.0\n", "same_27_40_and_10 = 0.0\n", @@ -141827,12 +141817,12 @@ "same_27_40_and_2 = 0.0\n", "same_27_40_and_3 = 0.0\n", "same_27_40_and_4 = 0.0\n", - "same_27_40_and_5 = 1.0\n", + "same_27_40_and_5 = 0.0\n", "same_27_40_and_6 = 0.0\n", "same_27_40_and_7 = 0.0\n", "same_27_40_and_8 = 0.0\n", "same_27_40_and_9 = 0.0\n", - "same_27_41 = 1.0\n", + "same_27_41 = 0.0\n", "same_27_41_and_0 = 0.0\n", "same_27_41_and_1 = 0.0\n", "same_27_41_and_10 = 0.0\n", @@ -141844,12 +141834,12 @@ "same_27_41_and_2 = 0.0\n", "same_27_41_and_3 = 0.0\n", "same_27_41_and_4 = 0.0\n", - "same_27_41_and_5 = 1.0\n", + "same_27_41_and_5 = 0.0\n", "same_27_41_and_6 = 0.0\n", "same_27_41_and_7 = 0.0\n", "same_27_41_and_8 = 0.0\n", "same_27_41_and_9 = 0.0\n", - "same_27_42 = 1.0\n", + "same_27_42 = 0.0\n", "same_27_42_and_0 = 0.0\n", "same_27_42_and_1 = 0.0\n", "same_27_42_and_10 = 0.0\n", @@ -141861,12 +141851,12 @@ "same_27_42_and_2 = 0.0\n", "same_27_42_and_3 = 0.0\n", "same_27_42_and_4 = 0.0\n", - "same_27_42_and_5 = 1.0\n", + "same_27_42_and_5 = 0.0\n", "same_27_42_and_6 = 0.0\n", "same_27_42_and_7 = 0.0\n", "same_27_42_and_8 = 0.0\n", "same_27_42_and_9 = 0.0\n", - "same_27_43 = 1.0\n", + "same_27_43 = 0.0\n", "same_27_43_and_0 = 0.0\n", "same_27_43_and_1 = 0.0\n", "same_27_43_and_10 = 0.0\n", @@ -141878,7 +141868,7 @@ "same_27_43_and_2 = 0.0\n", "same_27_43_and_3 = 0.0\n", "same_27_43_and_4 = 0.0\n", - "same_27_43_and_5 = 1.0\n", + "same_27_43_and_5 = 0.0\n", "same_27_43_and_6 = 0.0\n", "same_27_43_and_7 = 0.0\n", "same_27_43_and_8 = 0.0\n", @@ -142336,9 +142326,9 @@ "same_28_29_and_14 = 0.0\n", "same_28_29_and_15 = 0.0\n", "same_28_29_and_2 = 0.0\n", - "same_28_29_and_3 = 0.0\n", + "same_28_29_and_3 = 1.0\n", "same_28_29_and_4 = 0.0\n", - "same_28_29_and_5 = 1.0\n", + "same_28_29_and_5 = 0.0\n", "same_28_29_and_6 = 0.0\n", "same_28_29_and_7 = 0.0\n", "same_28_29_and_8 = 0.0\n", @@ -142353,9 +142343,9 @@ "same_28_30_and_14 = 0.0\n", "same_28_30_and_15 = 0.0\n", "same_28_30_and_2 = 0.0\n", - "same_28_30_and_3 = 0.0\n", + "same_28_30_and_3 = 1.0\n", "same_28_30_and_4 = 0.0\n", - "same_28_30_and_5 = 1.0\n", + "same_28_30_and_5 = 0.0\n", "same_28_30_and_6 = 0.0\n", "same_28_30_and_7 = 0.0\n", "same_28_30_and_8 = 0.0\n", @@ -142370,9 +142360,9 @@ "same_28_31_and_14 = 0.0\n", "same_28_31_and_15 = 0.0\n", "same_28_31_and_2 = 0.0\n", - "same_28_31_and_3 = 0.0\n", + "same_28_31_and_3 = 1.0\n", "same_28_31_and_4 = 0.0\n", - "same_28_31_and_5 = 1.0\n", + "same_28_31_and_5 = 0.0\n", "same_28_31_and_6 = 0.0\n", "same_28_31_and_7 = 0.0\n", "same_28_31_and_8 = 0.0\n", @@ -142387,9 +142377,9 @@ "same_28_32_and_14 = 0.0\n", "same_28_32_and_15 = 0.0\n", "same_28_32_and_2 = 0.0\n", - "same_28_32_and_3 = 0.0\n", + "same_28_32_and_3 = 1.0\n", "same_28_32_and_4 = 0.0\n", - "same_28_32_and_5 = 1.0\n", + "same_28_32_and_5 = 0.0\n", "same_28_32_and_6 = 0.0\n", "same_28_32_and_7 = 0.0\n", "same_28_32_and_8 = 0.0\n", @@ -142404,9 +142394,9 @@ "same_28_33_and_14 = 0.0\n", "same_28_33_and_15 = 0.0\n", "same_28_33_and_2 = 0.0\n", - "same_28_33_and_3 = 0.0\n", + "same_28_33_and_3 = 1.0\n", "same_28_33_and_4 = 0.0\n", - "same_28_33_and_5 = 1.0\n", + "same_28_33_and_5 = 0.0\n", "same_28_33_and_6 = 0.0\n", "same_28_33_and_7 = 0.0\n", "same_28_33_and_8 = 0.0\n", @@ -142421,14 +142411,14 @@ "same_28_34_and_14 = 0.0\n", "same_28_34_and_15 = 0.0\n", "same_28_34_and_2 = 0.0\n", - "same_28_34_and_3 = 0.0\n", + "same_28_34_and_3 = 1.0\n", "same_28_34_and_4 = 0.0\n", - "same_28_34_and_5 = 1.0\n", + "same_28_34_and_5 = 0.0\n", "same_28_34_and_6 = 0.0\n", "same_28_34_and_7 = 0.0\n", "same_28_34_and_8 = 0.0\n", "same_28_34_and_9 = 0.0\n", - "same_28_35 = 1.0\n", + "same_28_35 = 0.0\n", "same_28_35_and_0 = 0.0\n", "same_28_35_and_1 = 0.0\n", "same_28_35_and_10 = 0.0\n", @@ -142440,12 +142430,12 @@ "same_28_35_and_2 = 0.0\n", "same_28_35_and_3 = 0.0\n", "same_28_35_and_4 = 0.0\n", - "same_28_35_and_5 = 1.0\n", + "same_28_35_and_5 = 0.0\n", "same_28_35_and_6 = 0.0\n", "same_28_35_and_7 = 0.0\n", "same_28_35_and_8 = 0.0\n", "same_28_35_and_9 = 0.0\n", - "same_28_36 = 1.0\n", + "same_28_36 = 0.0\n", "same_28_36_and_0 = 0.0\n", "same_28_36_and_1 = 0.0\n", "same_28_36_and_10 = 0.0\n", @@ -142457,12 +142447,12 @@ "same_28_36_and_2 = 0.0\n", "same_28_36_and_3 = 0.0\n", "same_28_36_and_4 = 0.0\n", - "same_28_36_and_5 = 1.0\n", + "same_28_36_and_5 = 0.0\n", "same_28_36_and_6 = 0.0\n", "same_28_36_and_7 = 0.0\n", "same_28_36_and_8 = 0.0\n", "same_28_36_and_9 = 0.0\n", - "same_28_37 = 1.0\n", + "same_28_37 = 0.0\n", "same_28_37_and_0 = 0.0\n", "same_28_37_and_1 = 0.0\n", "same_28_37_and_10 = 0.0\n", @@ -142474,12 +142464,12 @@ "same_28_37_and_2 = 0.0\n", "same_28_37_and_3 = 0.0\n", "same_28_37_and_4 = 0.0\n", - "same_28_37_and_5 = 1.0\n", + "same_28_37_and_5 = 0.0\n", "same_28_37_and_6 = 0.0\n", "same_28_37_and_7 = 0.0\n", "same_28_37_and_8 = 0.0\n", "same_28_37_and_9 = 0.0\n", - "same_28_38 = 1.0\n", + "same_28_38 = 0.0\n", "same_28_38_and_0 = 0.0\n", "same_28_38_and_1 = 0.0\n", "same_28_38_and_10 = 0.0\n", @@ -142491,12 +142481,12 @@ "same_28_38_and_2 = 0.0\n", "same_28_38_and_3 = 0.0\n", "same_28_38_and_4 = 0.0\n", - "same_28_38_and_5 = 1.0\n", + "same_28_38_and_5 = 0.0\n", "same_28_38_and_6 = 0.0\n", "same_28_38_and_7 = 0.0\n", "same_28_38_and_8 = 0.0\n", "same_28_38_and_9 = 0.0\n", - "same_28_39 = 1.0\n", + "same_28_39 = 0.0\n", "same_28_39_and_0 = 0.0\n", "same_28_39_and_1 = 0.0\n", "same_28_39_and_10 = 0.0\n", @@ -142508,12 +142498,12 @@ "same_28_39_and_2 = 0.0\n", "same_28_39_and_3 = 0.0\n", "same_28_39_and_4 = 0.0\n", - "same_28_39_and_5 = 1.0\n", + "same_28_39_and_5 = 0.0\n", "same_28_39_and_6 = 0.0\n", "same_28_39_and_7 = 0.0\n", "same_28_39_and_8 = 0.0\n", "same_28_39_and_9 = 0.0\n", - "same_28_40 = 1.0\n", + "same_28_40 = 0.0\n", "same_28_40_and_0 = 0.0\n", "same_28_40_and_1 = 0.0\n", "same_28_40_and_10 = 0.0\n", @@ -142525,12 +142515,12 @@ "same_28_40_and_2 = 0.0\n", "same_28_40_and_3 = 0.0\n", "same_28_40_and_4 = 0.0\n", - "same_28_40_and_5 = 1.0\n", + "same_28_40_and_5 = 0.0\n", "same_28_40_and_6 = 0.0\n", "same_28_40_and_7 = 0.0\n", "same_28_40_and_8 = 0.0\n", "same_28_40_and_9 = 0.0\n", - "same_28_41 = 1.0\n", + "same_28_41 = 0.0\n", "same_28_41_and_0 = 0.0\n", "same_28_41_and_1 = 0.0\n", "same_28_41_and_10 = 0.0\n", @@ -142542,12 +142532,12 @@ "same_28_41_and_2 = 0.0\n", "same_28_41_and_3 = 0.0\n", "same_28_41_and_4 = 0.0\n", - "same_28_41_and_5 = 1.0\n", + "same_28_41_and_5 = 0.0\n", "same_28_41_and_6 = 0.0\n", "same_28_41_and_7 = 0.0\n", "same_28_41_and_8 = 0.0\n", "same_28_41_and_9 = 0.0\n", - "same_28_42 = 1.0\n", + "same_28_42 = 0.0\n", "same_28_42_and_0 = 0.0\n", "same_28_42_and_1 = 0.0\n", "same_28_42_and_10 = 0.0\n", @@ -142559,12 +142549,12 @@ "same_28_42_and_2 = 0.0\n", "same_28_42_and_3 = 0.0\n", "same_28_42_and_4 = 0.0\n", - "same_28_42_and_5 = 1.0\n", + "same_28_42_and_5 = 0.0\n", "same_28_42_and_6 = 0.0\n", "same_28_42_and_7 = 0.0\n", "same_28_42_and_8 = 0.0\n", "same_28_42_and_9 = 0.0\n", - "same_28_43 = 1.0\n", + "same_28_43 = 0.0\n", "same_28_43_and_0 = 0.0\n", "same_28_43_and_1 = 0.0\n", "same_28_43_and_10 = 0.0\n", @@ -142576,7 +142566,7 @@ "same_28_43_and_2 = 0.0\n", "same_28_43_and_3 = 0.0\n", "same_28_43_and_4 = 0.0\n", - "same_28_43_and_5 = 1.0\n", + "same_28_43_and_5 = 0.0\n", "same_28_43_and_6 = 0.0\n", "same_28_43_and_7 = 0.0\n", "same_28_43_and_8 = 0.0\n", @@ -143034,9 +143024,9 @@ "same_29_30_and_14 = 0.0\n", "same_29_30_and_15 = 0.0\n", "same_29_30_and_2 = 0.0\n", - "same_29_30_and_3 = 0.0\n", + "same_29_30_and_3 = 1.0\n", "same_29_30_and_4 = 0.0\n", - "same_29_30_and_5 = 1.0\n", + "same_29_30_and_5 = 0.0\n", "same_29_30_and_6 = 0.0\n", "same_29_30_and_7 = 0.0\n", "same_29_30_and_8 = 0.0\n", @@ -143051,9 +143041,9 @@ "same_29_31_and_14 = 0.0\n", "same_29_31_and_15 = 0.0\n", "same_29_31_and_2 = 0.0\n", - "same_29_31_and_3 = 0.0\n", + "same_29_31_and_3 = 1.0\n", "same_29_31_and_4 = 0.0\n", - "same_29_31_and_5 = 1.0\n", + "same_29_31_and_5 = 0.0\n", "same_29_31_and_6 = 0.0\n", "same_29_31_and_7 = 0.0\n", "same_29_31_and_8 = 0.0\n", @@ -143068,9 +143058,9 @@ "same_29_32_and_14 = 0.0\n", "same_29_32_and_15 = 0.0\n", "same_29_32_and_2 = 0.0\n", - "same_29_32_and_3 = 0.0\n", + "same_29_32_and_3 = 1.0\n", "same_29_32_and_4 = 0.0\n", - "same_29_32_and_5 = 1.0\n", + "same_29_32_and_5 = 0.0\n", "same_29_32_and_6 = 0.0\n", "same_29_32_and_7 = 0.0\n", "same_29_32_and_8 = 0.0\n", @@ -143085,9 +143075,9 @@ "same_29_33_and_14 = 0.0\n", "same_29_33_and_15 = 0.0\n", "same_29_33_and_2 = 0.0\n", - "same_29_33_and_3 = 0.0\n", + "same_29_33_and_3 = 1.0\n", "same_29_33_and_4 = 0.0\n", - "same_29_33_and_5 = 1.0\n", + "same_29_33_and_5 = 0.0\n", "same_29_33_and_6 = 0.0\n", "same_29_33_and_7 = 0.0\n", "same_29_33_and_8 = 0.0\n", @@ -143102,14 +143092,14 @@ "same_29_34_and_14 = 0.0\n", "same_29_34_and_15 = 0.0\n", "same_29_34_and_2 = 0.0\n", - "same_29_34_and_3 = 0.0\n", + "same_29_34_and_3 = 1.0\n", "same_29_34_and_4 = 0.0\n", - "same_29_34_and_5 = 1.0\n", + "same_29_34_and_5 = 0.0\n", "same_29_34_and_6 = 0.0\n", "same_29_34_and_7 = 0.0\n", "same_29_34_and_8 = 0.0\n", "same_29_34_and_9 = 0.0\n", - "same_29_35 = 1.0\n", + "same_29_35 = 0.0\n", "same_29_35_and_0 = 0.0\n", "same_29_35_and_1 = 0.0\n", "same_29_35_and_10 = 0.0\n", @@ -143121,12 +143111,12 @@ "same_29_35_and_2 = 0.0\n", "same_29_35_and_3 = 0.0\n", "same_29_35_and_4 = 0.0\n", - "same_29_35_and_5 = 1.0\n", + "same_29_35_and_5 = 0.0\n", "same_29_35_and_6 = 0.0\n", "same_29_35_and_7 = 0.0\n", "same_29_35_and_8 = 0.0\n", "same_29_35_and_9 = 0.0\n", - "same_29_36 = 1.0\n", + "same_29_36 = 0.0\n", "same_29_36_and_0 = 0.0\n", "same_29_36_and_1 = 0.0\n", "same_29_36_and_10 = 0.0\n", @@ -143138,12 +143128,12 @@ "same_29_36_and_2 = 0.0\n", "same_29_36_and_3 = 0.0\n", "same_29_36_and_4 = 0.0\n", - "same_29_36_and_5 = 1.0\n", + "same_29_36_and_5 = 0.0\n", "same_29_36_and_6 = 0.0\n", "same_29_36_and_7 = 0.0\n", "same_29_36_and_8 = 0.0\n", "same_29_36_and_9 = 0.0\n", - "same_29_37 = 1.0\n", + "same_29_37 = 0.0\n", "same_29_37_and_0 = 0.0\n", "same_29_37_and_1 = 0.0\n", "same_29_37_and_10 = 0.0\n", @@ -143155,12 +143145,12 @@ "same_29_37_and_2 = 0.0\n", "same_29_37_and_3 = 0.0\n", "same_29_37_and_4 = 0.0\n", - "same_29_37_and_5 = 1.0\n", + "same_29_37_and_5 = 0.0\n", "same_29_37_and_6 = 0.0\n", "same_29_37_and_7 = 0.0\n", "same_29_37_and_8 = 0.0\n", "same_29_37_and_9 = 0.0\n", - "same_29_38 = 1.0\n", + "same_29_38 = 0.0\n", "same_29_38_and_0 = 0.0\n", "same_29_38_and_1 = 0.0\n", "same_29_38_and_10 = 0.0\n", @@ -143172,12 +143162,12 @@ "same_29_38_and_2 = 0.0\n", "same_29_38_and_3 = 0.0\n", "same_29_38_and_4 = 0.0\n", - "same_29_38_and_5 = 1.0\n", + "same_29_38_and_5 = 0.0\n", "same_29_38_and_6 = 0.0\n", "same_29_38_and_7 = 0.0\n", "same_29_38_and_8 = 0.0\n", "same_29_38_and_9 = 0.0\n", - "same_29_39 = 1.0\n", + "same_29_39 = 0.0\n", "same_29_39_and_0 = 0.0\n", "same_29_39_and_1 = 0.0\n", "same_29_39_and_10 = 0.0\n", @@ -143189,12 +143179,12 @@ "same_29_39_and_2 = 0.0\n", "same_29_39_and_3 = 0.0\n", "same_29_39_and_4 = 0.0\n", - "same_29_39_and_5 = 1.0\n", + "same_29_39_and_5 = 0.0\n", "same_29_39_and_6 = 0.0\n", "same_29_39_and_7 = 0.0\n", "same_29_39_and_8 = 0.0\n", "same_29_39_and_9 = 0.0\n", - "same_29_40 = 1.0\n", + "same_29_40 = 0.0\n", "same_29_40_and_0 = 0.0\n", "same_29_40_and_1 = 0.0\n", "same_29_40_and_10 = 0.0\n", @@ -143206,12 +143196,12 @@ "same_29_40_and_2 = 0.0\n", "same_29_40_and_3 = 0.0\n", "same_29_40_and_4 = 0.0\n", - "same_29_40_and_5 = 1.0\n", + "same_29_40_and_5 = 0.0\n", "same_29_40_and_6 = 0.0\n", "same_29_40_and_7 = 0.0\n", "same_29_40_and_8 = 0.0\n", "same_29_40_and_9 = 0.0\n", - "same_29_41 = 1.0\n", + "same_29_41 = 0.0\n", "same_29_41_and_0 = 0.0\n", "same_29_41_and_1 = 0.0\n", "same_29_41_and_10 = 0.0\n", @@ -143223,12 +143213,12 @@ "same_29_41_and_2 = 0.0\n", "same_29_41_and_3 = 0.0\n", "same_29_41_and_4 = 0.0\n", - "same_29_41_and_5 = 1.0\n", + "same_29_41_and_5 = 0.0\n", "same_29_41_and_6 = 0.0\n", "same_29_41_and_7 = 0.0\n", "same_29_41_and_8 = 0.0\n", "same_29_41_and_9 = 0.0\n", - "same_29_42 = 1.0\n", + "same_29_42 = 0.0\n", "same_29_42_and_0 = 0.0\n", "same_29_42_and_1 = 0.0\n", "same_29_42_and_10 = 0.0\n", @@ -143240,12 +143230,12 @@ "same_29_42_and_2 = 0.0\n", "same_29_42_and_3 = 0.0\n", "same_29_42_and_4 = 0.0\n", - "same_29_42_and_5 = 1.0\n", + "same_29_42_and_5 = 0.0\n", "same_29_42_and_6 = 0.0\n", "same_29_42_and_7 = 0.0\n", "same_29_42_and_8 = 0.0\n", "same_29_42_and_9 = 0.0\n", - "same_29_43 = 1.0\n", + "same_29_43 = 0.0\n", "same_29_43_and_0 = 0.0\n", "same_29_43_and_1 = 0.0\n", "same_29_43_and_10 = 0.0\n", @@ -143257,7 +143247,7 @@ "same_29_43_and_2 = 0.0\n", "same_29_43_and_3 = 0.0\n", "same_29_43_and_4 = 0.0\n", - "same_29_43_and_5 = 1.0\n", + "same_29_43_and_5 = 0.0\n", "same_29_43_and_6 = 0.0\n", "same_29_43_and_7 = 0.0\n", "same_29_43_and_8 = 0.0\n", @@ -144216,11 +144206,11 @@ "same_2_39_and_7 = 0.0\n", "same_2_39_and_8 = 0.0\n", "same_2_39_and_9 = 0.0\n", - "same_2_3_and_0 = 0.0\n", + "same_2_3_and_0 = 1.0\n", "same_2_3_and_1 = 0.0\n", "same_2_3_and_10 = 0.0\n", "same_2_3_and_11 = 0.0\n", - "same_2_3_and_12 = 1.0\n", + "same_2_3_and_12 = 0.0\n", "same_2_3_and_13 = 0.0\n", "same_2_3_and_14 = 0.0\n", "same_2_3_and_15 = 0.0\n", @@ -144232,7 +144222,7 @@ "same_2_3_and_7 = 0.0\n", "same_2_3_and_8 = 0.0\n", "same_2_3_and_9 = 0.0\n", - "same_2_4 = 1.0\n", + "same_2_4 = 0.0\n", "same_2_40 = 0.0\n", "same_2_40_and_0 = 0.0\n", "same_2_40_and_1 = 0.0\n", @@ -144407,7 +144397,7 @@ "same_2_4_and_1 = 0.0\n", "same_2_4_and_10 = 0.0\n", "same_2_4_and_11 = 0.0\n", - "same_2_4_and_12 = 1.0\n", + "same_2_4_and_12 = 0.0\n", "same_2_4_and_13 = 0.0\n", "same_2_4_and_14 = 0.0\n", "same_2_4_and_15 = 0.0\n", @@ -144419,7 +144409,7 @@ "same_2_4_and_7 = 0.0\n", "same_2_4_and_8 = 0.0\n", "same_2_4_and_9 = 0.0\n", - "same_2_5 = 1.0\n", + "same_2_5 = 0.0\n", "same_2_50 = 0.0\n", "same_2_50_and_0 = 0.0\n", "same_2_50_and_1 = 0.0\n", @@ -144594,7 +144584,7 @@ "same_2_5_and_1 = 0.0\n", "same_2_5_and_10 = 0.0\n", "same_2_5_and_11 = 0.0\n", - "same_2_5_and_12 = 1.0\n", + "same_2_5_and_12 = 0.0\n", "same_2_5_and_13 = 0.0\n", "same_2_5_and_14 = 0.0\n", "same_2_5_and_15 = 0.0\n", @@ -144606,7 +144596,7 @@ "same_2_5_and_7 = 0.0\n", "same_2_5_and_8 = 0.0\n", "same_2_5_and_9 = 0.0\n", - "same_2_6 = 1.0\n", + "same_2_6 = 0.0\n", "same_2_60 = 0.0\n", "same_2_60_and_0 = 0.0\n", "same_2_60_and_1 = 0.0\n", @@ -144781,7 +144771,7 @@ "same_2_6_and_1 = 0.0\n", "same_2_6_and_10 = 0.0\n", "same_2_6_and_11 = 0.0\n", - "same_2_6_and_12 = 1.0\n", + "same_2_6_and_12 = 0.0\n", "same_2_6_and_13 = 0.0\n", "same_2_6_and_14 = 0.0\n", "same_2_6_and_15 = 0.0\n", @@ -144855,9 +144845,9 @@ "same_30_31_and_14 = 0.0\n", "same_30_31_and_15 = 0.0\n", "same_30_31_and_2 = 0.0\n", - "same_30_31_and_3 = 0.0\n", + "same_30_31_and_3 = 1.0\n", "same_30_31_and_4 = 0.0\n", - "same_30_31_and_5 = 1.0\n", + "same_30_31_and_5 = 0.0\n", "same_30_31_and_6 = 0.0\n", "same_30_31_and_7 = 0.0\n", "same_30_31_and_8 = 0.0\n", @@ -144872,9 +144862,9 @@ "same_30_32_and_14 = 0.0\n", "same_30_32_and_15 = 0.0\n", "same_30_32_and_2 = 0.0\n", - "same_30_32_and_3 = 0.0\n", + "same_30_32_and_3 = 1.0\n", "same_30_32_and_4 = 0.0\n", - "same_30_32_and_5 = 1.0\n", + "same_30_32_and_5 = 0.0\n", "same_30_32_and_6 = 0.0\n", "same_30_32_and_7 = 0.0\n", "same_30_32_and_8 = 0.0\n", @@ -144889,9 +144879,9 @@ "same_30_33_and_14 = 0.0\n", "same_30_33_and_15 = 0.0\n", "same_30_33_and_2 = 0.0\n", - "same_30_33_and_3 = 0.0\n", + "same_30_33_and_3 = 1.0\n", "same_30_33_and_4 = 0.0\n", - "same_30_33_and_5 = 1.0\n", + "same_30_33_and_5 = 0.0\n", "same_30_33_and_6 = 0.0\n", "same_30_33_and_7 = 0.0\n", "same_30_33_and_8 = 0.0\n", @@ -144906,14 +144896,14 @@ "same_30_34_and_14 = 0.0\n", "same_30_34_and_15 = 0.0\n", "same_30_34_and_2 = 0.0\n", - "same_30_34_and_3 = 0.0\n", + "same_30_34_and_3 = 1.0\n", "same_30_34_and_4 = 0.0\n", - "same_30_34_and_5 = 1.0\n", + "same_30_34_and_5 = 0.0\n", "same_30_34_and_6 = 0.0\n", "same_30_34_and_7 = 0.0\n", "same_30_34_and_8 = 0.0\n", "same_30_34_and_9 = 0.0\n", - "same_30_35 = 1.0\n", + "same_30_35 = 0.0\n", "same_30_35_and_0 = 0.0\n", "same_30_35_and_1 = 0.0\n", "same_30_35_and_10 = 0.0\n", @@ -144925,12 +144915,12 @@ "same_30_35_and_2 = 0.0\n", "same_30_35_and_3 = 0.0\n", "same_30_35_and_4 = 0.0\n", - "same_30_35_and_5 = 1.0\n", + "same_30_35_and_5 = 0.0\n", "same_30_35_and_6 = 0.0\n", "same_30_35_and_7 = 0.0\n", "same_30_35_and_8 = 0.0\n", "same_30_35_and_9 = 0.0\n", - "same_30_36 = 1.0\n", + "same_30_36 = 0.0\n", "same_30_36_and_0 = 0.0\n", "same_30_36_and_1 = 0.0\n", "same_30_36_and_10 = 0.0\n", @@ -144942,12 +144932,12 @@ "same_30_36_and_2 = 0.0\n", "same_30_36_and_3 = 0.0\n", "same_30_36_and_4 = 0.0\n", - "same_30_36_and_5 = 1.0\n", + "same_30_36_and_5 = 0.0\n", "same_30_36_and_6 = 0.0\n", "same_30_36_and_7 = 0.0\n", "same_30_36_and_8 = 0.0\n", "same_30_36_and_9 = 0.0\n", - "same_30_37 = 1.0\n", + "same_30_37 = 0.0\n", "same_30_37_and_0 = 0.0\n", "same_30_37_and_1 = 0.0\n", "same_30_37_and_10 = 0.0\n", @@ -144959,12 +144949,12 @@ "same_30_37_and_2 = 0.0\n", "same_30_37_and_3 = 0.0\n", "same_30_37_and_4 = 0.0\n", - "same_30_37_and_5 = 1.0\n", + "same_30_37_and_5 = 0.0\n", "same_30_37_and_6 = 0.0\n", "same_30_37_and_7 = 0.0\n", "same_30_37_and_8 = 0.0\n", "same_30_37_and_9 = 0.0\n", - "same_30_38 = 1.0\n", + "same_30_38 = 0.0\n", "same_30_38_and_0 = 0.0\n", "same_30_38_and_1 = 0.0\n", "same_30_38_and_10 = 0.0\n", @@ -144976,12 +144966,12 @@ "same_30_38_and_2 = 0.0\n", "same_30_38_and_3 = 0.0\n", "same_30_38_and_4 = 0.0\n", - "same_30_38_and_5 = 1.0\n", + "same_30_38_and_5 = 0.0\n", "same_30_38_and_6 = 0.0\n", "same_30_38_and_7 = 0.0\n", "same_30_38_and_8 = 0.0\n", "same_30_38_and_9 = 0.0\n", - "same_30_39 = 1.0\n", + "same_30_39 = 0.0\n", "same_30_39_and_0 = 0.0\n", "same_30_39_and_1 = 0.0\n", "same_30_39_and_10 = 0.0\n", @@ -144993,12 +144983,12 @@ "same_30_39_and_2 = 0.0\n", "same_30_39_and_3 = 0.0\n", "same_30_39_and_4 = 0.0\n", - "same_30_39_and_5 = 1.0\n", + "same_30_39_and_5 = 0.0\n", "same_30_39_and_6 = 0.0\n", "same_30_39_and_7 = 0.0\n", "same_30_39_and_8 = 0.0\n", "same_30_39_and_9 = 0.0\n", - "same_30_40 = 1.0\n", + "same_30_40 = 0.0\n", "same_30_40_and_0 = 0.0\n", "same_30_40_and_1 = 0.0\n", "same_30_40_and_10 = 0.0\n", @@ -145010,12 +145000,12 @@ "same_30_40_and_2 = 0.0\n", "same_30_40_and_3 = 0.0\n", "same_30_40_and_4 = 0.0\n", - "same_30_40_and_5 = 1.0\n", + "same_30_40_and_5 = 0.0\n", "same_30_40_and_6 = 0.0\n", "same_30_40_and_7 = 0.0\n", "same_30_40_and_8 = 0.0\n", "same_30_40_and_9 = 0.0\n", - "same_30_41 = 1.0\n", + "same_30_41 = 0.0\n", "same_30_41_and_0 = 0.0\n", "same_30_41_and_1 = 0.0\n", "same_30_41_and_10 = 0.0\n", @@ -145027,12 +145017,12 @@ "same_30_41_and_2 = 0.0\n", "same_30_41_and_3 = 0.0\n", "same_30_41_and_4 = 0.0\n", - "same_30_41_and_5 = 1.0\n", + "same_30_41_and_5 = 0.0\n", "same_30_41_and_6 = 0.0\n", "same_30_41_and_7 = 0.0\n", "same_30_41_and_8 = 0.0\n", "same_30_41_and_9 = 0.0\n", - "same_30_42 = 1.0\n", + "same_30_42 = 0.0\n", "same_30_42_and_0 = 0.0\n", "same_30_42_and_1 = 0.0\n", "same_30_42_and_10 = 0.0\n", @@ -145044,12 +145034,12 @@ "same_30_42_and_2 = 0.0\n", "same_30_42_and_3 = 0.0\n", "same_30_42_and_4 = 0.0\n", - "same_30_42_and_5 = 1.0\n", + "same_30_42_and_5 = 0.0\n", "same_30_42_and_6 = 0.0\n", "same_30_42_and_7 = 0.0\n", "same_30_42_and_8 = 0.0\n", "same_30_42_and_9 = 0.0\n", - "same_30_43 = 1.0\n", + "same_30_43 = 0.0\n", "same_30_43_and_0 = 0.0\n", "same_30_43_and_1 = 0.0\n", "same_30_43_and_10 = 0.0\n", @@ -145061,7 +145051,7 @@ "same_30_43_and_2 = 0.0\n", "same_30_43_and_3 = 0.0\n", "same_30_43_and_4 = 0.0\n", - "same_30_43_and_5 = 1.0\n", + "same_30_43_and_5 = 0.0\n", "same_30_43_and_6 = 0.0\n", "same_30_43_and_7 = 0.0\n", "same_30_43_and_8 = 0.0\n", @@ -145519,9 +145509,9 @@ "same_31_32_and_14 = 0.0\n", "same_31_32_and_15 = 0.0\n", "same_31_32_and_2 = 0.0\n", - "same_31_32_and_3 = 0.0\n", + "same_31_32_and_3 = 1.0\n", "same_31_32_and_4 = 0.0\n", - "same_31_32_and_5 = 1.0\n", + "same_31_32_and_5 = 0.0\n", "same_31_32_and_6 = 0.0\n", "same_31_32_and_7 = 0.0\n", "same_31_32_and_8 = 0.0\n", @@ -145536,9 +145526,9 @@ "same_31_33_and_14 = 0.0\n", "same_31_33_and_15 = 0.0\n", "same_31_33_and_2 = 0.0\n", - "same_31_33_and_3 = 0.0\n", + "same_31_33_and_3 = 1.0\n", "same_31_33_and_4 = 0.0\n", - "same_31_33_and_5 = 1.0\n", + "same_31_33_and_5 = 0.0\n", "same_31_33_and_6 = 0.0\n", "same_31_33_and_7 = 0.0\n", "same_31_33_and_8 = 0.0\n", @@ -145553,14 +145543,14 @@ "same_31_34_and_14 = 0.0\n", "same_31_34_and_15 = 0.0\n", "same_31_34_and_2 = 0.0\n", - "same_31_34_and_3 = 0.0\n", + "same_31_34_and_3 = 1.0\n", "same_31_34_and_4 = 0.0\n", - "same_31_34_and_5 = 1.0\n", + "same_31_34_and_5 = 0.0\n", "same_31_34_and_6 = 0.0\n", "same_31_34_and_7 = 0.0\n", "same_31_34_and_8 = 0.0\n", "same_31_34_and_9 = 0.0\n", - "same_31_35 = 1.0\n", + "same_31_35 = 0.0\n", "same_31_35_and_0 = 0.0\n", "same_31_35_and_1 = 0.0\n", "same_31_35_and_10 = 0.0\n", @@ -145572,12 +145562,12 @@ "same_31_35_and_2 = 0.0\n", "same_31_35_and_3 = 0.0\n", "same_31_35_and_4 = 0.0\n", - "same_31_35_and_5 = 1.0\n", + "same_31_35_and_5 = 0.0\n", "same_31_35_and_6 = 0.0\n", "same_31_35_and_7 = 0.0\n", "same_31_35_and_8 = 0.0\n", "same_31_35_and_9 = 0.0\n", - "same_31_36 = 1.0\n", + "same_31_36 = 0.0\n", "same_31_36_and_0 = 0.0\n", "same_31_36_and_1 = 0.0\n", "same_31_36_and_10 = 0.0\n", @@ -145589,12 +145579,12 @@ "same_31_36_and_2 = 0.0\n", "same_31_36_and_3 = 0.0\n", "same_31_36_and_4 = 0.0\n", - "same_31_36_and_5 = 1.0\n", + "same_31_36_and_5 = 0.0\n", "same_31_36_and_6 = 0.0\n", "same_31_36_and_7 = 0.0\n", "same_31_36_and_8 = 0.0\n", "same_31_36_and_9 = 0.0\n", - "same_31_37 = 1.0\n", + "same_31_37 = 0.0\n", "same_31_37_and_0 = 0.0\n", "same_31_37_and_1 = 0.0\n", "same_31_37_and_10 = 0.0\n", @@ -145606,12 +145596,12 @@ "same_31_37_and_2 = 0.0\n", "same_31_37_and_3 = 0.0\n", "same_31_37_and_4 = 0.0\n", - "same_31_37_and_5 = 1.0\n", + "same_31_37_and_5 = 0.0\n", "same_31_37_and_6 = 0.0\n", "same_31_37_and_7 = 0.0\n", "same_31_37_and_8 = 0.0\n", "same_31_37_and_9 = 0.0\n", - "same_31_38 = 1.0\n", + "same_31_38 = 0.0\n", "same_31_38_and_0 = 0.0\n", "same_31_38_and_1 = 0.0\n", "same_31_38_and_10 = 0.0\n", @@ -145623,12 +145613,12 @@ "same_31_38_and_2 = 0.0\n", "same_31_38_and_3 = 0.0\n", "same_31_38_and_4 = 0.0\n", - "same_31_38_and_5 = 1.0\n", + "same_31_38_and_5 = 0.0\n", "same_31_38_and_6 = 0.0\n", "same_31_38_and_7 = 0.0\n", "same_31_38_and_8 = 0.0\n", "same_31_38_and_9 = 0.0\n", - "same_31_39 = 1.0\n", + "same_31_39 = 0.0\n", "same_31_39_and_0 = 0.0\n", "same_31_39_and_1 = 0.0\n", "same_31_39_and_10 = 0.0\n", @@ -145640,12 +145630,12 @@ "same_31_39_and_2 = 0.0\n", "same_31_39_and_3 = 0.0\n", "same_31_39_and_4 = 0.0\n", - "same_31_39_and_5 = 1.0\n", + "same_31_39_and_5 = 0.0\n", "same_31_39_and_6 = 0.0\n", "same_31_39_and_7 = 0.0\n", "same_31_39_and_8 = 0.0\n", "same_31_39_and_9 = 0.0\n", - "same_31_40 = 1.0\n", + "same_31_40 = 0.0\n", "same_31_40_and_0 = 0.0\n", "same_31_40_and_1 = 0.0\n", "same_31_40_and_10 = 0.0\n", @@ -145657,12 +145647,12 @@ "same_31_40_and_2 = 0.0\n", "same_31_40_and_3 = 0.0\n", "same_31_40_and_4 = 0.0\n", - "same_31_40_and_5 = 1.0\n", + "same_31_40_and_5 = 0.0\n", "same_31_40_and_6 = 0.0\n", "same_31_40_and_7 = 0.0\n", "same_31_40_and_8 = 0.0\n", "same_31_40_and_9 = 0.0\n", - "same_31_41 = 1.0\n", + "same_31_41 = 0.0\n", "same_31_41_and_0 = 0.0\n", "same_31_41_and_1 = 0.0\n", "same_31_41_and_10 = 0.0\n", @@ -145674,12 +145664,12 @@ "same_31_41_and_2 = 0.0\n", "same_31_41_and_3 = 0.0\n", "same_31_41_and_4 = 0.0\n", - "same_31_41_and_5 = 1.0\n", + "same_31_41_and_5 = 0.0\n", "same_31_41_and_6 = 0.0\n", "same_31_41_and_7 = 0.0\n", "same_31_41_and_8 = 0.0\n", "same_31_41_and_9 = 0.0\n", - "same_31_42 = 1.0\n", + "same_31_42 = 0.0\n", "same_31_42_and_0 = 0.0\n", "same_31_42_and_1 = 0.0\n", "same_31_42_and_10 = 0.0\n", @@ -145691,12 +145681,12 @@ "same_31_42_and_2 = 0.0\n", "same_31_42_and_3 = 0.0\n", "same_31_42_and_4 = 0.0\n", - "same_31_42_and_5 = 1.0\n", + "same_31_42_and_5 = 0.0\n", "same_31_42_and_6 = 0.0\n", "same_31_42_and_7 = 0.0\n", "same_31_42_and_8 = 0.0\n", "same_31_42_and_9 = 0.0\n", - "same_31_43 = 1.0\n", + "same_31_43 = 0.0\n", "same_31_43_and_0 = 0.0\n", "same_31_43_and_1 = 0.0\n", "same_31_43_and_10 = 0.0\n", @@ -145708,7 +145698,7 @@ "same_31_43_and_2 = 0.0\n", "same_31_43_and_3 = 0.0\n", "same_31_43_and_4 = 0.0\n", - "same_31_43_and_5 = 1.0\n", + "same_31_43_and_5 = 0.0\n", "same_31_43_and_6 = 0.0\n", "same_31_43_and_7 = 0.0\n", "same_31_43_and_8 = 0.0\n", @@ -146166,9 +146156,9 @@ "same_32_33_and_14 = 0.0\n", "same_32_33_and_15 = 0.0\n", "same_32_33_and_2 = 0.0\n", - "same_32_33_and_3 = 0.0\n", + "same_32_33_and_3 = 1.0\n", "same_32_33_and_4 = 0.0\n", - "same_32_33_and_5 = 1.0\n", + "same_32_33_and_5 = 0.0\n", "same_32_33_and_6 = 0.0\n", "same_32_33_and_7 = 0.0\n", "same_32_33_and_8 = 0.0\n", @@ -146183,14 +146173,14 @@ "same_32_34_and_14 = 0.0\n", "same_32_34_and_15 = 0.0\n", "same_32_34_and_2 = 0.0\n", - "same_32_34_and_3 = 0.0\n", + "same_32_34_and_3 = 1.0\n", "same_32_34_and_4 = 0.0\n", - "same_32_34_and_5 = 1.0\n", + "same_32_34_and_5 = 0.0\n", "same_32_34_and_6 = 0.0\n", "same_32_34_and_7 = 0.0\n", "same_32_34_and_8 = 0.0\n", "same_32_34_and_9 = 0.0\n", - "same_32_35 = 1.0\n", + "same_32_35 = 0.0\n", "same_32_35_and_0 = 0.0\n", "same_32_35_and_1 = 0.0\n", "same_32_35_and_10 = 0.0\n", @@ -146202,12 +146192,12 @@ "same_32_35_and_2 = 0.0\n", "same_32_35_and_3 = 0.0\n", "same_32_35_and_4 = 0.0\n", - "same_32_35_and_5 = 1.0\n", + "same_32_35_and_5 = 0.0\n", "same_32_35_and_6 = 0.0\n", "same_32_35_and_7 = 0.0\n", "same_32_35_and_8 = 0.0\n", "same_32_35_and_9 = 0.0\n", - "same_32_36 = 1.0\n", + "same_32_36 = 0.0\n", "same_32_36_and_0 = 0.0\n", "same_32_36_and_1 = 0.0\n", "same_32_36_and_10 = 0.0\n", @@ -146219,12 +146209,12 @@ "same_32_36_and_2 = 0.0\n", "same_32_36_and_3 = 0.0\n", "same_32_36_and_4 = 0.0\n", - "same_32_36_and_5 = 1.0\n", + "same_32_36_and_5 = 0.0\n", "same_32_36_and_6 = 0.0\n", "same_32_36_and_7 = 0.0\n", "same_32_36_and_8 = 0.0\n", "same_32_36_and_9 = 0.0\n", - "same_32_37 = 1.0\n", + "same_32_37 = 0.0\n", "same_32_37_and_0 = 0.0\n", "same_32_37_and_1 = 0.0\n", "same_32_37_and_10 = 0.0\n", @@ -146236,12 +146226,12 @@ "same_32_37_and_2 = 0.0\n", "same_32_37_and_3 = 0.0\n", "same_32_37_and_4 = 0.0\n", - "same_32_37_and_5 = 1.0\n", + "same_32_37_and_5 = 0.0\n", "same_32_37_and_6 = 0.0\n", "same_32_37_and_7 = 0.0\n", "same_32_37_and_8 = 0.0\n", "same_32_37_and_9 = 0.0\n", - "same_32_38 = 1.0\n", + "same_32_38 = 0.0\n", "same_32_38_and_0 = 0.0\n", "same_32_38_and_1 = 0.0\n", "same_32_38_and_10 = 0.0\n", @@ -146253,12 +146243,12 @@ "same_32_38_and_2 = 0.0\n", "same_32_38_and_3 = 0.0\n", "same_32_38_and_4 = 0.0\n", - "same_32_38_and_5 = 1.0\n", + "same_32_38_and_5 = 0.0\n", "same_32_38_and_6 = 0.0\n", "same_32_38_and_7 = 0.0\n", "same_32_38_and_8 = 0.0\n", "same_32_38_and_9 = 0.0\n", - "same_32_39 = 1.0\n", + "same_32_39 = 0.0\n", "same_32_39_and_0 = 0.0\n", "same_32_39_and_1 = 0.0\n", "same_32_39_and_10 = 0.0\n", @@ -146270,12 +146260,12 @@ "same_32_39_and_2 = 0.0\n", "same_32_39_and_3 = 0.0\n", "same_32_39_and_4 = 0.0\n", - "same_32_39_and_5 = 1.0\n", + "same_32_39_and_5 = 0.0\n", "same_32_39_and_6 = 0.0\n", "same_32_39_and_7 = 0.0\n", "same_32_39_and_8 = 0.0\n", "same_32_39_and_9 = 0.0\n", - "same_32_40 = 1.0\n", + "same_32_40 = 0.0\n", "same_32_40_and_0 = 0.0\n", "same_32_40_and_1 = 0.0\n", "same_32_40_and_10 = 0.0\n", @@ -146287,12 +146277,12 @@ "same_32_40_and_2 = 0.0\n", "same_32_40_and_3 = 0.0\n", "same_32_40_and_4 = 0.0\n", - "same_32_40_and_5 = 1.0\n", + "same_32_40_and_5 = 0.0\n", "same_32_40_and_6 = 0.0\n", "same_32_40_and_7 = 0.0\n", "same_32_40_and_8 = 0.0\n", "same_32_40_and_9 = 0.0\n", - "same_32_41 = 1.0\n", + "same_32_41 = 0.0\n", "same_32_41_and_0 = 0.0\n", "same_32_41_and_1 = 0.0\n", "same_32_41_and_10 = 0.0\n", @@ -146304,12 +146294,12 @@ "same_32_41_and_2 = 0.0\n", "same_32_41_and_3 = 0.0\n", "same_32_41_and_4 = 0.0\n", - "same_32_41_and_5 = 1.0\n", + "same_32_41_and_5 = 0.0\n", "same_32_41_and_6 = 0.0\n", "same_32_41_and_7 = 0.0\n", "same_32_41_and_8 = 0.0\n", "same_32_41_and_9 = 0.0\n", - "same_32_42 = 1.0\n", + "same_32_42 = 0.0\n", "same_32_42_and_0 = 0.0\n", "same_32_42_and_1 = 0.0\n", "same_32_42_and_10 = 0.0\n", @@ -146321,12 +146311,12 @@ "same_32_42_and_2 = 0.0\n", "same_32_42_and_3 = 0.0\n", "same_32_42_and_4 = 0.0\n", - "same_32_42_and_5 = 1.0\n", + "same_32_42_and_5 = 0.0\n", "same_32_42_and_6 = 0.0\n", "same_32_42_and_7 = 0.0\n", "same_32_42_and_8 = 0.0\n", "same_32_42_and_9 = 0.0\n", - "same_32_43 = 1.0\n", + "same_32_43 = 0.0\n", "same_32_43_and_0 = 0.0\n", "same_32_43_and_1 = 0.0\n", "same_32_43_and_10 = 0.0\n", @@ -146338,7 +146328,7 @@ "same_32_43_and_2 = 0.0\n", "same_32_43_and_3 = 0.0\n", "same_32_43_and_4 = 0.0\n", - "same_32_43_and_5 = 1.0\n", + "same_32_43_and_5 = 0.0\n", "same_32_43_and_6 = 0.0\n", "same_32_43_and_7 = 0.0\n", "same_32_43_and_8 = 0.0\n", @@ -146796,14 +146786,14 @@ "same_33_34_and_14 = 0.0\n", "same_33_34_and_15 = 0.0\n", "same_33_34_and_2 = 0.0\n", - "same_33_34_and_3 = 0.0\n", + "same_33_34_and_3 = 1.0\n", "same_33_34_and_4 = 0.0\n", - "same_33_34_and_5 = 1.0\n", + "same_33_34_and_5 = 0.0\n", "same_33_34_and_6 = 0.0\n", "same_33_34_and_7 = 0.0\n", "same_33_34_and_8 = 0.0\n", "same_33_34_and_9 = 0.0\n", - "same_33_35 = 1.0\n", + "same_33_35 = 0.0\n", "same_33_35_and_0 = 0.0\n", "same_33_35_and_1 = 0.0\n", "same_33_35_and_10 = 0.0\n", @@ -146815,12 +146805,12 @@ "same_33_35_and_2 = 0.0\n", "same_33_35_and_3 = 0.0\n", "same_33_35_and_4 = 0.0\n", - "same_33_35_and_5 = 1.0\n", + "same_33_35_and_5 = 0.0\n", "same_33_35_and_6 = 0.0\n", "same_33_35_and_7 = 0.0\n", "same_33_35_and_8 = 0.0\n", "same_33_35_and_9 = 0.0\n", - "same_33_36 = 1.0\n", + "same_33_36 = 0.0\n", "same_33_36_and_0 = 0.0\n", "same_33_36_and_1 = 0.0\n", "same_33_36_and_10 = 0.0\n", @@ -146832,12 +146822,12 @@ "same_33_36_and_2 = 0.0\n", "same_33_36_and_3 = 0.0\n", "same_33_36_and_4 = 0.0\n", - "same_33_36_and_5 = 1.0\n", + "same_33_36_and_5 = 0.0\n", "same_33_36_and_6 = 0.0\n", "same_33_36_and_7 = 0.0\n", "same_33_36_and_8 = 0.0\n", "same_33_36_and_9 = 0.0\n", - "same_33_37 = 1.0\n", + "same_33_37 = 0.0\n", "same_33_37_and_0 = 0.0\n", "same_33_37_and_1 = 0.0\n", "same_33_37_and_10 = 0.0\n", @@ -146849,12 +146839,12 @@ "same_33_37_and_2 = 0.0\n", "same_33_37_and_3 = 0.0\n", "same_33_37_and_4 = 0.0\n", - "same_33_37_and_5 = 1.0\n", + "same_33_37_and_5 = 0.0\n", "same_33_37_and_6 = 0.0\n", "same_33_37_and_7 = 0.0\n", "same_33_37_and_8 = 0.0\n", "same_33_37_and_9 = 0.0\n", - "same_33_38 = 1.0\n", + "same_33_38 = 0.0\n", "same_33_38_and_0 = 0.0\n", "same_33_38_and_1 = 0.0\n", "same_33_38_and_10 = 0.0\n", @@ -146866,12 +146856,12 @@ "same_33_38_and_2 = 0.0\n", "same_33_38_and_3 = 0.0\n", "same_33_38_and_4 = 0.0\n", - "same_33_38_and_5 = 1.0\n", + "same_33_38_and_5 = 0.0\n", "same_33_38_and_6 = 0.0\n", "same_33_38_and_7 = 0.0\n", "same_33_38_and_8 = 0.0\n", "same_33_38_and_9 = 0.0\n", - "same_33_39 = 1.0\n", + "same_33_39 = 0.0\n", "same_33_39_and_0 = 0.0\n", "same_33_39_and_1 = 0.0\n", "same_33_39_and_10 = 0.0\n", @@ -146883,12 +146873,12 @@ "same_33_39_and_2 = 0.0\n", "same_33_39_and_3 = 0.0\n", "same_33_39_and_4 = 0.0\n", - "same_33_39_and_5 = 1.0\n", + "same_33_39_and_5 = 0.0\n", "same_33_39_and_6 = 0.0\n", "same_33_39_and_7 = 0.0\n", "same_33_39_and_8 = 0.0\n", "same_33_39_and_9 = 0.0\n", - "same_33_40 = 1.0\n", + "same_33_40 = 0.0\n", "same_33_40_and_0 = 0.0\n", "same_33_40_and_1 = 0.0\n", "same_33_40_and_10 = 0.0\n", @@ -146900,12 +146890,12 @@ "same_33_40_and_2 = 0.0\n", "same_33_40_and_3 = 0.0\n", "same_33_40_and_4 = 0.0\n", - "same_33_40_and_5 = 1.0\n", + "same_33_40_and_5 = 0.0\n", "same_33_40_and_6 = 0.0\n", "same_33_40_and_7 = 0.0\n", "same_33_40_and_8 = 0.0\n", "same_33_40_and_9 = 0.0\n", - "same_33_41 = 1.0\n", + "same_33_41 = 0.0\n", "same_33_41_and_0 = 0.0\n", "same_33_41_and_1 = 0.0\n", "same_33_41_and_10 = 0.0\n", @@ -146917,12 +146907,12 @@ "same_33_41_and_2 = 0.0\n", "same_33_41_and_3 = 0.0\n", "same_33_41_and_4 = 0.0\n", - "same_33_41_and_5 = 1.0\n", + "same_33_41_and_5 = 0.0\n", "same_33_41_and_6 = 0.0\n", "same_33_41_and_7 = 0.0\n", "same_33_41_and_8 = 0.0\n", "same_33_41_and_9 = 0.0\n", - "same_33_42 = 1.0\n", + "same_33_42 = 0.0\n", "same_33_42_and_0 = 0.0\n", "same_33_42_and_1 = 0.0\n", "same_33_42_and_10 = 0.0\n", @@ -146934,12 +146924,12 @@ "same_33_42_and_2 = 0.0\n", "same_33_42_and_3 = 0.0\n", "same_33_42_and_4 = 0.0\n", - "same_33_42_and_5 = 1.0\n", + "same_33_42_and_5 = 0.0\n", "same_33_42_and_6 = 0.0\n", "same_33_42_and_7 = 0.0\n", "same_33_42_and_8 = 0.0\n", "same_33_42_and_9 = 0.0\n", - "same_33_43 = 1.0\n", + "same_33_43 = 0.0\n", "same_33_43_and_0 = 0.0\n", "same_33_43_and_1 = 0.0\n", "same_33_43_and_10 = 0.0\n", @@ -146951,7 +146941,7 @@ "same_33_43_and_2 = 0.0\n", "same_33_43_and_3 = 0.0\n", "same_33_43_and_4 = 0.0\n", - "same_33_43_and_5 = 1.0\n", + "same_33_43_and_5 = 0.0\n", "same_33_43_and_6 = 0.0\n", "same_33_43_and_7 = 0.0\n", "same_33_43_and_8 = 0.0\n", @@ -147399,7 +147389,7 @@ "same_33_69_and_8 = 0.0\n", "same_33_69_and_9 = 0.0\n", "same_34_34 = 1.0\n", - "same_34_35 = 1.0\n", + "same_34_35 = 0.0\n", "same_34_35_and_0 = 0.0\n", "same_34_35_and_1 = 0.0\n", "same_34_35_and_10 = 0.0\n", @@ -147411,12 +147401,12 @@ "same_34_35_and_2 = 0.0\n", "same_34_35_and_3 = 0.0\n", "same_34_35_and_4 = 0.0\n", - "same_34_35_and_5 = 1.0\n", + "same_34_35_and_5 = 0.0\n", "same_34_35_and_6 = 0.0\n", "same_34_35_and_7 = 0.0\n", "same_34_35_and_8 = 0.0\n", "same_34_35_and_9 = 0.0\n", - "same_34_36 = 1.0\n", + "same_34_36 = 0.0\n", "same_34_36_and_0 = 0.0\n", "same_34_36_and_1 = 0.0\n", "same_34_36_and_10 = 0.0\n", @@ -147428,12 +147418,12 @@ "same_34_36_and_2 = 0.0\n", "same_34_36_and_3 = 0.0\n", "same_34_36_and_4 = 0.0\n", - "same_34_36_and_5 = 1.0\n", + "same_34_36_and_5 = 0.0\n", "same_34_36_and_6 = 0.0\n", "same_34_36_and_7 = 0.0\n", "same_34_36_and_8 = 0.0\n", "same_34_36_and_9 = 0.0\n", - "same_34_37 = 1.0\n", + "same_34_37 = 0.0\n", "same_34_37_and_0 = 0.0\n", "same_34_37_and_1 = 0.0\n", "same_34_37_and_10 = 0.0\n", @@ -147445,12 +147435,12 @@ "same_34_37_and_2 = 0.0\n", "same_34_37_and_3 = 0.0\n", "same_34_37_and_4 = 0.0\n", - "same_34_37_and_5 = 1.0\n", + "same_34_37_and_5 = 0.0\n", "same_34_37_and_6 = 0.0\n", "same_34_37_and_7 = 0.0\n", "same_34_37_and_8 = 0.0\n", "same_34_37_and_9 = 0.0\n", - "same_34_38 = 1.0\n", + "same_34_38 = 0.0\n", "same_34_38_and_0 = 0.0\n", "same_34_38_and_1 = 0.0\n", "same_34_38_and_10 = 0.0\n", @@ -147462,12 +147452,12 @@ "same_34_38_and_2 = 0.0\n", "same_34_38_and_3 = 0.0\n", "same_34_38_and_4 = 0.0\n", - "same_34_38_and_5 = 1.0\n", + "same_34_38_and_5 = 0.0\n", "same_34_38_and_6 = 0.0\n", "same_34_38_and_7 = 0.0\n", "same_34_38_and_8 = 0.0\n", "same_34_38_and_9 = 0.0\n", - "same_34_39 = 1.0\n", + "same_34_39 = 0.0\n", "same_34_39_and_0 = 0.0\n", "same_34_39_and_1 = 0.0\n", "same_34_39_and_10 = 0.0\n", @@ -147479,12 +147469,12 @@ "same_34_39_and_2 = 0.0\n", "same_34_39_and_3 = 0.0\n", "same_34_39_and_4 = 0.0\n", - "same_34_39_and_5 = 1.0\n", + "same_34_39_and_5 = 0.0\n", "same_34_39_and_6 = 0.0\n", "same_34_39_and_7 = 0.0\n", "same_34_39_and_8 = 0.0\n", "same_34_39_and_9 = 0.0\n", - "same_34_40 = 1.0\n", + "same_34_40 = 0.0\n", "same_34_40_and_0 = 0.0\n", "same_34_40_and_1 = 0.0\n", "same_34_40_and_10 = 0.0\n", @@ -147496,12 +147486,12 @@ "same_34_40_and_2 = 0.0\n", "same_34_40_and_3 = 0.0\n", "same_34_40_and_4 = 0.0\n", - "same_34_40_and_5 = 1.0\n", + "same_34_40_and_5 = 0.0\n", "same_34_40_and_6 = 0.0\n", "same_34_40_and_7 = 0.0\n", "same_34_40_and_8 = 0.0\n", "same_34_40_and_9 = 0.0\n", - "same_34_41 = 1.0\n", + "same_34_41 = 0.0\n", "same_34_41_and_0 = 0.0\n", "same_34_41_and_1 = 0.0\n", "same_34_41_and_10 = 0.0\n", @@ -147513,12 +147503,12 @@ "same_34_41_and_2 = 0.0\n", "same_34_41_and_3 = 0.0\n", "same_34_41_and_4 = 0.0\n", - "same_34_41_and_5 = 1.0\n", + "same_34_41_and_5 = 0.0\n", "same_34_41_and_6 = 0.0\n", "same_34_41_and_7 = 0.0\n", "same_34_41_and_8 = 0.0\n", "same_34_41_and_9 = 0.0\n", - "same_34_42 = 1.0\n", + "same_34_42 = 0.0\n", "same_34_42_and_0 = 0.0\n", "same_34_42_and_1 = 0.0\n", "same_34_42_and_10 = 0.0\n", @@ -147530,12 +147520,12 @@ "same_34_42_and_2 = 0.0\n", "same_34_42_and_3 = 0.0\n", "same_34_42_and_4 = 0.0\n", - "same_34_42_and_5 = 1.0\n", + "same_34_42_and_5 = 0.0\n", "same_34_42_and_6 = 0.0\n", "same_34_42_and_7 = 0.0\n", "same_34_42_and_8 = 0.0\n", "same_34_42_and_9 = 0.0\n", - "same_34_43 = 1.0\n", + "same_34_43 = 0.0\n", "same_34_43_and_0 = 0.0\n", "same_34_43_and_1 = 0.0\n", "same_34_43_and_10 = 0.0\n", @@ -147547,7 +147537,7 @@ "same_34_43_and_2 = 0.0\n", "same_34_43_and_3 = 0.0\n", "same_34_43_and_4 = 0.0\n", - "same_34_43_and_5 = 1.0\n", + "same_34_43_and_5 = 0.0\n", "same_34_43_and_6 = 0.0\n", "same_34_43_and_7 = 0.0\n", "same_34_43_and_8 = 0.0\n", @@ -148006,8 +147996,8 @@ "same_35_36_and_15 = 0.0\n", "same_35_36_and_2 = 0.0\n", "same_35_36_and_3 = 0.0\n", - "same_35_36_and_4 = 0.0\n", - "same_35_36_and_5 = 1.0\n", + "same_35_36_and_4 = 1.0\n", + "same_35_36_and_5 = 0.0\n", "same_35_36_and_6 = 0.0\n", "same_35_36_and_7 = 0.0\n", "same_35_36_and_8 = 0.0\n", @@ -148023,8 +148013,8 @@ "same_35_37_and_15 = 0.0\n", "same_35_37_and_2 = 0.0\n", "same_35_37_and_3 = 0.0\n", - "same_35_37_and_4 = 0.0\n", - "same_35_37_and_5 = 1.0\n", + "same_35_37_and_4 = 1.0\n", + "same_35_37_and_5 = 0.0\n", "same_35_37_and_6 = 0.0\n", "same_35_37_and_7 = 0.0\n", "same_35_37_and_8 = 0.0\n", @@ -148040,8 +148030,8 @@ "same_35_38_and_15 = 0.0\n", "same_35_38_and_2 = 0.0\n", "same_35_38_and_3 = 0.0\n", - "same_35_38_and_4 = 0.0\n", - "same_35_38_and_5 = 1.0\n", + "same_35_38_and_4 = 1.0\n", + "same_35_38_and_5 = 0.0\n", "same_35_38_and_6 = 0.0\n", "same_35_38_and_7 = 0.0\n", "same_35_38_and_8 = 0.0\n", @@ -148057,8 +148047,8 @@ "same_35_39_and_15 = 0.0\n", "same_35_39_and_2 = 0.0\n", "same_35_39_and_3 = 0.0\n", - "same_35_39_and_4 = 0.0\n", - "same_35_39_and_5 = 1.0\n", + "same_35_39_and_4 = 1.0\n", + "same_35_39_and_5 = 0.0\n", "same_35_39_and_6 = 0.0\n", "same_35_39_and_7 = 0.0\n", "same_35_39_and_8 = 0.0\n", @@ -148074,8 +148064,8 @@ "same_35_40_and_15 = 0.0\n", "same_35_40_and_2 = 0.0\n", "same_35_40_and_3 = 0.0\n", - "same_35_40_and_4 = 0.0\n", - "same_35_40_and_5 = 1.0\n", + "same_35_40_and_4 = 1.0\n", + "same_35_40_and_5 = 0.0\n", "same_35_40_and_6 = 0.0\n", "same_35_40_and_7 = 0.0\n", "same_35_40_and_8 = 0.0\n", @@ -148091,8 +148081,8 @@ "same_35_41_and_15 = 0.0\n", "same_35_41_and_2 = 0.0\n", "same_35_41_and_3 = 0.0\n", - "same_35_41_and_4 = 0.0\n", - "same_35_41_and_5 = 1.0\n", + "same_35_41_and_4 = 1.0\n", + "same_35_41_and_5 = 0.0\n", "same_35_41_and_6 = 0.0\n", "same_35_41_and_7 = 0.0\n", "same_35_41_and_8 = 0.0\n", @@ -148108,8 +148098,8 @@ "same_35_42_and_15 = 0.0\n", "same_35_42_and_2 = 0.0\n", "same_35_42_and_3 = 0.0\n", - "same_35_42_and_4 = 0.0\n", - "same_35_42_and_5 = 1.0\n", + "same_35_42_and_4 = 1.0\n", + "same_35_42_and_5 = 0.0\n", "same_35_42_and_6 = 0.0\n", "same_35_42_and_7 = 0.0\n", "same_35_42_and_8 = 0.0\n", @@ -148125,13 +148115,13 @@ "same_35_43_and_15 = 0.0\n", "same_35_43_and_2 = 0.0\n", "same_35_43_and_3 = 0.0\n", - "same_35_43_and_4 = 0.0\n", - "same_35_43_and_5 = 1.0\n", + "same_35_43_and_4 = 1.0\n", + "same_35_43_and_5 = 0.0\n", "same_35_43_and_6 = 0.0\n", "same_35_43_and_7 = 0.0\n", "same_35_43_and_8 = 0.0\n", "same_35_43_and_9 = 0.0\n", - "same_35_44 = 0.0\n", + "same_35_44 = 1.0\n", "same_35_44_and_0 = 0.0\n", "same_35_44_and_1 = 0.0\n", "same_35_44_and_10 = 0.0\n", @@ -148142,13 +148132,13 @@ "same_35_44_and_15 = 0.0\n", "same_35_44_and_2 = 0.0\n", "same_35_44_and_3 = 0.0\n", - "same_35_44_and_4 = 0.0\n", + "same_35_44_and_4 = 1.0\n", "same_35_44_and_5 = 0.0\n", "same_35_44_and_6 = 0.0\n", "same_35_44_and_7 = 0.0\n", "same_35_44_and_8 = 0.0\n", "same_35_44_and_9 = 0.0\n", - "same_35_45 = 0.0\n", + "same_35_45 = 1.0\n", "same_35_45_and_0 = 0.0\n", "same_35_45_and_1 = 0.0\n", "same_35_45_and_10 = 0.0\n", @@ -148159,13 +148149,13 @@ "same_35_45_and_15 = 0.0\n", "same_35_45_and_2 = 0.0\n", "same_35_45_and_3 = 0.0\n", - "same_35_45_and_4 = 0.0\n", + "same_35_45_and_4 = 1.0\n", "same_35_45_and_5 = 0.0\n", "same_35_45_and_6 = 0.0\n", "same_35_45_and_7 = 0.0\n", "same_35_45_and_8 = 0.0\n", "same_35_45_and_9 = 0.0\n", - "same_35_46 = 0.0\n", + "same_35_46 = 1.0\n", "same_35_46_and_0 = 0.0\n", "same_35_46_and_1 = 0.0\n", "same_35_46_and_10 = 0.0\n", @@ -148176,13 +148166,13 @@ "same_35_46_and_15 = 0.0\n", "same_35_46_and_2 = 0.0\n", "same_35_46_and_3 = 0.0\n", - "same_35_46_and_4 = 0.0\n", + "same_35_46_and_4 = 1.0\n", "same_35_46_and_5 = 0.0\n", "same_35_46_and_6 = 0.0\n", "same_35_46_and_7 = 0.0\n", "same_35_46_and_8 = 0.0\n", "same_35_46_and_9 = 0.0\n", - "same_35_47 = 0.0\n", + "same_35_47 = 1.0\n", "same_35_47_and_0 = 0.0\n", "same_35_47_and_1 = 0.0\n", "same_35_47_and_10 = 0.0\n", @@ -148193,13 +148183,13 @@ "same_35_47_and_15 = 0.0\n", "same_35_47_and_2 = 0.0\n", "same_35_47_and_3 = 0.0\n", - "same_35_47_and_4 = 0.0\n", + "same_35_47_and_4 = 1.0\n", "same_35_47_and_5 = 0.0\n", "same_35_47_and_6 = 0.0\n", "same_35_47_and_7 = 0.0\n", "same_35_47_and_8 = 0.0\n", "same_35_47_and_9 = 0.0\n", - "same_35_48 = 0.0\n", + "same_35_48 = 1.0\n", "same_35_48_and_0 = 0.0\n", "same_35_48_and_1 = 0.0\n", "same_35_48_and_10 = 0.0\n", @@ -148210,13 +148200,13 @@ "same_35_48_and_15 = 0.0\n", "same_35_48_and_2 = 0.0\n", "same_35_48_and_3 = 0.0\n", - "same_35_48_and_4 = 0.0\n", + "same_35_48_and_4 = 1.0\n", "same_35_48_and_5 = 0.0\n", "same_35_48_and_6 = 0.0\n", "same_35_48_and_7 = 0.0\n", "same_35_48_and_8 = 0.0\n", "same_35_48_and_9 = 0.0\n", - "same_35_49 = 0.0\n", + "same_35_49 = 1.0\n", "same_35_49_and_0 = 0.0\n", "same_35_49_and_1 = 0.0\n", "same_35_49_and_10 = 0.0\n", @@ -148227,13 +148217,13 @@ "same_35_49_and_15 = 0.0\n", "same_35_49_and_2 = 0.0\n", "same_35_49_and_3 = 0.0\n", - "same_35_49_and_4 = 0.0\n", + "same_35_49_and_4 = 1.0\n", "same_35_49_and_5 = 0.0\n", "same_35_49_and_6 = 0.0\n", "same_35_49_and_7 = 0.0\n", "same_35_49_and_8 = 0.0\n", "same_35_49_and_9 = 0.0\n", - "same_35_50 = 0.0\n", + "same_35_50 = 1.0\n", "same_35_50_and_0 = 0.0\n", "same_35_50_and_1 = 0.0\n", "same_35_50_and_10 = 0.0\n", @@ -148244,13 +148234,13 @@ "same_35_50_and_15 = 0.0\n", "same_35_50_and_2 = 0.0\n", "same_35_50_and_3 = 0.0\n", - "same_35_50_and_4 = 0.0\n", + "same_35_50_and_4 = 1.0\n", "same_35_50_and_5 = 0.0\n", "same_35_50_and_6 = 0.0\n", "same_35_50_and_7 = 0.0\n", "same_35_50_and_8 = 0.0\n", "same_35_50_and_9 = 0.0\n", - "same_35_51 = 0.0\n", + "same_35_51 = 1.0\n", "same_35_51_and_0 = 0.0\n", "same_35_51_and_1 = 0.0\n", "same_35_51_and_10 = 0.0\n", @@ -148261,13 +148251,13 @@ "same_35_51_and_15 = 0.0\n", "same_35_51_and_2 = 0.0\n", "same_35_51_and_3 = 0.0\n", - "same_35_51_and_4 = 0.0\n", + "same_35_51_and_4 = 1.0\n", "same_35_51_and_5 = 0.0\n", "same_35_51_and_6 = 0.0\n", "same_35_51_and_7 = 0.0\n", "same_35_51_and_8 = 0.0\n", "same_35_51_and_9 = 0.0\n", - "same_35_52 = 0.0\n", + "same_35_52 = 1.0\n", "same_35_52_and_0 = 0.0\n", "same_35_52_and_1 = 0.0\n", "same_35_52_and_10 = 0.0\n", @@ -148278,7 +148268,7 @@ "same_35_52_and_15 = 0.0\n", "same_35_52_and_2 = 0.0\n", "same_35_52_and_3 = 0.0\n", - "same_35_52_and_4 = 0.0\n", + "same_35_52_and_4 = 1.0\n", "same_35_52_and_5 = 0.0\n", "same_35_52_and_6 = 0.0\n", "same_35_52_and_7 = 0.0\n", @@ -148585,8 +148575,8 @@ "same_36_37_and_15 = 0.0\n", "same_36_37_and_2 = 0.0\n", "same_36_37_and_3 = 0.0\n", - "same_36_37_and_4 = 0.0\n", - "same_36_37_and_5 = 1.0\n", + "same_36_37_and_4 = 1.0\n", + "same_36_37_and_5 = 0.0\n", "same_36_37_and_6 = 0.0\n", "same_36_37_and_7 = 0.0\n", "same_36_37_and_8 = 0.0\n", @@ -148602,8 +148592,8 @@ "same_36_38_and_15 = 0.0\n", "same_36_38_and_2 = 0.0\n", "same_36_38_and_3 = 0.0\n", - "same_36_38_and_4 = 0.0\n", - "same_36_38_and_5 = 1.0\n", + "same_36_38_and_4 = 1.0\n", + "same_36_38_and_5 = 0.0\n", "same_36_38_and_6 = 0.0\n", "same_36_38_and_7 = 0.0\n", "same_36_38_and_8 = 0.0\n", @@ -148619,8 +148609,8 @@ "same_36_39_and_15 = 0.0\n", "same_36_39_and_2 = 0.0\n", "same_36_39_and_3 = 0.0\n", - "same_36_39_and_4 = 0.0\n", - "same_36_39_and_5 = 1.0\n", + "same_36_39_and_4 = 1.0\n", + "same_36_39_and_5 = 0.0\n", "same_36_39_and_6 = 0.0\n", "same_36_39_and_7 = 0.0\n", "same_36_39_and_8 = 0.0\n", @@ -148636,8 +148626,8 @@ "same_36_40_and_15 = 0.0\n", "same_36_40_and_2 = 0.0\n", "same_36_40_and_3 = 0.0\n", - "same_36_40_and_4 = 0.0\n", - "same_36_40_and_5 = 1.0\n", + "same_36_40_and_4 = 1.0\n", + "same_36_40_and_5 = 0.0\n", "same_36_40_and_6 = 0.0\n", "same_36_40_and_7 = 0.0\n", "same_36_40_and_8 = 0.0\n", @@ -148653,8 +148643,8 @@ "same_36_41_and_15 = 0.0\n", "same_36_41_and_2 = 0.0\n", "same_36_41_and_3 = 0.0\n", - "same_36_41_and_4 = 0.0\n", - "same_36_41_and_5 = 1.0\n", + "same_36_41_and_4 = 1.0\n", + "same_36_41_and_5 = 0.0\n", "same_36_41_and_6 = 0.0\n", "same_36_41_and_7 = 0.0\n", "same_36_41_and_8 = 0.0\n", @@ -148670,8 +148660,8 @@ "same_36_42_and_15 = 0.0\n", "same_36_42_and_2 = 0.0\n", "same_36_42_and_3 = 0.0\n", - "same_36_42_and_4 = 0.0\n", - "same_36_42_and_5 = 1.0\n", + "same_36_42_and_4 = 1.0\n", + "same_36_42_and_5 = 0.0\n", "same_36_42_and_6 = 0.0\n", "same_36_42_and_7 = 0.0\n", "same_36_42_and_8 = 0.0\n", @@ -148687,13 +148677,13 @@ "same_36_43_and_15 = 0.0\n", "same_36_43_and_2 = 0.0\n", "same_36_43_and_3 = 0.0\n", - "same_36_43_and_4 = 0.0\n", - "same_36_43_and_5 = 1.0\n", + "same_36_43_and_4 = 1.0\n", + "same_36_43_and_5 = 0.0\n", "same_36_43_and_6 = 0.0\n", "same_36_43_and_7 = 0.0\n", "same_36_43_and_8 = 0.0\n", "same_36_43_and_9 = 0.0\n", - "same_36_44 = 0.0\n", + "same_36_44 = 1.0\n", "same_36_44_and_0 = 0.0\n", "same_36_44_and_1 = 0.0\n", "same_36_44_and_10 = 0.0\n", @@ -148704,13 +148694,13 @@ "same_36_44_and_15 = 0.0\n", "same_36_44_and_2 = 0.0\n", "same_36_44_and_3 = 0.0\n", - "same_36_44_and_4 = 0.0\n", + "same_36_44_and_4 = 1.0\n", "same_36_44_and_5 = 0.0\n", "same_36_44_and_6 = 0.0\n", "same_36_44_and_7 = 0.0\n", "same_36_44_and_8 = 0.0\n", "same_36_44_and_9 = 0.0\n", - "same_36_45 = 0.0\n", + "same_36_45 = 1.0\n", "same_36_45_and_0 = 0.0\n", "same_36_45_and_1 = 0.0\n", "same_36_45_and_10 = 0.0\n", @@ -148721,13 +148711,13 @@ "same_36_45_and_15 = 0.0\n", "same_36_45_and_2 = 0.0\n", "same_36_45_and_3 = 0.0\n", - "same_36_45_and_4 = 0.0\n", + "same_36_45_and_4 = 1.0\n", "same_36_45_and_5 = 0.0\n", "same_36_45_and_6 = 0.0\n", "same_36_45_and_7 = 0.0\n", "same_36_45_and_8 = 0.0\n", "same_36_45_and_9 = 0.0\n", - "same_36_46 = 0.0\n", + "same_36_46 = 1.0\n", "same_36_46_and_0 = 0.0\n", "same_36_46_and_1 = 0.0\n", "same_36_46_and_10 = 0.0\n", @@ -148738,13 +148728,13 @@ "same_36_46_and_15 = 0.0\n", "same_36_46_and_2 = 0.0\n", "same_36_46_and_3 = 0.0\n", - "same_36_46_and_4 = 0.0\n", + "same_36_46_and_4 = 1.0\n", "same_36_46_and_5 = 0.0\n", "same_36_46_and_6 = 0.0\n", "same_36_46_and_7 = 0.0\n", "same_36_46_and_8 = 0.0\n", "same_36_46_and_9 = 0.0\n", - "same_36_47 = 0.0\n", + "same_36_47 = 1.0\n", "same_36_47_and_0 = 0.0\n", "same_36_47_and_1 = 0.0\n", "same_36_47_and_10 = 0.0\n", @@ -148755,13 +148745,13 @@ "same_36_47_and_15 = 0.0\n", "same_36_47_and_2 = 0.0\n", "same_36_47_and_3 = 0.0\n", - "same_36_47_and_4 = 0.0\n", + "same_36_47_and_4 = 1.0\n", "same_36_47_and_5 = 0.0\n", "same_36_47_and_6 = 0.0\n", "same_36_47_and_7 = 0.0\n", "same_36_47_and_8 = 0.0\n", "same_36_47_and_9 = 0.0\n", - "same_36_48 = 0.0\n", + "same_36_48 = 1.0\n", "same_36_48_and_0 = 0.0\n", "same_36_48_and_1 = 0.0\n", "same_36_48_and_10 = 0.0\n", @@ -148772,13 +148762,13 @@ "same_36_48_and_15 = 0.0\n", "same_36_48_and_2 = 0.0\n", "same_36_48_and_3 = 0.0\n", - "same_36_48_and_4 = 0.0\n", + "same_36_48_and_4 = 1.0\n", "same_36_48_and_5 = 0.0\n", "same_36_48_and_6 = 0.0\n", "same_36_48_and_7 = 0.0\n", "same_36_48_and_8 = 0.0\n", "same_36_48_and_9 = 0.0\n", - "same_36_49 = 0.0\n", + "same_36_49 = 1.0\n", "same_36_49_and_0 = 0.0\n", "same_36_49_and_1 = 0.0\n", "same_36_49_and_10 = 0.0\n", @@ -148789,13 +148779,13 @@ "same_36_49_and_15 = 0.0\n", "same_36_49_and_2 = 0.0\n", "same_36_49_and_3 = 0.0\n", - "same_36_49_and_4 = 0.0\n", + "same_36_49_and_4 = 1.0\n", "same_36_49_and_5 = 0.0\n", "same_36_49_and_6 = 0.0\n", "same_36_49_and_7 = 0.0\n", "same_36_49_and_8 = 0.0\n", "same_36_49_and_9 = 0.0\n", - "same_36_50 = 0.0\n", + "same_36_50 = 1.0\n", "same_36_50_and_0 = 0.0\n", "same_36_50_and_1 = 0.0\n", "same_36_50_and_10 = 0.0\n", @@ -148806,13 +148796,13 @@ "same_36_50_and_15 = 0.0\n", "same_36_50_and_2 = 0.0\n", "same_36_50_and_3 = 0.0\n", - "same_36_50_and_4 = 0.0\n", + "same_36_50_and_4 = 1.0\n", "same_36_50_and_5 = 0.0\n", "same_36_50_and_6 = 0.0\n", "same_36_50_and_7 = 0.0\n", "same_36_50_and_8 = 0.0\n", "same_36_50_and_9 = 0.0\n", - "same_36_51 = 0.0\n", + "same_36_51 = 1.0\n", "same_36_51_and_0 = 0.0\n", "same_36_51_and_1 = 0.0\n", "same_36_51_and_10 = 0.0\n", @@ -148823,13 +148813,13 @@ "same_36_51_and_15 = 0.0\n", "same_36_51_and_2 = 0.0\n", "same_36_51_and_3 = 0.0\n", - "same_36_51_and_4 = 0.0\n", + "same_36_51_and_4 = 1.0\n", "same_36_51_and_5 = 0.0\n", "same_36_51_and_6 = 0.0\n", "same_36_51_and_7 = 0.0\n", "same_36_51_and_8 = 0.0\n", "same_36_51_and_9 = 0.0\n", - "same_36_52 = 0.0\n", + "same_36_52 = 1.0\n", "same_36_52_and_0 = 0.0\n", "same_36_52_and_1 = 0.0\n", "same_36_52_and_10 = 0.0\n", @@ -148840,7 +148830,7 @@ "same_36_52_and_15 = 0.0\n", "same_36_52_and_2 = 0.0\n", "same_36_52_and_3 = 0.0\n", - "same_36_52_and_4 = 0.0\n", + "same_36_52_and_4 = 1.0\n", "same_36_52_and_5 = 0.0\n", "same_36_52_and_6 = 0.0\n", "same_36_52_and_7 = 0.0\n", @@ -149147,8 +149137,8 @@ "same_37_38_and_15 = 0.0\n", "same_37_38_and_2 = 0.0\n", "same_37_38_and_3 = 0.0\n", - "same_37_38_and_4 = 0.0\n", - "same_37_38_and_5 = 1.0\n", + "same_37_38_and_4 = 1.0\n", + "same_37_38_and_5 = 0.0\n", "same_37_38_and_6 = 0.0\n", "same_37_38_and_7 = 0.0\n", "same_37_38_and_8 = 0.0\n", @@ -149164,8 +149154,8 @@ "same_37_39_and_15 = 0.0\n", "same_37_39_and_2 = 0.0\n", "same_37_39_and_3 = 0.0\n", - "same_37_39_and_4 = 0.0\n", - "same_37_39_and_5 = 1.0\n", + "same_37_39_and_4 = 1.0\n", + "same_37_39_and_5 = 0.0\n", "same_37_39_and_6 = 0.0\n", "same_37_39_and_7 = 0.0\n", "same_37_39_and_8 = 0.0\n", @@ -149181,8 +149171,8 @@ "same_37_40_and_15 = 0.0\n", "same_37_40_and_2 = 0.0\n", "same_37_40_and_3 = 0.0\n", - "same_37_40_and_4 = 0.0\n", - "same_37_40_and_5 = 1.0\n", + "same_37_40_and_4 = 1.0\n", + "same_37_40_and_5 = 0.0\n", "same_37_40_and_6 = 0.0\n", "same_37_40_and_7 = 0.0\n", "same_37_40_and_8 = 0.0\n", @@ -149198,8 +149188,8 @@ "same_37_41_and_15 = 0.0\n", "same_37_41_and_2 = 0.0\n", "same_37_41_and_3 = 0.0\n", - "same_37_41_and_4 = 0.0\n", - "same_37_41_and_5 = 1.0\n", + "same_37_41_and_4 = 1.0\n", + "same_37_41_and_5 = 0.0\n", "same_37_41_and_6 = 0.0\n", "same_37_41_and_7 = 0.0\n", "same_37_41_and_8 = 0.0\n", @@ -149215,8 +149205,8 @@ "same_37_42_and_15 = 0.0\n", "same_37_42_and_2 = 0.0\n", "same_37_42_and_3 = 0.0\n", - "same_37_42_and_4 = 0.0\n", - "same_37_42_and_5 = 1.0\n", + "same_37_42_and_4 = 1.0\n", + "same_37_42_and_5 = 0.0\n", "same_37_42_and_6 = 0.0\n", "same_37_42_and_7 = 0.0\n", "same_37_42_and_8 = 0.0\n", @@ -149232,13 +149222,13 @@ "same_37_43_and_15 = 0.0\n", "same_37_43_and_2 = 0.0\n", "same_37_43_and_3 = 0.0\n", - "same_37_43_and_4 = 0.0\n", - "same_37_43_and_5 = 1.0\n", + "same_37_43_and_4 = 1.0\n", + "same_37_43_and_5 = 0.0\n", "same_37_43_and_6 = 0.0\n", "same_37_43_and_7 = 0.0\n", "same_37_43_and_8 = 0.0\n", "same_37_43_and_9 = 0.0\n", - "same_37_44 = 0.0\n", + "same_37_44 = 1.0\n", "same_37_44_and_0 = 0.0\n", "same_37_44_and_1 = 0.0\n", "same_37_44_and_10 = 0.0\n", @@ -149249,13 +149239,13 @@ "same_37_44_and_15 = 0.0\n", "same_37_44_and_2 = 0.0\n", "same_37_44_and_3 = 0.0\n", - "same_37_44_and_4 = 0.0\n", + "same_37_44_and_4 = 1.0\n", "same_37_44_and_5 = 0.0\n", "same_37_44_and_6 = 0.0\n", "same_37_44_and_7 = 0.0\n", "same_37_44_and_8 = 0.0\n", "same_37_44_and_9 = 0.0\n", - "same_37_45 = 0.0\n", + "same_37_45 = 1.0\n", "same_37_45_and_0 = 0.0\n", "same_37_45_and_1 = 0.0\n", "same_37_45_and_10 = 0.0\n", @@ -149266,13 +149256,13 @@ "same_37_45_and_15 = 0.0\n", "same_37_45_and_2 = 0.0\n", "same_37_45_and_3 = 0.0\n", - "same_37_45_and_4 = 0.0\n", + "same_37_45_and_4 = 1.0\n", "same_37_45_and_5 = 0.0\n", "same_37_45_and_6 = 0.0\n", "same_37_45_and_7 = 0.0\n", "same_37_45_and_8 = 0.0\n", "same_37_45_and_9 = 0.0\n", - "same_37_46 = 0.0\n", + "same_37_46 = 1.0\n", "same_37_46_and_0 = 0.0\n", "same_37_46_and_1 = 0.0\n", "same_37_46_and_10 = 0.0\n", @@ -149283,13 +149273,13 @@ "same_37_46_and_15 = 0.0\n", "same_37_46_and_2 = 0.0\n", "same_37_46_and_3 = 0.0\n", - "same_37_46_and_4 = 0.0\n", + "same_37_46_and_4 = 1.0\n", "same_37_46_and_5 = 0.0\n", "same_37_46_and_6 = 0.0\n", "same_37_46_and_7 = 0.0\n", "same_37_46_and_8 = 0.0\n", "same_37_46_and_9 = 0.0\n", - "same_37_47 = 0.0\n", + "same_37_47 = 1.0\n", "same_37_47_and_0 = 0.0\n", "same_37_47_and_1 = 0.0\n", "same_37_47_and_10 = 0.0\n", @@ -149300,13 +149290,13 @@ "same_37_47_and_15 = 0.0\n", "same_37_47_and_2 = 0.0\n", "same_37_47_and_3 = 0.0\n", - "same_37_47_and_4 = 0.0\n", + "same_37_47_and_4 = 1.0\n", "same_37_47_and_5 = 0.0\n", "same_37_47_and_6 = 0.0\n", "same_37_47_and_7 = 0.0\n", "same_37_47_and_8 = 0.0\n", "same_37_47_and_9 = 0.0\n", - "same_37_48 = 0.0\n", + "same_37_48 = 1.0\n", "same_37_48_and_0 = 0.0\n", "same_37_48_and_1 = 0.0\n", "same_37_48_and_10 = 0.0\n", @@ -149317,13 +149307,13 @@ "same_37_48_and_15 = 0.0\n", "same_37_48_and_2 = 0.0\n", "same_37_48_and_3 = 0.0\n", - "same_37_48_and_4 = 0.0\n", + "same_37_48_and_4 = 1.0\n", "same_37_48_and_5 = 0.0\n", "same_37_48_and_6 = 0.0\n", "same_37_48_and_7 = 0.0\n", "same_37_48_and_8 = 0.0\n", "same_37_48_and_9 = 0.0\n", - "same_37_49 = 0.0\n", + "same_37_49 = 1.0\n", "same_37_49_and_0 = 0.0\n", "same_37_49_and_1 = 0.0\n", "same_37_49_and_10 = 0.0\n", @@ -149334,13 +149324,13 @@ "same_37_49_and_15 = 0.0\n", "same_37_49_and_2 = 0.0\n", "same_37_49_and_3 = 0.0\n", - "same_37_49_and_4 = 0.0\n", + "same_37_49_and_4 = 1.0\n", "same_37_49_and_5 = 0.0\n", "same_37_49_and_6 = 0.0\n", "same_37_49_and_7 = 0.0\n", "same_37_49_and_8 = 0.0\n", "same_37_49_and_9 = 0.0\n", - "same_37_50 = 0.0\n", + "same_37_50 = 1.0\n", "same_37_50_and_0 = 0.0\n", "same_37_50_and_1 = 0.0\n", "same_37_50_and_10 = 0.0\n", @@ -149351,13 +149341,13 @@ "same_37_50_and_15 = 0.0\n", "same_37_50_and_2 = 0.0\n", "same_37_50_and_3 = 0.0\n", - "same_37_50_and_4 = 0.0\n", + "same_37_50_and_4 = 1.0\n", "same_37_50_and_5 = 0.0\n", "same_37_50_and_6 = 0.0\n", "same_37_50_and_7 = 0.0\n", "same_37_50_and_8 = 0.0\n", "same_37_50_and_9 = 0.0\n", - "same_37_51 = 0.0\n", + "same_37_51 = 1.0\n", "same_37_51_and_0 = 0.0\n", "same_37_51_and_1 = 0.0\n", "same_37_51_and_10 = 0.0\n", @@ -149368,13 +149358,13 @@ "same_37_51_and_15 = 0.0\n", "same_37_51_and_2 = 0.0\n", "same_37_51_and_3 = 0.0\n", - "same_37_51_and_4 = 0.0\n", + "same_37_51_and_4 = 1.0\n", "same_37_51_and_5 = 0.0\n", "same_37_51_and_6 = 0.0\n", "same_37_51_and_7 = 0.0\n", "same_37_51_and_8 = 0.0\n", "same_37_51_and_9 = 0.0\n", - "same_37_52 = 0.0\n", + "same_37_52 = 1.0\n", "same_37_52_and_0 = 0.0\n", "same_37_52_and_1 = 0.0\n", "same_37_52_and_10 = 0.0\n", @@ -149385,7 +149375,7 @@ "same_37_52_and_15 = 0.0\n", "same_37_52_and_2 = 0.0\n", "same_37_52_and_3 = 0.0\n", - "same_37_52_and_4 = 0.0\n", + "same_37_52_and_4 = 1.0\n", "same_37_52_and_5 = 0.0\n", "same_37_52_and_6 = 0.0\n", "same_37_52_and_7 = 0.0\n", @@ -149692,8 +149682,8 @@ "same_38_39_and_15 = 0.0\n", "same_38_39_and_2 = 0.0\n", "same_38_39_and_3 = 0.0\n", - "same_38_39_and_4 = 0.0\n", - "same_38_39_and_5 = 1.0\n", + "same_38_39_and_4 = 1.0\n", + "same_38_39_and_5 = 0.0\n", "same_38_39_and_6 = 0.0\n", "same_38_39_and_7 = 0.0\n", "same_38_39_and_8 = 0.0\n", @@ -149709,8 +149699,8 @@ "same_38_40_and_15 = 0.0\n", "same_38_40_and_2 = 0.0\n", "same_38_40_and_3 = 0.0\n", - "same_38_40_and_4 = 0.0\n", - "same_38_40_and_5 = 1.0\n", + "same_38_40_and_4 = 1.0\n", + "same_38_40_and_5 = 0.0\n", "same_38_40_and_6 = 0.0\n", "same_38_40_and_7 = 0.0\n", "same_38_40_and_8 = 0.0\n", @@ -149726,8 +149716,8 @@ "same_38_41_and_15 = 0.0\n", "same_38_41_and_2 = 0.0\n", "same_38_41_and_3 = 0.0\n", - "same_38_41_and_4 = 0.0\n", - "same_38_41_and_5 = 1.0\n", + "same_38_41_and_4 = 1.0\n", + "same_38_41_and_5 = 0.0\n", "same_38_41_and_6 = 0.0\n", "same_38_41_and_7 = 0.0\n", "same_38_41_and_8 = 0.0\n", @@ -149743,8 +149733,8 @@ "same_38_42_and_15 = 0.0\n", "same_38_42_and_2 = 0.0\n", "same_38_42_and_3 = 0.0\n", - "same_38_42_and_4 = 0.0\n", - "same_38_42_and_5 = 1.0\n", + "same_38_42_and_4 = 1.0\n", + "same_38_42_and_5 = 0.0\n", "same_38_42_and_6 = 0.0\n", "same_38_42_and_7 = 0.0\n", "same_38_42_and_8 = 0.0\n", @@ -149760,13 +149750,13 @@ "same_38_43_and_15 = 0.0\n", "same_38_43_and_2 = 0.0\n", "same_38_43_and_3 = 0.0\n", - "same_38_43_and_4 = 0.0\n", - "same_38_43_and_5 = 1.0\n", + "same_38_43_and_4 = 1.0\n", + "same_38_43_and_5 = 0.0\n", "same_38_43_and_6 = 0.0\n", "same_38_43_and_7 = 0.0\n", "same_38_43_and_8 = 0.0\n", "same_38_43_and_9 = 0.0\n", - "same_38_44 = 0.0\n", + "same_38_44 = 1.0\n", "same_38_44_and_0 = 0.0\n", "same_38_44_and_1 = 0.0\n", "same_38_44_and_10 = 0.0\n", @@ -149777,13 +149767,13 @@ "same_38_44_and_15 = 0.0\n", "same_38_44_and_2 = 0.0\n", "same_38_44_and_3 = 0.0\n", - "same_38_44_and_4 = 0.0\n", + "same_38_44_and_4 = 1.0\n", "same_38_44_and_5 = 0.0\n", "same_38_44_and_6 = 0.0\n", "same_38_44_and_7 = 0.0\n", "same_38_44_and_8 = 0.0\n", "same_38_44_and_9 = 0.0\n", - "same_38_45 = 0.0\n", + "same_38_45 = 1.0\n", "same_38_45_and_0 = 0.0\n", "same_38_45_and_1 = 0.0\n", "same_38_45_and_10 = 0.0\n", @@ -149794,13 +149784,13 @@ "same_38_45_and_15 = 0.0\n", "same_38_45_and_2 = 0.0\n", "same_38_45_and_3 = 0.0\n", - "same_38_45_and_4 = 0.0\n", + "same_38_45_and_4 = 1.0\n", "same_38_45_and_5 = 0.0\n", "same_38_45_and_6 = 0.0\n", "same_38_45_and_7 = 0.0\n", "same_38_45_and_8 = 0.0\n", "same_38_45_and_9 = 0.0\n", - "same_38_46 = 0.0\n", + "same_38_46 = 1.0\n", "same_38_46_and_0 = 0.0\n", "same_38_46_and_1 = 0.0\n", "same_38_46_and_10 = 0.0\n", @@ -149811,13 +149801,13 @@ "same_38_46_and_15 = 0.0\n", "same_38_46_and_2 = 0.0\n", "same_38_46_and_3 = 0.0\n", - "same_38_46_and_4 = 0.0\n", + "same_38_46_and_4 = 1.0\n", "same_38_46_and_5 = 0.0\n", "same_38_46_and_6 = 0.0\n", "same_38_46_and_7 = 0.0\n", "same_38_46_and_8 = 0.0\n", "same_38_46_and_9 = 0.0\n", - "same_38_47 = 0.0\n", + "same_38_47 = 1.0\n", "same_38_47_and_0 = 0.0\n", "same_38_47_and_1 = 0.0\n", "same_38_47_and_10 = 0.0\n", @@ -149828,13 +149818,13 @@ "same_38_47_and_15 = 0.0\n", "same_38_47_and_2 = 0.0\n", "same_38_47_and_3 = 0.0\n", - "same_38_47_and_4 = 0.0\n", + "same_38_47_and_4 = 1.0\n", "same_38_47_and_5 = 0.0\n", "same_38_47_and_6 = 0.0\n", "same_38_47_and_7 = 0.0\n", "same_38_47_and_8 = 0.0\n", "same_38_47_and_9 = 0.0\n", - "same_38_48 = 0.0\n", + "same_38_48 = 1.0\n", "same_38_48_and_0 = 0.0\n", "same_38_48_and_1 = 0.0\n", "same_38_48_and_10 = 0.0\n", @@ -149845,13 +149835,13 @@ "same_38_48_and_15 = 0.0\n", "same_38_48_and_2 = 0.0\n", "same_38_48_and_3 = 0.0\n", - "same_38_48_and_4 = 0.0\n", + "same_38_48_and_4 = 1.0\n", "same_38_48_and_5 = 0.0\n", "same_38_48_and_6 = 0.0\n", "same_38_48_and_7 = 0.0\n", "same_38_48_and_8 = 0.0\n", "same_38_48_and_9 = 0.0\n", - "same_38_49 = 0.0\n", + "same_38_49 = 1.0\n", "same_38_49_and_0 = 0.0\n", "same_38_49_and_1 = 0.0\n", "same_38_49_and_10 = 0.0\n", @@ -149862,13 +149852,13 @@ "same_38_49_and_15 = 0.0\n", "same_38_49_and_2 = 0.0\n", "same_38_49_and_3 = 0.0\n", - "same_38_49_and_4 = 0.0\n", + "same_38_49_and_4 = 1.0\n", "same_38_49_and_5 = 0.0\n", "same_38_49_and_6 = 0.0\n", "same_38_49_and_7 = 0.0\n", "same_38_49_and_8 = 0.0\n", "same_38_49_and_9 = 0.0\n", - "same_38_50 = 0.0\n", + "same_38_50 = 1.0\n", "same_38_50_and_0 = 0.0\n", "same_38_50_and_1 = 0.0\n", "same_38_50_and_10 = 0.0\n", @@ -149879,13 +149869,13 @@ "same_38_50_and_15 = 0.0\n", "same_38_50_and_2 = 0.0\n", "same_38_50_and_3 = 0.0\n", - "same_38_50_and_4 = 0.0\n", + "same_38_50_and_4 = 1.0\n", "same_38_50_and_5 = 0.0\n", "same_38_50_and_6 = 0.0\n", "same_38_50_and_7 = 0.0\n", "same_38_50_and_8 = 0.0\n", "same_38_50_and_9 = 0.0\n", - "same_38_51 = 0.0\n", + "same_38_51 = 1.0\n", "same_38_51_and_0 = 0.0\n", "same_38_51_and_1 = 0.0\n", "same_38_51_and_10 = 0.0\n", @@ -149896,13 +149886,13 @@ "same_38_51_and_15 = 0.0\n", "same_38_51_and_2 = 0.0\n", "same_38_51_and_3 = 0.0\n", - "same_38_51_and_4 = 0.0\n", + "same_38_51_and_4 = 1.0\n", "same_38_51_and_5 = 0.0\n", "same_38_51_and_6 = 0.0\n", "same_38_51_and_7 = 0.0\n", "same_38_51_and_8 = 0.0\n", "same_38_51_and_9 = 0.0\n", - "same_38_52 = 0.0\n", + "same_38_52 = 1.0\n", "same_38_52_and_0 = 0.0\n", "same_38_52_and_1 = 0.0\n", "same_38_52_and_10 = 0.0\n", @@ -149913,7 +149903,7 @@ "same_38_52_and_15 = 0.0\n", "same_38_52_and_2 = 0.0\n", "same_38_52_and_3 = 0.0\n", - "same_38_52_and_4 = 0.0\n", + "same_38_52_and_4 = 1.0\n", "same_38_52_and_5 = 0.0\n", "same_38_52_and_6 = 0.0\n", "same_38_52_and_7 = 0.0\n", @@ -150220,8 +150210,8 @@ "same_39_40_and_15 = 0.0\n", "same_39_40_and_2 = 0.0\n", "same_39_40_and_3 = 0.0\n", - "same_39_40_and_4 = 0.0\n", - "same_39_40_and_5 = 1.0\n", + "same_39_40_and_4 = 1.0\n", + "same_39_40_and_5 = 0.0\n", "same_39_40_and_6 = 0.0\n", "same_39_40_and_7 = 0.0\n", "same_39_40_and_8 = 0.0\n", @@ -150237,8 +150227,8 @@ "same_39_41_and_15 = 0.0\n", "same_39_41_and_2 = 0.0\n", "same_39_41_and_3 = 0.0\n", - "same_39_41_and_4 = 0.0\n", - "same_39_41_and_5 = 1.0\n", + "same_39_41_and_4 = 1.0\n", + "same_39_41_and_5 = 0.0\n", "same_39_41_and_6 = 0.0\n", "same_39_41_and_7 = 0.0\n", "same_39_41_and_8 = 0.0\n", @@ -150254,8 +150244,8 @@ "same_39_42_and_15 = 0.0\n", "same_39_42_and_2 = 0.0\n", "same_39_42_and_3 = 0.0\n", - "same_39_42_and_4 = 0.0\n", - "same_39_42_and_5 = 1.0\n", + "same_39_42_and_4 = 1.0\n", + "same_39_42_and_5 = 0.0\n", "same_39_42_and_6 = 0.0\n", "same_39_42_and_7 = 0.0\n", "same_39_42_and_8 = 0.0\n", @@ -150271,13 +150261,13 @@ "same_39_43_and_15 = 0.0\n", "same_39_43_and_2 = 0.0\n", "same_39_43_and_3 = 0.0\n", - "same_39_43_and_4 = 0.0\n", - "same_39_43_and_5 = 1.0\n", + "same_39_43_and_4 = 1.0\n", + "same_39_43_and_5 = 0.0\n", "same_39_43_and_6 = 0.0\n", "same_39_43_and_7 = 0.0\n", "same_39_43_and_8 = 0.0\n", "same_39_43_and_9 = 0.0\n", - "same_39_44 = 0.0\n", + "same_39_44 = 1.0\n", "same_39_44_and_0 = 0.0\n", "same_39_44_and_1 = 0.0\n", "same_39_44_and_10 = 0.0\n", @@ -150288,13 +150278,13 @@ "same_39_44_and_15 = 0.0\n", "same_39_44_and_2 = 0.0\n", "same_39_44_and_3 = 0.0\n", - "same_39_44_and_4 = 0.0\n", + "same_39_44_and_4 = 1.0\n", "same_39_44_and_5 = 0.0\n", "same_39_44_and_6 = 0.0\n", "same_39_44_and_7 = 0.0\n", "same_39_44_and_8 = 0.0\n", "same_39_44_and_9 = 0.0\n", - "same_39_45 = 0.0\n", + "same_39_45 = 1.0\n", "same_39_45_and_0 = 0.0\n", "same_39_45_and_1 = 0.0\n", "same_39_45_and_10 = 0.0\n", @@ -150305,13 +150295,13 @@ "same_39_45_and_15 = 0.0\n", "same_39_45_and_2 = 0.0\n", "same_39_45_and_3 = 0.0\n", - "same_39_45_and_4 = 0.0\n", + "same_39_45_and_4 = 1.0\n", "same_39_45_and_5 = 0.0\n", "same_39_45_and_6 = 0.0\n", "same_39_45_and_7 = 0.0\n", "same_39_45_and_8 = 0.0\n", "same_39_45_and_9 = 0.0\n", - "same_39_46 = 0.0\n", + "same_39_46 = 1.0\n", "same_39_46_and_0 = 0.0\n", "same_39_46_and_1 = 0.0\n", "same_39_46_and_10 = 0.0\n", @@ -150322,13 +150312,13 @@ "same_39_46_and_15 = 0.0\n", "same_39_46_and_2 = 0.0\n", "same_39_46_and_3 = 0.0\n", - "same_39_46_and_4 = 0.0\n", + "same_39_46_and_4 = 1.0\n", "same_39_46_and_5 = 0.0\n", "same_39_46_and_6 = 0.0\n", "same_39_46_and_7 = 0.0\n", "same_39_46_and_8 = 0.0\n", "same_39_46_and_9 = 0.0\n", - "same_39_47 = 0.0\n", + "same_39_47 = 1.0\n", "same_39_47_and_0 = 0.0\n", "same_39_47_and_1 = 0.0\n", "same_39_47_and_10 = 0.0\n", @@ -150339,13 +150329,13 @@ "same_39_47_and_15 = 0.0\n", "same_39_47_and_2 = 0.0\n", "same_39_47_and_3 = 0.0\n", - "same_39_47_and_4 = 0.0\n", + "same_39_47_and_4 = 1.0\n", "same_39_47_and_5 = 0.0\n", "same_39_47_and_6 = 0.0\n", "same_39_47_and_7 = 0.0\n", "same_39_47_and_8 = 0.0\n", "same_39_47_and_9 = 0.0\n", - "same_39_48 = 0.0\n", + "same_39_48 = 1.0\n", "same_39_48_and_0 = 0.0\n", "same_39_48_and_1 = 0.0\n", "same_39_48_and_10 = 0.0\n", @@ -150356,13 +150346,13 @@ "same_39_48_and_15 = 0.0\n", "same_39_48_and_2 = 0.0\n", "same_39_48_and_3 = 0.0\n", - "same_39_48_and_4 = 0.0\n", + "same_39_48_and_4 = 1.0\n", "same_39_48_and_5 = 0.0\n", "same_39_48_and_6 = 0.0\n", "same_39_48_and_7 = 0.0\n", "same_39_48_and_8 = 0.0\n", "same_39_48_and_9 = 0.0\n", - "same_39_49 = 0.0\n", + "same_39_49 = 1.0\n", "same_39_49_and_0 = 0.0\n", "same_39_49_and_1 = 0.0\n", "same_39_49_and_10 = 0.0\n", @@ -150373,13 +150363,13 @@ "same_39_49_and_15 = 0.0\n", "same_39_49_and_2 = 0.0\n", "same_39_49_and_3 = 0.0\n", - "same_39_49_and_4 = 0.0\n", + "same_39_49_and_4 = 1.0\n", "same_39_49_and_5 = 0.0\n", "same_39_49_and_6 = 0.0\n", "same_39_49_and_7 = 0.0\n", "same_39_49_and_8 = 0.0\n", "same_39_49_and_9 = 0.0\n", - "same_39_50 = 0.0\n", + "same_39_50 = 1.0\n", "same_39_50_and_0 = 0.0\n", "same_39_50_and_1 = 0.0\n", "same_39_50_and_10 = 0.0\n", @@ -150390,13 +150380,13 @@ "same_39_50_and_15 = 0.0\n", "same_39_50_and_2 = 0.0\n", "same_39_50_and_3 = 0.0\n", - "same_39_50_and_4 = 0.0\n", + "same_39_50_and_4 = 1.0\n", "same_39_50_and_5 = 0.0\n", "same_39_50_and_6 = 0.0\n", "same_39_50_and_7 = 0.0\n", "same_39_50_and_8 = 0.0\n", "same_39_50_and_9 = 0.0\n", - "same_39_51 = 0.0\n", + "same_39_51 = 1.0\n", "same_39_51_and_0 = 0.0\n", "same_39_51_and_1 = 0.0\n", "same_39_51_and_10 = 0.0\n", @@ -150407,13 +150397,13 @@ "same_39_51_and_15 = 0.0\n", "same_39_51_and_2 = 0.0\n", "same_39_51_and_3 = 0.0\n", - "same_39_51_and_4 = 0.0\n", + "same_39_51_and_4 = 1.0\n", "same_39_51_and_5 = 0.0\n", "same_39_51_and_6 = 0.0\n", "same_39_51_and_7 = 0.0\n", "same_39_51_and_8 = 0.0\n", "same_39_51_and_9 = 0.0\n", - "same_39_52 = 0.0\n", + "same_39_52 = 1.0\n", "same_39_52_and_0 = 0.0\n", "same_39_52_and_1 = 0.0\n", "same_39_52_and_10 = 0.0\n", @@ -150424,7 +150414,7 @@ "same_39_52_and_15 = 0.0\n", "same_39_52_and_2 = 0.0\n", "same_39_52_and_3 = 0.0\n", - "same_39_52_and_4 = 0.0\n", + "same_39_52_and_4 = 1.0\n", "same_39_52_and_5 = 0.0\n", "same_39_52_and_6 = 0.0\n", "same_39_52_and_7 = 0.0\n", @@ -151230,7 +151220,7 @@ "same_3_39_and_7 = 0.0\n", "same_3_39_and_8 = 0.0\n", "same_3_39_and_9 = 0.0\n", - "same_3_4 = 1.0\n", + "same_3_4 = 0.0\n", "same_3_40 = 0.0\n", "same_3_40_and_0 = 0.0\n", "same_3_40_and_1 = 0.0\n", @@ -151405,7 +151395,7 @@ "same_3_4_and_1 = 0.0\n", "same_3_4_and_10 = 0.0\n", "same_3_4_and_11 = 0.0\n", - "same_3_4_and_12 = 1.0\n", + "same_3_4_and_12 = 0.0\n", "same_3_4_and_13 = 0.0\n", "same_3_4_and_14 = 0.0\n", "same_3_4_and_15 = 0.0\n", @@ -151417,7 +151407,7 @@ "same_3_4_and_7 = 0.0\n", "same_3_4_and_8 = 0.0\n", "same_3_4_and_9 = 0.0\n", - "same_3_5 = 1.0\n", + "same_3_5 = 0.0\n", "same_3_50 = 0.0\n", "same_3_50_and_0 = 0.0\n", "same_3_50_and_1 = 0.0\n", @@ -151592,7 +151582,7 @@ "same_3_5_and_1 = 0.0\n", "same_3_5_and_10 = 0.0\n", "same_3_5_and_11 = 0.0\n", - "same_3_5_and_12 = 1.0\n", + "same_3_5_and_12 = 0.0\n", "same_3_5_and_13 = 0.0\n", "same_3_5_and_14 = 0.0\n", "same_3_5_and_15 = 0.0\n", @@ -151604,7 +151594,7 @@ "same_3_5_and_7 = 0.0\n", "same_3_5_and_8 = 0.0\n", "same_3_5_and_9 = 0.0\n", - "same_3_6 = 1.0\n", + "same_3_6 = 0.0\n", "same_3_60 = 0.0\n", "same_3_60_and_0 = 0.0\n", "same_3_60_and_1 = 0.0\n", @@ -151779,7 +151769,7 @@ "same_3_6_and_1 = 0.0\n", "same_3_6_and_10 = 0.0\n", "same_3_6_and_11 = 0.0\n", - "same_3_6_and_12 = 1.0\n", + "same_3_6_and_12 = 0.0\n", "same_3_6_and_13 = 0.0\n", "same_3_6_and_14 = 0.0\n", "same_3_6_and_15 = 0.0\n", @@ -151854,8 +151844,8 @@ "same_40_41_and_15 = 0.0\n", "same_40_41_and_2 = 0.0\n", "same_40_41_and_3 = 0.0\n", - "same_40_41_and_4 = 0.0\n", - "same_40_41_and_5 = 1.0\n", + "same_40_41_and_4 = 1.0\n", + "same_40_41_and_5 = 0.0\n", "same_40_41_and_6 = 0.0\n", "same_40_41_and_7 = 0.0\n", "same_40_41_and_8 = 0.0\n", @@ -151871,8 +151861,8 @@ "same_40_42_and_15 = 0.0\n", "same_40_42_and_2 = 0.0\n", "same_40_42_and_3 = 0.0\n", - "same_40_42_and_4 = 0.0\n", - "same_40_42_and_5 = 1.0\n", + "same_40_42_and_4 = 1.0\n", + "same_40_42_and_5 = 0.0\n", "same_40_42_and_6 = 0.0\n", "same_40_42_and_7 = 0.0\n", "same_40_42_and_8 = 0.0\n", @@ -151888,13 +151878,13 @@ "same_40_43_and_15 = 0.0\n", "same_40_43_and_2 = 0.0\n", "same_40_43_and_3 = 0.0\n", - "same_40_43_and_4 = 0.0\n", - "same_40_43_and_5 = 1.0\n", + "same_40_43_and_4 = 1.0\n", + "same_40_43_and_5 = 0.0\n", "same_40_43_and_6 = 0.0\n", "same_40_43_and_7 = 0.0\n", "same_40_43_and_8 = 0.0\n", "same_40_43_and_9 = 0.0\n", - "same_40_44 = 0.0\n", + "same_40_44 = 1.0\n", "same_40_44_and_0 = 0.0\n", "same_40_44_and_1 = 0.0\n", "same_40_44_and_10 = 0.0\n", @@ -151905,13 +151895,13 @@ "same_40_44_and_15 = 0.0\n", "same_40_44_and_2 = 0.0\n", "same_40_44_and_3 = 0.0\n", - "same_40_44_and_4 = 0.0\n", + "same_40_44_and_4 = 1.0\n", "same_40_44_and_5 = 0.0\n", "same_40_44_and_6 = 0.0\n", "same_40_44_and_7 = 0.0\n", "same_40_44_and_8 = 0.0\n", "same_40_44_and_9 = 0.0\n", - "same_40_45 = 0.0\n", + "same_40_45 = 1.0\n", "same_40_45_and_0 = 0.0\n", "same_40_45_and_1 = 0.0\n", "same_40_45_and_10 = 0.0\n", @@ -151922,13 +151912,13 @@ "same_40_45_and_15 = 0.0\n", "same_40_45_and_2 = 0.0\n", "same_40_45_and_3 = 0.0\n", - "same_40_45_and_4 = 0.0\n", + "same_40_45_and_4 = 1.0\n", "same_40_45_and_5 = 0.0\n", "same_40_45_and_6 = 0.0\n", "same_40_45_and_7 = 0.0\n", "same_40_45_and_8 = 0.0\n", "same_40_45_and_9 = 0.0\n", - "same_40_46 = 0.0\n", + "same_40_46 = 1.0\n", "same_40_46_and_0 = 0.0\n", "same_40_46_and_1 = 0.0\n", "same_40_46_and_10 = 0.0\n", @@ -151939,13 +151929,13 @@ "same_40_46_and_15 = 0.0\n", "same_40_46_and_2 = 0.0\n", "same_40_46_and_3 = 0.0\n", - "same_40_46_and_4 = 0.0\n", + "same_40_46_and_4 = 1.0\n", "same_40_46_and_5 = 0.0\n", "same_40_46_and_6 = 0.0\n", "same_40_46_and_7 = 0.0\n", "same_40_46_and_8 = 0.0\n", "same_40_46_and_9 = 0.0\n", - "same_40_47 = 0.0\n", + "same_40_47 = 1.0\n", "same_40_47_and_0 = 0.0\n", "same_40_47_and_1 = 0.0\n", "same_40_47_and_10 = 0.0\n", @@ -151956,13 +151946,13 @@ "same_40_47_and_15 = 0.0\n", "same_40_47_and_2 = 0.0\n", "same_40_47_and_3 = 0.0\n", - "same_40_47_and_4 = 0.0\n", + "same_40_47_and_4 = 1.0\n", "same_40_47_and_5 = 0.0\n", "same_40_47_and_6 = 0.0\n", "same_40_47_and_7 = 0.0\n", "same_40_47_and_8 = 0.0\n", "same_40_47_and_9 = 0.0\n", - "same_40_48 = 0.0\n", + "same_40_48 = 1.0\n", "same_40_48_and_0 = 0.0\n", "same_40_48_and_1 = 0.0\n", "same_40_48_and_10 = 0.0\n", @@ -151973,13 +151963,13 @@ "same_40_48_and_15 = 0.0\n", "same_40_48_and_2 = 0.0\n", "same_40_48_and_3 = 0.0\n", - "same_40_48_and_4 = 0.0\n", + "same_40_48_and_4 = 1.0\n", "same_40_48_and_5 = 0.0\n", "same_40_48_and_6 = 0.0\n", "same_40_48_and_7 = 0.0\n", "same_40_48_and_8 = 0.0\n", "same_40_48_and_9 = 0.0\n", - "same_40_49 = 0.0\n", + "same_40_49 = 1.0\n", "same_40_49_and_0 = 0.0\n", "same_40_49_and_1 = 0.0\n", "same_40_49_and_10 = 0.0\n", @@ -151990,13 +151980,13 @@ "same_40_49_and_15 = 0.0\n", "same_40_49_and_2 = 0.0\n", "same_40_49_and_3 = 0.0\n", - "same_40_49_and_4 = 0.0\n", + "same_40_49_and_4 = 1.0\n", "same_40_49_and_5 = 0.0\n", "same_40_49_and_6 = 0.0\n", "same_40_49_and_7 = 0.0\n", "same_40_49_and_8 = 0.0\n", "same_40_49_and_9 = 0.0\n", - "same_40_50 = 0.0\n", + "same_40_50 = 1.0\n", "same_40_50_and_0 = 0.0\n", "same_40_50_and_1 = 0.0\n", "same_40_50_and_10 = 0.0\n", @@ -152007,13 +151997,13 @@ "same_40_50_and_15 = 0.0\n", "same_40_50_and_2 = 0.0\n", "same_40_50_and_3 = 0.0\n", - "same_40_50_and_4 = 0.0\n", + "same_40_50_and_4 = 1.0\n", "same_40_50_and_5 = 0.0\n", "same_40_50_and_6 = 0.0\n", "same_40_50_and_7 = 0.0\n", "same_40_50_and_8 = 0.0\n", "same_40_50_and_9 = 0.0\n", - "same_40_51 = 0.0\n", + "same_40_51 = 1.0\n", "same_40_51_and_0 = 0.0\n", "same_40_51_and_1 = 0.0\n", "same_40_51_and_10 = 0.0\n", @@ -152024,13 +152014,13 @@ "same_40_51_and_15 = 0.0\n", "same_40_51_and_2 = 0.0\n", "same_40_51_and_3 = 0.0\n", - "same_40_51_and_4 = 0.0\n", + "same_40_51_and_4 = 1.0\n", "same_40_51_and_5 = 0.0\n", "same_40_51_and_6 = 0.0\n", "same_40_51_and_7 = 0.0\n", "same_40_51_and_8 = 0.0\n", "same_40_51_and_9 = 0.0\n", - "same_40_52 = 0.0\n", + "same_40_52 = 1.0\n", "same_40_52_and_0 = 0.0\n", "same_40_52_and_1 = 0.0\n", "same_40_52_and_10 = 0.0\n", @@ -152041,7 +152031,7 @@ "same_40_52_and_15 = 0.0\n", "same_40_52_and_2 = 0.0\n", "same_40_52_and_3 = 0.0\n", - "same_40_52_and_4 = 0.0\n", + "same_40_52_and_4 = 1.0\n", "same_40_52_and_5 = 0.0\n", "same_40_52_and_6 = 0.0\n", "same_40_52_and_7 = 0.0\n", @@ -152348,8 +152338,8 @@ "same_41_42_and_15 = 0.0\n", "same_41_42_and_2 = 0.0\n", "same_41_42_and_3 = 0.0\n", - "same_41_42_and_4 = 0.0\n", - "same_41_42_and_5 = 1.0\n", + "same_41_42_and_4 = 1.0\n", + "same_41_42_and_5 = 0.0\n", "same_41_42_and_6 = 0.0\n", "same_41_42_and_7 = 0.0\n", "same_41_42_and_8 = 0.0\n", @@ -152365,13 +152355,13 @@ "same_41_43_and_15 = 0.0\n", "same_41_43_and_2 = 0.0\n", "same_41_43_and_3 = 0.0\n", - "same_41_43_and_4 = 0.0\n", - "same_41_43_and_5 = 1.0\n", + "same_41_43_and_4 = 1.0\n", + "same_41_43_and_5 = 0.0\n", "same_41_43_and_6 = 0.0\n", "same_41_43_and_7 = 0.0\n", "same_41_43_and_8 = 0.0\n", "same_41_43_and_9 = 0.0\n", - "same_41_44 = 0.0\n", + "same_41_44 = 1.0\n", "same_41_44_and_0 = 0.0\n", "same_41_44_and_1 = 0.0\n", "same_41_44_and_10 = 0.0\n", @@ -152382,13 +152372,13 @@ "same_41_44_and_15 = 0.0\n", "same_41_44_and_2 = 0.0\n", "same_41_44_and_3 = 0.0\n", - "same_41_44_and_4 = 0.0\n", + "same_41_44_and_4 = 1.0\n", "same_41_44_and_5 = 0.0\n", "same_41_44_and_6 = 0.0\n", "same_41_44_and_7 = 0.0\n", "same_41_44_and_8 = 0.0\n", "same_41_44_and_9 = 0.0\n", - "same_41_45 = 0.0\n", + "same_41_45 = 1.0\n", "same_41_45_and_0 = 0.0\n", "same_41_45_and_1 = 0.0\n", "same_41_45_and_10 = 0.0\n", @@ -152399,13 +152389,13 @@ "same_41_45_and_15 = 0.0\n", "same_41_45_and_2 = 0.0\n", "same_41_45_and_3 = 0.0\n", - "same_41_45_and_4 = 0.0\n", + "same_41_45_and_4 = 1.0\n", "same_41_45_and_5 = 0.0\n", "same_41_45_and_6 = 0.0\n", "same_41_45_and_7 = 0.0\n", "same_41_45_and_8 = 0.0\n", "same_41_45_and_9 = 0.0\n", - "same_41_46 = 0.0\n", + "same_41_46 = 1.0\n", "same_41_46_and_0 = 0.0\n", "same_41_46_and_1 = 0.0\n", "same_41_46_and_10 = 0.0\n", @@ -152416,13 +152406,13 @@ "same_41_46_and_15 = 0.0\n", "same_41_46_and_2 = 0.0\n", "same_41_46_and_3 = 0.0\n", - "same_41_46_and_4 = 0.0\n", + "same_41_46_and_4 = 1.0\n", "same_41_46_and_5 = 0.0\n", "same_41_46_and_6 = 0.0\n", "same_41_46_and_7 = 0.0\n", "same_41_46_and_8 = 0.0\n", "same_41_46_and_9 = 0.0\n", - "same_41_47 = 0.0\n", + "same_41_47 = 1.0\n", "same_41_47_and_0 = 0.0\n", "same_41_47_and_1 = 0.0\n", "same_41_47_and_10 = 0.0\n", @@ -152433,13 +152423,13 @@ "same_41_47_and_15 = 0.0\n", "same_41_47_and_2 = 0.0\n", "same_41_47_and_3 = 0.0\n", - "same_41_47_and_4 = 0.0\n", + "same_41_47_and_4 = 1.0\n", "same_41_47_and_5 = 0.0\n", "same_41_47_and_6 = 0.0\n", "same_41_47_and_7 = 0.0\n", "same_41_47_and_8 = 0.0\n", "same_41_47_and_9 = 0.0\n", - "same_41_48 = 0.0\n", + "same_41_48 = 1.0\n", "same_41_48_and_0 = 0.0\n", "same_41_48_and_1 = 0.0\n", "same_41_48_and_10 = 0.0\n", @@ -152450,13 +152440,13 @@ "same_41_48_and_15 = 0.0\n", "same_41_48_and_2 = 0.0\n", "same_41_48_and_3 = 0.0\n", - "same_41_48_and_4 = 0.0\n", + "same_41_48_and_4 = 1.0\n", "same_41_48_and_5 = 0.0\n", "same_41_48_and_6 = 0.0\n", "same_41_48_and_7 = 0.0\n", "same_41_48_and_8 = 0.0\n", "same_41_48_and_9 = 0.0\n", - "same_41_49 = 0.0\n", + "same_41_49 = 1.0\n", "same_41_49_and_0 = 0.0\n", "same_41_49_and_1 = 0.0\n", "same_41_49_and_10 = 0.0\n", @@ -152467,13 +152457,13 @@ "same_41_49_and_15 = 0.0\n", "same_41_49_and_2 = 0.0\n", "same_41_49_and_3 = 0.0\n", - "same_41_49_and_4 = 0.0\n", + "same_41_49_and_4 = 1.0\n", "same_41_49_and_5 = 0.0\n", "same_41_49_and_6 = 0.0\n", "same_41_49_and_7 = 0.0\n", "same_41_49_and_8 = 0.0\n", "same_41_49_and_9 = 0.0\n", - "same_41_50 = 0.0\n", + "same_41_50 = 1.0\n", "same_41_50_and_0 = 0.0\n", "same_41_50_and_1 = 0.0\n", "same_41_50_and_10 = 0.0\n", @@ -152484,13 +152474,13 @@ "same_41_50_and_15 = 0.0\n", "same_41_50_and_2 = 0.0\n", "same_41_50_and_3 = 0.0\n", - "same_41_50_and_4 = 0.0\n", + "same_41_50_and_4 = 1.0\n", "same_41_50_and_5 = 0.0\n", "same_41_50_and_6 = 0.0\n", "same_41_50_and_7 = 0.0\n", "same_41_50_and_8 = 0.0\n", "same_41_50_and_9 = 0.0\n", - "same_41_51 = 0.0\n", + "same_41_51 = 1.0\n", "same_41_51_and_0 = 0.0\n", "same_41_51_and_1 = 0.0\n", "same_41_51_and_10 = 0.0\n", @@ -152501,13 +152491,13 @@ "same_41_51_and_15 = 0.0\n", "same_41_51_and_2 = 0.0\n", "same_41_51_and_3 = 0.0\n", - "same_41_51_and_4 = 0.0\n", + "same_41_51_and_4 = 1.0\n", "same_41_51_and_5 = 0.0\n", "same_41_51_and_6 = 0.0\n", "same_41_51_and_7 = 0.0\n", "same_41_51_and_8 = 0.0\n", "same_41_51_and_9 = 0.0\n", - "same_41_52 = 0.0\n", + "same_41_52 = 1.0\n", "same_41_52_and_0 = 0.0\n", "same_41_52_and_1 = 0.0\n", "same_41_52_and_10 = 0.0\n", @@ -152518,7 +152508,7 @@ "same_41_52_and_15 = 0.0\n", "same_41_52_and_2 = 0.0\n", "same_41_52_and_3 = 0.0\n", - "same_41_52_and_4 = 0.0\n", + "same_41_52_and_4 = 1.0\n", "same_41_52_and_5 = 0.0\n", "same_41_52_and_6 = 0.0\n", "same_41_52_and_7 = 0.0\n", @@ -152825,13 +152815,13 @@ "same_42_43_and_15 = 0.0\n", "same_42_43_and_2 = 0.0\n", "same_42_43_and_3 = 0.0\n", - "same_42_43_and_4 = 0.0\n", - "same_42_43_and_5 = 1.0\n", + "same_42_43_and_4 = 1.0\n", + "same_42_43_and_5 = 0.0\n", "same_42_43_and_6 = 0.0\n", "same_42_43_and_7 = 0.0\n", "same_42_43_and_8 = 0.0\n", "same_42_43_and_9 = 0.0\n", - "same_42_44 = 0.0\n", + "same_42_44 = 1.0\n", "same_42_44_and_0 = 0.0\n", "same_42_44_and_1 = 0.0\n", "same_42_44_and_10 = 0.0\n", @@ -152842,13 +152832,13 @@ "same_42_44_and_15 = 0.0\n", "same_42_44_and_2 = 0.0\n", "same_42_44_and_3 = 0.0\n", - "same_42_44_and_4 = 0.0\n", + "same_42_44_and_4 = 1.0\n", "same_42_44_and_5 = 0.0\n", "same_42_44_and_6 = 0.0\n", "same_42_44_and_7 = 0.0\n", "same_42_44_and_8 = 0.0\n", "same_42_44_and_9 = 0.0\n", - "same_42_45 = 0.0\n", + "same_42_45 = 1.0\n", "same_42_45_and_0 = 0.0\n", "same_42_45_and_1 = 0.0\n", "same_42_45_and_10 = 0.0\n", @@ -152859,13 +152849,13 @@ "same_42_45_and_15 = 0.0\n", "same_42_45_and_2 = 0.0\n", "same_42_45_and_3 = 0.0\n", - "same_42_45_and_4 = 0.0\n", + "same_42_45_and_4 = 1.0\n", "same_42_45_and_5 = 0.0\n", "same_42_45_and_6 = 0.0\n", "same_42_45_and_7 = 0.0\n", "same_42_45_and_8 = 0.0\n", "same_42_45_and_9 = 0.0\n", - "same_42_46 = 0.0\n", + "same_42_46 = 1.0\n", "same_42_46_and_0 = 0.0\n", "same_42_46_and_1 = 0.0\n", "same_42_46_and_10 = 0.0\n", @@ -152876,13 +152866,13 @@ "same_42_46_and_15 = 0.0\n", "same_42_46_and_2 = 0.0\n", "same_42_46_and_3 = 0.0\n", - "same_42_46_and_4 = 0.0\n", + "same_42_46_and_4 = 1.0\n", "same_42_46_and_5 = 0.0\n", "same_42_46_and_6 = 0.0\n", "same_42_46_and_7 = 0.0\n", "same_42_46_and_8 = 0.0\n", "same_42_46_and_9 = 0.0\n", - "same_42_47 = 0.0\n", + "same_42_47 = 1.0\n", "same_42_47_and_0 = 0.0\n", "same_42_47_and_1 = 0.0\n", "same_42_47_and_10 = 0.0\n", @@ -152893,13 +152883,13 @@ "same_42_47_and_15 = 0.0\n", "same_42_47_and_2 = 0.0\n", "same_42_47_and_3 = 0.0\n", - "same_42_47_and_4 = 0.0\n", + "same_42_47_and_4 = 1.0\n", "same_42_47_and_5 = 0.0\n", "same_42_47_and_6 = 0.0\n", "same_42_47_and_7 = 0.0\n", "same_42_47_and_8 = 0.0\n", "same_42_47_and_9 = 0.0\n", - "same_42_48 = 0.0\n", + "same_42_48 = 1.0\n", "same_42_48_and_0 = 0.0\n", "same_42_48_and_1 = 0.0\n", "same_42_48_and_10 = 0.0\n", @@ -152910,13 +152900,13 @@ "same_42_48_and_15 = 0.0\n", "same_42_48_and_2 = 0.0\n", "same_42_48_and_3 = 0.0\n", - "same_42_48_and_4 = 0.0\n", + "same_42_48_and_4 = 1.0\n", "same_42_48_and_5 = 0.0\n", "same_42_48_and_6 = 0.0\n", "same_42_48_and_7 = 0.0\n", "same_42_48_and_8 = 0.0\n", "same_42_48_and_9 = 0.0\n", - "same_42_49 = 0.0\n", + "same_42_49 = 1.0\n", "same_42_49_and_0 = 0.0\n", "same_42_49_and_1 = 0.0\n", "same_42_49_and_10 = 0.0\n", @@ -152927,13 +152917,13 @@ "same_42_49_and_15 = 0.0\n", "same_42_49_and_2 = 0.0\n", "same_42_49_and_3 = 0.0\n", - "same_42_49_and_4 = 0.0\n", + "same_42_49_and_4 = 1.0\n", "same_42_49_and_5 = 0.0\n", "same_42_49_and_6 = 0.0\n", "same_42_49_and_7 = 0.0\n", "same_42_49_and_8 = 0.0\n", "same_42_49_and_9 = 0.0\n", - "same_42_50 = 0.0\n", + "same_42_50 = 1.0\n", "same_42_50_and_0 = 0.0\n", "same_42_50_and_1 = 0.0\n", "same_42_50_and_10 = 0.0\n", @@ -152944,13 +152934,13 @@ "same_42_50_and_15 = 0.0\n", "same_42_50_and_2 = 0.0\n", "same_42_50_and_3 = 0.0\n", - "same_42_50_and_4 = 0.0\n", + "same_42_50_and_4 = 1.0\n", "same_42_50_and_5 = 0.0\n", "same_42_50_and_6 = 0.0\n", "same_42_50_and_7 = 0.0\n", "same_42_50_and_8 = 0.0\n", "same_42_50_and_9 = 0.0\n", - "same_42_51 = 0.0\n", + "same_42_51 = 1.0\n", "same_42_51_and_0 = 0.0\n", "same_42_51_and_1 = 0.0\n", "same_42_51_and_10 = 0.0\n", @@ -152961,13 +152951,13 @@ "same_42_51_and_15 = 0.0\n", "same_42_51_and_2 = 0.0\n", "same_42_51_and_3 = 0.0\n", - "same_42_51_and_4 = 0.0\n", + "same_42_51_and_4 = 1.0\n", "same_42_51_and_5 = 0.0\n", "same_42_51_and_6 = 0.0\n", "same_42_51_and_7 = 0.0\n", "same_42_51_and_8 = 0.0\n", "same_42_51_and_9 = 0.0\n", - "same_42_52 = 0.0\n", + "same_42_52 = 1.0\n", "same_42_52_and_0 = 0.0\n", "same_42_52_and_1 = 0.0\n", "same_42_52_and_10 = 0.0\n", @@ -152978,7 +152968,7 @@ "same_42_52_and_15 = 0.0\n", "same_42_52_and_2 = 0.0\n", "same_42_52_and_3 = 0.0\n", - "same_42_52_and_4 = 0.0\n", + "same_42_52_and_4 = 1.0\n", "same_42_52_and_5 = 0.0\n", "same_42_52_and_6 = 0.0\n", "same_42_52_and_7 = 0.0\n", @@ -153274,7 +153264,7 @@ "same_42_69_and_8 = 0.0\n", "same_42_69_and_9 = 0.0\n", "same_43_43 = 1.0\n", - "same_43_44 = 0.0\n", + "same_43_44 = 1.0\n", "same_43_44_and_0 = 0.0\n", "same_43_44_and_1 = 0.0\n", "same_43_44_and_10 = 0.0\n", @@ -153285,13 +153275,13 @@ "same_43_44_and_15 = 0.0\n", "same_43_44_and_2 = 0.0\n", "same_43_44_and_3 = 0.0\n", - "same_43_44_and_4 = 0.0\n", + "same_43_44_and_4 = 1.0\n", "same_43_44_and_5 = 0.0\n", "same_43_44_and_6 = 0.0\n", "same_43_44_and_7 = 0.0\n", "same_43_44_and_8 = 0.0\n", "same_43_44_and_9 = 0.0\n", - "same_43_45 = 0.0\n", + "same_43_45 = 1.0\n", "same_43_45_and_0 = 0.0\n", "same_43_45_and_1 = 0.0\n", "same_43_45_and_10 = 0.0\n", @@ -153302,13 +153292,13 @@ "same_43_45_and_15 = 0.0\n", "same_43_45_and_2 = 0.0\n", "same_43_45_and_3 = 0.0\n", - "same_43_45_and_4 = 0.0\n", + "same_43_45_and_4 = 1.0\n", "same_43_45_and_5 = 0.0\n", "same_43_45_and_6 = 0.0\n", "same_43_45_and_7 = 0.0\n", "same_43_45_and_8 = 0.0\n", "same_43_45_and_9 = 0.0\n", - "same_43_46 = 0.0\n", + "same_43_46 = 1.0\n", "same_43_46_and_0 = 0.0\n", "same_43_46_and_1 = 0.0\n", "same_43_46_and_10 = 0.0\n", @@ -153319,13 +153309,13 @@ "same_43_46_and_15 = 0.0\n", "same_43_46_and_2 = 0.0\n", "same_43_46_and_3 = 0.0\n", - "same_43_46_and_4 = 0.0\n", + "same_43_46_and_4 = 1.0\n", "same_43_46_and_5 = 0.0\n", "same_43_46_and_6 = 0.0\n", "same_43_46_and_7 = 0.0\n", "same_43_46_and_8 = 0.0\n", "same_43_46_and_9 = 0.0\n", - "same_43_47 = 0.0\n", + "same_43_47 = 1.0\n", "same_43_47_and_0 = 0.0\n", "same_43_47_and_1 = 0.0\n", "same_43_47_and_10 = 0.0\n", @@ -153336,13 +153326,13 @@ "same_43_47_and_15 = 0.0\n", "same_43_47_and_2 = 0.0\n", "same_43_47_and_3 = 0.0\n", - "same_43_47_and_4 = 0.0\n", + "same_43_47_and_4 = 1.0\n", "same_43_47_and_5 = 0.0\n", "same_43_47_and_6 = 0.0\n", "same_43_47_and_7 = 0.0\n", "same_43_47_and_8 = 0.0\n", "same_43_47_and_9 = 0.0\n", - "same_43_48 = 0.0\n", + "same_43_48 = 1.0\n", "same_43_48_and_0 = 0.0\n", "same_43_48_and_1 = 0.0\n", "same_43_48_and_10 = 0.0\n", @@ -153353,13 +153343,13 @@ "same_43_48_and_15 = 0.0\n", "same_43_48_and_2 = 0.0\n", "same_43_48_and_3 = 0.0\n", - "same_43_48_and_4 = 0.0\n", + "same_43_48_and_4 = 1.0\n", "same_43_48_and_5 = 0.0\n", "same_43_48_and_6 = 0.0\n", "same_43_48_and_7 = 0.0\n", "same_43_48_and_8 = 0.0\n", "same_43_48_and_9 = 0.0\n", - "same_43_49 = 0.0\n", + "same_43_49 = 1.0\n", "same_43_49_and_0 = 0.0\n", "same_43_49_and_1 = 0.0\n", "same_43_49_and_10 = 0.0\n", @@ -153370,13 +153360,13 @@ "same_43_49_and_15 = 0.0\n", "same_43_49_and_2 = 0.0\n", "same_43_49_and_3 = 0.0\n", - "same_43_49_and_4 = 0.0\n", + "same_43_49_and_4 = 1.0\n", "same_43_49_and_5 = 0.0\n", "same_43_49_and_6 = 0.0\n", "same_43_49_and_7 = 0.0\n", "same_43_49_and_8 = 0.0\n", "same_43_49_and_9 = 0.0\n", - "same_43_50 = 0.0\n", + "same_43_50 = 1.0\n", "same_43_50_and_0 = 0.0\n", "same_43_50_and_1 = 0.0\n", "same_43_50_and_10 = 0.0\n", @@ -153387,13 +153377,13 @@ "same_43_50_and_15 = 0.0\n", "same_43_50_and_2 = 0.0\n", "same_43_50_and_3 = 0.0\n", - "same_43_50_and_4 = 0.0\n", + "same_43_50_and_4 = 1.0\n", "same_43_50_and_5 = 0.0\n", "same_43_50_and_6 = 0.0\n", "same_43_50_and_7 = 0.0\n", "same_43_50_and_8 = 0.0\n", "same_43_50_and_9 = 0.0\n", - "same_43_51 = 0.0\n", + "same_43_51 = 1.0\n", "same_43_51_and_0 = 0.0\n", "same_43_51_and_1 = 0.0\n", "same_43_51_and_10 = 0.0\n", @@ -153404,13 +153394,13 @@ "same_43_51_and_15 = 0.0\n", "same_43_51_and_2 = 0.0\n", "same_43_51_and_3 = 0.0\n", - "same_43_51_and_4 = 0.0\n", + "same_43_51_and_4 = 1.0\n", "same_43_51_and_5 = 0.0\n", "same_43_51_and_6 = 0.0\n", "same_43_51_and_7 = 0.0\n", "same_43_51_and_8 = 0.0\n", "same_43_51_and_9 = 0.0\n", - "same_43_52 = 0.0\n", + "same_43_52 = 1.0\n", "same_43_52_and_0 = 0.0\n", "same_43_52_and_1 = 0.0\n", "same_43_52_and_10 = 0.0\n", @@ -153421,7 +153411,7 @@ "same_43_52_and_15 = 0.0\n", "same_43_52_and_2 = 0.0\n", "same_43_52_and_3 = 0.0\n", - "same_43_52_and_4 = 0.0\n", + "same_43_52_and_4 = 1.0\n", "same_43_52_and_5 = 0.0\n", "same_43_52_and_6 = 0.0\n", "same_43_52_and_7 = 0.0\n", @@ -153720,7 +153710,7 @@ "same_44_45 = 1.0\n", "same_44_45_and_0 = 0.0\n", "same_44_45_and_1 = 0.0\n", - "same_44_45_and_10 = 1.0\n", + "same_44_45_and_10 = 0.0\n", "same_44_45_and_11 = 0.0\n", "same_44_45_and_12 = 0.0\n", "same_44_45_and_13 = 0.0\n", @@ -153728,7 +153718,7 @@ "same_44_45_and_15 = 0.0\n", "same_44_45_and_2 = 0.0\n", "same_44_45_and_3 = 0.0\n", - "same_44_45_and_4 = 0.0\n", + "same_44_45_and_4 = 1.0\n", "same_44_45_and_5 = 0.0\n", "same_44_45_and_6 = 0.0\n", "same_44_45_and_7 = 0.0\n", @@ -153737,7 +153727,7 @@ "same_44_46 = 1.0\n", "same_44_46_and_0 = 0.0\n", "same_44_46_and_1 = 0.0\n", - "same_44_46_and_10 = 1.0\n", + "same_44_46_and_10 = 0.0\n", "same_44_46_and_11 = 0.0\n", "same_44_46_and_12 = 0.0\n", "same_44_46_and_13 = 0.0\n", @@ -153745,7 +153735,7 @@ "same_44_46_and_15 = 0.0\n", "same_44_46_and_2 = 0.0\n", "same_44_46_and_3 = 0.0\n", - "same_44_46_and_4 = 0.0\n", + "same_44_46_and_4 = 1.0\n", "same_44_46_and_5 = 0.0\n", "same_44_46_and_6 = 0.0\n", "same_44_46_and_7 = 0.0\n", @@ -153754,7 +153744,7 @@ "same_44_47 = 1.0\n", "same_44_47_and_0 = 0.0\n", "same_44_47_and_1 = 0.0\n", - "same_44_47_and_10 = 1.0\n", + "same_44_47_and_10 = 0.0\n", "same_44_47_and_11 = 0.0\n", "same_44_47_and_12 = 0.0\n", "same_44_47_and_13 = 0.0\n", @@ -153762,7 +153752,7 @@ "same_44_47_and_15 = 0.0\n", "same_44_47_and_2 = 0.0\n", "same_44_47_and_3 = 0.0\n", - "same_44_47_and_4 = 0.0\n", + "same_44_47_and_4 = 1.0\n", "same_44_47_and_5 = 0.0\n", "same_44_47_and_6 = 0.0\n", "same_44_47_and_7 = 0.0\n", @@ -153771,7 +153761,7 @@ "same_44_48 = 1.0\n", "same_44_48_and_0 = 0.0\n", "same_44_48_and_1 = 0.0\n", - "same_44_48_and_10 = 1.0\n", + "same_44_48_and_10 = 0.0\n", "same_44_48_and_11 = 0.0\n", "same_44_48_and_12 = 0.0\n", "same_44_48_and_13 = 0.0\n", @@ -153779,7 +153769,7 @@ "same_44_48_and_15 = 0.0\n", "same_44_48_and_2 = 0.0\n", "same_44_48_and_3 = 0.0\n", - "same_44_48_and_4 = 0.0\n", + "same_44_48_and_4 = 1.0\n", "same_44_48_and_5 = 0.0\n", "same_44_48_and_6 = 0.0\n", "same_44_48_and_7 = 0.0\n", @@ -153788,7 +153778,7 @@ "same_44_49 = 1.0\n", "same_44_49_and_0 = 0.0\n", "same_44_49_and_1 = 0.0\n", - "same_44_49_and_10 = 1.0\n", + "same_44_49_and_10 = 0.0\n", "same_44_49_and_11 = 0.0\n", "same_44_49_and_12 = 0.0\n", "same_44_49_and_13 = 0.0\n", @@ -153796,7 +153786,7 @@ "same_44_49_and_15 = 0.0\n", "same_44_49_and_2 = 0.0\n", "same_44_49_and_3 = 0.0\n", - "same_44_49_and_4 = 0.0\n", + "same_44_49_and_4 = 1.0\n", "same_44_49_and_5 = 0.0\n", "same_44_49_and_6 = 0.0\n", "same_44_49_and_7 = 0.0\n", @@ -153805,7 +153795,7 @@ "same_44_50 = 1.0\n", "same_44_50_and_0 = 0.0\n", "same_44_50_and_1 = 0.0\n", - "same_44_50_and_10 = 1.0\n", + "same_44_50_and_10 = 0.0\n", "same_44_50_and_11 = 0.0\n", "same_44_50_and_12 = 0.0\n", "same_44_50_and_13 = 0.0\n", @@ -153813,7 +153803,7 @@ "same_44_50_and_15 = 0.0\n", "same_44_50_and_2 = 0.0\n", "same_44_50_and_3 = 0.0\n", - "same_44_50_and_4 = 0.0\n", + "same_44_50_and_4 = 1.0\n", "same_44_50_and_5 = 0.0\n", "same_44_50_and_6 = 0.0\n", "same_44_50_and_7 = 0.0\n", @@ -153822,7 +153812,7 @@ "same_44_51 = 1.0\n", "same_44_51_and_0 = 0.0\n", "same_44_51_and_1 = 0.0\n", - "same_44_51_and_10 = 1.0\n", + "same_44_51_and_10 = 0.0\n", "same_44_51_and_11 = 0.0\n", "same_44_51_and_12 = 0.0\n", "same_44_51_and_13 = 0.0\n", @@ -153830,7 +153820,7 @@ "same_44_51_and_15 = 0.0\n", "same_44_51_and_2 = 0.0\n", "same_44_51_and_3 = 0.0\n", - "same_44_51_and_4 = 0.0\n", + "same_44_51_and_4 = 1.0\n", "same_44_51_and_5 = 0.0\n", "same_44_51_and_6 = 0.0\n", "same_44_51_and_7 = 0.0\n", @@ -153839,7 +153829,7 @@ "same_44_52 = 1.0\n", "same_44_52_and_0 = 0.0\n", "same_44_52_and_1 = 0.0\n", - "same_44_52_and_10 = 1.0\n", + "same_44_52_and_10 = 0.0\n", "same_44_52_and_11 = 0.0\n", "same_44_52_and_12 = 0.0\n", "same_44_52_and_13 = 0.0\n", @@ -153847,7 +153837,7 @@ "same_44_52_and_15 = 0.0\n", "same_44_52_and_2 = 0.0\n", "same_44_52_and_3 = 0.0\n", - "same_44_52_and_4 = 0.0\n", + "same_44_52_and_4 = 1.0\n", "same_44_52_and_5 = 0.0\n", "same_44_52_and_6 = 0.0\n", "same_44_52_and_7 = 0.0\n", @@ -154146,7 +154136,7 @@ "same_45_46 = 1.0\n", "same_45_46_and_0 = 0.0\n", "same_45_46_and_1 = 0.0\n", - "same_45_46_and_10 = 1.0\n", + "same_45_46_and_10 = 0.0\n", "same_45_46_and_11 = 0.0\n", "same_45_46_and_12 = 0.0\n", "same_45_46_and_13 = 0.0\n", @@ -154154,7 +154144,7 @@ "same_45_46_and_15 = 0.0\n", "same_45_46_and_2 = 0.0\n", "same_45_46_and_3 = 0.0\n", - "same_45_46_and_4 = 0.0\n", + "same_45_46_and_4 = 1.0\n", "same_45_46_and_5 = 0.0\n", "same_45_46_and_6 = 0.0\n", "same_45_46_and_7 = 0.0\n", @@ -154163,7 +154153,7 @@ "same_45_47 = 1.0\n", "same_45_47_and_0 = 0.0\n", "same_45_47_and_1 = 0.0\n", - "same_45_47_and_10 = 1.0\n", + "same_45_47_and_10 = 0.0\n", "same_45_47_and_11 = 0.0\n", "same_45_47_and_12 = 0.0\n", "same_45_47_and_13 = 0.0\n", @@ -154171,7 +154161,7 @@ "same_45_47_and_15 = 0.0\n", "same_45_47_and_2 = 0.0\n", "same_45_47_and_3 = 0.0\n", - "same_45_47_and_4 = 0.0\n", + "same_45_47_and_4 = 1.0\n", "same_45_47_and_5 = 0.0\n", "same_45_47_and_6 = 0.0\n", "same_45_47_and_7 = 0.0\n", @@ -154180,7 +154170,7 @@ "same_45_48 = 1.0\n", "same_45_48_and_0 = 0.0\n", "same_45_48_and_1 = 0.0\n", - "same_45_48_and_10 = 1.0\n", + "same_45_48_and_10 = 0.0\n", "same_45_48_and_11 = 0.0\n", "same_45_48_and_12 = 0.0\n", "same_45_48_and_13 = 0.0\n", @@ -154188,7 +154178,7 @@ "same_45_48_and_15 = 0.0\n", "same_45_48_and_2 = 0.0\n", "same_45_48_and_3 = 0.0\n", - "same_45_48_and_4 = 0.0\n", + "same_45_48_and_4 = 1.0\n", "same_45_48_and_5 = 0.0\n", "same_45_48_and_6 = 0.0\n", "same_45_48_and_7 = 0.0\n", @@ -154197,7 +154187,7 @@ "same_45_49 = 1.0\n", "same_45_49_and_0 = 0.0\n", "same_45_49_and_1 = 0.0\n", - "same_45_49_and_10 = 1.0\n", + "same_45_49_and_10 = 0.0\n", "same_45_49_and_11 = 0.0\n", "same_45_49_and_12 = 0.0\n", "same_45_49_and_13 = 0.0\n", @@ -154205,7 +154195,7 @@ "same_45_49_and_15 = 0.0\n", "same_45_49_and_2 = 0.0\n", "same_45_49_and_3 = 0.0\n", - "same_45_49_and_4 = 0.0\n", + "same_45_49_and_4 = 1.0\n", "same_45_49_and_5 = 0.0\n", "same_45_49_and_6 = 0.0\n", "same_45_49_and_7 = 0.0\n", @@ -154214,7 +154204,7 @@ "same_45_50 = 1.0\n", "same_45_50_and_0 = 0.0\n", "same_45_50_and_1 = 0.0\n", - "same_45_50_and_10 = 1.0\n", + "same_45_50_and_10 = 0.0\n", "same_45_50_and_11 = 0.0\n", "same_45_50_and_12 = 0.0\n", "same_45_50_and_13 = 0.0\n", @@ -154222,7 +154212,7 @@ "same_45_50_and_15 = 0.0\n", "same_45_50_and_2 = 0.0\n", "same_45_50_and_3 = 0.0\n", - "same_45_50_and_4 = 0.0\n", + "same_45_50_and_4 = 1.0\n", "same_45_50_and_5 = 0.0\n", "same_45_50_and_6 = 0.0\n", "same_45_50_and_7 = 0.0\n", @@ -154231,7 +154221,7 @@ "same_45_51 = 1.0\n", "same_45_51_and_0 = 0.0\n", "same_45_51_and_1 = 0.0\n", - "same_45_51_and_10 = 1.0\n", + "same_45_51_and_10 = 0.0\n", "same_45_51_and_11 = 0.0\n", "same_45_51_and_12 = 0.0\n", "same_45_51_and_13 = 0.0\n", @@ -154239,7 +154229,7 @@ "same_45_51_and_15 = 0.0\n", "same_45_51_and_2 = 0.0\n", "same_45_51_and_3 = 0.0\n", - "same_45_51_and_4 = 0.0\n", + "same_45_51_and_4 = 1.0\n", "same_45_51_and_5 = 0.0\n", "same_45_51_and_6 = 0.0\n", "same_45_51_and_7 = 0.0\n", @@ -154248,7 +154238,7 @@ "same_45_52 = 1.0\n", "same_45_52_and_0 = 0.0\n", "same_45_52_and_1 = 0.0\n", - "same_45_52_and_10 = 1.0\n", + "same_45_52_and_10 = 0.0\n", "same_45_52_and_11 = 0.0\n", "same_45_52_and_12 = 0.0\n", "same_45_52_and_13 = 0.0\n", @@ -154256,7 +154246,7 @@ "same_45_52_and_15 = 0.0\n", "same_45_52_and_2 = 0.0\n", "same_45_52_and_3 = 0.0\n", - "same_45_52_and_4 = 0.0\n", + "same_45_52_and_4 = 1.0\n", "same_45_52_and_5 = 0.0\n", "same_45_52_and_6 = 0.0\n", "same_45_52_and_7 = 0.0\n", @@ -154555,7 +154545,7 @@ "same_46_47 = 1.0\n", "same_46_47_and_0 = 0.0\n", "same_46_47_and_1 = 0.0\n", - "same_46_47_and_10 = 1.0\n", + "same_46_47_and_10 = 0.0\n", "same_46_47_and_11 = 0.0\n", "same_46_47_and_12 = 0.0\n", "same_46_47_and_13 = 0.0\n", @@ -154563,7 +154553,7 @@ "same_46_47_and_15 = 0.0\n", "same_46_47_and_2 = 0.0\n", "same_46_47_and_3 = 0.0\n", - "same_46_47_and_4 = 0.0\n", + "same_46_47_and_4 = 1.0\n", "same_46_47_and_5 = 0.0\n", "same_46_47_and_6 = 0.0\n", "same_46_47_and_7 = 0.0\n", @@ -154572,7 +154562,7 @@ "same_46_48 = 1.0\n", "same_46_48_and_0 = 0.0\n", "same_46_48_and_1 = 0.0\n", - "same_46_48_and_10 = 1.0\n", + "same_46_48_and_10 = 0.0\n", "same_46_48_and_11 = 0.0\n", "same_46_48_and_12 = 0.0\n", "same_46_48_and_13 = 0.0\n", @@ -154580,7 +154570,7 @@ "same_46_48_and_15 = 0.0\n", "same_46_48_and_2 = 0.0\n", "same_46_48_and_3 = 0.0\n", - "same_46_48_and_4 = 0.0\n", + "same_46_48_and_4 = 1.0\n", "same_46_48_and_5 = 0.0\n", "same_46_48_and_6 = 0.0\n", "same_46_48_and_7 = 0.0\n", @@ -154589,7 +154579,7 @@ "same_46_49 = 1.0\n", "same_46_49_and_0 = 0.0\n", "same_46_49_and_1 = 0.0\n", - "same_46_49_and_10 = 1.0\n", + "same_46_49_and_10 = 0.0\n", "same_46_49_and_11 = 0.0\n", "same_46_49_and_12 = 0.0\n", "same_46_49_and_13 = 0.0\n", @@ -154597,7 +154587,7 @@ "same_46_49_and_15 = 0.0\n", "same_46_49_and_2 = 0.0\n", "same_46_49_and_3 = 0.0\n", - "same_46_49_and_4 = 0.0\n", + "same_46_49_and_4 = 1.0\n", "same_46_49_and_5 = 0.0\n", "same_46_49_and_6 = 0.0\n", "same_46_49_and_7 = 0.0\n", @@ -154606,7 +154596,7 @@ "same_46_50 = 1.0\n", "same_46_50_and_0 = 0.0\n", "same_46_50_and_1 = 0.0\n", - "same_46_50_and_10 = 1.0\n", + "same_46_50_and_10 = 0.0\n", "same_46_50_and_11 = 0.0\n", "same_46_50_and_12 = 0.0\n", "same_46_50_and_13 = 0.0\n", @@ -154614,7 +154604,7 @@ "same_46_50_and_15 = 0.0\n", "same_46_50_and_2 = 0.0\n", "same_46_50_and_3 = 0.0\n", - "same_46_50_and_4 = 0.0\n", + "same_46_50_and_4 = 1.0\n", "same_46_50_and_5 = 0.0\n", "same_46_50_and_6 = 0.0\n", "same_46_50_and_7 = 0.0\n", @@ -154623,7 +154613,7 @@ "same_46_51 = 1.0\n", "same_46_51_and_0 = 0.0\n", "same_46_51_and_1 = 0.0\n", - "same_46_51_and_10 = 1.0\n", + "same_46_51_and_10 = 0.0\n", "same_46_51_and_11 = 0.0\n", "same_46_51_and_12 = 0.0\n", "same_46_51_and_13 = 0.0\n", @@ -154631,7 +154621,7 @@ "same_46_51_and_15 = 0.0\n", "same_46_51_and_2 = 0.0\n", "same_46_51_and_3 = 0.0\n", - "same_46_51_and_4 = 0.0\n", + "same_46_51_and_4 = 1.0\n", "same_46_51_and_5 = 0.0\n", "same_46_51_and_6 = 0.0\n", "same_46_51_and_7 = 0.0\n", @@ -154640,7 +154630,7 @@ "same_46_52 = 1.0\n", "same_46_52_and_0 = 0.0\n", "same_46_52_and_1 = 0.0\n", - "same_46_52_and_10 = 1.0\n", + "same_46_52_and_10 = 0.0\n", "same_46_52_and_11 = 0.0\n", "same_46_52_and_12 = 0.0\n", "same_46_52_and_13 = 0.0\n", @@ -154648,7 +154638,7 @@ "same_46_52_and_15 = 0.0\n", "same_46_52_and_2 = 0.0\n", "same_46_52_and_3 = 0.0\n", - "same_46_52_and_4 = 0.0\n", + "same_46_52_and_4 = 1.0\n", "same_46_52_and_5 = 0.0\n", "same_46_52_and_6 = 0.0\n", "same_46_52_and_7 = 0.0\n", @@ -154947,7 +154937,7 @@ "same_47_48 = 1.0\n", "same_47_48_and_0 = 0.0\n", "same_47_48_and_1 = 0.0\n", - "same_47_48_and_10 = 1.0\n", + "same_47_48_and_10 = 0.0\n", "same_47_48_and_11 = 0.0\n", "same_47_48_and_12 = 0.0\n", "same_47_48_and_13 = 0.0\n", @@ -154955,7 +154945,7 @@ "same_47_48_and_15 = 0.0\n", "same_47_48_and_2 = 0.0\n", "same_47_48_and_3 = 0.0\n", - "same_47_48_and_4 = 0.0\n", + "same_47_48_and_4 = 1.0\n", "same_47_48_and_5 = 0.0\n", "same_47_48_and_6 = 0.0\n", "same_47_48_and_7 = 0.0\n", @@ -154964,7 +154954,7 @@ "same_47_49 = 1.0\n", "same_47_49_and_0 = 0.0\n", "same_47_49_and_1 = 0.0\n", - "same_47_49_and_10 = 1.0\n", + "same_47_49_and_10 = 0.0\n", "same_47_49_and_11 = 0.0\n", "same_47_49_and_12 = 0.0\n", "same_47_49_and_13 = 0.0\n", @@ -154972,7 +154962,7 @@ "same_47_49_and_15 = 0.0\n", "same_47_49_and_2 = 0.0\n", "same_47_49_and_3 = 0.0\n", - "same_47_49_and_4 = 0.0\n", + "same_47_49_and_4 = 1.0\n", "same_47_49_and_5 = 0.0\n", "same_47_49_and_6 = 0.0\n", "same_47_49_and_7 = 0.0\n", @@ -154981,7 +154971,7 @@ "same_47_50 = 1.0\n", "same_47_50_and_0 = 0.0\n", "same_47_50_and_1 = 0.0\n", - "same_47_50_and_10 = 1.0\n", + "same_47_50_and_10 = 0.0\n", "same_47_50_and_11 = 0.0\n", "same_47_50_and_12 = 0.0\n", "same_47_50_and_13 = 0.0\n", @@ -154989,7 +154979,7 @@ "same_47_50_and_15 = 0.0\n", "same_47_50_and_2 = 0.0\n", "same_47_50_and_3 = 0.0\n", - "same_47_50_and_4 = 0.0\n", + "same_47_50_and_4 = 1.0\n", "same_47_50_and_5 = 0.0\n", "same_47_50_and_6 = 0.0\n", "same_47_50_and_7 = 0.0\n", @@ -154998,7 +154988,7 @@ "same_47_51 = 1.0\n", "same_47_51_and_0 = 0.0\n", "same_47_51_and_1 = 0.0\n", - "same_47_51_and_10 = 1.0\n", + "same_47_51_and_10 = 0.0\n", "same_47_51_and_11 = 0.0\n", "same_47_51_and_12 = 0.0\n", "same_47_51_and_13 = 0.0\n", @@ -155006,7 +154996,7 @@ "same_47_51_and_15 = 0.0\n", "same_47_51_and_2 = 0.0\n", "same_47_51_and_3 = 0.0\n", - "same_47_51_and_4 = 0.0\n", + "same_47_51_and_4 = 1.0\n", "same_47_51_and_5 = 0.0\n", "same_47_51_and_6 = 0.0\n", "same_47_51_and_7 = 0.0\n", @@ -155015,7 +155005,7 @@ "same_47_52 = 1.0\n", "same_47_52_and_0 = 0.0\n", "same_47_52_and_1 = 0.0\n", - "same_47_52_and_10 = 1.0\n", + "same_47_52_and_10 = 0.0\n", "same_47_52_and_11 = 0.0\n", "same_47_52_and_12 = 0.0\n", "same_47_52_and_13 = 0.0\n", @@ -155023,7 +155013,7 @@ "same_47_52_and_15 = 0.0\n", "same_47_52_and_2 = 0.0\n", "same_47_52_and_3 = 0.0\n", - "same_47_52_and_4 = 0.0\n", + "same_47_52_and_4 = 1.0\n", "same_47_52_and_5 = 0.0\n", "same_47_52_and_6 = 0.0\n", "same_47_52_and_7 = 0.0\n", @@ -155322,7 +155312,7 @@ "same_48_49 = 1.0\n", "same_48_49_and_0 = 0.0\n", "same_48_49_and_1 = 0.0\n", - "same_48_49_and_10 = 1.0\n", + "same_48_49_and_10 = 0.0\n", "same_48_49_and_11 = 0.0\n", "same_48_49_and_12 = 0.0\n", "same_48_49_and_13 = 0.0\n", @@ -155330,7 +155320,7 @@ "same_48_49_and_15 = 0.0\n", "same_48_49_and_2 = 0.0\n", "same_48_49_and_3 = 0.0\n", - "same_48_49_and_4 = 0.0\n", + "same_48_49_and_4 = 1.0\n", "same_48_49_and_5 = 0.0\n", "same_48_49_and_6 = 0.0\n", "same_48_49_and_7 = 0.0\n", @@ -155339,7 +155329,7 @@ "same_48_50 = 1.0\n", "same_48_50_and_0 = 0.0\n", "same_48_50_and_1 = 0.0\n", - "same_48_50_and_10 = 1.0\n", + "same_48_50_and_10 = 0.0\n", "same_48_50_and_11 = 0.0\n", "same_48_50_and_12 = 0.0\n", "same_48_50_and_13 = 0.0\n", @@ -155347,7 +155337,7 @@ "same_48_50_and_15 = 0.0\n", "same_48_50_and_2 = 0.0\n", "same_48_50_and_3 = 0.0\n", - "same_48_50_and_4 = 0.0\n", + "same_48_50_and_4 = 1.0\n", "same_48_50_and_5 = 0.0\n", "same_48_50_and_6 = 0.0\n", "same_48_50_and_7 = 0.0\n", @@ -155356,7 +155346,7 @@ "same_48_51 = 1.0\n", "same_48_51_and_0 = 0.0\n", "same_48_51_and_1 = 0.0\n", - "same_48_51_and_10 = 1.0\n", + "same_48_51_and_10 = 0.0\n", "same_48_51_and_11 = 0.0\n", "same_48_51_and_12 = 0.0\n", "same_48_51_and_13 = 0.0\n", @@ -155364,7 +155354,7 @@ "same_48_51_and_15 = 0.0\n", "same_48_51_and_2 = 0.0\n", "same_48_51_and_3 = 0.0\n", - "same_48_51_and_4 = 0.0\n", + "same_48_51_and_4 = 1.0\n", "same_48_51_and_5 = 0.0\n", "same_48_51_and_6 = 0.0\n", "same_48_51_and_7 = 0.0\n", @@ -155373,7 +155363,7 @@ "same_48_52 = 1.0\n", "same_48_52_and_0 = 0.0\n", "same_48_52_and_1 = 0.0\n", - "same_48_52_and_10 = 1.0\n", + "same_48_52_and_10 = 0.0\n", "same_48_52_and_11 = 0.0\n", "same_48_52_and_12 = 0.0\n", "same_48_52_and_13 = 0.0\n", @@ -155381,7 +155371,7 @@ "same_48_52_and_15 = 0.0\n", "same_48_52_and_2 = 0.0\n", "same_48_52_and_3 = 0.0\n", - "same_48_52_and_4 = 0.0\n", + "same_48_52_and_4 = 1.0\n", "same_48_52_and_5 = 0.0\n", "same_48_52_and_6 = 0.0\n", "same_48_52_and_7 = 0.0\n", @@ -155680,7 +155670,7 @@ "same_49_50 = 1.0\n", "same_49_50_and_0 = 0.0\n", "same_49_50_and_1 = 0.0\n", - "same_49_50_and_10 = 1.0\n", + "same_49_50_and_10 = 0.0\n", "same_49_50_and_11 = 0.0\n", "same_49_50_and_12 = 0.0\n", "same_49_50_and_13 = 0.0\n", @@ -155688,7 +155678,7 @@ "same_49_50_and_15 = 0.0\n", "same_49_50_and_2 = 0.0\n", "same_49_50_and_3 = 0.0\n", - "same_49_50_and_4 = 0.0\n", + "same_49_50_and_4 = 1.0\n", "same_49_50_and_5 = 0.0\n", "same_49_50_and_6 = 0.0\n", "same_49_50_and_7 = 0.0\n", @@ -155697,7 +155687,7 @@ "same_49_51 = 1.0\n", "same_49_51_and_0 = 0.0\n", "same_49_51_and_1 = 0.0\n", - "same_49_51_and_10 = 1.0\n", + "same_49_51_and_10 = 0.0\n", "same_49_51_and_11 = 0.0\n", "same_49_51_and_12 = 0.0\n", "same_49_51_and_13 = 0.0\n", @@ -155705,7 +155695,7 @@ "same_49_51_and_15 = 0.0\n", "same_49_51_and_2 = 0.0\n", "same_49_51_and_3 = 0.0\n", - "same_49_51_and_4 = 0.0\n", + "same_49_51_and_4 = 1.0\n", "same_49_51_and_5 = 0.0\n", "same_49_51_and_6 = 0.0\n", "same_49_51_and_7 = 0.0\n", @@ -155714,7 +155704,7 @@ "same_49_52 = 1.0\n", "same_49_52_and_0 = 0.0\n", "same_49_52_and_1 = 0.0\n", - "same_49_52_and_10 = 1.0\n", + "same_49_52_and_10 = 0.0\n", "same_49_52_and_11 = 0.0\n", "same_49_52_and_12 = 0.0\n", "same_49_52_and_13 = 0.0\n", @@ -155722,7 +155712,7 @@ "same_49_52_and_15 = 0.0\n", "same_49_52_and_2 = 0.0\n", "same_49_52_and_3 = 0.0\n", - "same_49_52_and_4 = 0.0\n", + "same_49_52_and_4 = 1.0\n", "same_49_52_and_5 = 0.0\n", "same_49_52_and_6 = 0.0\n", "same_49_52_and_7 = 0.0\n", @@ -156873,14 +156863,14 @@ "same_4_5_and_1 = 0.0\n", "same_4_5_and_10 = 0.0\n", "same_4_5_and_11 = 0.0\n", - "same_4_5_and_12 = 1.0\n", + "same_4_5_and_12 = 0.0\n", "same_4_5_and_13 = 0.0\n", "same_4_5_and_14 = 0.0\n", "same_4_5_and_15 = 0.0\n", "same_4_5_and_2 = 0.0\n", "same_4_5_and_3 = 0.0\n", "same_4_5_and_4 = 0.0\n", - "same_4_5_and_5 = 0.0\n", + "same_4_5_and_5 = 1.0\n", "same_4_5_and_6 = 0.0\n", "same_4_5_and_7 = 0.0\n", "same_4_5_and_8 = 0.0\n", @@ -157060,14 +157050,14 @@ "same_4_6_and_1 = 0.0\n", "same_4_6_and_10 = 0.0\n", "same_4_6_and_11 = 0.0\n", - "same_4_6_and_12 = 1.0\n", + "same_4_6_and_12 = 0.0\n", "same_4_6_and_13 = 0.0\n", "same_4_6_and_14 = 0.0\n", "same_4_6_and_15 = 0.0\n", "same_4_6_and_2 = 0.0\n", "same_4_6_and_3 = 0.0\n", "same_4_6_and_4 = 0.0\n", - "same_4_6_and_5 = 0.0\n", + "same_4_6_and_5 = 1.0\n", "same_4_6_and_6 = 0.0\n", "same_4_6_and_7 = 0.0\n", "same_4_6_and_8 = 0.0\n", @@ -157127,7 +157117,7 @@ "same_50_51 = 1.0\n", "same_50_51_and_0 = 0.0\n", "same_50_51_and_1 = 0.0\n", - "same_50_51_and_10 = 1.0\n", + "same_50_51_and_10 = 0.0\n", "same_50_51_and_11 = 0.0\n", "same_50_51_and_12 = 0.0\n", "same_50_51_and_13 = 0.0\n", @@ -157135,7 +157125,7 @@ "same_50_51_and_15 = 0.0\n", "same_50_51_and_2 = 0.0\n", "same_50_51_and_3 = 0.0\n", - "same_50_51_and_4 = 0.0\n", + "same_50_51_and_4 = 1.0\n", "same_50_51_and_5 = 0.0\n", "same_50_51_and_6 = 0.0\n", "same_50_51_and_7 = 0.0\n", @@ -157144,7 +157134,7 @@ "same_50_52 = 1.0\n", "same_50_52_and_0 = 0.0\n", "same_50_52_and_1 = 0.0\n", - "same_50_52_and_10 = 1.0\n", + "same_50_52_and_10 = 0.0\n", "same_50_52_and_11 = 0.0\n", "same_50_52_and_12 = 0.0\n", "same_50_52_and_13 = 0.0\n", @@ -157152,7 +157142,7 @@ "same_50_52_and_15 = 0.0\n", "same_50_52_and_2 = 0.0\n", "same_50_52_and_3 = 0.0\n", - "same_50_52_and_4 = 0.0\n", + "same_50_52_and_4 = 1.0\n", "same_50_52_and_5 = 0.0\n", "same_50_52_and_6 = 0.0\n", "same_50_52_and_7 = 0.0\n", @@ -157451,7 +157441,7 @@ "same_51_52 = 1.0\n", "same_51_52_and_0 = 0.0\n", "same_51_52_and_1 = 0.0\n", - "same_51_52_and_10 = 1.0\n", + "same_51_52_and_10 = 0.0\n", "same_51_52_and_11 = 0.0\n", "same_51_52_and_12 = 0.0\n", "same_51_52_and_13 = 0.0\n", @@ -157459,7 +157449,7 @@ "same_51_52_and_15 = 0.0\n", "same_51_52_and_2 = 0.0\n", "same_51_52_and_3 = 0.0\n", - "same_51_52_and_4 = 0.0\n", + "same_51_52_and_4 = 1.0\n", "same_51_52_and_5 = 0.0\n", "same_51_52_and_6 = 0.0\n", "same_51_52_and_7 = 0.0\n", @@ -158058,9 +158048,9 @@ "same_53_54_and_3 = 0.0\n", "same_53_54_and_4 = 0.0\n", "same_53_54_and_5 = 0.0\n", - "same_53_54_and_6 = 0.0\n", + "same_53_54_and_6 = 1.0\n", "same_53_54_and_7 = 0.0\n", - "same_53_54_and_8 = 1.0\n", + "same_53_54_and_8 = 0.0\n", "same_53_54_and_9 = 0.0\n", "same_53_55 = 1.0\n", "same_53_55_and_0 = 0.0\n", @@ -158075,11 +158065,11 @@ "same_53_55_and_3 = 0.0\n", "same_53_55_and_4 = 0.0\n", "same_53_55_and_5 = 0.0\n", - "same_53_55_and_6 = 0.0\n", + "same_53_55_and_6 = 1.0\n", "same_53_55_and_7 = 0.0\n", - "same_53_55_and_8 = 1.0\n", + "same_53_55_and_8 = 0.0\n", "same_53_55_and_9 = 0.0\n", - "same_53_56 = 0.0\n", + "same_53_56 = 1.0\n", "same_53_56_and_0 = 0.0\n", "same_53_56_and_1 = 0.0\n", "same_53_56_and_10 = 0.0\n", @@ -158092,11 +158082,11 @@ "same_53_56_and_3 = 0.0\n", "same_53_56_and_4 = 0.0\n", "same_53_56_and_5 = 0.0\n", - "same_53_56_and_6 = 0.0\n", + "same_53_56_and_6 = 1.0\n", "same_53_56_and_7 = 0.0\n", "same_53_56_and_8 = 0.0\n", "same_53_56_and_9 = 0.0\n", - "same_53_57 = 0.0\n", + "same_53_57 = 1.0\n", "same_53_57_and_0 = 0.0\n", "same_53_57_and_1 = 0.0\n", "same_53_57_and_10 = 0.0\n", @@ -158109,11 +158099,11 @@ "same_53_57_and_3 = 0.0\n", "same_53_57_and_4 = 0.0\n", "same_53_57_and_5 = 0.0\n", - "same_53_57_and_6 = 0.0\n", + "same_53_57_and_6 = 1.0\n", "same_53_57_and_7 = 0.0\n", "same_53_57_and_8 = 0.0\n", "same_53_57_and_9 = 0.0\n", - "same_53_58 = 0.0\n", + "same_53_58 = 1.0\n", "same_53_58_and_0 = 0.0\n", "same_53_58_and_1 = 0.0\n", "same_53_58_and_10 = 0.0\n", @@ -158126,11 +158116,11 @@ "same_53_58_and_3 = 0.0\n", "same_53_58_and_4 = 0.0\n", "same_53_58_and_5 = 0.0\n", - "same_53_58_and_6 = 0.0\n", + "same_53_58_and_6 = 1.0\n", "same_53_58_and_7 = 0.0\n", "same_53_58_and_8 = 0.0\n", "same_53_58_and_9 = 0.0\n", - "same_53_59 = 0.0\n", + "same_53_59 = 1.0\n", "same_53_59_and_0 = 0.0\n", "same_53_59_and_1 = 0.0\n", "same_53_59_and_10 = 0.0\n", @@ -158143,11 +158133,11 @@ "same_53_59_and_3 = 0.0\n", "same_53_59_and_4 = 0.0\n", "same_53_59_and_5 = 0.0\n", - "same_53_59_and_6 = 0.0\n", + "same_53_59_and_6 = 1.0\n", "same_53_59_and_7 = 0.0\n", "same_53_59_and_8 = 0.0\n", "same_53_59_and_9 = 0.0\n", - "same_53_60 = 0.0\n", + "same_53_60 = 1.0\n", "same_53_60_and_0 = 0.0\n", "same_53_60_and_1 = 0.0\n", "same_53_60_and_10 = 0.0\n", @@ -158160,11 +158150,11 @@ "same_53_60_and_3 = 0.0\n", "same_53_60_and_4 = 0.0\n", "same_53_60_and_5 = 0.0\n", - "same_53_60_and_6 = 0.0\n", + "same_53_60_and_6 = 1.0\n", "same_53_60_and_7 = 0.0\n", "same_53_60_and_8 = 0.0\n", "same_53_60_and_9 = 0.0\n", - "same_53_61 = 0.0\n", + "same_53_61 = 1.0\n", "same_53_61_and_0 = 0.0\n", "same_53_61_and_1 = 0.0\n", "same_53_61_and_10 = 0.0\n", @@ -158177,7 +158167,7 @@ "same_53_61_and_3 = 0.0\n", "same_53_61_and_4 = 0.0\n", "same_53_61_and_5 = 0.0\n", - "same_53_61_and_6 = 0.0\n", + "same_53_61_and_6 = 1.0\n", "same_53_61_and_7 = 0.0\n", "same_53_61_and_8 = 0.0\n", "same_53_61_and_9 = 0.0\n", @@ -158232,7 +158222,7 @@ "same_53_64_and_7 = 0.0\n", "same_53_64_and_8 = 0.0\n", "same_53_64_and_9 = 0.0\n", - "same_53_65 = 0.0\n", + "same_53_65 = 1.0\n", "same_53_65_and_0 = 0.0\n", "same_53_65_and_1 = 0.0\n", "same_53_65_and_10 = 0.0\n", @@ -158245,11 +158235,11 @@ "same_53_65_and_3 = 0.0\n", "same_53_65_and_4 = 0.0\n", "same_53_65_and_5 = 0.0\n", - "same_53_65_and_6 = 0.0\n", + "same_53_65_and_6 = 1.0\n", "same_53_65_and_7 = 0.0\n", "same_53_65_and_8 = 0.0\n", "same_53_65_and_9 = 0.0\n", - "same_53_66 = 0.0\n", + "same_53_66 = 1.0\n", "same_53_66_and_0 = 0.0\n", "same_53_66_and_1 = 0.0\n", "same_53_66_and_10 = 0.0\n", @@ -158262,11 +158252,11 @@ "same_53_66_and_3 = 0.0\n", "same_53_66_and_4 = 0.0\n", "same_53_66_and_5 = 0.0\n", - "same_53_66_and_6 = 0.0\n", + "same_53_66_and_6 = 1.0\n", "same_53_66_and_7 = 0.0\n", "same_53_66_and_8 = 0.0\n", "same_53_66_and_9 = 0.0\n", - "same_53_67 = 0.0\n", + "same_53_67 = 1.0\n", "same_53_67_and_0 = 0.0\n", "same_53_67_and_1 = 0.0\n", "same_53_67_and_10 = 0.0\n", @@ -158279,11 +158269,11 @@ "same_53_67_and_3 = 0.0\n", "same_53_67_and_4 = 0.0\n", "same_53_67_and_5 = 0.0\n", - "same_53_67_and_6 = 0.0\n", + "same_53_67_and_6 = 1.0\n", "same_53_67_and_7 = 0.0\n", "same_53_67_and_8 = 0.0\n", "same_53_67_and_9 = 0.0\n", - "same_53_68 = 0.0\n", + "same_53_68 = 1.0\n", "same_53_68_and_0 = 0.0\n", "same_53_68_and_1 = 0.0\n", "same_53_68_and_10 = 0.0\n", @@ -158296,11 +158286,11 @@ "same_53_68_and_3 = 0.0\n", "same_53_68_and_4 = 0.0\n", "same_53_68_and_5 = 0.0\n", - "same_53_68_and_6 = 0.0\n", + "same_53_68_and_6 = 1.0\n", "same_53_68_and_7 = 0.0\n", "same_53_68_and_8 = 0.0\n", "same_53_68_and_9 = 0.0\n", - "same_53_69 = 0.0\n", + "same_53_69 = 1.0\n", "same_53_69_and_0 = 0.0\n", "same_53_69_and_1 = 0.0\n", "same_53_69_and_10 = 0.0\n", @@ -158313,7 +158303,7 @@ "same_53_69_and_3 = 0.0\n", "same_53_69_and_4 = 0.0\n", "same_53_69_and_5 = 0.0\n", - "same_53_69_and_6 = 0.0\n", + "same_53_69_and_6 = 1.0\n", "same_53_69_and_7 = 0.0\n", "same_53_69_and_8 = 0.0\n", "same_53_69_and_9 = 0.0\n", @@ -158331,11 +158321,11 @@ "same_54_55_and_3 = 0.0\n", "same_54_55_and_4 = 0.0\n", "same_54_55_and_5 = 0.0\n", - "same_54_55_and_6 = 0.0\n", + "same_54_55_and_6 = 1.0\n", "same_54_55_and_7 = 0.0\n", - "same_54_55_and_8 = 1.0\n", + "same_54_55_and_8 = 0.0\n", "same_54_55_and_9 = 0.0\n", - "same_54_56 = 0.0\n", + "same_54_56 = 1.0\n", "same_54_56_and_0 = 0.0\n", "same_54_56_and_1 = 0.0\n", "same_54_56_and_10 = 0.0\n", @@ -158348,11 +158338,11 @@ "same_54_56_and_3 = 0.0\n", "same_54_56_and_4 = 0.0\n", "same_54_56_and_5 = 0.0\n", - "same_54_56_and_6 = 0.0\n", + "same_54_56_and_6 = 1.0\n", "same_54_56_and_7 = 0.0\n", "same_54_56_and_8 = 0.0\n", "same_54_56_and_9 = 0.0\n", - "same_54_57 = 0.0\n", + "same_54_57 = 1.0\n", "same_54_57_and_0 = 0.0\n", "same_54_57_and_1 = 0.0\n", "same_54_57_and_10 = 0.0\n", @@ -158365,11 +158355,11 @@ "same_54_57_and_3 = 0.0\n", "same_54_57_and_4 = 0.0\n", "same_54_57_and_5 = 0.0\n", - "same_54_57_and_6 = 0.0\n", + "same_54_57_and_6 = 1.0\n", "same_54_57_and_7 = 0.0\n", "same_54_57_and_8 = 0.0\n", "same_54_57_and_9 = 0.0\n", - "same_54_58 = 0.0\n", + "same_54_58 = 1.0\n", "same_54_58_and_0 = 0.0\n", "same_54_58_and_1 = 0.0\n", "same_54_58_and_10 = 0.0\n", @@ -158382,11 +158372,11 @@ "same_54_58_and_3 = 0.0\n", "same_54_58_and_4 = 0.0\n", "same_54_58_and_5 = 0.0\n", - "same_54_58_and_6 = 0.0\n", + "same_54_58_and_6 = 1.0\n", "same_54_58_and_7 = 0.0\n", "same_54_58_and_8 = 0.0\n", "same_54_58_and_9 = 0.0\n", - "same_54_59 = 0.0\n", + "same_54_59 = 1.0\n", "same_54_59_and_0 = 0.0\n", "same_54_59_and_1 = 0.0\n", "same_54_59_and_10 = 0.0\n", @@ -158399,11 +158389,11 @@ "same_54_59_and_3 = 0.0\n", "same_54_59_and_4 = 0.0\n", "same_54_59_and_5 = 0.0\n", - "same_54_59_and_6 = 0.0\n", + "same_54_59_and_6 = 1.0\n", "same_54_59_and_7 = 0.0\n", "same_54_59_and_8 = 0.0\n", "same_54_59_and_9 = 0.0\n", - "same_54_60 = 0.0\n", + "same_54_60 = 1.0\n", "same_54_60_and_0 = 0.0\n", "same_54_60_and_1 = 0.0\n", "same_54_60_and_10 = 0.0\n", @@ -158416,11 +158406,11 @@ "same_54_60_and_3 = 0.0\n", "same_54_60_and_4 = 0.0\n", "same_54_60_and_5 = 0.0\n", - "same_54_60_and_6 = 0.0\n", + "same_54_60_and_6 = 1.0\n", "same_54_60_and_7 = 0.0\n", "same_54_60_and_8 = 0.0\n", "same_54_60_and_9 = 0.0\n", - "same_54_61 = 0.0\n", + "same_54_61 = 1.0\n", "same_54_61_and_0 = 0.0\n", "same_54_61_and_1 = 0.0\n", "same_54_61_and_10 = 0.0\n", @@ -158433,7 +158423,7 @@ "same_54_61_and_3 = 0.0\n", "same_54_61_and_4 = 0.0\n", "same_54_61_and_5 = 0.0\n", - "same_54_61_and_6 = 0.0\n", + "same_54_61_and_6 = 1.0\n", "same_54_61_and_7 = 0.0\n", "same_54_61_and_8 = 0.0\n", "same_54_61_and_9 = 0.0\n", @@ -158488,7 +158478,7 @@ "same_54_64_and_7 = 0.0\n", "same_54_64_and_8 = 0.0\n", "same_54_64_and_9 = 0.0\n", - "same_54_65 = 0.0\n", + "same_54_65 = 1.0\n", "same_54_65_and_0 = 0.0\n", "same_54_65_and_1 = 0.0\n", "same_54_65_and_10 = 0.0\n", @@ -158501,11 +158491,11 @@ "same_54_65_and_3 = 0.0\n", "same_54_65_and_4 = 0.0\n", "same_54_65_and_5 = 0.0\n", - "same_54_65_and_6 = 0.0\n", + "same_54_65_and_6 = 1.0\n", "same_54_65_and_7 = 0.0\n", "same_54_65_and_8 = 0.0\n", "same_54_65_and_9 = 0.0\n", - "same_54_66 = 0.0\n", + "same_54_66 = 1.0\n", "same_54_66_and_0 = 0.0\n", "same_54_66_and_1 = 0.0\n", "same_54_66_and_10 = 0.0\n", @@ -158518,11 +158508,11 @@ "same_54_66_and_3 = 0.0\n", "same_54_66_and_4 = 0.0\n", "same_54_66_and_5 = 0.0\n", - "same_54_66_and_6 = 0.0\n", + "same_54_66_and_6 = 1.0\n", "same_54_66_and_7 = 0.0\n", "same_54_66_and_8 = 0.0\n", "same_54_66_and_9 = 0.0\n", - "same_54_67 = 0.0\n", + "same_54_67 = 1.0\n", "same_54_67_and_0 = 0.0\n", "same_54_67_and_1 = 0.0\n", "same_54_67_and_10 = 0.0\n", @@ -158535,11 +158525,11 @@ "same_54_67_and_3 = 0.0\n", "same_54_67_and_4 = 0.0\n", "same_54_67_and_5 = 0.0\n", - "same_54_67_and_6 = 0.0\n", + "same_54_67_and_6 = 1.0\n", "same_54_67_and_7 = 0.0\n", "same_54_67_and_8 = 0.0\n", "same_54_67_and_9 = 0.0\n", - "same_54_68 = 0.0\n", + "same_54_68 = 1.0\n", "same_54_68_and_0 = 0.0\n", "same_54_68_and_1 = 0.0\n", "same_54_68_and_10 = 0.0\n", @@ -158552,11 +158542,11 @@ "same_54_68_and_3 = 0.0\n", "same_54_68_and_4 = 0.0\n", "same_54_68_and_5 = 0.0\n", - "same_54_68_and_6 = 0.0\n", + "same_54_68_and_6 = 1.0\n", "same_54_68_and_7 = 0.0\n", "same_54_68_and_8 = 0.0\n", "same_54_68_and_9 = 0.0\n", - "same_54_69 = 0.0\n", + "same_54_69 = 1.0\n", "same_54_69_and_0 = 0.0\n", "same_54_69_and_1 = 0.0\n", "same_54_69_and_10 = 0.0\n", @@ -158569,12 +158559,12 @@ "same_54_69_and_3 = 0.0\n", "same_54_69_and_4 = 0.0\n", "same_54_69_and_5 = 0.0\n", - "same_54_69_and_6 = 0.0\n", + "same_54_69_and_6 = 1.0\n", "same_54_69_and_7 = 0.0\n", "same_54_69_and_8 = 0.0\n", "same_54_69_and_9 = 0.0\n", "same_55_55 = 1.0\n", - "same_55_56 = 0.0\n", + "same_55_56 = 1.0\n", "same_55_56_and_0 = 0.0\n", "same_55_56_and_1 = 0.0\n", "same_55_56_and_10 = 0.0\n", @@ -158587,11 +158577,11 @@ "same_55_56_and_3 = 0.0\n", "same_55_56_and_4 = 0.0\n", "same_55_56_and_5 = 0.0\n", - "same_55_56_and_6 = 0.0\n", + "same_55_56_and_6 = 1.0\n", "same_55_56_and_7 = 0.0\n", "same_55_56_and_8 = 0.0\n", "same_55_56_and_9 = 0.0\n", - "same_55_57 = 0.0\n", + "same_55_57 = 1.0\n", "same_55_57_and_0 = 0.0\n", "same_55_57_and_1 = 0.0\n", "same_55_57_and_10 = 0.0\n", @@ -158604,11 +158594,11 @@ "same_55_57_and_3 = 0.0\n", "same_55_57_and_4 = 0.0\n", "same_55_57_and_5 = 0.0\n", - "same_55_57_and_6 = 0.0\n", + "same_55_57_and_6 = 1.0\n", "same_55_57_and_7 = 0.0\n", "same_55_57_and_8 = 0.0\n", "same_55_57_and_9 = 0.0\n", - "same_55_58 = 0.0\n", + "same_55_58 = 1.0\n", "same_55_58_and_0 = 0.0\n", "same_55_58_and_1 = 0.0\n", "same_55_58_and_10 = 0.0\n", @@ -158621,11 +158611,11 @@ "same_55_58_and_3 = 0.0\n", "same_55_58_and_4 = 0.0\n", "same_55_58_and_5 = 0.0\n", - "same_55_58_and_6 = 0.0\n", + "same_55_58_and_6 = 1.0\n", "same_55_58_and_7 = 0.0\n", "same_55_58_and_8 = 0.0\n", "same_55_58_and_9 = 0.0\n", - "same_55_59 = 0.0\n", + "same_55_59 = 1.0\n", "same_55_59_and_0 = 0.0\n", "same_55_59_and_1 = 0.0\n", "same_55_59_and_10 = 0.0\n", @@ -158638,11 +158628,11 @@ "same_55_59_and_3 = 0.0\n", "same_55_59_and_4 = 0.0\n", "same_55_59_and_5 = 0.0\n", - "same_55_59_and_6 = 0.0\n", + "same_55_59_and_6 = 1.0\n", "same_55_59_and_7 = 0.0\n", "same_55_59_and_8 = 0.0\n", "same_55_59_and_9 = 0.0\n", - "same_55_60 = 0.0\n", + "same_55_60 = 1.0\n", "same_55_60_and_0 = 0.0\n", "same_55_60_and_1 = 0.0\n", "same_55_60_and_10 = 0.0\n", @@ -158655,11 +158645,11 @@ "same_55_60_and_3 = 0.0\n", "same_55_60_and_4 = 0.0\n", "same_55_60_and_5 = 0.0\n", - "same_55_60_and_6 = 0.0\n", + "same_55_60_and_6 = 1.0\n", "same_55_60_and_7 = 0.0\n", "same_55_60_and_8 = 0.0\n", "same_55_60_and_9 = 0.0\n", - "same_55_61 = 0.0\n", + "same_55_61 = 1.0\n", "same_55_61_and_0 = 0.0\n", "same_55_61_and_1 = 0.0\n", "same_55_61_and_10 = 0.0\n", @@ -158672,7 +158662,7 @@ "same_55_61_and_3 = 0.0\n", "same_55_61_and_4 = 0.0\n", "same_55_61_and_5 = 0.0\n", - "same_55_61_and_6 = 0.0\n", + "same_55_61_and_6 = 1.0\n", "same_55_61_and_7 = 0.0\n", "same_55_61_and_8 = 0.0\n", "same_55_61_and_9 = 0.0\n", @@ -158727,7 +158717,7 @@ "same_55_64_and_7 = 0.0\n", "same_55_64_and_8 = 0.0\n", "same_55_64_and_9 = 0.0\n", - "same_55_65 = 0.0\n", + "same_55_65 = 1.0\n", "same_55_65_and_0 = 0.0\n", "same_55_65_and_1 = 0.0\n", "same_55_65_and_10 = 0.0\n", @@ -158740,11 +158730,11 @@ "same_55_65_and_3 = 0.0\n", "same_55_65_and_4 = 0.0\n", "same_55_65_and_5 = 0.0\n", - "same_55_65_and_6 = 0.0\n", + "same_55_65_and_6 = 1.0\n", "same_55_65_and_7 = 0.0\n", "same_55_65_and_8 = 0.0\n", "same_55_65_and_9 = 0.0\n", - "same_55_66 = 0.0\n", + "same_55_66 = 1.0\n", "same_55_66_and_0 = 0.0\n", "same_55_66_and_1 = 0.0\n", "same_55_66_and_10 = 0.0\n", @@ -158757,11 +158747,11 @@ "same_55_66_and_3 = 0.0\n", "same_55_66_and_4 = 0.0\n", "same_55_66_and_5 = 0.0\n", - "same_55_66_and_6 = 0.0\n", + "same_55_66_and_6 = 1.0\n", "same_55_66_and_7 = 0.0\n", "same_55_66_and_8 = 0.0\n", "same_55_66_and_9 = 0.0\n", - "same_55_67 = 0.0\n", + "same_55_67 = 1.0\n", "same_55_67_and_0 = 0.0\n", "same_55_67_and_1 = 0.0\n", "same_55_67_and_10 = 0.0\n", @@ -158774,11 +158764,11 @@ "same_55_67_and_3 = 0.0\n", "same_55_67_and_4 = 0.0\n", "same_55_67_and_5 = 0.0\n", - "same_55_67_and_6 = 0.0\n", + "same_55_67_and_6 = 1.0\n", "same_55_67_and_7 = 0.0\n", "same_55_67_and_8 = 0.0\n", "same_55_67_and_9 = 0.0\n", - "same_55_68 = 0.0\n", + "same_55_68 = 1.0\n", "same_55_68_and_0 = 0.0\n", "same_55_68_and_1 = 0.0\n", "same_55_68_and_10 = 0.0\n", @@ -158791,11 +158781,11 @@ "same_55_68_and_3 = 0.0\n", "same_55_68_and_4 = 0.0\n", "same_55_68_and_5 = 0.0\n", - "same_55_68_and_6 = 0.0\n", + "same_55_68_and_6 = 1.0\n", "same_55_68_and_7 = 0.0\n", "same_55_68_and_8 = 0.0\n", "same_55_68_and_9 = 0.0\n", - "same_55_69 = 0.0\n", + "same_55_69 = 1.0\n", "same_55_69_and_0 = 0.0\n", "same_55_69_and_1 = 0.0\n", "same_55_69_and_10 = 0.0\n", @@ -158808,7 +158798,7 @@ "same_55_69_and_3 = 0.0\n", "same_55_69_and_4 = 0.0\n", "same_55_69_and_5 = 0.0\n", - "same_55_69_and_6 = 0.0\n", + "same_55_69_and_6 = 1.0\n", "same_55_69_and_7 = 0.0\n", "same_55_69_and_8 = 0.0\n", "same_55_69_and_9 = 0.0\n", @@ -158821,12 +158811,12 @@ "same_56_57_and_12 = 0.0\n", "same_56_57_and_13 = 0.0\n", "same_56_57_and_14 = 0.0\n", - "same_56_57_and_15 = 1.0\n", + "same_56_57_and_15 = 0.0\n", "same_56_57_and_2 = 0.0\n", "same_56_57_and_3 = 0.0\n", "same_56_57_and_4 = 0.0\n", "same_56_57_and_5 = 0.0\n", - "same_56_57_and_6 = 0.0\n", + "same_56_57_and_6 = 1.0\n", "same_56_57_and_7 = 0.0\n", "same_56_57_and_8 = 0.0\n", "same_56_57_and_9 = 0.0\n", @@ -158838,12 +158828,12 @@ "same_56_58_and_12 = 0.0\n", "same_56_58_and_13 = 0.0\n", "same_56_58_and_14 = 0.0\n", - "same_56_58_and_15 = 1.0\n", + "same_56_58_and_15 = 0.0\n", "same_56_58_and_2 = 0.0\n", "same_56_58_and_3 = 0.0\n", "same_56_58_and_4 = 0.0\n", "same_56_58_and_5 = 0.0\n", - "same_56_58_and_6 = 0.0\n", + "same_56_58_and_6 = 1.0\n", "same_56_58_and_7 = 0.0\n", "same_56_58_and_8 = 0.0\n", "same_56_58_and_9 = 0.0\n", @@ -158855,12 +158845,12 @@ "same_56_59_and_12 = 0.0\n", "same_56_59_and_13 = 0.0\n", "same_56_59_and_14 = 0.0\n", - "same_56_59_and_15 = 1.0\n", + "same_56_59_and_15 = 0.0\n", "same_56_59_and_2 = 0.0\n", "same_56_59_and_3 = 0.0\n", "same_56_59_and_4 = 0.0\n", "same_56_59_and_5 = 0.0\n", - "same_56_59_and_6 = 0.0\n", + "same_56_59_and_6 = 1.0\n", "same_56_59_and_7 = 0.0\n", "same_56_59_and_8 = 0.0\n", "same_56_59_and_9 = 0.0\n", @@ -158872,12 +158862,12 @@ "same_56_60_and_12 = 0.0\n", "same_56_60_and_13 = 0.0\n", "same_56_60_and_14 = 0.0\n", - "same_56_60_and_15 = 1.0\n", + "same_56_60_and_15 = 0.0\n", "same_56_60_and_2 = 0.0\n", "same_56_60_and_3 = 0.0\n", "same_56_60_and_4 = 0.0\n", "same_56_60_and_5 = 0.0\n", - "same_56_60_and_6 = 0.0\n", + "same_56_60_and_6 = 1.0\n", "same_56_60_and_7 = 0.0\n", "same_56_60_and_8 = 0.0\n", "same_56_60_and_9 = 0.0\n", @@ -158889,16 +158879,16 @@ "same_56_61_and_12 = 0.0\n", "same_56_61_and_13 = 0.0\n", "same_56_61_and_14 = 0.0\n", - "same_56_61_and_15 = 1.0\n", + "same_56_61_and_15 = 0.0\n", "same_56_61_and_2 = 0.0\n", "same_56_61_and_3 = 0.0\n", "same_56_61_and_4 = 0.0\n", "same_56_61_and_5 = 0.0\n", - "same_56_61_and_6 = 0.0\n", + "same_56_61_and_6 = 1.0\n", "same_56_61_and_7 = 0.0\n", "same_56_61_and_8 = 0.0\n", "same_56_61_and_9 = 0.0\n", - "same_56_62 = 1.0\n", + "same_56_62 = 0.0\n", "same_56_62_and_0 = 0.0\n", "same_56_62_and_1 = 0.0\n", "same_56_62_and_10 = 0.0\n", @@ -158906,7 +158896,7 @@ "same_56_62_and_12 = 0.0\n", "same_56_62_and_13 = 0.0\n", "same_56_62_and_14 = 0.0\n", - "same_56_62_and_15 = 1.0\n", + "same_56_62_and_15 = 0.0\n", "same_56_62_and_2 = 0.0\n", "same_56_62_and_3 = 0.0\n", "same_56_62_and_4 = 0.0\n", @@ -158915,7 +158905,7 @@ "same_56_62_and_7 = 0.0\n", "same_56_62_and_8 = 0.0\n", "same_56_62_and_9 = 0.0\n", - "same_56_63 = 1.0\n", + "same_56_63 = 0.0\n", "same_56_63_and_0 = 0.0\n", "same_56_63_and_1 = 0.0\n", "same_56_63_and_10 = 0.0\n", @@ -158923,7 +158913,7 @@ "same_56_63_and_12 = 0.0\n", "same_56_63_and_13 = 0.0\n", "same_56_63_and_14 = 0.0\n", - "same_56_63_and_15 = 1.0\n", + "same_56_63_and_15 = 0.0\n", "same_56_63_and_2 = 0.0\n", "same_56_63_and_3 = 0.0\n", "same_56_63_and_4 = 0.0\n", @@ -158932,7 +158922,7 @@ "same_56_63_and_7 = 0.0\n", "same_56_63_and_8 = 0.0\n", "same_56_63_and_9 = 0.0\n", - "same_56_64 = 1.0\n", + "same_56_64 = 0.0\n", "same_56_64_and_0 = 0.0\n", "same_56_64_and_1 = 0.0\n", "same_56_64_and_10 = 0.0\n", @@ -158940,7 +158930,7 @@ "same_56_64_and_12 = 0.0\n", "same_56_64_and_13 = 0.0\n", "same_56_64_and_14 = 0.0\n", - "same_56_64_and_15 = 1.0\n", + "same_56_64_and_15 = 0.0\n", "same_56_64_and_2 = 0.0\n", "same_56_64_and_3 = 0.0\n", "same_56_64_and_4 = 0.0\n", @@ -158957,12 +158947,12 @@ "same_56_65_and_12 = 0.0\n", "same_56_65_and_13 = 0.0\n", "same_56_65_and_14 = 0.0\n", - "same_56_65_and_15 = 1.0\n", + "same_56_65_and_15 = 0.0\n", "same_56_65_and_2 = 0.0\n", "same_56_65_and_3 = 0.0\n", "same_56_65_and_4 = 0.0\n", "same_56_65_and_5 = 0.0\n", - "same_56_65_and_6 = 0.0\n", + "same_56_65_and_6 = 1.0\n", "same_56_65_and_7 = 0.0\n", "same_56_65_and_8 = 0.0\n", "same_56_65_and_9 = 0.0\n", @@ -158974,12 +158964,12 @@ "same_56_66_and_12 = 0.0\n", "same_56_66_and_13 = 0.0\n", "same_56_66_and_14 = 0.0\n", - "same_56_66_and_15 = 1.0\n", + "same_56_66_and_15 = 0.0\n", "same_56_66_and_2 = 0.0\n", "same_56_66_and_3 = 0.0\n", "same_56_66_and_4 = 0.0\n", "same_56_66_and_5 = 0.0\n", - "same_56_66_and_6 = 0.0\n", + "same_56_66_and_6 = 1.0\n", "same_56_66_and_7 = 0.0\n", "same_56_66_and_8 = 0.0\n", "same_56_66_and_9 = 0.0\n", @@ -158991,12 +158981,12 @@ "same_56_67_and_12 = 0.0\n", "same_56_67_and_13 = 0.0\n", "same_56_67_and_14 = 0.0\n", - "same_56_67_and_15 = 1.0\n", + "same_56_67_and_15 = 0.0\n", "same_56_67_and_2 = 0.0\n", "same_56_67_and_3 = 0.0\n", "same_56_67_and_4 = 0.0\n", "same_56_67_and_5 = 0.0\n", - "same_56_67_and_6 = 0.0\n", + "same_56_67_and_6 = 1.0\n", "same_56_67_and_7 = 0.0\n", "same_56_67_and_8 = 0.0\n", "same_56_67_and_9 = 0.0\n", @@ -159008,12 +158998,12 @@ "same_56_68_and_12 = 0.0\n", "same_56_68_and_13 = 0.0\n", "same_56_68_and_14 = 0.0\n", - "same_56_68_and_15 = 1.0\n", + "same_56_68_and_15 = 0.0\n", "same_56_68_and_2 = 0.0\n", "same_56_68_and_3 = 0.0\n", "same_56_68_and_4 = 0.0\n", "same_56_68_and_5 = 0.0\n", - "same_56_68_and_6 = 0.0\n", + "same_56_68_and_6 = 1.0\n", "same_56_68_and_7 = 0.0\n", "same_56_68_and_8 = 0.0\n", "same_56_68_and_9 = 0.0\n", @@ -159025,12 +159015,12 @@ "same_56_69_and_12 = 0.0\n", "same_56_69_and_13 = 0.0\n", "same_56_69_and_14 = 0.0\n", - "same_56_69_and_15 = 1.0\n", + "same_56_69_and_15 = 0.0\n", "same_56_69_and_2 = 0.0\n", "same_56_69_and_3 = 0.0\n", "same_56_69_and_4 = 0.0\n", "same_56_69_and_5 = 0.0\n", - "same_56_69_and_6 = 0.0\n", + "same_56_69_and_6 = 1.0\n", "same_56_69_and_7 = 0.0\n", "same_56_69_and_8 = 0.0\n", "same_56_69_and_9 = 0.0\n", @@ -159043,12 +159033,12 @@ "same_57_58_and_12 = 0.0\n", "same_57_58_and_13 = 0.0\n", "same_57_58_and_14 = 0.0\n", - "same_57_58_and_15 = 1.0\n", + "same_57_58_and_15 = 0.0\n", "same_57_58_and_2 = 0.0\n", "same_57_58_and_3 = 0.0\n", "same_57_58_and_4 = 0.0\n", "same_57_58_and_5 = 0.0\n", - "same_57_58_and_6 = 0.0\n", + "same_57_58_and_6 = 1.0\n", "same_57_58_and_7 = 0.0\n", "same_57_58_and_8 = 0.0\n", "same_57_58_and_9 = 0.0\n", @@ -159060,12 +159050,12 @@ "same_57_59_and_12 = 0.0\n", "same_57_59_and_13 = 0.0\n", "same_57_59_and_14 = 0.0\n", - "same_57_59_and_15 = 1.0\n", + "same_57_59_and_15 = 0.0\n", "same_57_59_and_2 = 0.0\n", "same_57_59_and_3 = 0.0\n", "same_57_59_and_4 = 0.0\n", "same_57_59_and_5 = 0.0\n", - "same_57_59_and_6 = 0.0\n", + "same_57_59_and_6 = 1.0\n", "same_57_59_and_7 = 0.0\n", "same_57_59_and_8 = 0.0\n", "same_57_59_and_9 = 0.0\n", @@ -159077,12 +159067,12 @@ "same_57_60_and_12 = 0.0\n", "same_57_60_and_13 = 0.0\n", "same_57_60_and_14 = 0.0\n", - "same_57_60_and_15 = 1.0\n", + "same_57_60_and_15 = 0.0\n", "same_57_60_and_2 = 0.0\n", "same_57_60_and_3 = 0.0\n", "same_57_60_and_4 = 0.0\n", "same_57_60_and_5 = 0.0\n", - "same_57_60_and_6 = 0.0\n", + "same_57_60_and_6 = 1.0\n", "same_57_60_and_7 = 0.0\n", "same_57_60_and_8 = 0.0\n", "same_57_60_and_9 = 0.0\n", @@ -159094,16 +159084,16 @@ "same_57_61_and_12 = 0.0\n", "same_57_61_and_13 = 0.0\n", "same_57_61_and_14 = 0.0\n", - "same_57_61_and_15 = 1.0\n", + "same_57_61_and_15 = 0.0\n", "same_57_61_and_2 = 0.0\n", "same_57_61_and_3 = 0.0\n", "same_57_61_and_4 = 0.0\n", "same_57_61_and_5 = 0.0\n", - "same_57_61_and_6 = 0.0\n", + "same_57_61_and_6 = 1.0\n", "same_57_61_and_7 = 0.0\n", "same_57_61_and_8 = 0.0\n", "same_57_61_and_9 = 0.0\n", - "same_57_62 = 1.0\n", + "same_57_62 = 0.0\n", "same_57_62_and_0 = 0.0\n", "same_57_62_and_1 = 0.0\n", "same_57_62_and_10 = 0.0\n", @@ -159111,7 +159101,7 @@ "same_57_62_and_12 = 0.0\n", "same_57_62_and_13 = 0.0\n", "same_57_62_and_14 = 0.0\n", - "same_57_62_and_15 = 1.0\n", + "same_57_62_and_15 = 0.0\n", "same_57_62_and_2 = 0.0\n", "same_57_62_and_3 = 0.0\n", "same_57_62_and_4 = 0.0\n", @@ -159120,7 +159110,7 @@ "same_57_62_and_7 = 0.0\n", "same_57_62_and_8 = 0.0\n", "same_57_62_and_9 = 0.0\n", - "same_57_63 = 1.0\n", + "same_57_63 = 0.0\n", "same_57_63_and_0 = 0.0\n", "same_57_63_and_1 = 0.0\n", "same_57_63_and_10 = 0.0\n", @@ -159128,7 +159118,7 @@ "same_57_63_and_12 = 0.0\n", "same_57_63_and_13 = 0.0\n", "same_57_63_and_14 = 0.0\n", - "same_57_63_and_15 = 1.0\n", + "same_57_63_and_15 = 0.0\n", "same_57_63_and_2 = 0.0\n", "same_57_63_and_3 = 0.0\n", "same_57_63_and_4 = 0.0\n", @@ -159137,7 +159127,7 @@ "same_57_63_and_7 = 0.0\n", "same_57_63_and_8 = 0.0\n", "same_57_63_and_9 = 0.0\n", - "same_57_64 = 1.0\n", + "same_57_64 = 0.0\n", "same_57_64_and_0 = 0.0\n", "same_57_64_and_1 = 0.0\n", "same_57_64_and_10 = 0.0\n", @@ -159145,7 +159135,7 @@ "same_57_64_and_12 = 0.0\n", "same_57_64_and_13 = 0.0\n", "same_57_64_and_14 = 0.0\n", - "same_57_64_and_15 = 1.0\n", + "same_57_64_and_15 = 0.0\n", "same_57_64_and_2 = 0.0\n", "same_57_64_and_3 = 0.0\n", "same_57_64_and_4 = 0.0\n", @@ -159162,12 +159152,12 @@ "same_57_65_and_12 = 0.0\n", "same_57_65_and_13 = 0.0\n", "same_57_65_and_14 = 0.0\n", - "same_57_65_and_15 = 1.0\n", + "same_57_65_and_15 = 0.0\n", "same_57_65_and_2 = 0.0\n", "same_57_65_and_3 = 0.0\n", "same_57_65_and_4 = 0.0\n", "same_57_65_and_5 = 0.0\n", - "same_57_65_and_6 = 0.0\n", + "same_57_65_and_6 = 1.0\n", "same_57_65_and_7 = 0.0\n", "same_57_65_and_8 = 0.0\n", "same_57_65_and_9 = 0.0\n", @@ -159179,12 +159169,12 @@ "same_57_66_and_12 = 0.0\n", "same_57_66_and_13 = 0.0\n", "same_57_66_and_14 = 0.0\n", - "same_57_66_and_15 = 1.0\n", + "same_57_66_and_15 = 0.0\n", "same_57_66_and_2 = 0.0\n", "same_57_66_and_3 = 0.0\n", "same_57_66_and_4 = 0.0\n", "same_57_66_and_5 = 0.0\n", - "same_57_66_and_6 = 0.0\n", + "same_57_66_and_6 = 1.0\n", "same_57_66_and_7 = 0.0\n", "same_57_66_and_8 = 0.0\n", "same_57_66_and_9 = 0.0\n", @@ -159196,12 +159186,12 @@ "same_57_67_and_12 = 0.0\n", "same_57_67_and_13 = 0.0\n", "same_57_67_and_14 = 0.0\n", - "same_57_67_and_15 = 1.0\n", + "same_57_67_and_15 = 0.0\n", "same_57_67_and_2 = 0.0\n", "same_57_67_and_3 = 0.0\n", "same_57_67_and_4 = 0.0\n", "same_57_67_and_5 = 0.0\n", - "same_57_67_and_6 = 0.0\n", + "same_57_67_and_6 = 1.0\n", "same_57_67_and_7 = 0.0\n", "same_57_67_and_8 = 0.0\n", "same_57_67_and_9 = 0.0\n", @@ -159213,12 +159203,12 @@ "same_57_68_and_12 = 0.0\n", "same_57_68_and_13 = 0.0\n", "same_57_68_and_14 = 0.0\n", - "same_57_68_and_15 = 1.0\n", + "same_57_68_and_15 = 0.0\n", "same_57_68_and_2 = 0.0\n", "same_57_68_and_3 = 0.0\n", "same_57_68_and_4 = 0.0\n", "same_57_68_and_5 = 0.0\n", - "same_57_68_and_6 = 0.0\n", + "same_57_68_and_6 = 1.0\n", "same_57_68_and_7 = 0.0\n", "same_57_68_and_8 = 0.0\n", "same_57_68_and_9 = 0.0\n", @@ -159230,12 +159220,12 @@ "same_57_69_and_12 = 0.0\n", "same_57_69_and_13 = 0.0\n", "same_57_69_and_14 = 0.0\n", - "same_57_69_and_15 = 1.0\n", + "same_57_69_and_15 = 0.0\n", "same_57_69_and_2 = 0.0\n", "same_57_69_and_3 = 0.0\n", "same_57_69_and_4 = 0.0\n", "same_57_69_and_5 = 0.0\n", - "same_57_69_and_6 = 0.0\n", + "same_57_69_and_6 = 1.0\n", "same_57_69_and_7 = 0.0\n", "same_57_69_and_8 = 0.0\n", "same_57_69_and_9 = 0.0\n", @@ -159248,12 +159238,12 @@ "same_58_59_and_12 = 0.0\n", "same_58_59_and_13 = 0.0\n", "same_58_59_and_14 = 0.0\n", - "same_58_59_and_15 = 1.0\n", + "same_58_59_and_15 = 0.0\n", "same_58_59_and_2 = 0.0\n", "same_58_59_and_3 = 0.0\n", "same_58_59_and_4 = 0.0\n", "same_58_59_and_5 = 0.0\n", - "same_58_59_and_6 = 0.0\n", + "same_58_59_and_6 = 1.0\n", "same_58_59_and_7 = 0.0\n", "same_58_59_and_8 = 0.0\n", "same_58_59_and_9 = 0.0\n", @@ -159265,12 +159255,12 @@ "same_58_60_and_12 = 0.0\n", "same_58_60_and_13 = 0.0\n", "same_58_60_and_14 = 0.0\n", - "same_58_60_and_15 = 1.0\n", + "same_58_60_and_15 = 0.0\n", "same_58_60_and_2 = 0.0\n", "same_58_60_and_3 = 0.0\n", "same_58_60_and_4 = 0.0\n", "same_58_60_and_5 = 0.0\n", - "same_58_60_and_6 = 0.0\n", + "same_58_60_and_6 = 1.0\n", "same_58_60_and_7 = 0.0\n", "same_58_60_and_8 = 0.0\n", "same_58_60_and_9 = 0.0\n", @@ -159282,16 +159272,16 @@ "same_58_61_and_12 = 0.0\n", "same_58_61_and_13 = 0.0\n", "same_58_61_and_14 = 0.0\n", - "same_58_61_and_15 = 1.0\n", + "same_58_61_and_15 = 0.0\n", "same_58_61_and_2 = 0.0\n", "same_58_61_and_3 = 0.0\n", "same_58_61_and_4 = 0.0\n", "same_58_61_and_5 = 0.0\n", - "same_58_61_and_6 = 0.0\n", + "same_58_61_and_6 = 1.0\n", "same_58_61_and_7 = 0.0\n", "same_58_61_and_8 = 0.0\n", "same_58_61_and_9 = 0.0\n", - "same_58_62 = 1.0\n", + "same_58_62 = 0.0\n", "same_58_62_and_0 = 0.0\n", "same_58_62_and_1 = 0.0\n", "same_58_62_and_10 = 0.0\n", @@ -159299,7 +159289,7 @@ "same_58_62_and_12 = 0.0\n", "same_58_62_and_13 = 0.0\n", "same_58_62_and_14 = 0.0\n", - "same_58_62_and_15 = 1.0\n", + "same_58_62_and_15 = 0.0\n", "same_58_62_and_2 = 0.0\n", "same_58_62_and_3 = 0.0\n", "same_58_62_and_4 = 0.0\n", @@ -159308,7 +159298,7 @@ "same_58_62_and_7 = 0.0\n", "same_58_62_and_8 = 0.0\n", "same_58_62_and_9 = 0.0\n", - "same_58_63 = 1.0\n", + "same_58_63 = 0.0\n", "same_58_63_and_0 = 0.0\n", "same_58_63_and_1 = 0.0\n", "same_58_63_and_10 = 0.0\n", @@ -159316,7 +159306,7 @@ "same_58_63_and_12 = 0.0\n", "same_58_63_and_13 = 0.0\n", "same_58_63_and_14 = 0.0\n", - "same_58_63_and_15 = 1.0\n", + "same_58_63_and_15 = 0.0\n", "same_58_63_and_2 = 0.0\n", "same_58_63_and_3 = 0.0\n", "same_58_63_and_4 = 0.0\n", @@ -159325,7 +159315,7 @@ "same_58_63_and_7 = 0.0\n", "same_58_63_and_8 = 0.0\n", "same_58_63_and_9 = 0.0\n", - "same_58_64 = 1.0\n", + "same_58_64 = 0.0\n", "same_58_64_and_0 = 0.0\n", "same_58_64_and_1 = 0.0\n", "same_58_64_and_10 = 0.0\n", @@ -159333,7 +159323,7 @@ "same_58_64_and_12 = 0.0\n", "same_58_64_and_13 = 0.0\n", "same_58_64_and_14 = 0.0\n", - "same_58_64_and_15 = 1.0\n", + "same_58_64_and_15 = 0.0\n", "same_58_64_and_2 = 0.0\n", "same_58_64_and_3 = 0.0\n", "same_58_64_and_4 = 0.0\n", @@ -159350,12 +159340,12 @@ "same_58_65_and_12 = 0.0\n", "same_58_65_and_13 = 0.0\n", "same_58_65_and_14 = 0.0\n", - "same_58_65_and_15 = 1.0\n", + "same_58_65_and_15 = 0.0\n", "same_58_65_and_2 = 0.0\n", "same_58_65_and_3 = 0.0\n", "same_58_65_and_4 = 0.0\n", "same_58_65_and_5 = 0.0\n", - "same_58_65_and_6 = 0.0\n", + "same_58_65_and_6 = 1.0\n", "same_58_65_and_7 = 0.0\n", "same_58_65_and_8 = 0.0\n", "same_58_65_and_9 = 0.0\n", @@ -159367,12 +159357,12 @@ "same_58_66_and_12 = 0.0\n", "same_58_66_and_13 = 0.0\n", "same_58_66_and_14 = 0.0\n", - "same_58_66_and_15 = 1.0\n", + "same_58_66_and_15 = 0.0\n", "same_58_66_and_2 = 0.0\n", "same_58_66_and_3 = 0.0\n", "same_58_66_and_4 = 0.0\n", "same_58_66_and_5 = 0.0\n", - "same_58_66_and_6 = 0.0\n", + "same_58_66_and_6 = 1.0\n", "same_58_66_and_7 = 0.0\n", "same_58_66_and_8 = 0.0\n", "same_58_66_and_9 = 0.0\n", @@ -159384,12 +159374,12 @@ "same_58_67_and_12 = 0.0\n", "same_58_67_and_13 = 0.0\n", "same_58_67_and_14 = 0.0\n", - "same_58_67_and_15 = 1.0\n", + "same_58_67_and_15 = 0.0\n", "same_58_67_and_2 = 0.0\n", "same_58_67_and_3 = 0.0\n", "same_58_67_and_4 = 0.0\n", "same_58_67_and_5 = 0.0\n", - "same_58_67_and_6 = 0.0\n", + "same_58_67_and_6 = 1.0\n", "same_58_67_and_7 = 0.0\n", "same_58_67_and_8 = 0.0\n", "same_58_67_and_9 = 0.0\n", @@ -159401,12 +159391,12 @@ "same_58_68_and_12 = 0.0\n", "same_58_68_and_13 = 0.0\n", "same_58_68_and_14 = 0.0\n", - "same_58_68_and_15 = 1.0\n", + "same_58_68_and_15 = 0.0\n", "same_58_68_and_2 = 0.0\n", "same_58_68_and_3 = 0.0\n", "same_58_68_and_4 = 0.0\n", "same_58_68_and_5 = 0.0\n", - "same_58_68_and_6 = 0.0\n", + "same_58_68_and_6 = 1.0\n", "same_58_68_and_7 = 0.0\n", "same_58_68_and_8 = 0.0\n", "same_58_68_and_9 = 0.0\n", @@ -159418,12 +159408,12 @@ "same_58_69_and_12 = 0.0\n", "same_58_69_and_13 = 0.0\n", "same_58_69_and_14 = 0.0\n", - "same_58_69_and_15 = 1.0\n", + "same_58_69_and_15 = 0.0\n", "same_58_69_and_2 = 0.0\n", "same_58_69_and_3 = 0.0\n", "same_58_69_and_4 = 0.0\n", "same_58_69_and_5 = 0.0\n", - "same_58_69_and_6 = 0.0\n", + "same_58_69_and_6 = 1.0\n", "same_58_69_and_7 = 0.0\n", "same_58_69_and_8 = 0.0\n", "same_58_69_and_9 = 0.0\n", @@ -159436,12 +159426,12 @@ "same_59_60_and_12 = 0.0\n", "same_59_60_and_13 = 0.0\n", "same_59_60_and_14 = 0.0\n", - "same_59_60_and_15 = 1.0\n", + "same_59_60_and_15 = 0.0\n", "same_59_60_and_2 = 0.0\n", "same_59_60_and_3 = 0.0\n", "same_59_60_and_4 = 0.0\n", "same_59_60_and_5 = 0.0\n", - "same_59_60_and_6 = 0.0\n", + "same_59_60_and_6 = 1.0\n", "same_59_60_and_7 = 0.0\n", "same_59_60_and_8 = 0.0\n", "same_59_60_and_9 = 0.0\n", @@ -159453,16 +159443,16 @@ "same_59_61_and_12 = 0.0\n", "same_59_61_and_13 = 0.0\n", "same_59_61_and_14 = 0.0\n", - "same_59_61_and_15 = 1.0\n", + "same_59_61_and_15 = 0.0\n", "same_59_61_and_2 = 0.0\n", "same_59_61_and_3 = 0.0\n", "same_59_61_and_4 = 0.0\n", "same_59_61_and_5 = 0.0\n", - "same_59_61_and_6 = 0.0\n", + "same_59_61_and_6 = 1.0\n", "same_59_61_and_7 = 0.0\n", "same_59_61_and_8 = 0.0\n", "same_59_61_and_9 = 0.0\n", - "same_59_62 = 1.0\n", + "same_59_62 = 0.0\n", "same_59_62_and_0 = 0.0\n", "same_59_62_and_1 = 0.0\n", "same_59_62_and_10 = 0.0\n", @@ -159470,7 +159460,7 @@ "same_59_62_and_12 = 0.0\n", "same_59_62_and_13 = 0.0\n", "same_59_62_and_14 = 0.0\n", - "same_59_62_and_15 = 1.0\n", + "same_59_62_and_15 = 0.0\n", "same_59_62_and_2 = 0.0\n", "same_59_62_and_3 = 0.0\n", "same_59_62_and_4 = 0.0\n", @@ -159479,7 +159469,7 @@ "same_59_62_and_7 = 0.0\n", "same_59_62_and_8 = 0.0\n", "same_59_62_and_9 = 0.0\n", - "same_59_63 = 1.0\n", + "same_59_63 = 0.0\n", "same_59_63_and_0 = 0.0\n", "same_59_63_and_1 = 0.0\n", "same_59_63_and_10 = 0.0\n", @@ -159487,7 +159477,7 @@ "same_59_63_and_12 = 0.0\n", "same_59_63_and_13 = 0.0\n", "same_59_63_and_14 = 0.0\n", - "same_59_63_and_15 = 1.0\n", + "same_59_63_and_15 = 0.0\n", "same_59_63_and_2 = 0.0\n", "same_59_63_and_3 = 0.0\n", "same_59_63_and_4 = 0.0\n", @@ -159496,7 +159486,7 @@ "same_59_63_and_7 = 0.0\n", "same_59_63_and_8 = 0.0\n", "same_59_63_and_9 = 0.0\n", - "same_59_64 = 1.0\n", + "same_59_64 = 0.0\n", "same_59_64_and_0 = 0.0\n", "same_59_64_and_1 = 0.0\n", "same_59_64_and_10 = 0.0\n", @@ -159504,7 +159494,7 @@ "same_59_64_and_12 = 0.0\n", "same_59_64_and_13 = 0.0\n", "same_59_64_and_14 = 0.0\n", - "same_59_64_and_15 = 1.0\n", + "same_59_64_and_15 = 0.0\n", "same_59_64_and_2 = 0.0\n", "same_59_64_and_3 = 0.0\n", "same_59_64_and_4 = 0.0\n", @@ -159521,12 +159511,12 @@ "same_59_65_and_12 = 0.0\n", "same_59_65_and_13 = 0.0\n", "same_59_65_and_14 = 0.0\n", - "same_59_65_and_15 = 1.0\n", + "same_59_65_and_15 = 0.0\n", "same_59_65_and_2 = 0.0\n", "same_59_65_and_3 = 0.0\n", "same_59_65_and_4 = 0.0\n", "same_59_65_and_5 = 0.0\n", - "same_59_65_and_6 = 0.0\n", + "same_59_65_and_6 = 1.0\n", "same_59_65_and_7 = 0.0\n", "same_59_65_and_8 = 0.0\n", "same_59_65_and_9 = 0.0\n", @@ -159538,12 +159528,12 @@ "same_59_66_and_12 = 0.0\n", "same_59_66_and_13 = 0.0\n", "same_59_66_and_14 = 0.0\n", - "same_59_66_and_15 = 1.0\n", + "same_59_66_and_15 = 0.0\n", "same_59_66_and_2 = 0.0\n", "same_59_66_and_3 = 0.0\n", "same_59_66_and_4 = 0.0\n", "same_59_66_and_5 = 0.0\n", - "same_59_66_and_6 = 0.0\n", + "same_59_66_and_6 = 1.0\n", "same_59_66_and_7 = 0.0\n", "same_59_66_and_8 = 0.0\n", "same_59_66_and_9 = 0.0\n", @@ -159555,12 +159545,12 @@ "same_59_67_and_12 = 0.0\n", "same_59_67_and_13 = 0.0\n", "same_59_67_and_14 = 0.0\n", - "same_59_67_and_15 = 1.0\n", + "same_59_67_and_15 = 0.0\n", "same_59_67_and_2 = 0.0\n", "same_59_67_and_3 = 0.0\n", "same_59_67_and_4 = 0.0\n", "same_59_67_and_5 = 0.0\n", - "same_59_67_and_6 = 0.0\n", + "same_59_67_and_6 = 1.0\n", "same_59_67_and_7 = 0.0\n", "same_59_67_and_8 = 0.0\n", "same_59_67_and_9 = 0.0\n", @@ -159572,12 +159562,12 @@ "same_59_68_and_12 = 0.0\n", "same_59_68_and_13 = 0.0\n", "same_59_68_and_14 = 0.0\n", - "same_59_68_and_15 = 1.0\n", + "same_59_68_and_15 = 0.0\n", "same_59_68_and_2 = 0.0\n", "same_59_68_and_3 = 0.0\n", "same_59_68_and_4 = 0.0\n", "same_59_68_and_5 = 0.0\n", - "same_59_68_and_6 = 0.0\n", + "same_59_68_and_6 = 1.0\n", "same_59_68_and_7 = 0.0\n", "same_59_68_and_8 = 0.0\n", "same_59_68_and_9 = 0.0\n", @@ -159589,12 +159579,12 @@ "same_59_69_and_12 = 0.0\n", "same_59_69_and_13 = 0.0\n", "same_59_69_and_14 = 0.0\n", - "same_59_69_and_15 = 1.0\n", + "same_59_69_and_15 = 0.0\n", "same_59_69_and_2 = 0.0\n", "same_59_69_and_3 = 0.0\n", "same_59_69_and_4 = 0.0\n", "same_59_69_and_5 = 0.0\n", - "same_59_69_and_6 = 0.0\n", + "same_59_69_and_6 = 1.0\n", "same_59_69_and_7 = 0.0\n", "same_59_69_and_8 = 0.0\n", "same_59_69_and_9 = 0.0\n", @@ -160624,14 +160614,14 @@ "same_5_6_and_1 = 0.0\n", "same_5_6_and_10 = 0.0\n", "same_5_6_and_11 = 0.0\n", - "same_5_6_and_12 = 1.0\n", + "same_5_6_and_12 = 0.0\n", "same_5_6_and_13 = 0.0\n", "same_5_6_and_14 = 0.0\n", "same_5_6_and_15 = 0.0\n", "same_5_6_and_2 = 0.0\n", "same_5_6_and_3 = 0.0\n", "same_5_6_and_4 = 0.0\n", - "same_5_6_and_5 = 0.0\n", + "same_5_6_and_5 = 1.0\n", "same_5_6_and_6 = 0.0\n", "same_5_6_and_7 = 0.0\n", "same_5_6_and_8 = 0.0\n", @@ -160696,16 +160686,16 @@ "same_60_61_and_12 = 0.0\n", "same_60_61_and_13 = 0.0\n", "same_60_61_and_14 = 0.0\n", - "same_60_61_and_15 = 1.0\n", + "same_60_61_and_15 = 0.0\n", "same_60_61_and_2 = 0.0\n", "same_60_61_and_3 = 0.0\n", "same_60_61_and_4 = 0.0\n", "same_60_61_and_5 = 0.0\n", - "same_60_61_and_6 = 0.0\n", + "same_60_61_and_6 = 1.0\n", "same_60_61_and_7 = 0.0\n", "same_60_61_and_8 = 0.0\n", "same_60_61_and_9 = 0.0\n", - "same_60_62 = 1.0\n", + "same_60_62 = 0.0\n", "same_60_62_and_0 = 0.0\n", "same_60_62_and_1 = 0.0\n", "same_60_62_and_10 = 0.0\n", @@ -160713,7 +160703,7 @@ "same_60_62_and_12 = 0.0\n", "same_60_62_and_13 = 0.0\n", "same_60_62_and_14 = 0.0\n", - "same_60_62_and_15 = 1.0\n", + "same_60_62_and_15 = 0.0\n", "same_60_62_and_2 = 0.0\n", "same_60_62_and_3 = 0.0\n", "same_60_62_and_4 = 0.0\n", @@ -160722,7 +160712,7 @@ "same_60_62_and_7 = 0.0\n", "same_60_62_and_8 = 0.0\n", "same_60_62_and_9 = 0.0\n", - "same_60_63 = 1.0\n", + "same_60_63 = 0.0\n", "same_60_63_and_0 = 0.0\n", "same_60_63_and_1 = 0.0\n", "same_60_63_and_10 = 0.0\n", @@ -160730,7 +160720,7 @@ "same_60_63_and_12 = 0.0\n", "same_60_63_and_13 = 0.0\n", "same_60_63_and_14 = 0.0\n", - "same_60_63_and_15 = 1.0\n", + "same_60_63_and_15 = 0.0\n", "same_60_63_and_2 = 0.0\n", "same_60_63_and_3 = 0.0\n", "same_60_63_and_4 = 0.0\n", @@ -160739,7 +160729,7 @@ "same_60_63_and_7 = 0.0\n", "same_60_63_and_8 = 0.0\n", "same_60_63_and_9 = 0.0\n", - "same_60_64 = 1.0\n", + "same_60_64 = 0.0\n", "same_60_64_and_0 = 0.0\n", "same_60_64_and_1 = 0.0\n", "same_60_64_and_10 = 0.0\n", @@ -160747,7 +160737,7 @@ "same_60_64_and_12 = 0.0\n", "same_60_64_and_13 = 0.0\n", "same_60_64_and_14 = 0.0\n", - "same_60_64_and_15 = 1.0\n", + "same_60_64_and_15 = 0.0\n", "same_60_64_and_2 = 0.0\n", "same_60_64_and_3 = 0.0\n", "same_60_64_and_4 = 0.0\n", @@ -160764,12 +160754,12 @@ "same_60_65_and_12 = 0.0\n", "same_60_65_and_13 = 0.0\n", "same_60_65_and_14 = 0.0\n", - "same_60_65_and_15 = 1.0\n", + "same_60_65_and_15 = 0.0\n", "same_60_65_and_2 = 0.0\n", "same_60_65_and_3 = 0.0\n", "same_60_65_and_4 = 0.0\n", "same_60_65_and_5 = 0.0\n", - "same_60_65_and_6 = 0.0\n", + "same_60_65_and_6 = 1.0\n", "same_60_65_and_7 = 0.0\n", "same_60_65_and_8 = 0.0\n", "same_60_65_and_9 = 0.0\n", @@ -160781,12 +160771,12 @@ "same_60_66_and_12 = 0.0\n", "same_60_66_and_13 = 0.0\n", "same_60_66_and_14 = 0.0\n", - "same_60_66_and_15 = 1.0\n", + "same_60_66_and_15 = 0.0\n", "same_60_66_and_2 = 0.0\n", "same_60_66_and_3 = 0.0\n", "same_60_66_and_4 = 0.0\n", "same_60_66_and_5 = 0.0\n", - "same_60_66_and_6 = 0.0\n", + "same_60_66_and_6 = 1.0\n", "same_60_66_and_7 = 0.0\n", "same_60_66_and_8 = 0.0\n", "same_60_66_and_9 = 0.0\n", @@ -160798,12 +160788,12 @@ "same_60_67_and_12 = 0.0\n", "same_60_67_and_13 = 0.0\n", "same_60_67_and_14 = 0.0\n", - "same_60_67_and_15 = 1.0\n", + "same_60_67_and_15 = 0.0\n", "same_60_67_and_2 = 0.0\n", "same_60_67_and_3 = 0.0\n", "same_60_67_and_4 = 0.0\n", "same_60_67_and_5 = 0.0\n", - "same_60_67_and_6 = 0.0\n", + "same_60_67_and_6 = 1.0\n", "same_60_67_and_7 = 0.0\n", "same_60_67_and_8 = 0.0\n", "same_60_67_and_9 = 0.0\n", @@ -160815,12 +160805,12 @@ "same_60_68_and_12 = 0.0\n", "same_60_68_and_13 = 0.0\n", "same_60_68_and_14 = 0.0\n", - "same_60_68_and_15 = 1.0\n", + "same_60_68_and_15 = 0.0\n", "same_60_68_and_2 = 0.0\n", "same_60_68_and_3 = 0.0\n", "same_60_68_and_4 = 0.0\n", "same_60_68_and_5 = 0.0\n", - "same_60_68_and_6 = 0.0\n", + "same_60_68_and_6 = 1.0\n", "same_60_68_and_7 = 0.0\n", "same_60_68_and_8 = 0.0\n", "same_60_68_and_9 = 0.0\n", @@ -160832,17 +160822,17 @@ "same_60_69_and_12 = 0.0\n", "same_60_69_and_13 = 0.0\n", "same_60_69_and_14 = 0.0\n", - "same_60_69_and_15 = 1.0\n", + "same_60_69_and_15 = 0.0\n", "same_60_69_and_2 = 0.0\n", "same_60_69_and_3 = 0.0\n", "same_60_69_and_4 = 0.0\n", "same_60_69_and_5 = 0.0\n", - "same_60_69_and_6 = 0.0\n", + "same_60_69_and_6 = 1.0\n", "same_60_69_and_7 = 0.0\n", "same_60_69_and_8 = 0.0\n", "same_60_69_and_9 = 0.0\n", "same_61_61 = 1.0\n", - "same_61_62 = 1.0\n", + "same_61_62 = 0.0\n", "same_61_62_and_0 = 0.0\n", "same_61_62_and_1 = 0.0\n", "same_61_62_and_10 = 0.0\n", @@ -160850,7 +160840,7 @@ "same_61_62_and_12 = 0.0\n", "same_61_62_and_13 = 0.0\n", "same_61_62_and_14 = 0.0\n", - "same_61_62_and_15 = 1.0\n", + "same_61_62_and_15 = 0.0\n", "same_61_62_and_2 = 0.0\n", "same_61_62_and_3 = 0.0\n", "same_61_62_and_4 = 0.0\n", @@ -160859,7 +160849,7 @@ "same_61_62_and_7 = 0.0\n", "same_61_62_and_8 = 0.0\n", "same_61_62_and_9 = 0.0\n", - "same_61_63 = 1.0\n", + "same_61_63 = 0.0\n", "same_61_63_and_0 = 0.0\n", "same_61_63_and_1 = 0.0\n", "same_61_63_and_10 = 0.0\n", @@ -160867,7 +160857,7 @@ "same_61_63_and_12 = 0.0\n", "same_61_63_and_13 = 0.0\n", "same_61_63_and_14 = 0.0\n", - "same_61_63_and_15 = 1.0\n", + "same_61_63_and_15 = 0.0\n", "same_61_63_and_2 = 0.0\n", "same_61_63_and_3 = 0.0\n", "same_61_63_and_4 = 0.0\n", @@ -160876,7 +160866,7 @@ "same_61_63_and_7 = 0.0\n", "same_61_63_and_8 = 0.0\n", "same_61_63_and_9 = 0.0\n", - "same_61_64 = 1.0\n", + "same_61_64 = 0.0\n", "same_61_64_and_0 = 0.0\n", "same_61_64_and_1 = 0.0\n", "same_61_64_and_10 = 0.0\n", @@ -160884,7 +160874,7 @@ "same_61_64_and_12 = 0.0\n", "same_61_64_and_13 = 0.0\n", "same_61_64_and_14 = 0.0\n", - "same_61_64_and_15 = 1.0\n", + "same_61_64_and_15 = 0.0\n", "same_61_64_and_2 = 0.0\n", "same_61_64_and_3 = 0.0\n", "same_61_64_and_4 = 0.0\n", @@ -160901,12 +160891,12 @@ "same_61_65_and_12 = 0.0\n", "same_61_65_and_13 = 0.0\n", "same_61_65_and_14 = 0.0\n", - "same_61_65_and_15 = 1.0\n", + "same_61_65_and_15 = 0.0\n", "same_61_65_and_2 = 0.0\n", "same_61_65_and_3 = 0.0\n", "same_61_65_and_4 = 0.0\n", "same_61_65_and_5 = 0.0\n", - "same_61_65_and_6 = 0.0\n", + "same_61_65_and_6 = 1.0\n", "same_61_65_and_7 = 0.0\n", "same_61_65_and_8 = 0.0\n", "same_61_65_and_9 = 0.0\n", @@ -160918,12 +160908,12 @@ "same_61_66_and_12 = 0.0\n", "same_61_66_and_13 = 0.0\n", "same_61_66_and_14 = 0.0\n", - "same_61_66_and_15 = 1.0\n", + "same_61_66_and_15 = 0.0\n", "same_61_66_and_2 = 0.0\n", "same_61_66_and_3 = 0.0\n", "same_61_66_and_4 = 0.0\n", "same_61_66_and_5 = 0.0\n", - "same_61_66_and_6 = 0.0\n", + "same_61_66_and_6 = 1.0\n", "same_61_66_and_7 = 0.0\n", "same_61_66_and_8 = 0.0\n", "same_61_66_and_9 = 0.0\n", @@ -160935,12 +160925,12 @@ "same_61_67_and_12 = 0.0\n", "same_61_67_and_13 = 0.0\n", "same_61_67_and_14 = 0.0\n", - "same_61_67_and_15 = 1.0\n", + "same_61_67_and_15 = 0.0\n", "same_61_67_and_2 = 0.0\n", "same_61_67_and_3 = 0.0\n", "same_61_67_and_4 = 0.0\n", "same_61_67_and_5 = 0.0\n", - "same_61_67_and_6 = 0.0\n", + "same_61_67_and_6 = 1.0\n", "same_61_67_and_7 = 0.0\n", "same_61_67_and_8 = 0.0\n", "same_61_67_and_9 = 0.0\n", @@ -160952,12 +160942,12 @@ "same_61_68_and_12 = 0.0\n", "same_61_68_and_13 = 0.0\n", "same_61_68_and_14 = 0.0\n", - "same_61_68_and_15 = 1.0\n", + "same_61_68_and_15 = 0.0\n", "same_61_68_and_2 = 0.0\n", "same_61_68_and_3 = 0.0\n", "same_61_68_and_4 = 0.0\n", "same_61_68_and_5 = 0.0\n", - "same_61_68_and_6 = 0.0\n", + "same_61_68_and_6 = 1.0\n", "same_61_68_and_7 = 0.0\n", "same_61_68_and_8 = 0.0\n", "same_61_68_and_9 = 0.0\n", @@ -160969,12 +160959,12 @@ "same_61_69_and_12 = 0.0\n", "same_61_69_and_13 = 0.0\n", "same_61_69_and_14 = 0.0\n", - "same_61_69_and_15 = 1.0\n", + "same_61_69_and_15 = 0.0\n", "same_61_69_and_2 = 0.0\n", "same_61_69_and_3 = 0.0\n", "same_61_69_and_4 = 0.0\n", "same_61_69_and_5 = 0.0\n", - "same_61_69_and_6 = 0.0\n", + "same_61_69_and_6 = 1.0\n", "same_61_69_and_7 = 0.0\n", "same_61_69_and_8 = 0.0\n", "same_61_69_and_9 = 0.0\n", @@ -160987,13 +160977,13 @@ "same_62_63_and_12 = 0.0\n", "same_62_63_and_13 = 0.0\n", "same_62_63_and_14 = 0.0\n", - "same_62_63_and_15 = 1.0\n", + "same_62_63_and_15 = 0.0\n", "same_62_63_and_2 = 0.0\n", "same_62_63_and_3 = 0.0\n", "same_62_63_and_4 = 0.0\n", "same_62_63_and_5 = 0.0\n", "same_62_63_and_6 = 0.0\n", - "same_62_63_and_7 = 0.0\n", + "same_62_63_and_7 = 1.0\n", "same_62_63_and_8 = 0.0\n", "same_62_63_and_9 = 0.0\n", "same_62_64 = 1.0\n", @@ -161004,16 +160994,16 @@ "same_62_64_and_12 = 0.0\n", "same_62_64_and_13 = 0.0\n", "same_62_64_and_14 = 0.0\n", - "same_62_64_and_15 = 1.0\n", + "same_62_64_and_15 = 0.0\n", "same_62_64_and_2 = 0.0\n", "same_62_64_and_3 = 0.0\n", "same_62_64_and_4 = 0.0\n", "same_62_64_and_5 = 0.0\n", "same_62_64_and_6 = 0.0\n", - "same_62_64_and_7 = 0.0\n", + "same_62_64_and_7 = 1.0\n", "same_62_64_and_8 = 0.0\n", "same_62_64_and_9 = 0.0\n", - "same_62_65 = 1.0\n", + "same_62_65 = 0.0\n", "same_62_65_and_0 = 0.0\n", "same_62_65_and_1 = 0.0\n", "same_62_65_and_10 = 0.0\n", @@ -161021,7 +161011,7 @@ "same_62_65_and_12 = 0.0\n", "same_62_65_and_13 = 0.0\n", "same_62_65_and_14 = 0.0\n", - "same_62_65_and_15 = 1.0\n", + "same_62_65_and_15 = 0.0\n", "same_62_65_and_2 = 0.0\n", "same_62_65_and_3 = 0.0\n", "same_62_65_and_4 = 0.0\n", @@ -161030,7 +161020,7 @@ "same_62_65_and_7 = 0.0\n", "same_62_65_and_8 = 0.0\n", "same_62_65_and_9 = 0.0\n", - "same_62_66 = 1.0\n", + "same_62_66 = 0.0\n", "same_62_66_and_0 = 0.0\n", "same_62_66_and_1 = 0.0\n", "same_62_66_and_10 = 0.0\n", @@ -161038,7 +161028,7 @@ "same_62_66_and_12 = 0.0\n", "same_62_66_and_13 = 0.0\n", "same_62_66_and_14 = 0.0\n", - "same_62_66_and_15 = 1.0\n", + "same_62_66_and_15 = 0.0\n", "same_62_66_and_2 = 0.0\n", "same_62_66_and_3 = 0.0\n", "same_62_66_and_4 = 0.0\n", @@ -161047,7 +161037,7 @@ "same_62_66_and_7 = 0.0\n", "same_62_66_and_8 = 0.0\n", "same_62_66_and_9 = 0.0\n", - "same_62_67 = 1.0\n", + "same_62_67 = 0.0\n", "same_62_67_and_0 = 0.0\n", "same_62_67_and_1 = 0.0\n", "same_62_67_and_10 = 0.0\n", @@ -161055,7 +161045,7 @@ "same_62_67_and_12 = 0.0\n", "same_62_67_and_13 = 0.0\n", "same_62_67_and_14 = 0.0\n", - "same_62_67_and_15 = 1.0\n", + "same_62_67_and_15 = 0.0\n", "same_62_67_and_2 = 0.0\n", "same_62_67_and_3 = 0.0\n", "same_62_67_and_4 = 0.0\n", @@ -161064,7 +161054,7 @@ "same_62_67_and_7 = 0.0\n", "same_62_67_and_8 = 0.0\n", "same_62_67_and_9 = 0.0\n", - "same_62_68 = 1.0\n", + "same_62_68 = 0.0\n", "same_62_68_and_0 = 0.0\n", "same_62_68_and_1 = 0.0\n", "same_62_68_and_10 = 0.0\n", @@ -161072,7 +161062,7 @@ "same_62_68_and_12 = 0.0\n", "same_62_68_and_13 = 0.0\n", "same_62_68_and_14 = 0.0\n", - "same_62_68_and_15 = 1.0\n", + "same_62_68_and_15 = 0.0\n", "same_62_68_and_2 = 0.0\n", "same_62_68_and_3 = 0.0\n", "same_62_68_and_4 = 0.0\n", @@ -161081,7 +161071,7 @@ "same_62_68_and_7 = 0.0\n", "same_62_68_and_8 = 0.0\n", "same_62_68_and_9 = 0.0\n", - "same_62_69 = 1.0\n", + "same_62_69 = 0.0\n", "same_62_69_and_0 = 0.0\n", "same_62_69_and_1 = 0.0\n", "same_62_69_and_10 = 0.0\n", @@ -161089,7 +161079,7 @@ "same_62_69_and_12 = 0.0\n", "same_62_69_and_13 = 0.0\n", "same_62_69_and_14 = 0.0\n", - "same_62_69_and_15 = 1.0\n", + "same_62_69_and_15 = 0.0\n", "same_62_69_and_2 = 0.0\n", "same_62_69_and_3 = 0.0\n", "same_62_69_and_4 = 0.0\n", @@ -161107,16 +161097,16 @@ "same_63_64_and_12 = 0.0\n", "same_63_64_and_13 = 0.0\n", "same_63_64_and_14 = 0.0\n", - "same_63_64_and_15 = 1.0\n", + "same_63_64_and_15 = 0.0\n", "same_63_64_and_2 = 0.0\n", "same_63_64_and_3 = 0.0\n", "same_63_64_and_4 = 0.0\n", "same_63_64_and_5 = 0.0\n", "same_63_64_and_6 = 0.0\n", - "same_63_64_and_7 = 0.0\n", + "same_63_64_and_7 = 1.0\n", "same_63_64_and_8 = 0.0\n", "same_63_64_and_9 = 0.0\n", - "same_63_65 = 1.0\n", + "same_63_65 = 0.0\n", "same_63_65_and_0 = 0.0\n", "same_63_65_and_1 = 0.0\n", "same_63_65_and_10 = 0.0\n", @@ -161124,7 +161114,7 @@ "same_63_65_and_12 = 0.0\n", "same_63_65_and_13 = 0.0\n", "same_63_65_and_14 = 0.0\n", - "same_63_65_and_15 = 1.0\n", + "same_63_65_and_15 = 0.0\n", "same_63_65_and_2 = 0.0\n", "same_63_65_and_3 = 0.0\n", "same_63_65_and_4 = 0.0\n", @@ -161133,7 +161123,7 @@ "same_63_65_and_7 = 0.0\n", "same_63_65_and_8 = 0.0\n", "same_63_65_and_9 = 0.0\n", - "same_63_66 = 1.0\n", + "same_63_66 = 0.0\n", "same_63_66_and_0 = 0.0\n", "same_63_66_and_1 = 0.0\n", "same_63_66_and_10 = 0.0\n", @@ -161141,7 +161131,7 @@ "same_63_66_and_12 = 0.0\n", "same_63_66_and_13 = 0.0\n", "same_63_66_and_14 = 0.0\n", - "same_63_66_and_15 = 1.0\n", + "same_63_66_and_15 = 0.0\n", "same_63_66_and_2 = 0.0\n", "same_63_66_and_3 = 0.0\n", "same_63_66_and_4 = 0.0\n", @@ -161150,7 +161140,7 @@ "same_63_66_and_7 = 0.0\n", "same_63_66_and_8 = 0.0\n", "same_63_66_and_9 = 0.0\n", - "same_63_67 = 1.0\n", + "same_63_67 = 0.0\n", "same_63_67_and_0 = 0.0\n", "same_63_67_and_1 = 0.0\n", "same_63_67_and_10 = 0.0\n", @@ -161158,7 +161148,7 @@ "same_63_67_and_12 = 0.0\n", "same_63_67_and_13 = 0.0\n", "same_63_67_and_14 = 0.0\n", - "same_63_67_and_15 = 1.0\n", + "same_63_67_and_15 = 0.0\n", "same_63_67_and_2 = 0.0\n", "same_63_67_and_3 = 0.0\n", "same_63_67_and_4 = 0.0\n", @@ -161167,7 +161157,7 @@ "same_63_67_and_7 = 0.0\n", "same_63_67_and_8 = 0.0\n", "same_63_67_and_9 = 0.0\n", - "same_63_68 = 1.0\n", + "same_63_68 = 0.0\n", "same_63_68_and_0 = 0.0\n", "same_63_68_and_1 = 0.0\n", "same_63_68_and_10 = 0.0\n", @@ -161175,7 +161165,7 @@ "same_63_68_and_12 = 0.0\n", "same_63_68_and_13 = 0.0\n", "same_63_68_and_14 = 0.0\n", - "same_63_68_and_15 = 1.0\n", + "same_63_68_and_15 = 0.0\n", "same_63_68_and_2 = 0.0\n", "same_63_68_and_3 = 0.0\n", "same_63_68_and_4 = 0.0\n", @@ -161184,7 +161174,7 @@ "same_63_68_and_7 = 0.0\n", "same_63_68_and_8 = 0.0\n", "same_63_68_and_9 = 0.0\n", - "same_63_69 = 1.0\n", + "same_63_69 = 0.0\n", "same_63_69_and_0 = 0.0\n", "same_63_69_and_1 = 0.0\n", "same_63_69_and_10 = 0.0\n", @@ -161192,7 +161182,7 @@ "same_63_69_and_12 = 0.0\n", "same_63_69_and_13 = 0.0\n", "same_63_69_and_14 = 0.0\n", - "same_63_69_and_15 = 1.0\n", + "same_63_69_and_15 = 0.0\n", "same_63_69_and_2 = 0.0\n", "same_63_69_and_3 = 0.0\n", "same_63_69_and_4 = 0.0\n", @@ -161202,7 +161192,7 @@ "same_63_69_and_8 = 0.0\n", "same_63_69_and_9 = 0.0\n", "same_64_64 = 1.0\n", - "same_64_65 = 1.0\n", + "same_64_65 = 0.0\n", "same_64_65_and_0 = 0.0\n", "same_64_65_and_1 = 0.0\n", "same_64_65_and_10 = 0.0\n", @@ -161210,7 +161200,7 @@ "same_64_65_and_12 = 0.0\n", "same_64_65_and_13 = 0.0\n", "same_64_65_and_14 = 0.0\n", - "same_64_65_and_15 = 1.0\n", + "same_64_65_and_15 = 0.0\n", "same_64_65_and_2 = 0.0\n", "same_64_65_and_3 = 0.0\n", "same_64_65_and_4 = 0.0\n", @@ -161219,7 +161209,7 @@ "same_64_65_and_7 = 0.0\n", "same_64_65_and_8 = 0.0\n", "same_64_65_and_9 = 0.0\n", - "same_64_66 = 1.0\n", + "same_64_66 = 0.0\n", "same_64_66_and_0 = 0.0\n", "same_64_66_and_1 = 0.0\n", "same_64_66_and_10 = 0.0\n", @@ -161227,7 +161217,7 @@ "same_64_66_and_12 = 0.0\n", "same_64_66_and_13 = 0.0\n", "same_64_66_and_14 = 0.0\n", - "same_64_66_and_15 = 1.0\n", + "same_64_66_and_15 = 0.0\n", "same_64_66_and_2 = 0.0\n", "same_64_66_and_3 = 0.0\n", "same_64_66_and_4 = 0.0\n", @@ -161236,7 +161226,7 @@ "same_64_66_and_7 = 0.0\n", "same_64_66_and_8 = 0.0\n", "same_64_66_and_9 = 0.0\n", - "same_64_67 = 1.0\n", + "same_64_67 = 0.0\n", "same_64_67_and_0 = 0.0\n", "same_64_67_and_1 = 0.0\n", "same_64_67_and_10 = 0.0\n", @@ -161244,7 +161234,7 @@ "same_64_67_and_12 = 0.0\n", "same_64_67_and_13 = 0.0\n", "same_64_67_and_14 = 0.0\n", - "same_64_67_and_15 = 1.0\n", + "same_64_67_and_15 = 0.0\n", "same_64_67_and_2 = 0.0\n", "same_64_67_and_3 = 0.0\n", "same_64_67_and_4 = 0.0\n", @@ -161253,7 +161243,7 @@ "same_64_67_and_7 = 0.0\n", "same_64_67_and_8 = 0.0\n", "same_64_67_and_9 = 0.0\n", - "same_64_68 = 1.0\n", + "same_64_68 = 0.0\n", "same_64_68_and_0 = 0.0\n", "same_64_68_and_1 = 0.0\n", "same_64_68_and_10 = 0.0\n", @@ -161261,7 +161251,7 @@ "same_64_68_and_12 = 0.0\n", "same_64_68_and_13 = 0.0\n", "same_64_68_and_14 = 0.0\n", - "same_64_68_and_15 = 1.0\n", + "same_64_68_and_15 = 0.0\n", "same_64_68_and_2 = 0.0\n", "same_64_68_and_3 = 0.0\n", "same_64_68_and_4 = 0.0\n", @@ -161270,7 +161260,7 @@ "same_64_68_and_7 = 0.0\n", "same_64_68_and_8 = 0.0\n", "same_64_68_and_9 = 0.0\n", - "same_64_69 = 1.0\n", + "same_64_69 = 0.0\n", "same_64_69_and_0 = 0.0\n", "same_64_69_and_1 = 0.0\n", "same_64_69_and_10 = 0.0\n", @@ -161278,7 +161268,7 @@ "same_64_69_and_12 = 0.0\n", "same_64_69_and_13 = 0.0\n", "same_64_69_and_14 = 0.0\n", - "same_64_69_and_15 = 1.0\n", + "same_64_69_and_15 = 0.0\n", "same_64_69_and_2 = 0.0\n", "same_64_69_and_3 = 0.0\n", "same_64_69_and_4 = 0.0\n", @@ -161296,12 +161286,12 @@ "same_65_66_and_12 = 0.0\n", "same_65_66_and_13 = 0.0\n", "same_65_66_and_14 = 0.0\n", - "same_65_66_and_15 = 1.0\n", + "same_65_66_and_15 = 0.0\n", "same_65_66_and_2 = 0.0\n", "same_65_66_and_3 = 0.0\n", "same_65_66_and_4 = 0.0\n", "same_65_66_and_5 = 0.0\n", - "same_65_66_and_6 = 0.0\n", + "same_65_66_and_6 = 1.0\n", "same_65_66_and_7 = 0.0\n", "same_65_66_and_8 = 0.0\n", "same_65_66_and_9 = 0.0\n", @@ -161313,12 +161303,12 @@ "same_65_67_and_12 = 0.0\n", "same_65_67_and_13 = 0.0\n", "same_65_67_and_14 = 0.0\n", - "same_65_67_and_15 = 1.0\n", + "same_65_67_and_15 = 0.0\n", "same_65_67_and_2 = 0.0\n", "same_65_67_and_3 = 0.0\n", "same_65_67_and_4 = 0.0\n", "same_65_67_and_5 = 0.0\n", - "same_65_67_and_6 = 0.0\n", + "same_65_67_and_6 = 1.0\n", "same_65_67_and_7 = 0.0\n", "same_65_67_and_8 = 0.0\n", "same_65_67_and_9 = 0.0\n", @@ -161330,12 +161320,12 @@ "same_65_68_and_12 = 0.0\n", "same_65_68_and_13 = 0.0\n", "same_65_68_and_14 = 0.0\n", - "same_65_68_and_15 = 1.0\n", + "same_65_68_and_15 = 0.0\n", "same_65_68_and_2 = 0.0\n", "same_65_68_and_3 = 0.0\n", "same_65_68_and_4 = 0.0\n", "same_65_68_and_5 = 0.0\n", - "same_65_68_and_6 = 0.0\n", + "same_65_68_and_6 = 1.0\n", "same_65_68_and_7 = 0.0\n", "same_65_68_and_8 = 0.0\n", "same_65_68_and_9 = 0.0\n", @@ -161347,12 +161337,12 @@ "same_65_69_and_12 = 0.0\n", "same_65_69_and_13 = 0.0\n", "same_65_69_and_14 = 0.0\n", - "same_65_69_and_15 = 1.0\n", + "same_65_69_and_15 = 0.0\n", "same_65_69_and_2 = 0.0\n", "same_65_69_and_3 = 0.0\n", "same_65_69_and_4 = 0.0\n", "same_65_69_and_5 = 0.0\n", - "same_65_69_and_6 = 0.0\n", + "same_65_69_and_6 = 1.0\n", "same_65_69_and_7 = 0.0\n", "same_65_69_and_8 = 0.0\n", "same_65_69_and_9 = 0.0\n", @@ -161365,12 +161355,12 @@ "same_66_67_and_12 = 0.0\n", "same_66_67_and_13 = 0.0\n", "same_66_67_and_14 = 0.0\n", - "same_66_67_and_15 = 1.0\n", + "same_66_67_and_15 = 0.0\n", "same_66_67_and_2 = 0.0\n", "same_66_67_and_3 = 0.0\n", "same_66_67_and_4 = 0.0\n", "same_66_67_and_5 = 0.0\n", - "same_66_67_and_6 = 0.0\n", + "same_66_67_and_6 = 1.0\n", "same_66_67_and_7 = 0.0\n", "same_66_67_and_8 = 0.0\n", "same_66_67_and_9 = 0.0\n", @@ -161382,12 +161372,12 @@ "same_66_68_and_12 = 0.0\n", "same_66_68_and_13 = 0.0\n", "same_66_68_and_14 = 0.0\n", - "same_66_68_and_15 = 1.0\n", + "same_66_68_and_15 = 0.0\n", "same_66_68_and_2 = 0.0\n", "same_66_68_and_3 = 0.0\n", "same_66_68_and_4 = 0.0\n", "same_66_68_and_5 = 0.0\n", - "same_66_68_and_6 = 0.0\n", + "same_66_68_and_6 = 1.0\n", "same_66_68_and_7 = 0.0\n", "same_66_68_and_8 = 0.0\n", "same_66_68_and_9 = 0.0\n", @@ -161399,12 +161389,12 @@ "same_66_69_and_12 = 0.0\n", "same_66_69_and_13 = 0.0\n", "same_66_69_and_14 = 0.0\n", - "same_66_69_and_15 = 1.0\n", + "same_66_69_and_15 = 0.0\n", "same_66_69_and_2 = 0.0\n", "same_66_69_and_3 = 0.0\n", "same_66_69_and_4 = 0.0\n", "same_66_69_and_5 = 0.0\n", - "same_66_69_and_6 = 0.0\n", + "same_66_69_and_6 = 1.0\n", "same_66_69_and_7 = 0.0\n", "same_66_69_and_8 = 0.0\n", "same_66_69_and_9 = 0.0\n", @@ -161417,12 +161407,12 @@ "same_67_68_and_12 = 0.0\n", "same_67_68_and_13 = 0.0\n", "same_67_68_and_14 = 0.0\n", - "same_67_68_and_15 = 1.0\n", + "same_67_68_and_15 = 0.0\n", "same_67_68_and_2 = 0.0\n", "same_67_68_and_3 = 0.0\n", "same_67_68_and_4 = 0.0\n", "same_67_68_and_5 = 0.0\n", - "same_67_68_and_6 = 0.0\n", + "same_67_68_and_6 = 1.0\n", "same_67_68_and_7 = 0.0\n", "same_67_68_and_8 = 0.0\n", "same_67_68_and_9 = 0.0\n", @@ -161434,12 +161424,12 @@ "same_67_69_and_12 = 0.0\n", "same_67_69_and_13 = 0.0\n", "same_67_69_and_14 = 0.0\n", - "same_67_69_and_15 = 1.0\n", + "same_67_69_and_15 = 0.0\n", "same_67_69_and_2 = 0.0\n", "same_67_69_and_3 = 0.0\n", "same_67_69_and_4 = 0.0\n", "same_67_69_and_5 = 0.0\n", - "same_67_69_and_6 = 0.0\n", + "same_67_69_and_6 = 1.0\n", "same_67_69_and_7 = 0.0\n", "same_67_69_and_8 = 0.0\n", "same_67_69_and_9 = 0.0\n", @@ -161452,12 +161442,12 @@ "same_68_69_and_12 = 0.0\n", "same_68_69_and_13 = 0.0\n", "same_68_69_and_14 = 0.0\n", - "same_68_69_and_15 = 1.0\n", + "same_68_69_and_15 = 0.0\n", "same_68_69_and_2 = 0.0\n", "same_68_69_and_3 = 0.0\n", "same_68_69_and_4 = 0.0\n", "same_68_69_and_5 = 0.0\n", - "same_68_69_and_6 = 0.0\n", + "same_68_69_and_6 = 1.0\n", "same_68_69_and_7 = 0.0\n", "same_68_69_and_8 = 0.0\n", "same_68_69_and_9 = 0.0\n", @@ -162555,12 +162545,12 @@ "same_7_11_and_0 = 0.0\n", "same_7_11_and_1 = 0.0\n", "same_7_11_and_10 = 0.0\n", - "same_7_11_and_11 = 1.0\n", + "same_7_11_and_11 = 0.0\n", "same_7_11_and_12 = 0.0\n", "same_7_11_and_13 = 0.0\n", "same_7_11_and_14 = 0.0\n", "same_7_11_and_15 = 0.0\n", - "same_7_11_and_2 = 0.0\n", + "same_7_11_and_2 = 1.0\n", "same_7_11_and_3 = 0.0\n", "same_7_11_and_4 = 0.0\n", "same_7_11_and_5 = 0.0\n", @@ -162572,12 +162562,12 @@ "same_7_12_and_0 = 0.0\n", "same_7_12_and_1 = 0.0\n", "same_7_12_and_10 = 0.0\n", - "same_7_12_and_11 = 1.0\n", + "same_7_12_and_11 = 0.0\n", "same_7_12_and_12 = 0.0\n", "same_7_12_and_13 = 0.0\n", "same_7_12_and_14 = 0.0\n", "same_7_12_and_15 = 0.0\n", - "same_7_12_and_2 = 0.0\n", + "same_7_12_and_2 = 1.0\n", "same_7_12_and_3 = 0.0\n", "same_7_12_and_4 = 0.0\n", "same_7_12_and_5 = 0.0\n", @@ -162589,12 +162579,12 @@ "same_7_13_and_0 = 0.0\n", "same_7_13_and_1 = 0.0\n", "same_7_13_and_10 = 0.0\n", - "same_7_13_and_11 = 1.0\n", + "same_7_13_and_11 = 0.0\n", "same_7_13_and_12 = 0.0\n", "same_7_13_and_13 = 0.0\n", "same_7_13_and_14 = 0.0\n", "same_7_13_and_15 = 0.0\n", - "same_7_13_and_2 = 0.0\n", + "same_7_13_and_2 = 1.0\n", "same_7_13_and_3 = 0.0\n", "same_7_13_and_4 = 0.0\n", "same_7_13_and_5 = 0.0\n", @@ -162602,7 +162592,7 @@ "same_7_13_and_7 = 0.0\n", "same_7_13_and_8 = 0.0\n", "same_7_13_and_9 = 0.0\n", - "same_7_14 = 0.0\n", + "same_7_14 = 1.0\n", "same_7_14_and_0 = 0.0\n", "same_7_14_and_1 = 0.0\n", "same_7_14_and_10 = 0.0\n", @@ -162611,7 +162601,7 @@ "same_7_14_and_13 = 0.0\n", "same_7_14_and_14 = 0.0\n", "same_7_14_and_15 = 0.0\n", - "same_7_14_and_2 = 0.0\n", + "same_7_14_and_2 = 1.0\n", "same_7_14_and_3 = 0.0\n", "same_7_14_and_4 = 0.0\n", "same_7_14_and_5 = 0.0\n", @@ -162619,7 +162609,7 @@ "same_7_14_and_7 = 0.0\n", "same_7_14_and_8 = 0.0\n", "same_7_14_and_9 = 0.0\n", - "same_7_15 = 0.0\n", + "same_7_15 = 1.0\n", "same_7_15_and_0 = 0.0\n", "same_7_15_and_1 = 0.0\n", "same_7_15_and_10 = 0.0\n", @@ -162628,7 +162618,7 @@ "same_7_15_and_13 = 0.0\n", "same_7_15_and_14 = 0.0\n", "same_7_15_and_15 = 0.0\n", - "same_7_15_and_2 = 0.0\n", + "same_7_15_and_2 = 1.0\n", "same_7_15_and_3 = 0.0\n", "same_7_15_and_4 = 0.0\n", "same_7_15_and_5 = 0.0\n", @@ -162636,7 +162626,7 @@ "same_7_15_and_7 = 0.0\n", "same_7_15_and_8 = 0.0\n", "same_7_15_and_9 = 0.0\n", - "same_7_16 = 0.0\n", + "same_7_16 = 1.0\n", "same_7_16_and_0 = 0.0\n", "same_7_16_and_1 = 0.0\n", "same_7_16_and_10 = 0.0\n", @@ -162645,7 +162635,7 @@ "same_7_16_and_13 = 0.0\n", "same_7_16_and_14 = 0.0\n", "same_7_16_and_15 = 0.0\n", - "same_7_16_and_2 = 0.0\n", + "same_7_16_and_2 = 1.0\n", "same_7_16_and_3 = 0.0\n", "same_7_16_and_4 = 0.0\n", "same_7_16_and_5 = 0.0\n", @@ -163591,14 +163581,14 @@ "same_7_9_and_9 = 0.0\n", "same_8_10 = 1.0\n", "same_8_10_and_0 = 0.0\n", - "same_8_10_and_1 = 0.0\n", + "same_8_10_and_1 = 1.0\n", "same_8_10_and_10 = 0.0\n", "same_8_10_and_11 = 0.0\n", "same_8_10_and_12 = 0.0\n", "same_8_10_and_13 = 0.0\n", "same_8_10_and_14 = 0.0\n", "same_8_10_and_15 = 0.0\n", - "same_8_10_and_2 = 1.0\n", + "same_8_10_and_2 = 0.0\n", "same_8_10_and_3 = 0.0\n", "same_8_10_and_4 = 0.0\n", "same_8_10_and_5 = 0.0\n", @@ -164612,14 +164602,14 @@ "same_8_8 = 1.0\n", "same_8_9 = 1.0\n", "same_8_9_and_0 = 0.0\n", - "same_8_9_and_1 = 0.0\n", + "same_8_9_and_1 = 1.0\n", "same_8_9_and_10 = 0.0\n", "same_8_9_and_11 = 0.0\n", "same_8_9_and_12 = 0.0\n", "same_8_9_and_13 = 0.0\n", "same_8_9_and_14 = 0.0\n", "same_8_9_and_15 = 0.0\n", - "same_8_9_and_2 = 1.0\n", + "same_8_9_and_2 = 0.0\n", "same_8_9_and_3 = 0.0\n", "same_8_9_and_4 = 0.0\n", "same_8_9_and_5 = 0.0\n", @@ -164629,14 +164619,14 @@ "same_8_9_and_9 = 0.0\n", "same_9_10 = 1.0\n", "same_9_10_and_0 = 0.0\n", - "same_9_10_and_1 = 0.0\n", + "same_9_10_and_1 = 1.0\n", "same_9_10_and_10 = 0.0\n", "same_9_10_and_11 = 0.0\n", "same_9_10_and_12 = 0.0\n", "same_9_10_and_13 = 0.0\n", "same_9_10_and_14 = 0.0\n", "same_9_10_and_15 = 0.0\n", - "same_9_10_and_2 = 1.0\n", + "same_9_10_and_2 = 0.0\n", "same_9_10_and_3 = 0.0\n", "same_9_10_and_4 = 0.0\n", "same_9_10_and_5 = 0.0\n", @@ -165648,76 +165638,76 @@ "same_9_69_and_8 = 0.0\n", "same_9_69_and_9 = 0.0\n", "same_9_9 = 1.0\n", - "t_comp_0 = 6.0\n", - "t_comp_1 = 56.0\n", - "t_comp_10 = 43.0\n", - "t_comp_11 = 78.0\n", + "t_comp_0 = 4.0\n", + "t_comp_1 = 34.0\n", + "t_comp_10 = 26.0\n", + "t_comp_11 = 47.0\n", "t_comp_12 = 0.0\n", - "t_comp_13 = 114.0\n", + "t_comp_13 = 69.0\n", "t_comp_14 = 1.0\n", "t_comp_15 = 0.0\n", - "t_comp_16 = 13.0\n", - "t_comp_17 = 9.0\n", - "t_comp_18 = 19.0\n", - "t_comp_19 = 9.0\n", - "t_comp_2 = 112.0\n", - "t_comp_20 = 19.0\n", - "t_comp_21 = 29.0\n", + "t_comp_16 = 8.0\n", + "t_comp_17 = 6.0\n", + "t_comp_18 = 12.0\n", + "t_comp_19 = 6.0\n", + "t_comp_2 = 67.0\n", + "t_comp_20 = 12.0\n", + "t_comp_21 = 18.0\n", "t_comp_22 = 1.0\n", - "t_comp_23 = 13.0\n", + "t_comp_23 = 8.0\n", "t_comp_24 = 0.0\n", - "t_comp_25 = 13.0\n", - "t_comp_26 = 9.0\n", - "t_comp_27 = 19.0\n", - "t_comp_28 = 9.0\n", - "t_comp_29 = 19.0\n", + "t_comp_25 = 8.0\n", + "t_comp_26 = 6.0\n", + "t_comp_27 = 12.0\n", + "t_comp_28 = 6.0\n", + "t_comp_29 = 12.0\n", "t_comp_3 = 1.0\n", - "t_comp_30 = 29.0\n", + "t_comp_30 = 18.0\n", "t_comp_31 = 1.0\n", - "t_comp_32 = 13.0\n", + "t_comp_32 = 8.0\n", "t_comp_33 = 0.0\n", - "t_comp_34 = 13.0\n", - "t_comp_35 = 9.0\n", - "t_comp_36 = 19.0\n", - "t_comp_37 = 9.0\n", - "t_comp_38 = 19.0\n", - "t_comp_39 = 29.0\n", - "t_comp_4 = 83.0\n", + "t_comp_34 = 8.0\n", + "t_comp_35 = 6.0\n", + "t_comp_36 = 12.0\n", + "t_comp_37 = 6.0\n", + "t_comp_38 = 12.0\n", + "t_comp_39 = 18.0\n", + "t_comp_4 = 50.0\n", "t_comp_40 = 1.0\n", - "t_comp_41 = 13.0\n", + "t_comp_41 = 8.0\n", "t_comp_42 = 0.0\n", - "t_comp_43 = 13.0\n", - "t_comp_44 = 9.0\n", - "t_comp_45 = 19.0\n", - "t_comp_46 = 9.0\n", - "t_comp_47 = 19.0\n", - "t_comp_48 = 29.0\n", + "t_comp_43 = 8.0\n", + "t_comp_44 = 6.0\n", + "t_comp_45 = 12.0\n", + "t_comp_46 = 6.0\n", + "t_comp_47 = 12.0\n", + "t_comp_48 = 18.0\n", "t_comp_49 = 1.0\n", "t_comp_5 = 0.0\n", - "t_comp_50 = 13.0\n", + "t_comp_50 = 8.0\n", "t_comp_51 = 0.0\n", - "t_comp_52 = 108.0\n", - "t_comp_53 = 26.0\n", - "t_comp_54 = 133.0\n", - "t_comp_55 = 42.0\n", + "t_comp_52 = 65.0\n", + "t_comp_53 = 16.0\n", + "t_comp_54 = 80.0\n", + "t_comp_55 = 25.0\n", "t_comp_56 = 1.0\n", "t_comp_57 = 0.0\n", - "t_comp_58 = 32.0\n", - "t_comp_59 = 16.0\n", - "t_comp_6 = 16.0\n", - "t_comp_60 = 25.0\n", - "t_comp_61 = 33.0\n", - "t_comp_62 = 16.0\n", - "t_comp_63 = 21.0\n", - "t_comp_64 = 25.0\n", - "t_comp_65 = 29.0\n", - "t_comp_66 = 33.0\n", + "t_comp_58 = 20.0\n", + "t_comp_59 = 10.0\n", + "t_comp_6 = 10.0\n", + "t_comp_60 = 15.0\n", + "t_comp_61 = 20.0\n", + "t_comp_62 = 10.0\n", + "t_comp_63 = 13.0\n", + "t_comp_64 = 15.0\n", + "t_comp_65 = 18.0\n", + "t_comp_66 = 20.0\n", "t_comp_67 = 1.0\n", - "t_comp_68 = 11.0\n", - "t_comp_69 = 11.0\n", - "t_comp_7 = 78.0\n", - "t_comp_8 = 16.0\n", - "t_comp_9 = 43.0\n" + "t_comp_68 = 7.0\n", + "t_comp_69 = 7.0\n", + "t_comp_7 = 47.0\n", + "t_comp_8 = 10.0\n", + "t_comp_9 = 26.0\n" ] } ], @@ -165726,8 +165716,8 @@ "import os\n", "import re\n", "\n", - "subfolder = \"inception70\"\n", - "filename = \"No_mem_fast3x280.pkl\"\n", + "subfolder = \"inception70/Opt_noChange_5x_new\" \n", + "filename = \"No_mem_Fullopt_5x_NoC1.0_Comp1.0.pkl\"\n", "\n", "# subfolder = \"inceptionALL\"\n", "# filename = \"zero_mem_ALL.pkl\"\n", @@ -165854,7 +165844,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 154, "id": "e8eaff1d", "metadata": {}, "outputs": [ @@ -165862,16 +165852,16 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sum of total_comp: 1658.00\n", - "Variance of total_comp: 3572.19\n", - "Standard deviation of total_comp: 59.77\n", - "Sum of total_sending: 540.00\n", - "Variance of total_sending: 2205.75\n", - "Standard deviation of total_sending: 46.97\n", + "Sum of total_comp: 1019.00\n", + "Variance of total_comp: 4659.73\n", + "Standard deviation of total_comp: 68.26\n", + "Sum of total_sending: 60.00\n", + "Variance of total_sending: 27.75\n", + "Standard deviation of total_sending: 5.27\n", "Sum of total_memory: 29582.00\n", - "Variance of total_memory: 12404062.94\n", - "Standard deviation of total_memory: 3521.94\n", - "max_router_delay: 280.0\n" + "Variance of total_memory: 16327996.69\n", + "Standard deviation of total_memory: 4040.79\n", + "max_router_delay: 238.0\n" ] } ], @@ -165905,7 +165895,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 155, "id": "b76f3ef8", "metadata": {}, "outputs": [ @@ -165913,18 +165903,18 @@ "name": "stdout", "output_type": "stream", "text": [ - "Reverse mapping: {12: [0, 1, 2, 3, 4, 5, 6], 2: [10, 8, 9], 11: [11, 12, 13, 7], 13: [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25], 5: [26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43], 10: [44, 45, 46, 47, 48, 49, 50, 51, 52], 8: [53, 54, 55], 15: [56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]}\n", - "total_comp: {12: 274, 2: 102, 11: 270, 13: 126, 5: 224, 10: 207, 8: 201, 15: 254}\n", - "total_sending: {12: 137.0, 2: 137.0, 11: 95.0, 13: 48.0, 5: 48.0, 10: 45.0, 8: 30.0, 15: 0.0}\n", - "total_memory: {12: 1456.0, 2: 274.0, 11: 1775.0, 13: 1426.0, 5: 2554.0, 10: 6439.0, 8: 3913.0, 15: 11745.0}\n", - "Computation (sum of t_comp): [102, 224, 201, 207, 270, 274, 126, 254]\n", - "Computation (duration): [102.0, 280.0, 201.0, 280.0, 270.0, 274.0, 280.0, 280.0]\n", - "Difference (duration - sum): [0.0, 56.0, 0.0, 73.0, 0.0, 0.0, 154.0, 26.0]\n" + "Reverse mapping: {0: [0, 1, 2, 3], 1: [10, 8, 9], 2: [11, 12, 13, 14, 15, 16, 7], 3: [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], 4: [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52], 5: [4, 5, 6], 6: [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69], 7: [62, 63, 64]}\n", + "total_comp: {0: 106, 1: 62, 2: 172, 3: 142, 4: 199, 5: 60, 6: 240, 7: 38}\n", + "total_sending: {0: 14.0, 1: 14.0, 2: 5.0, 3: 5.0, 4: 5.0, 5: 14.0, 6: 0.0, 7: 3.0}\n", + "total_memory: {0: 1191.0, 1: 274.0, 2: 1924.0, 3: 2554.0, 4: 7716.0, 5: 265.0, 6: 12630.0, 7: 3028.0}\n", + "Computation (sum of t_comp): [106, 62, 172, 142, 199, 60, 240, 38]\n", + "Computation (duration): [120.0, 76.0, 182.0, 147.0, 204.0, 74.0, 238.0, 41.0]\n", + "Difference (duration - sum): [14.0, 14.0, 10.0, 5.0, 5.0, 14.0, -2.0, 3.0]\n" ] }, { "data": { - 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", 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", 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GYRhpaWlGoUKFjBYtWljMP3HiRMNkMhl//fXXXddzq/Hjx2f6Hb19Wsb23eqZZ54xnnvuuUztderUMUqXLp3t9QN4dDDiDcDp1K5dW1u2bNFLL72kPXv2aNy4cYqJidETTzzxwHd8ffPNN80/u7q6qlKlSjIMQx07djS3+/v7q1SpUvrrr7/uuqyffvpJkjKNlvbu3VuS9OOPP1qdLzk5WZKyNdqdkSE4OFitWrUyt7m5uemdd95RSkqKNm7caNG/WbNmFjeuynh8zeuvv25xKmTlypV1/fr1TKe3hoSE6OWXXza/zziNc9euXUpISMjmVt6bh4eHXFxu/heWlpamc+fOydvbW6VKldLOnTvva5k//fSTXF1d9c4771i09+7dW4ZhaPny5Rbt0dHRKl68uPl92bJl5evre8/PRXZ4e3tLki5evHhf84eFhWU5Ennrdd5JSUn6999/VaNGDf31119KSkqyej2//fabzp49q65du1pc+92gQQOFh4dn+Rn/z3/+Y/G+WrVq2dpn586dU968ee/ap3nz5rpy5YqWLVumixcvatmyZXc8zXz+/Pny8/NT7dq19e+//5pfFStWlLe3t9avX2/RPyIiQlFRUeb3Gb8bL774ogoXLpypPWObTp8+rd27d6t9+/YKCAgw9ytbtqxq165t/nfiVrfvI0lq27atTp06ZZFr7ty58vLyUtOmTe+4T9LS0rRy5Uo1adLEImfp0qXvOlqdoUWLFkpNTbW4ZGTVqlVKTExUixYt7jjfmjVrdP36db399tsWl0n06NEjU9/58+erWrVqyps3r8WxiI6OVlpamvnsop9++km5cuXSW2+9ZZ7X1dU1043I7qVz584WZ0689dZbypUrl/lYuLi4qHXr1lq6dKnF7+DcuXP1/PPPKywszKr13cmVK1ckZX1dvaenp3n6rTL2EQDnQ+ENwCk988wzWrhwoS5cuKBt27Zp4MCBunjxol599VXt37//vpd76x+m0s1T+zw9PZU/f/5M7bdfB3q7Y8eOycXFRSVKlLBoDw4Olr+/v44dO2Z1Pl9fX0nZL8iOHTumkiVLmovUDBl32r09Q1bbL0mhoaFZtt++D0qUKJHpWuQnn3xSkrL1fN/sSk9P18cff6ySJUvKw8ND+fPnV4ECBbR37977KiClm/siJCQk05ca2d1X0s0/iu/1uciOlJQUSdn/guV2dyoMNm/erOjoaPN1xgUKFNB7770nSfe13zL2SVbXvIaHh2faZ56enipQoIBFmzX7zLjtWvvbFShQQNHR0Zo3b54WLlyotLQ0vfrqq1n2PXz4sJKSkhQYGKgCBQpYvFJSUjLdqPF+fzfuto9Kly6tf//9N9Op11kdv9q1a6tgwYLm083T09P1zTffqHHjxnf9nPzzzz+6cuWKSpYsmWnava5VlqRy5copPDxc3333nbntu+++U/78+fXiiy/ecb6M7b59vQUKFMj0Bcrhw4e1YsWKTMch45rmjGNx7NgxFSxY0PzFlDXbcavbM3l7e6tgwYIW/0a1bdtWV65cMZ+Of+jQIe3YsUNt2rSxal13k/FF2K33/MhwpxsiGoaR5f0eADz6uKs5AKfm7u6uZ555Rs8884yefPJJdejQQfPnz9eQIUPu+MfJ3W7klNVdee90p957FQEZbPlHUsYdbuPi4my2zFvdaVsfdB/c6n6Oy+1GjRqlQYMG6Y033tDw4cMVEBAgFxcX9ejRI9PNmOzFlvvkdr///rsCAwPNX7RYu8+y+oP9yJEjqlWrlsLDwzVx4kSFhobK3d1dP/30kz7++OOHst8e5K7X+fLly1aB/tprr6lTp05KSEhQvXr1srwJo3SzcA0MDMzyumlJmb4geBi/GxmyOn6urq567bXX9Pnnn+uTTz7R5s2bderUKZtdb3w3LVq00MiRI/Xvv//Kx8dHS5cuVatWrSzOgnkQ6enpql27tvr165fl9Iwv7x6miIgIVaxY0Xzd+ddffy13d3c1b97cZusoWLCgpJtnRdz+Bc7p06f17LPPZprnwoULmb4IBuAcKLwB5BgZN6g5ffq0JJlHVW6/wdP9jDTfjyJFiig9PV2HDx+2eJbrmTNnlJiYeF/Pu33yySdVqlQpLVmyRJMnT8408pNVhr179yo9Pd1i1PvgwYPm6bb0559/ZhqR+eOPPyTJfAfxW4/LrUVRVsflTgXnDz/8oJo1a+qLL76waE9MTLT4o9SaLz2KFCmiNWvW6OLFixYjiPbaV3eyZcsWHTlyxKKgsmaf3cl///tfXbt2TUuXLrUYvb39lGop+/stY58cOnQo0+jnoUOHbLrPwsPDFR8ff89+L7/8srp06aJff/3VYpT2dsWLF9eaNWtUpUoVmzxq7U5u3Ue3O3jwoPLnz5/tx4W1bdtWH330kf773/9q+fLlKlCgwD1PFy9QoIC8vLx0+PDhTNOy+xz7Fi1a6MMPP9SCBQsUFBSk5OTkO96wLkPGdh8+fNji0Vf//PNPpi9QihcvrpSUFPMI992WuXbtWqWkpFj825fd7chw+PBh1axZ0/w+JSVFp0+fVv369S36tW3bVr169dLp06c1b948NWjQ4J6XO1gj46aHv/32m0WRferUKf3999/q3Llzpnni4+Nt8phBAA8fp5oDcDrr16/PcjQp4/q8jNMOfX19lT9//kx3H//kk0/sH1Iy/xE3adIki/aJEydKunkd7P348MMPde7cOb355pu6ceNGpumrVq0yP+Knfv36SkhIsChAbty4oalTp8rb21s1atS4rwx3curUKYs7JScnJ+vLL79U+fLlFRwcLEnm66JvPS6XLl3K8pFFefLkyfJRQa6urpk+A/Pnz890zXlGQZOdxw3Vr19faWlpmjZtmkX7xx9/LJPJpHr16t1zGQ/q2LFjat++vdzd3dW3b19zuzX77E4yRmZv3W9JSUmaPXt2pr532u+3q1SpkgIDAzVz5kyL02WXL1+uAwcO3PdnPCtRUVH6/fffszwt91be3t6aMWOGhg4dqkaNGt2xX/PmzZWWlqbhw4dnmnbjxg2rH1F1JwULFlT58uU1Z84ci2X+/vvvWrVqVaZi727Kli2rsmXL6v/+7/+0YMECtWzZ8p6jzq6uroqJidHixYt1/Phxc/uBAwcy3bX7TkqXLq3IyEh99913+u6771SwYME7Ph0gQ3R0tNzc3DR16lSLz9zt/x5KN4/Fli1bssyTmJho/neufv36unHjhsUj8NLS0jR16tRsbUeGzz77zOKu9TNmzNCNGzcy/Y63atVKJpNJ7777rv766y+bn11QpkwZhYeH67PPPrM4e2XGjBkymUyZLpNISkrSkSNH9Pzzz9s0B4CHgxFvAE7n7bff1uXLl/Xyyy8rPDxc169f1y+//KLvvvtORYsWVYcOHcx933zzTY0ZM0ZvvvmmKlWqpE2bNplHYO2tXLlyateunT777DMlJiaqRo0a2rZtm+bMmaMmTZpYjLhYo0WLFoqLi9PIkSO1a9cutWrVSkWKFNG5c+e0YsUKrV27VvPmzZN08yZCn376qdq3b68dO3aoaNGi+uGHH7R582ZNmjTpvq8hvpMnn3xSHTt21Pbt2xUUFKRZs2bpzJkzFsVdnTp1VLhwYXXs2FF9+/aVq6urZs2apQIFClgUBpJUsWJFzZgxQyNGjFCJEiUUGBioF198UQ0bNtSwYcPUoUMHPf/884qLi9PcuXMtRtakmwWrv7+/Zs6cKR8fH+XJk0eVK1fO8hraRo0aqWbNmnr//fd19OhRlStXTqtWrdKSJUvUo0cPixup2cLOnTv19ddfKz09XYmJidq+fbsWLFggk8mkr776SmXLlr2vfXYnderUkbu7uxo1aqQuXbooJSVFn3/+uQIDA81niWS4036/nZubm8aOHasOHTqoRo0aatWqlc6cOaPJkyeraNGi6tmz54PtpFs0btxYw4cP18aNG1WnTp279s3O46Vq1KihLl26aPTo0dq9e7fq1KkjNzc3HT58WPPnz9fkyZPveH24tcaPH6969eopKipKHTt21JUrVzR16lT5+flp6NChVi2rbdu25kf5ZbcQ/PDDD7VixQpVq1ZNXbt2NX/5VqZMGe3duzdby2jRooUGDx4sT09PdezYMdN9I26X8Yz20aNHq2HDhqpfv7527dql5cuXZzpVum/fvlq6dKkaNmyo9u3bq2LFirp06ZLi4uL0ww8/6OjRo8qfP78aNWqkKlWqaMCAATp69KgiIiK0cOFCq+9PcP36ddWqVUvNmzfXoUOH9Mknn6hq1ap66aWXMm1D3bp1NX/+fPn7+2f7i6SkpCTzlwEZj/6aNm2a/P395e/vr+7du5v7jh8/Xi+99JLq1Kmjli1b6vfff9e0adP05ptvWpwpJd28YZ3x/z9SDYATcsSt1AHgQSxfvtx44403jPDwcMPb29twd3c3SpQoYbz99tvGmTNnLPpevnzZ6Nixo+Hn52f4+PgYzZs3N86ePXvHx4n9888/FvPf6TFfNWrUMMqUKXPPrKmpqcaHH35ohIWFGW5ubkZoaKgxcOBAi8dw3W09d7N27VqjcePGRmBgoJErVy6jQIECRqNGjcyPxMlw5swZo0OHDkb+/PkNd3d3IzIyMtNjd+70iKuMx0fNnz/fov3WRzhlyHhc08qVK42yZcsaHh4eRnh4eKZ5DcMwduzYYVSuXNlwd3c3ChcubEycODHLR2MlJCQYDRo0MHx8fAxJ5kdcXb161ejdu7dRsGBBw8vLy6hSpYqxZcsWo0aNGpkeg7VkyRIjIiLCyJUrl8Ujh25/nJhhGMbFixeNnj17GiEhIYabm5tRsmRJY/z48RaPQzKMm48T69atW6btuv1RTFnJ2NcZr1y5chkBAQFG5cqVjYEDB1o88ul+9tntj8261dKlS42yZcsanp6eRtGiRY2xY8cas2bNyvZ+v/1xYhm+++47o0KFCoaHh4cREBBgtG7d2vj7778t+tzpM36nR6VlpWzZskbHjh0t2rL6LGblTvvls88+MypWrGh4eXkZPj4+RmRkpNGvXz/j1KlT95w3q8/BnX6X1qxZY1SpUsXw8vIyfH19jUaNGhn79++36HOnf4dudfr0acPV1dV48skn77q9t9u4caNRsWJFw93d3ShWrJgxc+bMLPf9nT7Dhw8fNn9mf/7550zTs/ospqWlGR9++KH59/SFF14wfv/99yzXcfHiRWPgwIFGiRIlDHd3dyN//vzG888/b0yYMMHi0V/nzp0z2rRpY/j6+hp+fn5GmzZtjF27dln1OLGNGzcanTt3NvLmzWt4e3sbrVu3tnjU262+//77TI+avJfbf8dvfd3+b45hGMaiRYuM8uXLGx4eHkahQoWMDz74INPjMQ3DMFq0aGFUrVo12zkAPFpMhmGDu8AAAB57RYsW1VNPPWU+zR2wta+++krdunXT8ePH73jTtJzu33//VcGCBTV48GANGjTI0XFyvCVLlqhJkybatGmTqlWr5rAcCQkJCgsL07fffsuIN+CkuMYbAAA4hdatW6tw4cKaPn26o6M4TGxsrNLS0mz6WCvc2eeff65ixYqpatWqDs0xadIkRUZGUnQDToxrvAEAgFNwcXHR77//7ugYDrFu3Trt379fI0eOVJMmTcxPCYB9fPvtt9q7d69+/PFHTZ482eHPzh4zZoxD1w/gwVF4AwAAPOKGDRumX375RVWqVLH6Lt6wXqtWreTt7a2OHTuqa9eujo4DIAfgGm8AAAAAAOyIa7wBAAAAALAjCm8AAAAAAOyIa7yzIT09XadOnZKPj4/Db64BAAAAAHA8wzB08eJFhYSEyMXl7mPaFN7ZcOrUKYWGhjo6BgAAAADgEXPixAkVKlTorn0ovLPBx8dH0s0d6uvr6+A0AAAAAABHS05OVmhoqLlevBsK72zIOL3c19eXwhsAAAAAYJady5G5uRoAAAAAAHZE4Q0AAAAAgB1ReAMAAAAAYEdc421DaWlpSk1NdXQM5BDu7u73fCwBAAAAgEcfhbcNGIahhIQEJSYmOjoKchAXFxeFhYXJ3d3d0VEAAAAAPAAKbxvIKLoDAwOVO3fubN3VDrib9PR0nTp1SqdPn1bhwoX5TAEAAABOjML7AaWlpZmL7nz58jk6DnKQAgUK6NSpU7px44bc3NwcHQcAAADAfeIC0geUcU137ty5HZwEOU3GKeZpaWkOTgIAAADgQVB42winAsPW+EwBAAAAOQOFNwAAAAAAdkThDYd44YUX1KNHD/P7okWLatKkSQ7LAwAAAAD2ws3V7KjogB8f6vqOjmlg9Tz//POPBg8erB9//FFnzpxR3rx5Va5cOQ0ePFhVqlSxQ8qsbd++XXny5Hlo6wMAAACAh4XC+zHXtGlTXb9+XXPmzFGxYsV05swZrV27VufOnXuoOQoUKPBQ1wcAAAAADwunmj/GEhMT9b///U9jx45VzZo1VaRIET377LMaOHCgXnrpJXOfN998UwUKFJCvr69efPFF7dmzx7yMoUOHqnz58vrqq69UtGhR+fn5qWXLlrp48aK5z6VLl9S2bVt5e3urYMGC+uijjzJluf1Uc5PJpP/7v//Tyy+/rNy5c6tkyZJaunSpxTxLly5VyZIl5enpqZo1a2rOnDkymUxKTEy07Y4CAAAAgAdA4f0Y8/b2lre3txYvXqxr165l2adZs2Y6e/asli9frh07dujpp59WrVq1dP78eXOfI0eOaPHixVq2bJmWLVumjRs3asyYMebpffv21caNG7VkyRKtWrVKGzZs0M6dO++Z78MPP1Tz5s21d+9e1a9fX61btzavNz4+Xq+++qqaNGmiPXv2qEuXLnr//fcfcI8AAAAAgO1ReD/GcuXKpdjYWM2ZM0f+/v6qUqWK3nvvPe3du1eS9PPPP2vbtm2aP3++KlWqpJIlS2rChAny9/fXDz/8YF5Oenq6YmNj9dRTT6latWpq06aN1q5dK0lKSUnRF198oQkTJqhWrVqKjIzUnDlzdOPGjXvma9++vVq1aqUSJUpo1KhRSklJ0bZt2yRJn376qUqVKqXx48erVKlSatmypdq3b2/7nQQAAAAAD4jC+zHXtGlTnTp1SkuXLlXdunW1YcMGPf3004qNjdWePXuUkpKifPnymUfHvb29FR8fryNHjpiXUbRoUfn4+JjfFyxYUGfPnpV0czT8+vXrqly5snl6QECASpUqdc9sZcuWNf+cJ08e+fr6mpd76NAhPfPMMxb9n3322fvbCQAAAABgR9xcDfL09FTt2rVVu3ZtDRo0SG+++aaGDBmirl27qmDBgtqwYUOmefz9/c0/u7m5WUwzmUxKT09/4Fz2Wi4AAAAAPEyMeCOTiIgIXbp0SU8//bQSEhKUK1culShRwuKVP3/+bC2rePHicnNz09atW81tFy5c0B9//PFAGUuVKqXffvvNom379u0PtEwAAAAAsAcK78fYuXPn9OKLL+rrr7/W3r17FR8fr/nz52vcuHFq3LixoqOjFRUVpSZNmmjVqlU6evSofvnlF73//vuZit478fb2VseOHdW3b1+tW7dOv//+u9q3by8Xlwf76HXp0kUHDx5U//799ccff+j7779XbGyspJsj4wAAAADwqOBU88eYt7e3KleurI8//lhHjhxRamqqQkND1alTJ7333nsymUz66aef9P7776tDhw76559/FBwcrOrVqysoKCjb6xk/frxSUlLUqFEj+fj4qHfv3kpKSnqg7GFhYfrhhx/Uu3dvTZ48WVFRUXr//ff11ltvycPD44GWDQAAAAC2ZDIMw3B0iEddcnKy/Pz8lJSUJF9fX4tpV69eVXx8vMLCwuTp6emghJCkkSNHaubMmTpx4oSjo9gEny0AAIDHV+ScSEdHcLi4dnGOjnBXd6sTb8eIN5zWJ598omeeeUb58uXT5s2bNX78eHXv3t3RsQAAAADAAoU3nNbhw4c1YsQInT9/XoULF1bv3r01cOBAR8cCAAAAAAsU3nBaH3/8sT7++GNHxwAAAACAu+Ku5gAAAAAA2JFDC+9NmzapUaNGCgkJkclk0uLFi+/Y9z//+Y9MJpMmTZpk0X7+/Hm1bt1avr6+8vf3V8eOHZWSkmLRZ+/evapWrZo8PT0VGhqqcePG2WFrAAAAAADIzKGF96VLl1SuXDlNnz79rv0WLVqkX3/9VSEhIZmmtW7dWvv27dPq1au1bNkybdq0SZ07dzZPT05OVp06dVSkSBHt2LFD48eP19ChQ/XZZ5/ZfHsAAAAAALidQ6/xrlevnurVq3fXPidPntTbb7+tlStXqkGDBhbTDhw4oBUrVmj79u2qVKmSJGnq1KmqX7++JkyYoJCQEM2dO1fXr1/XrFmz5O7urjJlymj37t2aOHGiRYEOAAAAAIA9PNLXeKenp6tNmzbq27evypQpk2n6li1b5O/vby66JSk6OlouLi7aunWruU/16tXl7u5u7hMTE6NDhw7pwoUL9t8IAAAAAMBj7ZG+q/nYsWOVK1cuvfPOO1lOT0hIUGBgoEVbrly5FBAQoISEBHOfsLAwiz5BQUHmaXnz5s203GvXrunatWvm98nJyQ+0HQAAAACAx9cjO+K9Y8cOTZ48WbGxsTKZTA913aNHj5afn5/5FRoa+lDXD8d54YUX1KNHD0fHAAAAAJCDPLIj3v/73/909uxZFS5c2NyWlpam3r17a9KkSTp69KiCg4N19uxZi/lu3Lih8+fPKzg4WJIUHBysM2fOWPTJeJ/R53YDBw5Ur169zO+Tk5Pvr/ge6mf9PA9iaNJ9zZaQkKCRI0fqxx9/1MmTJxUYGKjy5curR48eqlWrlo1D2lZsbKx69OihxMREq+bbsGGDatasqQsXLsjf39/cvnDhQrm5udk2JAAAAIDH2iNbeLdp00bR0dEWbTExMWrTpo06dOggSYqKilJiYqJ27NihihUrSpLWrVun9PR0Va5c2dzn/fffV2pqqrmgWr16tUqVKpXlaeaS5OHhIQ8PD3tt2iPl6NGjqlKlivz9/TV+/HhFRkYqNTVVK1euVLdu3XTw4EFHR3yoAgICHB0BAAAAQA7j0FPNU1JStHv3bu3evVuSFB8fr927d+v48ePKly+fnnrqKYuXm5ubgoODVapUKUlS6dKlVbduXXXq1Enbtm3T5s2b1b17d7Vs2dL86LHXXntN7u7u6tixo/bt26fvvvtOkydPthjRfpx17dpVJpNJ27ZtU9OmTfXkk0+qTJky6tWrl3799VdJ0vHjx9W4cWN5e3vL19dXzZs3tziLYOjQoSpfvrxmzZqlwoULy9vbW127dlVaWprGjRun4OBgBQYGauTIkRbrNplMmjFjhurVqycvLy8VK1ZMP/zwg3n6hg0bZDKZLEazd+/eLZPJpKNHj2rDhg3q0KGDkpKSZDKZZDKZNHToUEnSV199pUqVKsnHx0fBwcF67bXXzGdHHD16VDVr1pQk5c2bVyaTSe3bt5eU+VTzCxcuqG3btsqbN69y586tevXq6fDhw+bpsbGx8vf318qVK1W6dGl5e3urbt26On369AMfGwAAAAA5g0ML799++00VKlRQhQoVJEm9evVShQoVNHjw4GwvY+7cuQoPD1etWrVUv359Va1a1eIZ3X5+flq1apXi4+NVsWJF9e7dW4MHD+ZRYpLOnz+vFStWqFu3bsqTJ0+m6f7+/kpPT1fjxo11/vx5bdy4UatXr9Zff/2lFi1aWPQ9cuSIli9frhUrVuibb77RF198oQYNGujvv//Wxo0bNXbsWH3wwQfmu81nGDRokJo2bao9e/aodevWatmypQ4cOJCt/M8//7wmTZokX19fnT59WqdPn1afPn0kSampqRo+fLj27NmjxYsX6+jRo+biOjQ0VAsWLJAkHTp0SKdPn9bkyZOzXEf79u3122+/aenSpdqyZYsMw1D9+vWVmppq7nP58mVNmDBBX331lTZt2qTjx4+bcwAAAACAQ081f+GFF2QYRrb7Hz16NFNbQECA5s2bd9f5ypYtq//973/Wxsvx/vzzTxmGofDw8Dv2Wbt2reLi4hQfH2++zv3LL79UmTJltH37dj3zzDOSbj76bdasWfLx8VFERIRq1qypQ4cO6aeffpKLi4tKlSqlsWPHav369ebLACSpWbNmevPNNyVJw4cP1+rVqzV16lR98skn98zv7u4uPz8/mUymTNfrv/HGG+afixUrpilTpuiZZ55RSkqKvL29zaeUBwYGWlzjfavDhw9r6dKl2rx5s55//nlJN7/oCQ0N1eLFi9WsWTNJN4v8mTNnqnjx4pKk7t27a9iwYffMDwAAAODx8Mje1Rz2l50vPQ4cOKDQ0FCLm8tFRETI39/fYmS6aNGi8vHxMb8PCgpSRESEXFxcLNpuvxleVFRUpvfZHfG+mx07dqhRo0YqXLiwfHx8VKNGDUk3T5vPrgMHDihXrlwWXxTky5dPpUqVssiYO3duc9EtSQULFsy0nQAAAAAeXxTej7GSJUvKZDLZ5AZqt98J3GQyZdmWnp6e7WVmFO23fkFw6yned3Lp0iXFxMTI19dXc+fO1fbt27Vo0SJJ0vXr17O9/uzKajutOZMDAAAAQM5G4f0YCwgIUExMjKZPn65Lly5lmp6YmKjSpUvrxIkTOnHihLl9//79SkxMVERExANnyLiB263vS5cuLUkqUKCAJFncqCzjRnwZ3N3dlZaWZtF28OBBnTt3TmPGjFG1atUUHh6eaQTa3d1dkjLNe6vSpUvrxo0bFtelnzt3TocOHbLJtgMAAAB4PFB4P+amT5+utLQ0Pfvss1qwYIEOHz6sAwcOaMqUKYqKilJ0dLQiIyPVunVr7dy5U9u2bVPbtm1Vo0YNVapU6YHXP3/+fM2aNUt//PGHhgwZom3btql79+6SpBIlSig0NFRDhw7V4cOH9eOPP+qjjz6ymL9o0aJKSUnR2rVr9e+//+ry5csqXLiw3N3dNXXqVP31119aunSphg8fbjFfkSJFZDKZtGzZMv3zzz9KSUnJlK1kyZJq3LixOnXqpJ9//ll79uzR66+/rieeeEKNGzd+4G0HAAAA8Hig8H7MFStWTDt37lTNmjXVu3dvPfXUU6pdu7bWrl2rGTNmyGQyacmSJcqbN6+qV6+u6OhoFStWTN99951N1v/hhx/q22+/VdmyZfXll1/qm2++MY8mu7m56ZtvvtHBgwdVtmxZjR07ViNGjLCY//nnn9d//vMftWjRQgUKFNC4ceNUoEABxcbGav78+YqIiNCYMWM0YcIEi/meeOIJffjhhxowYICCgoLMxf7tZs+erYoVK6phw4aKioqSYRj66aefMp1eDgAAAAB3YjK4GPWekpOT5efnp6SkJPn6+lpMu3r1quLj4xUWFiZPT08HJXROJpNJixYtUpMmTRwd5ZHEZwsAAODxFTkn0tERHC6uXZyjI9zV3erE2zHiDQAAAACAHVF4AwAAAABgR7kcHQCPL65yAAAAAPA4YMQbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOyIwhsAAAAAADui8AYAAAAAwI4ovPHYOXTokIKDg3Xx4kWHZfj3338VGBiov//+22EZAAAAADwcPMfbjiLnRD7U9cW1i7Oqf/v27TVnzhx16dJFM2fOtJjWrVs3ffLJJ2rXrp1iY2NtmNLxBg4cqLfffls+Pj73Nf+mTZs0fvx47dixQ6dPn9aiRYvUpEkTiz6GYWjIkCH6/PPPlZiYqCpVqmjGjBkqWbKkJCl//vxq27athgwZoi+++OJBNwkAAADAI4wR78dcaGiovv32W125csXcdvXqVc2bN0+FCxd2YLI7MwxDN27cuK95jx8/rmXLlql9+/b3vf5Lly6pXLlymj59+h37jBs3TlOmTNHMmTO1detW5cmTRzExMbp69aq5T4cOHTR37lydP3/+vrMAAAAAePRReD/mnn76aYWGhmrhwoXmtoULF6pw4cKqUKGCRd/09HSNHj1aYWFh8vLyUrly5fTDDz+Yp2/YsEEmk0krV65UhQoV5OXlpRdffFFnz57V8uXLVbp0afn6+uq1117T5cuXzfNdu3ZN77zzjgIDA+Xp6amqVatq+/btmZa7fPlyVaxYUR4eHvr666/l4uKi3377zSLjpEmTVKRIEaWnp2e5vd9//73KlSunJ5544o77pH379jKZTHecXq9ePY0YMUIvv/xyltMNw9CkSZP0wQcfqHHjxipbtqy+/PJLnTp1SosXLzb3K1OmjEJCQrRo0aI7rgsAAACA86Pwht544w3Nnj3b/H7WrFnq0KFDpn6jR4/Wl19+qZkzZ2rfvn3q2bOnXn/9dW3cuNGi39ChQzVt2jT98ssvOnHihJo3b65JkyZp3rx5+vHHH7Vq1SpNnTrV3L9fv35asGCB5syZo507d6pEiRKKiYnJNBI8YMAAjRkzRgcOHNBLL72k6Ohoi9ySNHv2bLVv314uLll/tP/3v/+pUqVKd90fkydP1unTp+/a527i4+OVkJCg6Ohoc5ufn58qV66sLVu2WPR99tln9b///e++1wUAAADg0UfhDb3++uv6+eefdezYMR07dkybN2/W66+/btHn2rVrGjVqlGbNmqWYmBgVK1ZM7du31+uvv65PP/3Uou+IESNUpUoVVahQQR07dtTGjRs1Y8YMVahQQdWqVdOrr76q9evXS7p52vaMGTM0fvx41atXTxEREfr888/l5eWV6drnYcOGqXbt2ipevLgCAgL05ptv6ptvvtG1a9ckSTt37lRcXFyWXxpkOHbsmEJCQizajh8/Lm9vb/PriSeeUIkSJSzaRo0ale39mZCQIEkKCgqyaA8KCjJPyxASEqJjx45le9kAAAAAnA83V4MKFCigBg0aKDY2VoZhqEGDBsqfP79Fnz///FOXL19W7dq1LdqvX7+e6ZT0smXLmn8OCgpS7ty5VaxYMYu2bdu2SZKOHDmi1NRUValSxTzdzc1Nzz77rA4cOGCx3NtHqps0aaJu3bpp0aJFatmypWJjY1WzZk0VLVr0jtt65coVeXp6WrSFhIRo9+7dd5xHkgICAu46/X55eXlZnHYPAAAAIOeh8Iakm6ebd+/eXZKyvGlYSkqKJOnHH3/MdH20h4eHxXs3NzfzzyaTyeJ9RtudrsG+mzx58li8d3d3V9u2bTV79my98sormjdvniZPnnzXZeTPn18XLlywaMuVK5dKlChhdZ47CQ4OliSdOXNGBQsWNLefOXNG5cuXt+h7/vx5FShQwGbrBgAAAPDo4VRzSJLq1q2r69evKzU1VTExMZmmR0REyMPDQ8ePH1eJEiUsXqGhofe93uLFi8vd3V2bN282t6Wmpmr79u2KiIi45/xvvvmm1qxZo08++UQ3btzQK6+8ctf+FSpU0P79++/a5z//+Y+8vb2ztwFZCAsLU3BwsNauXWtuS05O1tatWxUVFWXR9/fff890xgAAAACAnIURb0iSXF1dzad2u7q6Zpru4+OjPn36qGfPnkpPT1fVqlWVlJSkzZs3y9fXV+3atbuv9ebJk0dvvfWW+vbtq4CAABUuXFjjxo3T5cuX1bFjx3vOX7p0aT333HPq37+/3njjDXl5ed21f0xMjN58802lpaVluZ3SzWvJ+/Tpc8dlpKSk6M8//zS/j4+P1+7du835TSaTevTooREjRqhkyZIKCwvToEGDFBISYvG878uXL2vHjh1WXT8OAAAAwPlQeMPM19f3rtOHDx+uAgUKaPTo0frrr7/k7++vp59+Wu+9994DrXfMmDFKT09XmzZtdPHiRVWqVEkrV65U3rx5szV/x44d9csvv+iNN964Z9969eopV65cWrNmTZYj+5IUGBiowMDAOy7jt99+U82aNc3ve/XqJUlq166dYmNjJd28U/ulS5fUuXNnJSYmqmrVqlqxYoXF9eVLlixR4cKFVa1atexsJgAAAAAnZTIMw3B0iEddcnKy/Pz8lJSUlKk4vXr1quLj4xUWFpbppl14OIYPH6758+dr79692eo/ffp0LV26VCtXrrRzsrt77rnn9M477+i1117LcjqfLQAAgMdX5JxIR0dwuLh2cY6OcFd3qxNvx4g3nFZKSoqOHj2qadOmacSIEdmer0uXLkpMTNTFixfl4+Njx4R39u+//+qVV15Rq1atHLJ+AAAAAA8PN1eD0+revbsqVqyoF154IVunmWfIlSuX3n//fYcV3dLNu6v369dPJpPJYRkAAAAAPByMeMNpxcbGmq+pBgAAAIBHFSPeAAAAAADYEYW3jXCPOtganykAAAAgZ6DwfkBubm6Sbj6TGbCl69evS8r6ueoAAAAAnAfXeD8gV1dX+fv76+zZs5Kk3Llzc8MsPLD09HT9888/yp07t3Ll4tcUAAAAcGb8RW8DwcHBkmQuvgFbcHFxUeHChfkiBwAAAHByFN42YDKZVLBgQQUGBio1NdXRcZBDuLu7y8WFq0EAAAAAZ0fhbUOurq5cjwsAAAAAsMBwGgAAAAAAdkThDQAAAACAHVF4AwAAAABgRxTeAAAAAADYEYU3AAAAAAB2ROENAAAAAIAdUXgDAAAAAGBHFN4AAAAAANgRhTcAAAAAAHZE4Q0AAAAAgB1ReAMAAAAAYEcU3gAAAAAA2BGFNwAAAAAAdkThDQAAAACAHVF4AwAAAABgRxTeAAAAAADYEYU3AAAAAAB2ROENAAAAAIAdUXgDAAAAAGBHFN4AAAAAANiRQwvvTZs2qVGjRgoJCZHJZNLixYvN01JTU9W/f39FRkYqT548CgkJUdu2bXXq1CmLZZw/f16tW7eWr6+v/P391bFjR6WkpFj02bt3r6pVqyZPT0+FhoZq3LhxD2PzAAAAAABwbOF96dIllStXTtOnT8807fLly9q5c6cGDRqknTt3auHChTp06JBeeukli36tW7fWvn37tHr1ai1btkybNm1S586dzdOTk5NVp04dFSlSRDt27ND48eM1dOhQffbZZ3bfPgAAAAAATIZhGI4OIUkmk0mLFi1SkyZN7thn+/btevbZZ3Xs2DEVLlxYBw4cUEREhLZv365KlSpJklasWKH69evr77//VkhIiGbMmKH3339fCQkJcnd3lyQNGDBAixcv1sGDB7OVLTk5WX5+fkpKSpKvr+8DbysAAAAA3E3knEhHR3C4uHZxjo5wV9bUiU51jXdSUpJMJpP8/f0lSVu2bJG/v7+56Jak6Ohoubi4aOvWreY+1atXNxfdkhQTE6NDhw7pwoULWa7n2rVrSk5OtngBAAAAAHA/nKbwvnr1qvr3769WrVqZv01ISEhQYGCgRb9cuXIpICBACQkJ5j5BQUEWfTLeZ/S53ejRo+Xn52d+hYaG2npzAAAAAACPCacovFNTU9W8eXMZhqEZM2bYfX0DBw5UUlKS+XXixAm7rxMAAAAAkDPlcnSAe8kouo8dO6Z169ZZnDsfHByss2fPWvS/ceOGzp8/r+DgYHOfM2fOWPTJeJ/R53YeHh7y8PCw5WYAAAAAAB5Tj/SId0bRffjwYa1Zs0b58uWzmB4VFaXExETt2LHD3LZu3Tqlp6ercuXK5j6bNm1Samqquc/q1atVqlQp5c2b9+FsCAAAAADgseXQwjslJUW7d+/W7t27JUnx8fHavXu3jh8/rtTUVL366qv67bffNHfuXKWlpSkhIUEJCQm6fv26JKl06dKqW7euOnXqpG3btmnz5s3q3r27WrZsqZCQEEnSa6+9Jnd3d3Xs2FH79u3Td999p8mTJ6tXr16O2mwAAAAAwGPEoY8T27Bhg2rWrJmpvV27dho6dKjCwsKynG/9+vV64YUXJEnnz59X9+7d9d///lcuLi5q2rSppkyZIm9vb3P/vXv3qlu3btq+fbvy58+vt99+W/379892Th4nBgAAAOBh4nFiOetxYo/Mc7wfZRTeAAAAAB4mCu+cVXg/0td4AwAAAADg7Ci8AQAAAACwIwpvAAAAAADsiMIbAAAAAAA7ymXtDAkJCdq6dasSEhIkScHBwapcubKCg4NtHg4AAAAAAGeX7cL70qVL6tKli7799luZTCYFBARIuvk4L8Mw1KpVK3366afKnTu33cICAAAAAOBssn2q+bvvvqtt27bpxx9/1NWrV3XmzBmdOXNGV69e1U8//aRt27bp3XfftWdWAAAAAACcTrYL7wULFig2NlYxMTFydXU1t7u6uqpOnTqaNWuWfvjhB7uEBAAAAADAWWW78E5PT5e7u/sdp7u7uys9Pd0moQAAAAAAyCmyXXg3bNhQnTt31q5duzJN27Vrl9566y01atTIpuEAAAAAAHB22S68p02bpqCgIFWsWFH58uVT6dKlVbp0aeXLl0+VKlVSYGCgpk2bZs+sAAAAAAA4nWzf1Txv3rxavny5Dh48qC1btlg8TiwqKkrh4eF2CwkAAAAAgLOy+jne4eHhFNkAAAAAAGRTtk81v5cLFy7oyy+/tNXiAAAAAADIEWxWeB8/flwdOnSw1eIAAAAAAMgRsn2qeXJy8l2nX7x48YHDAAAAAACQ02S78Pb395fJZLrjdMMw7jodAAAAAIDHUbYLbx8fH73//vuqXLlyltMPHz6sLl262CwYAAAAAAA5QbYL76efflqSVKNGjSyn+/v7yzAM26QCAAAAACCHyPbN1V577TV5eHjccXpwcLCGDBlik1AAAAAAAOQUJoNh6ntKTk6Wn5+fkpKS5Ovr6+g4AAAAAHK4yDmRjo7gcHHt4hwd4a6sqROzPeLdtm1bLViwQCkpKQ8cEAAAAACAx0W2C+8SJUpo1KhRKlCggOrVq6cZM2bo5MmT9swGAAAAAIDTy3bhPXjwYO3YsUOHDx9Wo0aNtHjxYhUvXlwVK1bUsGHDtHv3bjvGBAAAAADAOWW78M5QqFAhde3aVStXrtQ///yj/v3769ChQ3rxxRdVpEgRde/eXfv27bNHVgAAAAAAnI7VhfetfHx81Lx5c82dO1f//POPZs2aJVdXV23ZssVW+QAAAAAAcGrZfo53hitXrsgwDOXOnVuSdOzYMS1atEgRERGqU6eOatWqZfOQAAAAAAA4K6tHvBs3bqwvv/xSkpSYmKhnn31WH330kRo3bqwZM2bYPCAAAAAAAM7M6sJ7586dqlatmiTphx9+UHBwsI4dO6Yvv/xSU6ZMsXlAAAAAAACcmdWF9+XLl+Xj4yNJWrVqlV555RW5uLjoueee07Fjx2weEAAAAAAAZ2Z14V2iRAktXrxYJ06c0MqVK1WnTh1J0tmzZ+Xr62vzgAAAAAAAODOrC+/BgwerT58+Klq0qJ599llFRUVJujn6XaFCBZsHBAAAAADAmVl9V/NXX31VVatW1enTp1WuXDlze61atfTyyy/bNBwAAAAAAM7uvp7jHRwcLB8fH61evVpXrlyRJD3zzDMKDw+3aTgAAAAAAJyd1YX3uXPnVKtWLT355JOqX7++Tp8+LUnq2LGjevfubfOAAAAAAAA4M6sL7549e8rNzU3Hjx9X7ty5ze0tWrTQihUrbBoOAAAAAABnZ/U13qtWrdLKlStVqFAhi/aSJUvyODEAAAAAAG5j9Yj3pUuXLEa6M5w/f14eHh42CQUAAAAAQE5hdeFdrVo1ffnll+b3JpNJ6enpGjdunGrWrGnTcAAAAAAAODurTzUfN26catWqpd9++03Xr19Xv379tG/fPp0/f16bN2+2R0YAAAAAAJyW1SPeTz31lP744w9VrVpVjRs31qVLl/TKK69o165dKl68uD0yAgAAAADgtKwe8T5+/LhCQ0P1/vvvZzmtcOHCNgkGAAAAAEBOYPWId1hYmP75559M7efOnVNYWJhNQgEAAAAAkFNYXXgbhiGTyZSpPSUlRZ6enjYJBQAAAABATpHtU8179eol6eZdzAcNGmTxSLG0tDRt3bpV5cuXt3lAAAAAAACcWbYL7127dkm6OeIdFxcnd3d38zR3d3eVK1dOffr0sX1CAAAAAACcWLYL7/Xr10uSOnTooMmTJ8vX19duoQAAAAAAyCmsvsa7evXqcnNzs0cWAAAAAAByHKsL7wEDBigoKEgdO3bUL7/8Yo9MAAAAAADkGFYX3idPntScOXP077//6oUXXlB4eLjGjh2rhIQEe+QDAAAAAMCpWV1458qVSy+//LKWLFmiEydOqFOnTpo7d64KFy6sl156SUuWLFF6ero9sgIAAAAA4HSsLrxvFRQUpKpVqyoqKkouLi6Ki4tTu3btVLx4cW3YsMFGEQEAAAAAcF73VXifOXNGEyZMUJkyZfTCCy8oOTlZy5YtU3x8vE6ePKnmzZurXbt2ts4KAAAAAIDTsbrwbtSokUJDQxUbG6tOnTrp5MmT+uabbxQdHS1JypMnj3r37q0TJ07YPCwAAAAAAM4m28/xzhAYGKiNGzcqKirqjn0KFCig+Pj4BwoGAAAAAEBOYHXh/cUXX9yzj8lkUpEiRe4rEAAAAAAAOcl9XeO9du1aNWzYUMWLF1fx4sXVsGFDrVmzxurlbNq0SY0aNVJISIhMJpMWL15sMd0wDA0ePFgFCxaUl5eXoqOjdfjwYYs+58+fV+vWreXr6yt/f3917NhRKSkpFn327t2ratWqydPTU6GhoRo3bpzVWQEAAAAAuB9WF96ffPKJ6tatKx8fH7377rt699135evrq/r162v69OlWLevSpUsqV67cHecbN26cpkyZopkzZ2rr1q3KkyePYmJidPXqVXOf1q1ba9++fVq9erWWLVumTZs2qXPnzubpycnJqlOnjooUKaIdO3Zo/PjxGjp0qD777DNrNx0AAAAAAKuZDMMwrJmhUKFCGjBggLp3727RPn36dI0aNUonT568vyAmkxYtWqQmTZpIujnaHRISot69e6tPnz6SpKSkJAUFBSk2NlYtW7bUgQMHFBERoe3bt6tSpUqSpBUrVqh+/fr6+++/FRISohkzZuj9999XQkKC3N3dJUkDBgzQ4sWLdfDgwWxlS05Olp+fn5KSkuTr63tf2wcAAAAA2RU5J9LRERwurl2coyPclTV1otUj3omJiapbt26m9jp16igpKcnaxd1RfHy8EhISzHdLlyQ/Pz9VrlxZW7ZskSRt2bJF/v7+5qJbkqKjo+Xi4qKtW7ea+1SvXt1cdEtSTEyMDh06pAsXLmS57mvXrik5OdniBQAAAADA/bC68H7ppZe0aNGiTO1LlixRw4YNbRJKkhISEiRJQUFBFu1BQUHmaQkJCQoMDLSYnitXLgUEBFj0yWoZt67jdqNHj5afn5/5FRoa+uAbBAAAAAB4LGXrruZTpkwx/xwREaGRI0dqw4YN5keK/frrr9q8ebN69+5tn5QP2cCBA9WrVy/z++TkZIpvAAAAAMB9yVbh/fHHH1u8z5s3r/bv36/9+/eb2/z9/TVr1ix98MEHNgkWHBwsSTpz5owKFixobj9z5ozKly9v7nP27FmL+W7cuKHz58+b5w8ODtaZM2cs+mS8z+hzOw8PD3l4eNhkOwAAAAAAj7dsFd7x8fH2zpFJWFiYgoODtXbtWnOhnZycrK1bt+qtt96SJEVFRSkxMVE7duxQxYoVJUnr1q1Tenq6KleubO7z/vvvKzU1VW5ubpKk1atXq1SpUsqbN+9D3y4AAAAAwOPlvp7jbSspKSnavXu3du/eLelmgb97924dP35cJpNJPXr00IgRI7R06VLFxcWpbdu2CgkJMd/5vHTp0qpbt646deqkbdu2afPmzerevbtatmypkJAQSdJrr70md3d3dezYUfv27dN3332nyZMnW5xKDgAAAACAvWRrxPt2mzZtUu7cuS3uJv7bb7/p8uXLql69eraX89tvv6lmzZrm9xnFcLt27RQbG6t+/frp0qVL6ty5sxITE1W1alWtWLFCnp6e5nnmzp2r7t27q1atWnJxcVHTpk0trkn38/PTqlWr1K1bN1WsWFH58+fX4MGDLZ71DQAAAACAvVj9HG9JcnFxUXh4uMU13qVLl9Yff/yhtLQ0mwZ8FPAcbwAAAAAPE8/xzlnP8b6vEe/4+Hjz9dIZ1q5dq9TU1PtZHAAAAAAAOZbV13i3a9dOx44dM19DnSEkJERFihSxWTAAAAAAAHICqwvvpKQkRUdHq2TJkho1apROnjxpj1wAAAAAAOQIVhfeixcv1smTJ/XWW2/pu+++U9GiRVWvXj3Nnz+fU80BAAAAALjNfT1OrECBAurVq5f27NmjrVu3qkSJEuZHffXs2VOHDx+2dU4AAAAAAJzSAz3H+/Tp01q9erVWr14tV1dX1a9fX3FxcYqIiNDHH39sq4wAAAAAADgtqwvv1NRULViwQA0bNlSRIkU0f/589ejRQ6dOndKcOXO0Zs0aff/99xo2bJg98gIAAAAA4FSsfpxYwYIFlZ6erlatWmnbtm0qX758pj41a9aUv7+/DeIBAAAAAODcrC68P/74YzVr1kyenp537OPv76/4+PgHCgYAAAAAQE5g1anmqamp6tChg/7880975QEAAAAAIEexqvB2c3NT4cKFlZaWZq88AAAAAADkKFbfXO3999/Xe++9p/Pnz9sjDwAAAAAAOYrV13hPmzZNf/75p0JCQlSkSBHlyZPHYvrOnTttFg4AAAAAAGdndeHdpEkTO8QAAAAAACBnsrrwHjJkiD1yAAAAAACQI1ldeGfYsWOHDhw4IEkqU6aMKlSoYLNQAAAAAADkFFYX3mfPnlXLli21YcMG+fv7S5ISExNVs2ZNffvttypQoICtMwIAAAAA4LSsvqv522+/rYsXL2rfvn06f/68zp8/r99//13Jycl655137JERAAAAAACnZfWI94oVK7RmzRqVLl3a3BYREaHp06erTp06Ng0HAAAAAICzs3rEOz09XW5ubpna3dzclJ6ebpNQAAAAAADkFFYX3i+++KLeffddnTp1ytx28uRJ9ezZU7Vq1bJpOAAAAAAAnJ3Vhfe0adOUnJysokWLqnjx4ipevLjCwsKUnJysqVOn2iMjAAAAAABOy+prvENDQ7Vz506tWbNGBw8elCSVLl1a0dHRNg8HAAAAAICzu6/neJtMJtWuXVu1a9e2dR4AAAAAAHKU+yq8t2/frvXr1+vs2bOZbqg2ceJEmwQDAAAAACAnsLrwHjVqlD744AOVKlVKQUFBMplM5mm3/gwAAAAAAO6j8J48ebJmzZql9u3b2yEOAAAAAAA5i9V3NXdxcVGVKlXskQUAAAAAgBzH6hHvnj17avr06Zo0aZId4gAAYDuRcyIdHcHh4trFOToCAACPPasL7z59+qhBgwYqXry4IiIi5ObmZjF94cKFNgsHAAAAAICzs7rwfuedd7R+/XrVrFlT+fLl44ZqAAAAAADchdWF95w5c7RgwQI1aNDAHnkAAAAAAMhRrL65WkBAgIoXL26PLAAAAAAA5DhWF95Dhw7VkCFDdPnyZXvkAQAAAAAgR7H6VPMpU6boyJEjCgoKUtGiRTPdXG3nzp02CwcAAAAAgLOzuvBu0qSJHWIAAAAAAJAzWV14DxkyxB45AAAAAADIkay+xluSEhMT9X//938aOHCgzp8/L+nmKeYnT560aTgAAAAAAJyd1SPee/fuVXR0tPz8/HT06FF16tRJAQEBWrhwoY4fP64vv/zSHjkBAAAAAHBKVo949+rVS+3bt9fhw4fl6elpbq9fv742bdpk03AAAAAAADg7qwvv7du3q0uXLpnan3jiCSUkJNgkFAAAAAAAOYXVhbeHh4eSk5Mztf/xxx8qUKCATUIBAAAAAJBTWF14v/TSSxo2bJhSU1MlSSaTScePH1f//v3VtGlTmwcEAAAAAMCZWV14f/TRR0pJSVFgYKCuXLmiGjVqqESJEvLx8dHIkSPtkREAAAAAAKdl9V3N/fz8tHr1av3888/au3evUlJS9PTTTys6Otoe+QAAAAAAcGpWF94ZqlatqqpVq9oyCwAAAAAAOc59Fd7bt2/X+vXrdfbsWaWnp1tMmzhxok2CAQAAAACQE1hdeI8aNUoffPCBSpUqpaCgIJlMJvO0W38GAAAAAAD3UXhPnjxZs2bNUvv27e0QBwAAAACAnMXqu5q7uLioSpUq9sgCAAAAAECOY3Xh3bNnT02fPt0eWQAAAAAAyHGsPtW8T58+atCggYoXL66IiAi5ublZTF+4cKHNwgEAAAAA4OysLrzfeecdrV+/XjVr1lS+fPm4oRoAAAAAAHdhdeE9Z84cLViwQA0aNLBHHgAAAAAAchSrr/EOCAhQ8eLF7ZEFAAAAAIAcx+rCe+jQoRoyZIguX75sjzwAAAAAAOQoVhfeU6ZM0fLlyxUUFKTIyEg9/fTTFi9bSktL06BBgxQWFiYvLy8VL15cw4cPl2EY5j6GYWjw4MEqWLCgvLy8FB0drcOHD1ss5/z582rdurV8fX3l7++vjh07KiUlxaZZAQAAAADIitXXeDdp0sQOMbI2duxYzZgxQ3PmzFGZMmX022+/qUOHDvLz89M777wjSRo3bpymTJmiOXPmKCwsTIMGDVJMTIz2798vT09PSVLr1q11+vRprV69WqmpqerQoYM6d+6sefPmPbRtAQAAAAA8nkzGrcPHj5iGDRsqKChIX3zxhbmtadOm8vLy0tdffy3DMBQSEqLevXurT58+kqSkpCQFBQUpNjZWLVu21IEDBxQREaHt27erUqVKkqQVK1aofv36+vvvvxUSEnLPHMnJyfLz81NSUpJ8fX3ts7EAAJuLnBPp6AgOF9cuztERAAD3gf/DHv3/w6ypE60+1fxhev7557V27Vr98ccfkqQ9e/bo559/Vr169SRJ8fHxSkhIUHR0tHkePz8/Va5cWVu2bJEkbdmyRf7+/uaiW5Kio6Pl4uKirVu3PsStAQAAAAA8jqw+1fxhGjBggJKTkxUeHi5XV1elpaVp5MiRat26tSQpISFBkhQUFGQxX1BQkHlaQkKCAgMDLabnypVLAQEB5j63u3btmq5du2Z+n5ycbLNtAgAAAAA8Xh7pEe/vv/9ec+fO1bx587Rz507NmTNHEyZM0Jw5c+y63tGjR8vPz8/8Cg0Ntev6AAAAAAA51yNdePft21cDBgxQy5YtFRkZqTZt2qhnz54aPXq0JCk4OFiSdObMGYv5zpw5Y54WHByss2fPWky/ceOGzp8/b+5zu4EDByopKcn8OnHihK03DQAAAADwmHikC+/Lly/LxcUyoqurq9LT0yVJYWFhCg4O1tq1a83Tk5OTtXXrVkVFRUmSoqKilJiYqB07dpj7rFu3Tunp6apcuXKW6/Xw8JCvr6/FCwAAAACA+2HTa7yHDRummjVrqlq1ajZZXqNGjTRy5EgVLlxYZcqU0a5duzRx4kS98cYbkiSTyaQePXpoxIgRKlmypPlxYiEhIebHnpUuXVp169ZVp06dNHPmTKWmpqp79+5q2bJltu5oDgAAAADAg7Bp4T179myNGTNGtWrV0n//+98HXt7UqVM1aNAgde3aVWfPnlVISIi6dOmiwYMHm/v069dPly5dUufOnZWYmKiqVatqxYoV5md4S9LcuXPVvXt31apVSy4uLmratKmmTJnywPkAAAAAALgXmz/H+8qVK1q/fr3q169vy8U6FM/xBgDnxDNQH/1noAIAssb/YY/+/2EOfY63l5dXjiq6AQAAAAB4EFYX3itWrNDPP/9sfj99+nSVL19er732mi5cuGDTcAAAAAAAODurC+++ffsqOTlZkhQXF6fevXurfv36io+PV69evWweEAAAAAAAZ2b1zdXi4+MVEREhSVqwYIEaNmyoUaNGaefOnZxiDgAAAADAbawe8XZ3d9fly5clSWvWrFGdOnUkSQEBAeaRcAAAAAAAcJPVI95Vq1ZVr169VKVKFW3btk3fffedJOmPP/5QoUKFbB4QAAAAAABnZvWI97Rp05QrVy798MMPmjFjhp544glJ0vLly1W3bl2bBwQAAAAAwJlZPeJduHBhLVu2LFP7xx9/bJNAAAAAAADkJFaPeLu6uurs2bOZ2s+dOydXV1ebhAIAAAAAIKewuvA2DCPL9mvXrsnd3f2BAwEAAAAAkJNk+1TzKVOmSJJMJpP+7//+T97e3uZpaWlp2rRpk8LDw22fEAAAAAAAJ5btwjvjGm7DMDRz5kyL08rd3d1VtGhRzZw50/YJAQAAAABwYtkuvOPj4yVJNWvW1MKFC5U3b167hQIAAAAAIKew+q7m69evt0cOAAAAAABypGwV3r169dLw4cOVJ08e9erV6659J06caJNgAAAAAADkBNkqvHft2qXU1FTzz3diMplskwoAAAAAgBwiW4X3raeXc6o5AAAAAADZZ/VzvAEAAAAAQPZla8T75ZdfzvZp5AsXLnygQAAAAAAA5CTZKrz9/f3tHAMAAAAAgJwp2yPedevWlbu7u73zAAAAAACQo2TrGu+XX35ZSUlJkiRXV1edPXvWrqEAAAAAAMgpslV4FyhQQL/++qskyTAMHhsGAAAAAEA2ZetU8//85z9q3LixTCaTTCaTgoOD79g3LS3NZuEAAAAAAHB22Sq8hw4dqpYtW+rPP//USy+9pNmzZ3PDNQAAAAAAsiFbhbckhYeHKzw8XEOGDFGzZs2UO3due+YCAAAAACBHyHbhnWHIkCH2yAEAAAAAQI6UrZur3W7YsGH65JNPLNo++eQTDRs2zCahAAAAAADIKe6r8J49e7YWLVpk0bZgwQLFxsbaIhMAAAAAADmG1aeaS1J8fHymtrVr1z5wGAAAAAAAcpr7GvEGAAAAAADZY/WI9969e7NsN5lM8vT0VOHCheXh4fHAwQAAAAAAyAmsLrzLly8vk8l0x+lubm5q0aKFPv30U3l6ej5QOAAAAAAAnJ3Vp5ovWrRIJUuW1Geffabdu3dr9+7d+uyzz1SqVCnNmzdPX3zxhdatW6cPPvjAHnkBAAAAAHAqVo94jxw5UpMnT1ZMTIy5LTIyUoUKFdKgQYO0bds25cmTR71799aECRNsGhYAAAAAAGdj9Yh3XFycihQpkqm9SJEiiouLk3TzdPTTp08/eDoAAAAAAJyc1YV3eHi4xowZo+vXr5vbUlNTNWbMGIWHh0uSTp48qaCgINulBAAAAADASVl9qvn06dP10ksvqVChQipbtqykm6PgaWlpWrZsmSTpr7/+UteuXW2bFAAAAAAAJ2R14f38888rPj5ec+fO1R9//CFJatasmV577TX5+PhIktq0aWPblAAAAAAAOCmrC29J8vHx0X/+8x9bZwEAAAAAIMe5r8L78OHDWr9+vc6ePav09HSLaYMHD7ZJMAAAAAAAcgKrC+/PP/9cb731lvLnz6/g4GCZTCbzNJPJROENAAAAAMAtrC68R4wYoZEjR6p///72yAMAAAAAQI5i9ePELly4oGbNmtkjCwAAAAAAOY7VhXezZs20atUqe2QBAAAAACDHsfpU8xIlSmjQoEH69ddfFRkZKTc3N4vp77zzjs3CAQAAAADg7KwuvD/77DN5e3tr48aN2rhxo8U0k8lE4Q0AAAAAwC2sLrzj4+PtkQMAAAAAgBzJ6mu8AQAAAABA9mVrxLtXr14aPny48uTJo169et2178SJE20SDAAAAACAnCBbhfeuXbuUmppq/vlOTCaTbVIBAAAAAJBDZKvwXr9+fZY/AwAAAACAu+MabwAAAAAA7ChbI96vvPJKthe4cOHC+w4DAI+yyDmRjo7gcHHt4hwdAQAAwOlka8Tbz8/P/PL19dXatWv122+/mafv2LFDa9eulZ+fn92CAgAAAADgjLI14j179mzzz/3791fz5s01c+ZMubq6SpLS0tLUtWtX+fr62iclAAAAAABOyuprvGfNmqU+ffqYi25JcnV1Va9evTRr1iybhpOkkydP6vXXX1e+fPnk5eWlyMhIi9F2wzA0ePBgFSxYUF5eXoqOjtbhw4ctlnH+/Hm1bt1avr6+8vf3V8eOHZWSkmLzrAAAAAAA3M7qwvvGjRs6ePBgpvaDBw8qPT3dJqEyXLhwQVWqVJGbm5uWL1+u/fv366OPPlLevHnNfcaNG6cpU6Zo5syZ2rp1q/LkyaOYmBhdvXrV3Kd169bat2+fVq9erWXLlmnTpk3q3LmzTbMCAAAAAJCVbJ1qfqsOHTqoY8eOOnLkiJ599llJ0tatWzVmzBh16NDBpuHGjh2r0NBQi1Pdw8LCzD8bhqFJkybpgw8+UOPGjSVJX375pYKCgrR48WK1bNlSBw4c0IoVK7R9+3ZVqlRJkjR16lTVr19fEyZMUEhIiE0zAwAAAABwK6tHvCdMmKB+/frpo48+UvXq1VW9enVNnDhRffv21fjx420abunSpapUqZKaNWumwMBAVahQQZ9//rl5enx8vBISEhQdHW1u8/PzU+XKlbVlyxZJ0pYtW+Tv728uuiUpOjpaLi4u2rp1q03zAgAAAABwO6tHvF1cXNSvXz/169dPycnJkmS3m6r99ddfmjFjhnr16qX33ntP27dv1zvvvCN3d3e1a9dOCQkJkqSgoCCL+YKCgszTEhISFBgYaDE9V65cCggIMPe53bVr13Tt2jXz+4ztBAAAAADAWlYX3rey913M09PTValSJY0aNUqSVKFCBf3++++aOXOm2rVrZ7f1jh49Wh9++KHdlg8AAAAAeHxYfar5mTNn1KZNG4WEhChXrlxydXW1eNlSwYIFFRERYdFWunRpHT9+XJIUHBxsznR7xoxpwcHBOnv2rMX0Gzdu6Pz58+Y+txs4cKCSkpLMrxMnTthkewAAAAAAjx+rR7zbt2+v48ePa9CgQSpYsKBMJpM9ckmSqlSpokOHDlm0/fHHHypSpIikmzdaCw4O1tq1a1W+fHlJN08L37p1q9566y1JUlRUlBITE7Vjxw5VrFhRkrRu3Tqlp6ercuXKWa7Xw8NDHh4edtoqAAAAAMDjxOrC++eff9b//vc/c6FrTz179tTzzz+vUaNGqXnz5tq2bZs+++wzffbZZ5Ikk8mkHj16aMSIESpZsqTCwsI0aNAghYSEqEmTJpJujpDXrVtXnTp10syZM5Wamqru3burZcuW3NEcAAAAAGB3VhfeoaGhMgzDHlkyeeaZZ7Ro0SINHDhQw4YNU1hYmCZNmqTWrVub+/Tr10+XLl1S586dlZiYqKpVq2rFihXy9PQ095k7d666d++uWrVqycXFRU2bNtWUKVMeyjYAAAAAAB5vJsPKKnrVqlX66KOP9Omnn6po0aJ2ivVoSU5Olp+fn5KSkux+QzkAj67IOZGOjuBwce3iHB3BKhwz5ztmAICb+D/s0f8/zJo60eoR7xYtWujy5csqXry4cufOLTc3N4vp58+ft3aRAAAAAADkWFYX3pMmTbJDDAAAAAAAciarC297Pj8bAAAAAICcxurneEvSkSNH9MEHH6hVq1bmZ2QvX75c+/bts2k4AAAAAACcndWF98aNGxUZGamtW7dq4cKFSklJkSTt2bNHQ4YMsXlAAAAAAACcmdWF94ABAzRixAitXr1a7u7u5vYXX3xRv/76q03DAQAAAADg7KwuvOPi4vTyyy9nag8MDNS///5rk1AAAAAAAOQUVhfe/v7+On36dKb2Xbt26YknnrBJKAAAAAAAcgqrC++WLVuqf//+SkhIkMlkUnp6ujZv3qw+ffqobdu29sgIAAAAAIDTsvpxYqNGjVK3bt0UGhqqtLQ0RUREKC0tTa+99po++OADe2QEAADAIyZyTqSjIzhcXLs4R0cA4CSsLrzd3d31+eefa/DgwYqLi1NKSooqVKigkiVL2iMfAAAAAABOzerCO0NoaKh51DsuLk4XLlxQ3rx5bZkNAAAAAACnZ/U13j169NAXX3whSUpLS1ONGjX09NNPKzQ0VBs2bLB1PgAAAAAAnJrVI94//PCDXn/9dUnSf//7X/311186ePCgvvrqK73//vvavHmzzUMCAICcj2uGuWYYAHIqq0e8//33XwUHB0uSfvrpJzVv3lxPPvmk3njjDcXF8Z8FAAAAAAC3srrwDgoK0v79+5WWlqYVK1aodu3akqTLly/L1dXV5gEBAAAAAHBmVp9q3qFDBzVv3lwFCxaUyWRSdHS0JGnr1q0KDw+3eUAAAAAAAJyZ1YX30KFD9dRTT+nEiRNq1qyZPDw8JEmurq4aMGCAzQMCAAAAAODM7utxYq+++mqmtnbt2j1wGOBxw42EuJEQAAAAcj6rr/EGAAAAAADZR+ENAAAAAIAdUXgDAAAAAGBHFN4AAAAAANgRhTcAAAAAAHZk08LbxcVFL774onbs2GHLxQIAAAAA4LRsWnjPmjVL1atXV7du3Wy5WAAAAAAAnNZ9Pcf7Ttq3by9JGjp0qC0XCwAAAACA03rgEe/k5GQtXrxYBw4csEUeAAAAAAByFKsL7+bNm2vatGmSpCtXrqhSpUpq3ry5ypYtqwULFtg8IAAAAAAAzszqwnvTpk2qVq2aJGnRokUyDEOJiYmaMmWKRowYYfOAAAAAAAA4M6sL76SkJAUEBEiSVqxYoaZNmyp37txq0KCBDh8+bPOAAAAAAAA4M6sL79DQUG3ZskWXLl3SihUrVKdOHUnShQsX5OnpafOAAAAAAAA4M6vvat6jRw+1bt1a3t7eKlKkiF544QVJN09Bj4yMtHU+AAAAAACcmtWFd9euXfXss8/qxIkTql27tlxcbg6aFytWjGu8AQAAAAC4zX09x7tSpUqqVKmSRVuDBg1sEggAAAAAgJzE6sI7LS1NsbGxWrt2rc6ePav09HSL6evWrbNZOAAAAAAAnJ3Vhfe7776r2NhYNWjQQE899ZRMJpM9cgEAAAAAkCNYXXh/++23+v7771W/fn175AEAAAAAIEex+nFi7u7uKlGihD2yAAAAAACQ41hdePfu3VuTJ0+WYRj2yAMAAAAAQI5i9anmP//8s9avX6/ly5erTJkycnNzs5i+cOFCm4UDAAAAAMDZWV14+/v76+WXX7ZHFgAAAAAAchyrC+/Zs2fbIwcAAAAAADmS1dd4AwAAAACA7LuvwnvYsGH65JNPLNo++eQTDRs2zCahAAAAAADIKe6r8J49e7YWLVpk0bZgwQLFxsbaIhMAAAAAADmG1dd4S1J8fHymtrVr1z5wGAAAAAAAchqu8QYAAAAAwI7ua8T7woUL+uKLL3TgwAFJUunSpfXGG28oICDApuEAAAAAAHB2Vo94b9q0SWFhYZoyZYouXLigCxcuaOrUqQoLC9OmTZvskREAAAAAAKdl9Yh3t27d1Lx5c82YMUOurq6SpLS0NHXt2lXdunVTXFyczUMCAAAAAOCsrB7x/vPPP9W7d29z0S1Jrq6u6tWrl/7880+bhgMAAAAAwNlZXXg//fTT5mu7b3XgwAGVK1fOJqEAAAAAAMgprD7V/J133tG7776rP//8U88995wk6ddff9X06dM1ZswY7d2719y3bNmytksKAAAAAIATsrrwbtWqlSSpX79+WU4zmUwyDEMmk0lpaWkPnhAAAAAAACdmdeEdHx9vjxwAAAAAAORIVhfeRYoUsUcOAAAAAAByJKtvriZJp06d0vfff69p06ZpypQpFi97GjNmjEwmk3r06GFuu3r1qrp166Z8+fLJ29tbTZs21ZkzZyzmO378uBo0aKDcuXMrMDBQffv21Y0bN+yaFQAAAAAA6T5GvGNjY9WlSxe5u7srX758MplM5mkmk0nvvPOOTQNm2L59uz799NNMN2zr2bOnfvzxR82fP19+fn7q3r27XnnlFW3evFnSzWeMN2jQQMHBwfrll190+vRptW3bVm5ubho1apRdsgIAAOR0cfHHHR0BAJyG1SPegwYN0uDBg5WUlKSjR48qPj7e/Prrr7/skVEpKSlq3bq1Pv/8c+XNm9fcnpSUpC+++EITJ07Uiy++qIoVK2r27Nn65Zdf9Ouvv0qSVq1apf379+vrr79W+fLlVa9ePQ0fPlzTp0/X9evX7ZIXAAAAAIAMVhfely9fVsuWLeXicl9nqd+Xbt26qUGDBoqOjrZo37Fjh1JTUy3aw8PDVbhwYW3ZskWStGXLFkVGRiooKMjcJyYmRsnJydq3b1+W67t27ZqSk5MtXgAAAAAA3A+rq+eOHTtq/vz59siSpW+//VY7d+7U6NGjM01LSEiQu7u7/P39LdqDgoKUkJBg7nNr0Z0xPWNaVkaPHi0/Pz/zKzQ01AZbAgAAAAB4HFl9jffo0aPVsGFDrVixQpGRkXJzc7OYPnHiRJuFO3HihN59912tXr1anp6eNlvuvQwcOFC9evUyv09OTqb4BgAAAADcl/sqvFeuXKlSpUpJUqabq9nSjh07dPbsWT399NPmtrS0NG3atEnTpk3TypUrdf36dSUmJlqMep85c0bBwcGSpODgYG3bts1iuRl3Pc/oczsPDw95eHjYdFsAAAAAAI8nqwvvjz76SLNmzVL79u3tEMdSrVq1FBcXZ9HWoUMHhYeHq3///goNDZWbm5vWrl2rpk2bSpIOHTqk48ePKyoqSpIUFRWlkSNH6uzZswoMDJQkrV69Wr6+voqIiLD7NgAAAAAAHm9WF94eHh6qUqWKPbJk4uPjo6eeesqiLU+ePMqXL5+5vWPHjurVq5cCAgLk6+urt99+W1FRUXruueckSXXq1FFERITatGmjcePGKSEhQR988IG6devGqDYAAAAAwO6svrnau+++q6lTp9ojy335+OOP1bBhQzVt2lTVq1dXcHCwFi5caJ7u6uqqZcuWydXVVVFRUXr99dfVtm1bDRs2zIGpAQAAAACPC6tHvLdt26Z169Zp2bJlKlOmTKabq91a9NrDhg0bLN57enpq+vTpmj59+h3nKVKkiH766Se75gIAAAAAICtWF97+/v565ZVX7JEFAAAAAIAcx+rCe/bs2fbIAQAAAABAjmR14Z3hn3/+0aFDhyRJpUqVUoECBWwWCgAAAACAnMLqm6tdunRJb7zxhgoWLKjq1aurevXqCgkJUceOHXX58mV7ZAQAAAAAwGlZXXj36tVLGzdu1H//+18lJiYqMTFRS5Ys0caNG9W7d297ZAQAAAAAwGlZfar5ggUL9MMPP+iFF14wt9WvX19eXl5q3ry5ZsyYYct8AADgMREXf9zREQAAsAurR7wvX76soKCgTO2BgYGcag4AAAAAwG2sLryjoqI0ZMgQXb161dx25coVffjhh4qKirJpOAAAAAAAnJ3Vp5pPnjxZMTExKlSokMqVKydJ2rNnjzw9PbVy5UqbBwQAAAAAwJlZXXg/9dRTOnz4sObOnauDBw9Kklq1aqXWrVvLy8vL5gEBAAAAAHBm9/Uc79y5c6tTp062zgIAAAAAQI5j9TXeo0eP1qxZszK1z5o1S2PHjrVJKAAAAAAAcgqrC+9PP/1U4eHhmdrLlCmjmTNn2iQUAAAAAAA5hdWFd0JCggoWLJipvUCBAjp9+rRNQgEAAAAAkFNYXXiHhoZq8+bNmdo3b96skJAQm4QCAAAAACCnsPrmap06dVKPHj2UmpqqF198UZK0du1a9evXT71797Z5QAAAAAAAnJnVhXffvn117tw5de3aVdevX5ckeXp6qn///ho4cKDNAwIAAAAA4MysLrxNJpPGjh2rQYMG6cCBA/Ly8lLJkiXl4eFhj3wAAAAAADi1+3qOtyR5e3vrmWeesWUWAAAAAAByHKtvrgYAAAAAALKPwhsAAAAAADu671PNAQAAADiPyDmRjo7gcHHt4hwdAY8pRrwBAAAAALAjCm8AAAAAAOyIwhsAAAAAADui8AYAAAAAwI4ovAEAAAAAsCMKbwAAAAAA7IjCGwAAAAAAO6LwBgAAAADAjii8AQAAAACwIwpvAAAAAADsiMIbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOwol6MDAI+zuPjjjo4AAAAAwM4Y8QYAAAAAwI4Y8c5hIudEOjqCw8W1i3N0BAAAAAAwY8QbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALAjrvEGAAAAgEcMT7/JWSi8AQA5Fn+0AACARwGnmgMAAAAAYEcU3gAAAAAA2BGFNwAAAAAAdsQ13jkM1zMCAAAAwKOFEW8AAAAAAOyIwhsAAAAAADviVHMAyCYu5QAAAMD9YMQbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOyIwhsAAAAAADt6pAvv0aNH65lnnpGPj48CAwPVpEkTHTp0yKLP1atX1a1bN+XLl0/e3t5q2rSpzpw5Y9Hn+PHjatCggXLnzq3AwED17dtXN27ceJibAgAAAAB4TD3ShffGjRvVrVs3/frrr1q9erVSU1NVp04dXbp0ydynZ8+e+u9//6v58+dr48aNOnXqlF555RXz9LS0NDVo0EDXr1/XL7/8ojlz5ig2NlaDBw92xCYBAAAAAB4zj/RzvFesWGHxPjY2VoGBgdqxY4eqV6+upKQkffHFF5o3b55efPFFSdLs2bNVunRp/frrr3ruuee0atUq7d+/X2vWrFFQUJDKly+v4cOHq3///ho6dKjc3d0dsWkAAAAAgMfEIz3ifbukpCRJUkBAgCRpx44dSk1NVXR0tLlPeHi4ChcurC1btkiStmzZosjISAUFBZn7xMTEKDk5Wfv27ctyPdeuXVNycrLFCwAAAACA++E0hXd6erp69OihKlWq6KmnnpIkJSQkyN3dXf7+/hZ9g4KClJCQYO5za9GdMT1jWlZGjx4tPz8/8ys0NNTGWwMAAAAAeFw4TeHdrVs3/f777/r222/tvq6BAwcqKSnJ/Dpx4oTd1wkAAAAAyJke6Wu8M3Tv3l3Lli3Tpk2bVKhQIXN7cHCwrl+/rsTERItR7zNnzig4ONjcZ9u2bRbLy7jreUaf23l4eMjDw8PGWwEAAAAAeBw90iPehmGoe/fuWrRokdatW6ewsDCL6RUrVpSbm5vWrl1rbjt06JCOHz+uqKgoSVJUVJTi4uJ09uxZc5/Vq1fL19dXERERD2dDAAAAAACPrUd6xLtbt26aN2+elixZIh8fH/M12X5+fvLy8pKfn586duyoXr16KSAgQL6+vnr77bcVFRWl5557TpJUp04dRUREqE2bNho3bpwSEhL0wQcfqFu3boxqAwAAAADs7pEuvGfMmCFJeuGFFyzaZ8+erfbt20uSPv74Y7m4uKhp06a6du2aYmJi9Mknn5j7urq6atmyZXrrrbcUFRWlPHnyqF27dho2bNjD2gwAAAAAwGPskS68DcO4Zx9PT09Nnz5d06dPv2OfIkWK6KeffrJlNAAAAAAAsuWRvsYbAAAAAABnR+ENAAAAAIAdPdKnmgMAAACwjbj4446OADy2GPEGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOyIwhsAAAAAADui8AYAAAAAwI4ovAEAAAAAsCMKbwAAAAAA7IjCGwAAAAAAO6LwBgAAAADAjii8AQAAAACwIwpvAAAAAADsiMIbAAAAAAA7yuXoALCtolfnOTqCwx11dAAAAB4D/M3B3xwAso8RbwAAAAAA7IjCGwAAAAAAO6LwBgAAAADAjii8AQAAAACwIwpvAAAAAADsiMIbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOyIwhsAAAAAADui8AYAAAAAwI4ovAEAAAAAsCMKbwAAAAAA7CiXowMAAABIUtGr8xwdweGOOjoAAMAuGPEGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOyIwhsAAAAAADui8AYAAAAAwI4ovAEAAAAAsCMKbwAAAAAA7IjCGwAAAAAAO6LwBgAAAADAjii8AQAAAACwIwpvAAAAAADsiMIbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALAjCm8AAAAAAOwol6MDAI+zolfnOTqCwx11dAAAAB4T/N3B3x1wHApvAECOxR+Z/JEJAMCjgFPNAQAAAACwIwpvAAAAAADsiMIbAAAAAAA7ovAGAAAAAMCOuLkaAGQTN+riRl0AAAD3gxFvAAAAAADsiMIbAAAAAAA7ovAGAAAAAMCOKLwBAAAAALCjx6rwnj59uooWLSpPT09VrlxZ27Ztc3QkAAAAAEAO99gU3t9995169eqlIUOGaOfOnSpXrpxiYmJ09uxZR0cDAAAAAORgj03hPXHiRHXq1EkdOnRQRESEZs6cqdy5c2vWrFmOjgYAAAAAyMEei8L7+vXr2rFjh6Kjo81tLi4uio6O1pYtWxyYDAAAAACQ0+VydICH4d9//1VaWpqCgoIs2oOCgnTw4MFM/a9du6Zr166Z3yclJUmSkpOT7RvUBtKvXXZ0BIdzhuOUgePF8XI2znS8JI6Z5FzHjOPF8XI2znS8JI6Z5GTH7Jrh6ASO94gfr4zPk2Hc+1g9FoW3tUaPHq0PP/wwU3toaKgD0sBafpMcnQDW4Hg5F46X8+GYOReOl3PheDkfjpmTGePn6ATZcvHiRfn53T3rY1F458+fX66urjpz5oxF+5kzZxQcHJyp/8CBA9WrVy/z+/T0dJ0/f1758uWTyWSye15nlZycrNDQUJ04cUK+vr6OjoN74Hg5H46Zc+F4OReOl/PhmDkXjpdz4Xhlj2EYunjxokJCQu7Z97EovN3d3VWxYkWtXbtWTZo0kXSzmF67dq26d++eqb+Hh4c8PDws2vz9/R9C0pzB19eXX1AnwvFyPhwz58Lxci4cL+fDMXMuHC/nwvG6t3uNdGd4LApvSerVq5fatWunSpUq6dlnn9WkSZN06dIldejQwdHRAAAAAAA52GNTeLdo0UL//POPBg8erISEBJUvX14rVqzIdMM1AAAAAABs6bEpvCWpe/fuWZ5aDtvw8PDQkCFDMp2mj0cTx8v5cMycC8fLuXC8nA/HzLlwvJwLx8v2TEZ27n0OAAAAAADui4ujAwAAAAAAkJNReAMAAAAAYEcU3gAAAAAA2BGFNx7Y6NGj9cwzz8jHx0eBgYFq0qSJDh065OhYuIOhQ4fKZDJZvMLDwx0dC3eQlpamQYMGKSwsTF5eXipevLiGDx8ubs/x6Ni0aZMaNWqkkJAQmUwmLV682GK6YRgaPHiwChYsKC8vL0VHR+vw4cOOCYt7Hq+FCxeqTp06ypcvn0wmk3bv3u2QnLjpbscrNTVV/fv3V2RkpPLkyaOQkBC1bdtWp06dclxg3PN3bOjQoQoPD1eePHmUN29eRUdHa+vWrY4Ji3ser/bt22f6u7Fu3bqOCevkKLzxwDZu3Khu3brp119/1erVq5Wamqo6dero0qVLjo6GOyhTpoxOnz5tfv3888+OjoQ7GDt2rGbMmKFp06bpwIEDGjt2rMaNG6epU6c6Ohr+f5cuXVK5cuU0ffr0LKePGzdOU6ZM0cyZM7V161blyZNHMTExunr16kNOCunex+vSpUuqWrWqxo4d+5CTISt3O16XL1/Wzp07NWjQIO3cuVMLFy7UoUOH9NJLLzkgKTLc63fsySef1LRp0xQXF6eff/5ZRYsWVZ06dfTPP/885KSQ7n28JKlu3boWfzd+8803DzFhzsFdzWFz//zzjwIDA7Vx40ZVr17d0XFwm6FDh2rx4sWM4jiJhg0bKigoSF988YW5rWnTpvLy8tLXX3/twGTIislk0qJFi9SkSRNJN0e7Q0JC1Lt3b/Xp00eSlJSUpKCgIMXGxqply5YOTIvbj9etjh49qrCwMO3atUvly5d/6NmQ2d2OV4bt27fr2Wef1bFjx1S4cOGHFw5Zys4xS05Olp+fn9asWaNatWo9vHDIJKvj1b59eyUmJmYaCYf1GPGGzSUlJUmSAgICHJwEd3L48GGFhISoWLFiat26tY4fP+7oSLiD559/XmvXrtUff/whSdqzZ49+/vln1atXz8HJkB3x8fFKSEhQdHS0uc3Pz0+VK1fWli1bHJgMyJmSkpJkMpnk7+/v6CjIhuvXr+uzzz6Tn5+fypUr5+g4uIMNGzYoMDBQpUqV0ltvvaVz5845OpJTyuXoAMhZ0tPT1aNHD1WpUkVPPfWUo+MgC5UrV1ZsbKxKlSql06dP68MPP1S1atX0+++/y8fHx9HxcJsBAwYoOTlZ4eHhcnV1VVpamkaOHKnWrVs7OhqyISEhQZIUFBRk0R4UFGSeBsA2rl69qv79+6tVq1by9fV1dBzcxbJly9SyZUtdvnxZBQsW1OrVq5U/f35Hx0IW6tatq1deeUVhYWE6cuSI3nvvPdWrV09btmyRq6uro+M5FQpv2FS3bt30+++/c83wI+zWkdKyZcuqcuXKKlKkiL7//nt17NjRgcmQle+//15z587VvHnzVKZMGe3evVs9evRQSEiI2rVr5+h4APBISE1NVfPmzWUYhmbMmOHoOLiHmjVravfu3fr333/1+eefq3nz5tq6dasCAwMdHQ23ufWSqMjISJUtW1bFixfXhg0buDTASpxqDpvp3r27li1bpvXr16tQoUKOjoNs8vf315NPPqk///zT0VGQhb59+2rAgAFq2bKlIiMj1aZNG/Xs2VOjR492dDRkQ3BwsCTpzJkzFu1nzpwxTwPwYDKK7mPHjmn16tWMdjuBPHnyqESJEnruuef0xRdfKFeuXBb3MsGjq1ixYsqfPz9/N94HCm88MMMw1L17dy1atEjr1q1TWFiYoyPBCikpKTpy5IgKFizo6CjIwuXLl+XiYvlPtaurq9LT0x2UCNYICwtTcHCw1q5da25LTk7W1q1bFRUV5cBkQM6QUXQfPnxYa9asUb58+RwdCfchPT1d165dc3QMZMPff/+tc+fO8XfjfeBUczywbt26ad68eVqyZIl8fHzM1y36+fnJy8vLwelwuz59+qhRo0YqUqSITp06pSFDhsjV1VWtWrVydDRkoVGjRho5cqQKFy6sMmXKaNeuXZo4caLeeOMNR0fD/y8lJcXim//4+Hjt3r1bAQEBKly4sHr06KERI0aoZMmSCgsL06BBgxQSEnLXu/zCfu51vM6fP6/jx4+bnwV96NAhSTfPXuAshYfvbserYMGCevXVV7Vz504tW7ZMaWlp5r9BAgIC5O7u7qjYj7W7HbN8+fJp5MiReumll1SwYEH9+++/mj59uk6ePKlmzZo5MPXj627HKyAgQB9++KGaNm2q4OBgHTlyRP369VOJEiUUExPjwNROygAekKQsX7Nnz3Z0NGShRYsWRsGCBQ13d3fjiSeeMFq0+P/au59X2P44juPvKTNDhpSMH4lIWfgHWKJkpaxu2bCxkIU/QCL/hKU/QUlKKcpC8RcoZStLCwyaz3fzTbnX9b3dOp3x9XjU2ZyZqVedmuZZ5zQ/0vX1dd6z+I37+/u0traWBgYGUnNzcxoeHk7r6+upVqvlPY1/nZycfPgduLi4mFJKqV6vp42NjdTd3Z3K5XKanp5OV1dX+Y7+xv7reu3u7n74+ubmZq67v6vPrtfNzc1vf4OcnJzkPf3b+uyaPT4+pvn5+dTX15dKpVLq7e1Nc3Nz6eLiIu/Z39Zn1+vh4SHNzMykrq6uVCwW0+DgYFpeXk63t7d5z/6S/I83AAAAZMgz3gAAAJAh4Q0AAAAZEt4AAACQIeENAAAAGRLeAAAAkCHhDQAAABkS3gAAAJAh4Q0AAAAZEt4AAACQIeENAPxiaWkpCoVCFAqFKJVKMTIyEtvb2/H6+hqnp6dvr/183N7e5j0dABpOU94DAIDGNDs7G7u7u1Gr1eLw8DBWV1ejWCzGxMRERERcXV1Fe3v7u89Uq9U8pgJAQxPeAMCHyuVy9PT0RETEyspK7O3txf7+/lt4V6vV6OjoyHEhAHwNbjUHAP5IS0tLPD8/5z0DAL4c4Q0AfCqlFMfHx3F0dBRTU1Nv5/v7+6NSqbwdY2NjOa4EgMblVnMA4EMHBwdRqVTi5eUl6vV6LCwsxNbWVlxeXkZExNnZWbS1tb29v1gs5jUVABqa8AYAPjQ5ORk7OztRKpWir68vmpre/2wYGhryjDcA/AHhDQB8qLW1NUZGRvKeAQBfnvAGAP7K3d1dPD09vTvX2dnplnMA+InwBgD+yujo6C/nzs/PY3x8PIc1ANC4CimllPcIAAAA+L/yd2IAAACQIeENAAAAGRLeAAAAkCHhDQAAABkS3gAAAJAh4Q0AAAAZEt4AAACQIeENAAAAGRLeAAAAkCHhDQAAABkS3gAAAJAh4Q0AAAAZ+gfSbNxLi1XNewAAAABJRU5ErkJggg==", + "image/png": 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", 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", 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" ] @@ -166024,13 +166014,23 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 156, "id": "0389888e", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", 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" ] @@ -166042,8 +166042,23 @@ "source": [ "memory_div10 = [m / 10 for m in memory]\n", "plt.figure(figsize=(10, 6))\n", + "plt.bar(ind, comp_real, bar_width, label='Computation')\n", "plt.bar(ind, sending, bar_width, label='Sending')\n", - "plt.bar(ind, comp_real, bar_width, bottom=sending, label='Computation')\n", + "bottoms_div10 = [s + c for s, c in zip(sending, comp_real)]\n", + "# plt.bar(ind, memory_div10, bar_width, bottom=bottoms_div10, label='Memory (÷10)')\n", + "\n", + "plt.xlabel('PE')\n", + "plt.ylabel('comp:ns, sending:flits, memory:bytes')\n", + "plt.title('Real Computation Duration')\n", + "plt.xticks(ind, pes)\n", + "plt.legend()\n", + "plt.tight_layout()\n", + "plt.show()\n", + "\n", + "\n", + "plt.figure(figsize=(10, 6))\n", + "# plt.bar(ind, sending, bar_width, label='Sending')\n", + "plt.bar(ind, comp_real, bar_width, label='Computation')\n", "bottoms_div10 = [s + c for s, c in zip(sending, comp_real)]\n", "# plt.bar(ind, memory_div10, bar_width, bottom=bottoms_div10, label='Memory (÷10)')\n", "\n", diff --git a/LinProg_Scripts/CombinedMapping.txt b/LinProg_Scripts/CombinedMapping.txt index e3d7cdf..d883554 100644 --- a/LinProg_Scripts/CombinedMapping.txt +++ b/LinProg_Scripts/CombinedMapping.txt @@ -1,2 +1,8 @@ -Router 0: Tasks [0, 1, 2, 3, 4, 5] -Router 10: Tasks [10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 6, 7, 8, 9] +Router 0: Tasks [0, 1, 2, 3] +Router 10: Tasks [10, 8, 9] +Router 11: Tasks [11, 12, 13, 14, 15, 16, 7] +Router 17: Tasks [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34] +Router 35: Tasks [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52] +Router 4: Tasks [4, 5, 6] +Router 53: Tasks [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69] +Router 62: Tasks [62, 63, 64] diff --git a/LinProg_Scripts/LinProgResults.json b/LinProg_Scripts/LinProgResults.json index 988ffc9..15ba88b 100644 --- a/LinProg_Scripts/LinProgResults.json +++ b/LinProg_Scripts/LinProgResults.json @@ -4,35 +4,136 @@ 0, 1, 2, - 3, - 4, - 5 + 3 ], "10": [ 10, + 8, + 9 + ], + "11": [ 11, 12, 13, 14, 15, 16, + 7 + ], + "17": [ 17, 18, 19, - 6, - 7, - 8, - 9 + 20, + 21, + 22, + 23, + 24, + 25, + 26, + 27, + 28, + 29, + 30, + 31, + 32, + 33, + 34 + ], + "35": [ + 35, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 51, + 52 + ], + "4": [ + 4, + 5, + 6 + ], + "53": [ + 53, + 54, + 55, + 56, + 57, + 58, + 59, + 60, + 61, + 65, + 66, + 67, + 68, + 69 + ], + "62": [ + 62, + 63, + 64 ] }, "mapping": { - "10": 2, - "0": 3 + "17": 2, + "10": 7, + "35": 1, + "4": 6, + "11": 3, + "53": 0, + "62": 4, + "0": 10 }, "shortest_path": [ + [ + 10, + 6 + ], + [ + 6, + 7 + ], + [ + 7, + 3 + ], [ 3, 2 + ], + [ + 2, + 1 + ], + [ + 1, + 0 + ], + [ + 6, + 2, + 3 + ], + [ + 0, + 4 + ], + [ + 4, + 0 ] ] } \ No newline at end of file diff --git a/LinProg_Scripts/NoC_LinProg.ipynb b/LinProg_Scripts/NoC_LinProg.ipynb index 8567dd4..517c590 100644 --- a/LinProg_Scripts/NoC_LinProg.ipynb +++ b/LinProg_Scripts/NoC_LinProg.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 24, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -44,7 +44,7 @@ " " + "" ] }, "metadata": {}, @@ -231,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -274,39 +274,29 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 34, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Parallel paths between 0 and 56 are [['0', '17', '44', '51', '53', '56'], ['0', '17', '44', '51', '56'], ['0', '17', '46', '51', '53', '56'], ['0', '17', '46', '51', '56'], ['0', '17', '49', '51', '53', '56'], ['0', '17', '49', '51', '56'], ['0', '17', '51', '53', '56'], ['0', '17', '51', '56']]\n", - "Nodes with unequal in and out degree: ['17', '51']\n", - "parallel_paths_edges: [['0', '17', '44', '51', '53', '56'], ['0', '17', '44', '51', '56'], ['0', '17', '46', '51', '53', '56'], ['0', '17', '46', '51', '56'], ['0', '17', '49', '51', '53', '56'], ['0', '17', '49', '51', '56'], ['0', '17', '51', '53', '56'], ['0', '17', '51', '56'], ['56', '59'], ['56', '62'], ['59', '56'], ['62', '56']]\n", - "Nodes with unequal in and out degree: ['56', '59', '17', '62', '51']\n", - "Updated parallel paths after splitting: [['0', '17'], ['17', '44', '51'], ['51', '53', '56'], ['51', '56'], ['17', '46', '51'], ['17', '49', '51'], ['17', '51'], ['56', '59'], ['56', '62'], ['59', '56'], ['62', '56']]\n", - "Path: ['0', '17']\n", + "Parallel paths between 0 and 53 are [['0', '4', '10', '11', '17', '35', '53'], ['0', '4', '11', '17', '35', '53']]\n", + "Nodes with unequal in and out degree: ['4', '11']\n", + "parallel_paths_edges: [['0', '4', '10', '11', '17', '35', '53'], ['0', '4', '11', '17', '35', '53'], ['53', '62'], ['62', '53']]\n", + "Nodes with unequal in and out degree: ['11', '4', '62', '53']\n", + "Updated parallel paths after splitting: [['0', '4'], ['4', '10', '11'], ['11', '17', '35', '53'], ['4', '11'], ['53', '62'], ['62', '53']]\n", + "Path: ['0', '4']\n", "Number of hops: 1\n", - "Path: ['17', '44', '51']\n", + "Path: ['4', '10', '11']\n", "Number of hops: 2\n", - "Path: ['51', '53', '56']\n", - "Number of hops: 2\n", - "Path: ['51', '56']\n", + "Path: ['11', '17', '35', '53']\n", + "Number of hops: 3\n", + "Path: ['4', '11']\n", "Number of hops: 1\n", - "Path: ['17', '46', '51']\n", - "Number of hops: 2\n", - "Path: ['17', '49', '51']\n", - "Number of hops: 2\n", - "Path: ['17', '51']\n", + "Path: ['53', '62']\n", "Number of hops: 1\n", - "Path: ['56', '59']\n", - "Number of hops: 1\n", - "Path: ['56', '62']\n", - "Number of hops: 1\n", - "Path: ['59', '56']\n", - "Number of hops: 1\n", - "Path: ['62', '56']\n", + "Path: ['62', '53']\n", "Number of hops: 1\n" ] } @@ -473,7 +463,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -482,7 +472,7 @@ "text": [ "Set parameter Username\n", "Set parameter LicenseID to value 2631888\n", - "Set parameter TimeLimit to value 600\n", + "Set parameter TimeLimit to value 60\n", "Set parameter LogFile to value \"gurobi.log\"\n", "Set parameter Threads to value 26\n", "Using license file /home/sfischer/Software/gurobi12.0.1_linux64/gurobi1201/gurobi.lic\n", @@ -491,9 +481,9 @@ "Gurobi Optimizer version 12.0.1 build v12.0.1rc0 (linux64 - \"Ubuntu 24.04.2 LTS\")\n", "Copyright (c) 2025, Gurobi Optimization, LLC\n", "\n", - "Read LP format model from file /tmp/ce9d8d8f949044d6883a0af73d25678c-pulp.lp\n", - "Reading time = 0.01 seconds\n", - "OBJ: 9986 rows, 2194 columns, 31714 nonzeros\n", + "Read LP format model from file /tmp/d15c7784f22542d08e6079669283e281-pulp.lp\n", + "Reading time = 0.00 seconds\n", + "OBJ: 4724 rows, 1219 columns, 15780 nonzeros\n", "\n", "Using Gurobi shared library /home/sfischer/Software/gurobi12.0.1_linux64/gurobi1201/linux64/lib/libgurobi.so.12.0.1\n", "\n", @@ -501,2457 +491,1474 @@ "Thread count: 28 physical cores, 28 logical processors, using up to 26 threads\n", "\n", "Non-default parameters:\n", - "TimeLimit 600\n", + "TimeLimit 60\n", "Threads 26\n", "\n", - "Optimize a model with 9986 rows, 2194 columns and 31714 nonzeros\n", - "Model fingerprint: 0x2476eb6c\n", - "Variable types: 0 continuous, 2194 integer (1424 binary)\n", + "Optimize a model with 4724 rows, 1219 columns and 15780 nonzeros\n", + "Model fingerprint: 0x7a0be82e\n", + "Variable types: 0 continuous, 1219 integer (784 binary)\n", "Coefficient statistics:\n", " Matrix range [1e+00, 1e+02]\n", " Objective range [1e+00, 1e+00]\n", " Bounds range [1e+00, 1e+00]\n", " RHS range [1e+00, 1e+02]\n", - "Presolve removed 4209 rows and 279 columns\n", - "Presolve time: 0.03s\n", - "Presolved: 5777 rows, 1915 columns, 21507 nonzeros\n", - "Variable types: 0 continuous, 1915 integer (1712 binary)\n", + "Presolve removed 1513 rows and 125 columns\n", + "Presolve time: 0.02s\n", + "Presolved: 3211 rows, 1094 columns, 11851 nonzeros\n", + "Variable types: 0 continuous, 1094 integer (976 binary)\n", + "Found heuristic solution: objective 22.0000000\n", "\n", - "Root relaxation: objective 1.500000e+01, 717 iterations, 0.01 seconds (0.03 work units)\n", + "Root relaxation: objective 9.000000e+00, 220 iterations, 0.00 seconds (0.01 work units)\n", "\n", " Nodes | Current Node | Objective Bounds | Work\n", " Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time\n", "\n", - " 0 0 15.00000 0 74 - 15.00000 - - 0s\n", - " 0 0 15.00000 0 164 - 15.00000 - - 0s\n", - " 0 0 15.00000 0 250 - 15.00000 - - 0s\n", - " 0 0 15.00000 0 152 - 15.00000 - - 0s\n", - " 0 0 15.00000 0 203 - 15.00000 - - 0s\n", - " 0 0 1.000e+100 0 154 - infeasible - - 0s\n", + " 0 0 9.00000 0 35 22.00000 9.00000 59.1% - 0s\n", + "H 0 0 15.0000000 9.00000 40.0% - 0s\n", + " 0 0 9.00000 0 62 15.00000 9.00000 40.0% - 0s\n", + "H 0 0 12.0000000 9.00000 25.0% - 0s\n", + " 0 0 9.00000 0 80 12.00000 9.00000 25.0% - 0s\n", + "H 0 0 10.0000000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 15 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 26 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 28 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 30 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 25 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 30 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 11 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 35 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 34 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 51 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 72 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 77 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 34 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 64 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 48 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 55 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 40 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 107 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 17 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 116 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 95 10.00000 9.00000 10.0% - 0s\n", + " 0 0 9.00000 0 74 10.00000 9.00000 10.0% - 0s\n", + " 0 2 9.00000 0 25 10.00000 9.00000 10.0% - 0s\n", + " 10311 358 9.00000 31 145 10.00000 9.00000 10.0% 103 5s\n", + " 21829 26 infeasible 14 10.00000 9.00000 10.0% 121 10s\n", "\n", "Cutting planes:\n", - " Learned: 158\n", - " Cover: 113\n", - " Implied bound: 96\n", - " Clique: 89\n", - " MIR: 163\n", - " StrongCG: 9\n", - " Flow cover: 29\n", - " Zero half: 22\n", - " RLT: 57\n", - " Relax-and-lift: 9\n", - " BQP: 9\n", + " Learned: 816\n", + " Gomory: 3\n", + " Cover: 1645\n", + " Implied bound: 195\n", + " Clique: 37\n", + " MIR: 142\n", + " StrongCG: 15\n", + " Flow cover: 87\n", + " Inf proof: 79\n", + " Zero half: 26\n", + " RLT: 53\n", + " Relax-and-lift: 24\n", + " PSD: 1\n", "\n", - "Explored 1 nodes (14350 simplex iterations) in 0.55 seconds (1.18 work units)\n", + "Explored 22445 nodes (2775185 simplex iterations) in 10.85 seconds (20.12 work units)\n", "Thread count was 26 (of 28 available processors)\n", "\n", - "Solution count 0\n", + "Solution count 4: 10 12 15 22 \n", "\n", - "Model is infeasible or unbounded\n", - "Best objective -, best bound -, gap -\n", + "Optimal solution found (tolerance 1.00e-04)\n", + "Best objective 1.000000000000e+01, best bound 1.000000000000e+01, gap 0.0000%\n", "\n", - "Unable to retrieve attribute 'X'\n", + "Wrote result file '/tmp/d15c7784f22542d08e6079669283e281-pulp.sol'\n", "\n", - "Objective value: None\n", - "Problem status: Not Solved\n", - "Position of node (0, 0): None\n", - "Position of node (1, 0): None\n", - "Position of node (2, 0): None\n", - "Position of node (3, 0): None\n", - "Position of node (4, 0): None\n", - "Position of node (5, 0): None\n", - "Position of node (6, 0): None\n", - "Position of node (7, 0): None\n", - "Position of node (8, 0): None\n", - "Position of node (9, 0): None\n", - "Position of node (10, 0): None\n", - "Position of node (0, 1): None\n", - "Position of node (1, 1): None\n", - "Position of node (2, 1): None\n", - "Position of node (3, 1): None\n", - "Position of node (4, 1): None\n", - "Position of node (5, 1): None\n", - "Position of node (6, 1): None\n", - "Position of node (7, 1): None\n", - "Position of node (8, 1): None\n", - "Position of node (9, 1): None\n", - "Position of node (10, 1): None\n", - "Position of node (0, 2): None\n", - "Position of node (1, 2): None\n", - "Position of node (2, 2): None\n", - "Position of node (3, 2): None\n", - "Position of node (4, 2): None\n", - "Position of node (5, 2): None\n", - "Position of node (6, 2): None\n", - "Position of node (7, 2): None\n", - "Position of node (8, 2): None\n", - "Position of node (9, 2): None\n", - "Position of node (10, 2): None\n", - "Position of node (0, 3): None\n", - "Position of node (1, 3): None\n", - "Position of node (2, 3): None\n", - "Position of node (3, 3): None\n", - "Position of node (4, 3): None\n", - "Position of node (5, 3): None\n", - "Position of node (6, 3): None\n", - "Position of node (7, 3): None\n", - "Position of node (8, 3): None\n", - "Position of node (9, 3): None\n", - "Position of node (10, 3): None\n", - "Position of node (0, 4): None\n", - "Position of node (1, 4): None\n", - "Position of node (2, 4): None\n", - "Position of node (3, 4): None\n", - "Position of node (4, 4): None\n", - "Position of node (5, 4): None\n", - "Position of node (6, 4): None\n", - "Position of node (7, 4): None\n", - "Position of node (8, 4): None\n", - "Position of node (9, 4): None\n", - "Position of node (10, 4): None\n", - "Position of node (0, 5): None\n", - "Position of node (1, 5): None\n", - "Position of node (2, 5): None\n", - "Position of node (3, 5): None\n", - "Position of node (4, 5): None\n", - "Position of node (5, 5): None\n", - "Position of node (6, 5): None\n", - "Position of node (7, 5): None\n", - "Position of node (8, 5): None\n", - "Position of node (9, 5): None\n", - "Position of node (10, 5): None\n", - "Position of node (0, 6): None\n", - "Position of node (1, 6): None\n", - "Position of node (2, 6): None\n", - "Position of node (3, 6): None\n", - "Position of node (4, 6): None\n", - "Position of node (5, 6): None\n", - "Position of node (6, 6): None\n", - "Position of node (7, 6): None\n", - "Position of node (8, 6): None\n", - "Position of node (9, 6): None\n", - "Position of node (10, 6): None\n", - "Position of node (0, 7): None\n", - "Position of node (1, 7): None\n", - "Position of node (2, 7): None\n", - "Position of node (3, 7): None\n", - "Position of node (4, 7): None\n", - "Position of node (5, 7): None\n", - "Position of node (6, 7): None\n", - "Position of node (7, 7): None\n", - "Position of node (8, 7): None\n", - "Position of node (9, 7): None\n", - "Position of node (10, 7): None\n", - "Position of node (0, 8): None\n", - "Position of node (1, 8): None\n", - "Position of node (2, 8): None\n", - "Position of node (3, 8): None\n", - "Position of node (4, 8): None\n", - "Position of node (5, 8): None\n", - "Position of node (6, 8): None\n", - "Position of node (7, 8): None\n", - "Position of node (8, 8): None\n", - "Position of node (9, 8): None\n", - "Position of node (10, 8): None\n", - "Position of node (0, 9): None\n", - "Position of node (1, 9): None\n", - "Position of node (2, 9): None\n", - "Position of node (3, 9): None\n", - "Position of node (4, 9): None\n", - "Position of node (5, 9): None\n", - "Position of node (6, 9): None\n", - "Position of node (7, 9): None\n", - "Position of node (8, 9): None\n", - "Position of node (9, 9): None\n", - "Position of node (10, 9): None\n", - "Position of node (0, 10): None\n", - "Position of node (1, 10): None\n", - "Position of node (2, 10): None\n", - "Position of node (3, 10): None\n", - "Position of node (4, 10): None\n", - "Position of node (5, 10): None\n", - "Position of node (6, 10): None\n", - "Position of node (7, 10): None\n", - "Position of node (8, 10): None\n", - "Position of node (9, 10): None\n", - "Position of node (10, 10): None\n", - "Position of node (0, 11): None\n", - "Position of node (1, 11): None\n", - "Position of node (2, 11): None\n", - "Position of node (3, 11): None\n", - "Position of node (4, 11): None\n", - "Position of node (5, 11): None\n", - "Position of node (6, 11): None\n", - "Position of node (7, 11): None\n", - "Position of node (8, 11): None\n", - "Position of node (9, 11): None\n", - "Position of node (10, 11): None\n", - "Position of node (0, 12): None\n", - "Position of node (1, 12): None\n", - "Position of node (2, 12): None\n", - "Position of node (3, 12): None\n", - "Position of node (4, 12): None\n", - "Position of node (5, 12): None\n", - "Position of node (6, 12): None\n", - "Position of node (7, 12): None\n", - "Position of node (8, 12): None\n", - "Position of node (9, 12): None\n", - "Position of node (10, 12): None\n", - "Position of node (0, 13): None\n", - "Position of node (1, 13): None\n", - "Position of node (2, 13): None\n", - "Position of node (3, 13): None\n", - "Position of node (4, 13): None\n", - "Position of node (5, 13): None\n", - "Position of node (6, 13): None\n", - "Position of node (7, 13): None\n", - "Position of node (8, 13): None\n", - "Position of node (9, 13): None\n", - "Position of node (10, 13): None\n", - "Position of node (0, 14): None\n", - "Position of node (1, 14): None\n", - "Position of node (2, 14): None\n", - "Position of node (3, 14): None\n", - "Position of node (4, 14): None\n", - "Position of node (5, 14): None\n", - "Position of node (6, 14): None\n", - "Position of node (7, 14): None\n", - "Position of node (8, 14): None\n", - "Position of node (9, 14): None\n", - "Position of node (10, 14): None\n", - "Position of node (0, 15): None\n", - "Position of node (1, 15): None\n", - "Position of node (2, 15): None\n", - "Position of node (3, 15): None\n", - "Position of node (4, 15): None\n", - "Position of node (5, 15): None\n", - "Position of node (6, 15): None\n", - "Position of node (7, 15): None\n", - "Position of node (8, 15): None\n", - "Position of node (9, 15): None\n", - "Position of node (10, 15): None\n", - "Source position (src_0): None\n", - "Source position (src_1): None\n", - "Source position (src_2): None\n", - "Source position (src_3): None\n", - "Source position (src_4): None\n", - "Source position (src_5): None\n", - "Source position (src_6): None\n", - "Source position (src_7): None\n", - "Source position (src_8): None\n", - "Source position (src_9): None\n", - "Source position (src_10): None\n", - "Destination position (dst_0): None\n", - "Destination position (dst_1): None\n", - "Destination position (dst_2): None\n", - "Destination position (dst_3): None\n", - "Destination position (dst_4): None\n", - "Destination position (dst_5): None\n", - "Destination position (dst_6): None\n", - "Destination position (dst_7): None\n", - "Destination position (dst_8): None\n", - "Destination position (dst_9): None\n", - "Destination position (dst_10): None\n", - "choose_mid_0_node0 = None\n", - "choose_mid_0_node1 = None\n", - "choose_mid_0_node10 = None\n", - "choose_mid_0_node11 = None\n", - "choose_mid_0_node12 = None\n", - "choose_mid_0_node13 = None\n", - "choose_mid_0_node14 = None\n", - "choose_mid_0_node15 = None\n", - "choose_mid_0_node2 = None\n", - "choose_mid_0_node3 = None\n", - "choose_mid_0_node4 = None\n", - "choose_mid_0_node5 = None\n", - "choose_mid_0_node6 = None\n", - "choose_mid_0_node7 = None\n", - "choose_mid_0_node8 = None\n", - "choose_mid_0_node9 = None\n", - "choose_mid_10_node0 = None\n", - "choose_mid_10_node1 = None\n", - "choose_mid_10_node10 = None\n", - "choose_mid_10_node11 = None\n", - "choose_mid_10_node12 = None\n", - "choose_mid_10_node13 = None\n", - "choose_mid_10_node14 = None\n", - "choose_mid_10_node15 = None\n", - "choose_mid_10_node2 = None\n", - "choose_mid_10_node3 = None\n", - "choose_mid_10_node4 = None\n", - "choose_mid_10_node5 = None\n", - "choose_mid_10_node6 = None\n", - "choose_mid_10_node7 = None\n", - "choose_mid_10_node8 = None\n", - "choose_mid_10_node9 = None\n", - "choose_mid_1_node0 = None\n", - "choose_mid_1_node1 = None\n", - "choose_mid_1_node10 = None\n", - "choose_mid_1_node11 = None\n", - "choose_mid_1_node12 = None\n", - "choose_mid_1_node13 = None\n", - "choose_mid_1_node14 = None\n", - "choose_mid_1_node15 = None\n", - "choose_mid_1_node2 = None\n", - "choose_mid_1_node3 = None\n", - "choose_mid_1_node4 = None\n", - "choose_mid_1_node5 = None\n", - "choose_mid_1_node6 = None\n", - "choose_mid_1_node7 = None\n", - "choose_mid_1_node8 = None\n", - "choose_mid_1_node9 = None\n", - "choose_mid_2_node0 = None\n", - "choose_mid_2_node1 = None\n", - "choose_mid_2_node10 = None\n", - "choose_mid_2_node11 = None\n", - "choose_mid_2_node12 = None\n", - "choose_mid_2_node13 = None\n", - "choose_mid_2_node14 = None\n", - "choose_mid_2_node15 = None\n", - "choose_mid_2_node2 = None\n", - "choose_mid_2_node3 = None\n", - "choose_mid_2_node4 = None\n", - "choose_mid_2_node5 = None\n", - "choose_mid_2_node6 = None\n", - "choose_mid_2_node7 = None\n", - "choose_mid_2_node8 = None\n", - "choose_mid_2_node9 = None\n", - "choose_mid_3_node0 = None\n", - "choose_mid_3_node1 = None\n", - "choose_mid_3_node10 = None\n", - "choose_mid_3_node11 = None\n", - "choose_mid_3_node12 = None\n", - "choose_mid_3_node13 = None\n", - "choose_mid_3_node14 = None\n", - "choose_mid_3_node15 = None\n", - "choose_mid_3_node2 = None\n", - "choose_mid_3_node3 = None\n", - "choose_mid_3_node4 = None\n", - "choose_mid_3_node5 = None\n", - "choose_mid_3_node6 = None\n", - "choose_mid_3_node7 = None\n", - "choose_mid_3_node8 = None\n", - "choose_mid_3_node9 = None\n", - "choose_mid_4_node0 = None\n", - "choose_mid_4_node1 = None\n", - "choose_mid_4_node10 = None\n", - "choose_mid_4_node11 = None\n", - "choose_mid_4_node12 = None\n", - "choose_mid_4_node13 = None\n", - "choose_mid_4_node14 = None\n", - "choose_mid_4_node15 = None\n", - "choose_mid_4_node2 = None\n", - "choose_mid_4_node3 = None\n", - "choose_mid_4_node4 = None\n", - "choose_mid_4_node5 = None\n", - "choose_mid_4_node6 = None\n", - "choose_mid_4_node7 = None\n", - "choose_mid_4_node8 = None\n", - "choose_mid_4_node9 = None\n", - "choose_mid_5_node0 = None\n", - "choose_mid_5_node1 = None\n", - "choose_mid_5_node10 = None\n", - "choose_mid_5_node11 = None\n", - "choose_mid_5_node12 = None\n", - "choose_mid_5_node13 = None\n", - "choose_mid_5_node14 = None\n", - "choose_mid_5_node15 = None\n", - "choose_mid_5_node2 = None\n", - "choose_mid_5_node3 = None\n", - "choose_mid_5_node4 = None\n", - "choose_mid_5_node5 = None\n", - "choose_mid_5_node6 = None\n", - "choose_mid_5_node7 = None\n", - "choose_mid_5_node8 = None\n", - "choose_mid_5_node9 = None\n", - "choose_mid_6_node0 = None\n", - "choose_mid_6_node1 = None\n", - "choose_mid_6_node10 = None\n", - "choose_mid_6_node11 = None\n", - "choose_mid_6_node12 = None\n", - "choose_mid_6_node13 = None\n", - "choose_mid_6_node14 = None\n", - "choose_mid_6_node15 = None\n", - "choose_mid_6_node2 = None\n", - "choose_mid_6_node3 = None\n", - "choose_mid_6_node4 = None\n", - "choose_mid_6_node5 = None\n", - "choose_mid_6_node6 = None\n", - "choose_mid_6_node7 = None\n", - "choose_mid_6_node8 = None\n", - "choose_mid_6_node9 = None\n", - "choose_mid_7_node0 = None\n", - "choose_mid_7_node1 = None\n", - "choose_mid_7_node10 = None\n", - "choose_mid_7_node11 = None\n", - "choose_mid_7_node12 = None\n", - "choose_mid_7_node13 = None\n", - "choose_mid_7_node14 = None\n", - "choose_mid_7_node15 = None\n", - "choose_mid_7_node2 = None\n", - "choose_mid_7_node3 = None\n", - "choose_mid_7_node4 = None\n", - "choose_mid_7_node5 = None\n", - "choose_mid_7_node6 = None\n", - "choose_mid_7_node7 = None\n", - "choose_mid_7_node8 = None\n", - "choose_mid_7_node9 = None\n", - "choose_mid_8_node0 = None\n", - "choose_mid_8_node1 = None\n", - "choose_mid_8_node10 = None\n", - "choose_mid_8_node11 = None\n", - "choose_mid_8_node12 = None\n", - "choose_mid_8_node13 = None\n", - "choose_mid_8_node14 = None\n", - "choose_mid_8_node15 = None\n", - "choose_mid_8_node2 = None\n", - "choose_mid_8_node3 = None\n", - "choose_mid_8_node4 = None\n", - "choose_mid_8_node5 = None\n", - "choose_mid_8_node6 = None\n", - "choose_mid_8_node7 = None\n", - "choose_mid_8_node8 = None\n", - "choose_mid_8_node9 = None\n", - "choose_mid_9_node0 = None\n", - "choose_mid_9_node1 = None\n", - "choose_mid_9_node10 = None\n", - "choose_mid_9_node11 = None\n", - "choose_mid_9_node12 = None\n", - "choose_mid_9_node13 = None\n", - "choose_mid_9_node14 = None\n", - "choose_mid_9_node15 = None\n", - "choose_mid_9_node2 = None\n", - "choose_mid_9_node3 = None\n", - "choose_mid_9_node4 = None\n", - "choose_mid_9_node5 = None\n", - "choose_mid_9_node6 = None\n", - "choose_mid_9_node7 = None\n", - "choose_mid_9_node8 = None\n", - "choose_mid_9_node9 = None\n", - "dst_0_0 = None\n", - "dst_0_1 = None\n", - "dst_0_10 = None\n", - "dst_0_11 = None\n", - "dst_0_12 = None\n", - "dst_0_13 = None\n", - "dst_0_14 = None\n", - "dst_0_15 = None\n", - "dst_0_2 = None\n", - "dst_0_3 = None\n", - "dst_0_4 = None\n", - "dst_0_5 = None\n", - "dst_0_6 = None\n", - "dst_0_7 = None\n", - "dst_0_8 = None\n", - "dst_0_9 = None\n", - "dst_10_0 = None\n", - "dst_10_1 = None\n", - "dst_10_10 = None\n", - "dst_10_11 = None\n", - "dst_10_12 = None\n", - "dst_10_13 = None\n", - "dst_10_14 = None\n", - "dst_10_15 = None\n", - "dst_10_2 = None\n", - "dst_10_3 = None\n", - "dst_10_4 = None\n", - "dst_10_5 = None\n", - "dst_10_6 = None\n", - "dst_10_7 = None\n", - "dst_10_8 = None\n", - "dst_10_9 = None\n", - "dst_1_0 = None\n", - "dst_1_1 = None\n", - "dst_1_10 = None\n", - "dst_1_11 = None\n", - "dst_1_12 = None\n", - "dst_1_13 = None\n", - "dst_1_14 = None\n", - "dst_1_15 = None\n", - "dst_1_2 = None\n", - "dst_1_3 = None\n", - "dst_1_4 = None\n", - "dst_1_5 = None\n", - "dst_1_6 = None\n", - "dst_1_7 = None\n", - "dst_1_8 = None\n", - "dst_1_9 = None\n", - "dst_2_0 = None\n", - "dst_2_1 = None\n", - "dst_2_10 = None\n", - "dst_2_11 = None\n", - "dst_2_12 = None\n", - "dst_2_13 = None\n", - "dst_2_14 = None\n", - "dst_2_15 = None\n", - "dst_2_2 = None\n", - "dst_2_3 = None\n", - "dst_2_4 = None\n", - "dst_2_5 = None\n", - "dst_2_6 = None\n", - "dst_2_7 = None\n", - "dst_2_8 = None\n", - "dst_2_9 = None\n", - "dst_3_0 = None\n", - "dst_3_1 = None\n", - "dst_3_10 = None\n", - "dst_3_11 = None\n", - "dst_3_12 = None\n", - "dst_3_13 = None\n", - "dst_3_14 = None\n", - "dst_3_15 = None\n", - "dst_3_2 = None\n", - "dst_3_3 = None\n", - "dst_3_4 = None\n", - "dst_3_5 = None\n", - "dst_3_6 = None\n", - "dst_3_7 = None\n", - "dst_3_8 = None\n", - "dst_3_9 = None\n", - "dst_4_0 = None\n", - "dst_4_1 = None\n", - "dst_4_10 = None\n", - "dst_4_11 = None\n", - "dst_4_12 = None\n", - "dst_4_13 = None\n", - "dst_4_14 = None\n", - "dst_4_15 = None\n", - "dst_4_2 = None\n", - "dst_4_3 = None\n", - "dst_4_4 = None\n", - "dst_4_5 = None\n", - "dst_4_6 = None\n", - "dst_4_7 = None\n", - "dst_4_8 = None\n", - "dst_4_9 = None\n", - "dst_5_0 = None\n", - "dst_5_1 = None\n", - "dst_5_10 = None\n", - "dst_5_11 = None\n", - "dst_5_12 = None\n", - "dst_5_13 = None\n", - "dst_5_14 = None\n", - "dst_5_15 = None\n", - "dst_5_2 = None\n", - "dst_5_3 = None\n", - "dst_5_4 = None\n", - "dst_5_5 = None\n", - "dst_5_6 = None\n", - "dst_5_7 = None\n", - "dst_5_8 = None\n", - "dst_5_9 = None\n", - "dst_6_0 = None\n", - "dst_6_1 = None\n", - "dst_6_10 = None\n", - "dst_6_11 = None\n", - "dst_6_12 = None\n", - "dst_6_13 = None\n", - "dst_6_14 = None\n", - "dst_6_15 = None\n", - "dst_6_2 = None\n", - "dst_6_3 = None\n", - "dst_6_4 = None\n", - "dst_6_5 = None\n", - "dst_6_6 = None\n", - "dst_6_7 = None\n", - "dst_6_8 = None\n", - "dst_6_9 = None\n", - "dst_7_0 = None\n", - "dst_7_1 = None\n", - "dst_7_10 = None\n", - "dst_7_11 = None\n", - "dst_7_12 = None\n", - "dst_7_13 = None\n", - "dst_7_14 = None\n", - "dst_7_15 = None\n", - "dst_7_2 = None\n", - "dst_7_3 = None\n", - "dst_7_4 = None\n", - "dst_7_5 = None\n", - "dst_7_6 = None\n", - "dst_7_7 = None\n", - "dst_7_8 = None\n", - "dst_7_9 = None\n", - "dst_8_0 = None\n", - "dst_8_1 = None\n", - "dst_8_10 = None\n", - "dst_8_11 = None\n", - "dst_8_12 = None\n", - "dst_8_13 = None\n", - "dst_8_14 = None\n", - "dst_8_15 = None\n", - "dst_8_2 = None\n", - "dst_8_3 = None\n", - "dst_8_4 = None\n", - "dst_8_5 = None\n", - "dst_8_6 = None\n", - "dst_8_7 = None\n", - "dst_8_8 = None\n", - "dst_8_9 = None\n", - "dst_9_0 = None\n", - "dst_9_1 = None\n", - "dst_9_10 = None\n", - "dst_9_11 = None\n", - "dst_9_12 = None\n", - "dst_9_13 = None\n", - "dst_9_14 = None\n", - "dst_9_15 = None\n", - "dst_9_2 = None\n", - "dst_9_3 = None\n", - "dst_9_4 = None\n", - "dst_9_5 = None\n", - "dst_9_6 = None\n", - "dst_9_7 = None\n", - "dst_9_8 = None\n", - "dst_9_9 = None\n", - "edge_0_0_1 = None\n", - "edge_0_0_4 = None\n", - "edge_0_10_11 = None\n", - "edge_0_10_14 = None\n", - "edge_0_10_6 = None\n", - "edge_0_10_9 = None\n", - "edge_0_11_10 = None\n", - "edge_0_11_15 = None\n", - "edge_0_11_7 = None\n", - "edge_0_12_13 = None\n", - "edge_0_12_8 = None\n", - "edge_0_13_12 = None\n", - "edge_0_13_14 = None\n", - "edge_0_13_9 = None\n", - "edge_0_14_10 = None\n", - "edge_0_14_13 = None\n", - "edge_0_14_15 = None\n", - "edge_0_15_11 = None\n", - "edge_0_15_14 = None\n", - "edge_0_1_0 = None\n", - "edge_0_1_2 = None\n", - "edge_0_1_5 = None\n", - "edge_0_2_1 = None\n", - "edge_0_2_3 = None\n", - "edge_0_2_6 = None\n", - "edge_0_3_2 = None\n", - "edge_0_3_7 = None\n", - "edge_0_4_0 = None\n", - "edge_0_4_5 = None\n", - "edge_0_4_8 = None\n", - "edge_0_5_1 = None\n", - "edge_0_5_4 = None\n", - "edge_0_5_6 = None\n", - "edge_0_5_9 = None\n", - "edge_0_6_10 = None\n", - "edge_0_6_2 = None\n", - "edge_0_6_5 = None\n", - "edge_0_6_7 = None\n", - "edge_0_7_11 = None\n", - "edge_0_7_3 = None\n", - "edge_0_7_6 = None\n", - "edge_0_8_12 = None\n", - "edge_0_8_4 = None\n", - "edge_0_8_9 = None\n", - "edge_0_9_10 = None\n", - "edge_0_9_13 = None\n", - "edge_0_9_5 = None\n", - "edge_0_9_8 = None\n", - "edge_10_0_1 = None\n", - "edge_10_0_4 = None\n", - "edge_10_10_11 = None\n", - "edge_10_10_14 = None\n", - "edge_10_10_6 = None\n", - "edge_10_10_9 = None\n", - "edge_10_11_10 = None\n", - "edge_10_11_15 = None\n", - "edge_10_11_7 = None\n", - "edge_10_12_13 = None\n", - "edge_10_12_8 = None\n", - "edge_10_13_12 = None\n", - "edge_10_13_14 = None\n", - "edge_10_13_9 = None\n", - "edge_10_14_10 = None\n", - "edge_10_14_13 = None\n", - "edge_10_14_15 = None\n", - "edge_10_15_11 = None\n", - "edge_10_15_14 = None\n", - "edge_10_1_0 = None\n", - "edge_10_1_2 = None\n", - "edge_10_1_5 = None\n", - "edge_10_2_1 = None\n", - "edge_10_2_3 = None\n", - "edge_10_2_6 = None\n", - "edge_10_3_2 = None\n", - "edge_10_3_7 = None\n", - "edge_10_4_0 = None\n", - "edge_10_4_5 = None\n", - "edge_10_4_8 = None\n", - "edge_10_5_1 = None\n", - "edge_10_5_4 = None\n", - "edge_10_5_6 = None\n", - "edge_10_5_9 = None\n", - "edge_10_6_10 = None\n", - "edge_10_6_2 = None\n", - "edge_10_6_5 = None\n", - "edge_10_6_7 = None\n", - "edge_10_7_11 = None\n", - "edge_10_7_3 = None\n", - "edge_10_7_6 = None\n", - "edge_10_8_12 = None\n", - "edge_10_8_4 = None\n", - "edge_10_8_9 = None\n", - "edge_10_9_10 = None\n", - "edge_10_9_13 = None\n", - "edge_10_9_5 = None\n", - "edge_10_9_8 = None\n", - "edge_1_0_1 = None\n", - "edge_1_0_4 = None\n", - "edge_1_10_11 = None\n", - "edge_1_10_14 = None\n", - "edge_1_10_6 = None\n", - "edge_1_10_9 = None\n", - "edge_1_11_10 = None\n", - "edge_1_11_15 = None\n", - "edge_1_11_7 = None\n", - "edge_1_12_13 = None\n", - "edge_1_12_8 = None\n", - "edge_1_13_12 = None\n", - "edge_1_13_14 = None\n", - "edge_1_13_9 = None\n", - "edge_1_14_10 = None\n", - "edge_1_14_13 = None\n", - "edge_1_14_15 = None\n", - "edge_1_15_11 = None\n", - "edge_1_15_14 = None\n", - "edge_1_1_0 = None\n", - "edge_1_1_2 = None\n", - "edge_1_1_5 = None\n", - "edge_1_2_1 = None\n", - "edge_1_2_3 = None\n", - "edge_1_2_6 = None\n", - "edge_1_3_2 = None\n", - "edge_1_3_7 = None\n", - "edge_1_4_0 = None\n", - "edge_1_4_5 = None\n", - "edge_1_4_8 = None\n", - "edge_1_5_1 = None\n", - "edge_1_5_4 = None\n", - "edge_1_5_6 = None\n", - "edge_1_5_9 = None\n", - "edge_1_6_10 = None\n", - "edge_1_6_2 = None\n", - "edge_1_6_5 = None\n", - "edge_1_6_7 = None\n", - "edge_1_7_11 = None\n", - "edge_1_7_3 = None\n", - "edge_1_7_6 = None\n", - "edge_1_8_12 = None\n", - "edge_1_8_4 = None\n", - "edge_1_8_9 = None\n", - "edge_1_9_10 = None\n", - "edge_1_9_13 = None\n", - "edge_1_9_5 = None\n", - "edge_1_9_8 = None\n", - "edge_2_0_1 = None\n", - "edge_2_0_4 = None\n", - "edge_2_10_11 = None\n", - "edge_2_10_14 = None\n", - "edge_2_10_6 = None\n", - "edge_2_10_9 = None\n", - "edge_2_11_10 = None\n", - "edge_2_11_15 = None\n", - "edge_2_11_7 = None\n", - "edge_2_12_13 = None\n", - "edge_2_12_8 = None\n", - "edge_2_13_12 = None\n", - "edge_2_13_14 = None\n", - "edge_2_13_9 = None\n", - "edge_2_14_10 = None\n", - "edge_2_14_13 = None\n", - "edge_2_14_15 = None\n", - "edge_2_15_11 = None\n", - "edge_2_15_14 = None\n", - "edge_2_1_0 = None\n", - "edge_2_1_2 = None\n", - "edge_2_1_5 = None\n", - "edge_2_2_1 = None\n", - "edge_2_2_3 = None\n", - "edge_2_2_6 = None\n", - "edge_2_3_2 = None\n", - "edge_2_3_7 = None\n", - "edge_2_4_0 = None\n", - "edge_2_4_5 = None\n", - "edge_2_4_8 = None\n", - "edge_2_5_1 = None\n", - "edge_2_5_4 = None\n", - "edge_2_5_6 = None\n", - "edge_2_5_9 = None\n", - "edge_2_6_10 = None\n", - "edge_2_6_2 = None\n", - "edge_2_6_5 = None\n", - "edge_2_6_7 = None\n", - "edge_2_7_11 = None\n", - "edge_2_7_3 = None\n", - "edge_2_7_6 = None\n", - "edge_2_8_12 = None\n", - "edge_2_8_4 = None\n", - "edge_2_8_9 = None\n", - "edge_2_9_10 = None\n", - "edge_2_9_13 = None\n", - "edge_2_9_5 = None\n", - "edge_2_9_8 = None\n", - "edge_3_0_1 = None\n", - "edge_3_0_4 = None\n", - "edge_3_10_11 = None\n", - "edge_3_10_14 = None\n", - "edge_3_10_6 = None\n", - "edge_3_10_9 = None\n", - "edge_3_11_10 = None\n", - "edge_3_11_15 = None\n", - "edge_3_11_7 = None\n", - "edge_3_12_13 = None\n", - "edge_3_12_8 = None\n", - "edge_3_13_12 = None\n", - "edge_3_13_14 = None\n", - "edge_3_13_9 = None\n", - "edge_3_14_10 = None\n", - "edge_3_14_13 = None\n", - "edge_3_14_15 = None\n", - "edge_3_15_11 = None\n", - "edge_3_15_14 = None\n", - "edge_3_1_0 = None\n", - "edge_3_1_2 = None\n", - "edge_3_1_5 = None\n", - "edge_3_2_1 = None\n", - "edge_3_2_3 = None\n", - "edge_3_2_6 = None\n", - "edge_3_3_2 = None\n", - "edge_3_3_7 = None\n", - "edge_3_4_0 = None\n", - "edge_3_4_5 = None\n", - "edge_3_4_8 = None\n", - "edge_3_5_1 = None\n", - "edge_3_5_4 = None\n", - "edge_3_5_6 = None\n", - "edge_3_5_9 = None\n", - "edge_3_6_10 = None\n", - "edge_3_6_2 = None\n", - "edge_3_6_5 = None\n", - "edge_3_6_7 = None\n", - "edge_3_7_11 = None\n", - "edge_3_7_3 = None\n", - "edge_3_7_6 = None\n", - "edge_3_8_12 = None\n", - "edge_3_8_4 = None\n", - "edge_3_8_9 = None\n", - "edge_3_9_10 = None\n", - "edge_3_9_13 = None\n", - "edge_3_9_5 = None\n", - "edge_3_9_8 = None\n", - "edge_4_0_1 = None\n", - "edge_4_0_4 = None\n", - "edge_4_10_11 = None\n", - "edge_4_10_14 = None\n", - "edge_4_10_6 = None\n", - "edge_4_10_9 = None\n", - "edge_4_11_10 = None\n", - "edge_4_11_15 = None\n", - "edge_4_11_7 = None\n", - "edge_4_12_13 = None\n", - "edge_4_12_8 = None\n", - "edge_4_13_12 = None\n", - "edge_4_13_14 = None\n", - "edge_4_13_9 = None\n", - "edge_4_14_10 = None\n", - "edge_4_14_13 = None\n", - "edge_4_14_15 = None\n", - "edge_4_15_11 = None\n", - "edge_4_15_14 = None\n", - "edge_4_1_0 = None\n", - "edge_4_1_2 = None\n", - "edge_4_1_5 = None\n", - "edge_4_2_1 = None\n", - "edge_4_2_3 = None\n", - "edge_4_2_6 = None\n", - "edge_4_3_2 = None\n", - "edge_4_3_7 = None\n", - "edge_4_4_0 = None\n", - "edge_4_4_5 = None\n", - "edge_4_4_8 = None\n", - "edge_4_5_1 = None\n", - "edge_4_5_4 = None\n", - "edge_4_5_6 = None\n", - "edge_4_5_9 = None\n", - "edge_4_6_10 = None\n", - "edge_4_6_2 = None\n", - "edge_4_6_5 = None\n", - "edge_4_6_7 = None\n", - "edge_4_7_11 = None\n", - "edge_4_7_3 = None\n", - "edge_4_7_6 = None\n", - "edge_4_8_12 = None\n", - "edge_4_8_4 = None\n", - "edge_4_8_9 = None\n", - "edge_4_9_10 = None\n", - "edge_4_9_13 = None\n", - "edge_4_9_5 = None\n", - "edge_4_9_8 = None\n", - "edge_5_0_1 = None\n", - "edge_5_0_4 = None\n", - "edge_5_10_11 = None\n", - "edge_5_10_14 = None\n", - "edge_5_10_6 = None\n", - "edge_5_10_9 = None\n", - "edge_5_11_10 = None\n", - "edge_5_11_15 = None\n", - "edge_5_11_7 = None\n", - "edge_5_12_13 = None\n", - "edge_5_12_8 = None\n", - "edge_5_13_12 = None\n", - "edge_5_13_14 = None\n", - "edge_5_13_9 = None\n", - "edge_5_14_10 = None\n", - "edge_5_14_13 = None\n", - "edge_5_14_15 = None\n", - "edge_5_15_11 = None\n", - "edge_5_15_14 = None\n", - "edge_5_1_0 = None\n", - "edge_5_1_2 = None\n", - "edge_5_1_5 = None\n", - "edge_5_2_1 = None\n", - "edge_5_2_3 = None\n", - "edge_5_2_6 = None\n", - "edge_5_3_2 = None\n", - "edge_5_3_7 = None\n", - "edge_5_4_0 = None\n", - "edge_5_4_5 = None\n", - "edge_5_4_8 = None\n", - "edge_5_5_1 = None\n", - "edge_5_5_4 = None\n", - "edge_5_5_6 = None\n", - "edge_5_5_9 = None\n", - "edge_5_6_10 = None\n", - "edge_5_6_2 = None\n", - "edge_5_6_5 = None\n", - "edge_5_6_7 = None\n", - "edge_5_7_11 = None\n", - "edge_5_7_3 = None\n", - "edge_5_7_6 = None\n", - "edge_5_8_12 = None\n", - "edge_5_8_4 = None\n", - "edge_5_8_9 = None\n", - "edge_5_9_10 = None\n", - "edge_5_9_13 = None\n", - "edge_5_9_5 = None\n", - "edge_5_9_8 = None\n", - "edge_6_0_1 = None\n", - "edge_6_0_4 = None\n", - "edge_6_10_11 = None\n", - "edge_6_10_14 = None\n", - "edge_6_10_6 = None\n", - "edge_6_10_9 = None\n", - "edge_6_11_10 = None\n", - "edge_6_11_15 = None\n", - "edge_6_11_7 = None\n", - "edge_6_12_13 = None\n", - "edge_6_12_8 = None\n", - "edge_6_13_12 = None\n", - "edge_6_13_14 = None\n", - "edge_6_13_9 = None\n", - "edge_6_14_10 = None\n", - "edge_6_14_13 = None\n", - "edge_6_14_15 = None\n", - "edge_6_15_11 = None\n", - "edge_6_15_14 = None\n", - "edge_6_1_0 = None\n", - "edge_6_1_2 = None\n", - "edge_6_1_5 = None\n", - "edge_6_2_1 = None\n", - "edge_6_2_3 = None\n", - "edge_6_2_6 = None\n", - "edge_6_3_2 = None\n", - "edge_6_3_7 = None\n", - "edge_6_4_0 = None\n", - "edge_6_4_5 = None\n", - "edge_6_4_8 = None\n", - "edge_6_5_1 = None\n", - "edge_6_5_4 = None\n", - "edge_6_5_6 = None\n", - "edge_6_5_9 = None\n", - "edge_6_6_10 = None\n", - "edge_6_6_2 = None\n", - "edge_6_6_5 = None\n", - "edge_6_6_7 = None\n", - "edge_6_7_11 = None\n", - "edge_6_7_3 = None\n", - "edge_6_7_6 = None\n", - "edge_6_8_12 = None\n", - "edge_6_8_4 = None\n", - "edge_6_8_9 = None\n", - "edge_6_9_10 = None\n", - "edge_6_9_13 = None\n", - "edge_6_9_5 = None\n", - "edge_6_9_8 = None\n", - "edge_7_0_1 = None\n", - "edge_7_0_4 = None\n", - "edge_7_10_11 = None\n", - "edge_7_10_14 = None\n", - "edge_7_10_6 = None\n", - "edge_7_10_9 = None\n", - "edge_7_11_10 = None\n", - "edge_7_11_15 = None\n", - "edge_7_11_7 = None\n", - "edge_7_12_13 = None\n", - "edge_7_12_8 = None\n", - "edge_7_13_12 = None\n", - "edge_7_13_14 = None\n", - "edge_7_13_9 = None\n", - "edge_7_14_10 = None\n", - "edge_7_14_13 = None\n", - "edge_7_14_15 = None\n", - "edge_7_15_11 = None\n", - "edge_7_15_14 = None\n", - "edge_7_1_0 = None\n", - "edge_7_1_2 = None\n", - "edge_7_1_5 = None\n", - "edge_7_2_1 = None\n", - "edge_7_2_3 = None\n", - "edge_7_2_6 = None\n", - "edge_7_3_2 = None\n", - "edge_7_3_7 = None\n", - "edge_7_4_0 = None\n", - "edge_7_4_5 = None\n", - "edge_7_4_8 = None\n", - "edge_7_5_1 = None\n", - "edge_7_5_4 = None\n", - "edge_7_5_6 = None\n", - "edge_7_5_9 = None\n", - "edge_7_6_10 = None\n", - "edge_7_6_2 = None\n", - "edge_7_6_5 = None\n", - "edge_7_6_7 = None\n", - "edge_7_7_11 = None\n", - "edge_7_7_3 = None\n", - "edge_7_7_6 = None\n", - "edge_7_8_12 = None\n", - "edge_7_8_4 = None\n", - "edge_7_8_9 = None\n", - "edge_7_9_10 = None\n", - "edge_7_9_13 = None\n", - "edge_7_9_5 = None\n", - "edge_7_9_8 = None\n", - "edge_8_0_1 = None\n", - "edge_8_0_4 = None\n", - "edge_8_10_11 = None\n", - "edge_8_10_14 = None\n", - "edge_8_10_6 = None\n", - "edge_8_10_9 = None\n", - "edge_8_11_10 = None\n", - "edge_8_11_15 = None\n", - "edge_8_11_7 = None\n", - "edge_8_12_13 = None\n", - "edge_8_12_8 = None\n", - "edge_8_13_12 = None\n", - "edge_8_13_14 = None\n", - "edge_8_13_9 = None\n", - "edge_8_14_10 = None\n", - "edge_8_14_13 = None\n", - "edge_8_14_15 = None\n", - "edge_8_15_11 = None\n", - "edge_8_15_14 = None\n", - "edge_8_1_0 = None\n", - "edge_8_1_2 = None\n", - "edge_8_1_5 = None\n", - "edge_8_2_1 = None\n", - "edge_8_2_3 = None\n", - "edge_8_2_6 = None\n", - "edge_8_3_2 = None\n", - "edge_8_3_7 = None\n", - "edge_8_4_0 = None\n", - "edge_8_4_5 = None\n", - "edge_8_4_8 = None\n", - "edge_8_5_1 = None\n", - "edge_8_5_4 = None\n", - "edge_8_5_6 = None\n", - "edge_8_5_9 = None\n", - "edge_8_6_10 = None\n", - "edge_8_6_2 = None\n", - "edge_8_6_5 = None\n", - "edge_8_6_7 = None\n", - "edge_8_7_11 = None\n", - "edge_8_7_3 = None\n", - "edge_8_7_6 = None\n", - "edge_8_8_12 = None\n", - "edge_8_8_4 = None\n", - "edge_8_8_9 = None\n", - "edge_8_9_10 = None\n", - "edge_8_9_13 = None\n", - "edge_8_9_5 = None\n", - "edge_8_9_8 = None\n", - "edge_9_0_1 = None\n", - "edge_9_0_4 = None\n", - "edge_9_10_11 = None\n", - "edge_9_10_14 = None\n", - "edge_9_10_6 = None\n", - "edge_9_10_9 = None\n", - "edge_9_11_10 = None\n", - "edge_9_11_15 = None\n", - "edge_9_11_7 = None\n", - "edge_9_12_13 = None\n", - "edge_9_12_8 = None\n", - "edge_9_13_12 = None\n", - "edge_9_13_14 = None\n", - "edge_9_13_9 = None\n", - "edge_9_14_10 = None\n", - "edge_9_14_13 = None\n", - "edge_9_14_15 = None\n", - "edge_9_15_11 = None\n", - "edge_9_15_14 = None\n", - "edge_9_1_0 = None\n", - "edge_9_1_2 = None\n", - "edge_9_1_5 = None\n", - "edge_9_2_1 = None\n", - "edge_9_2_3 = None\n", - "edge_9_2_6 = None\n", - "edge_9_3_2 = None\n", - "edge_9_3_7 = None\n", - "edge_9_4_0 = None\n", - "edge_9_4_5 = None\n", - "edge_9_4_8 = None\n", - "edge_9_5_1 = None\n", - "edge_9_5_4 = None\n", - "edge_9_5_6 = None\n", - "edge_9_5_9 = None\n", - "edge_9_6_10 = None\n", - "edge_9_6_2 = None\n", - "edge_9_6_5 = None\n", - "edge_9_6_7 = None\n", - "edge_9_7_11 = None\n", - "edge_9_7_3 = None\n", - "edge_9_7_6 = None\n", - "edge_9_8_12 = None\n", - "edge_9_8_4 = None\n", - "edge_9_8_9 = None\n", - "edge_9_9_10 = None\n", - "edge_9_9_13 = None\n", - "edge_9_9_5 = None\n", - "edge_9_9_8 = None\n", - "inout_layer0_node0 = None\n", - "inout_layer0_node1 = None\n", - "inout_layer0_node10 = None\n", - "inout_layer0_node11 = None\n", - "inout_layer0_node12 = None\n", - "inout_layer0_node13 = None\n", - "inout_layer0_node14 = None\n", - "inout_layer0_node15 = None\n", - "inout_layer0_node2 = None\n", - "inout_layer0_node3 = None\n", - "inout_layer0_node4 = None\n", - "inout_layer0_node5 = None\n", - "inout_layer0_node6 = None\n", - "inout_layer0_node7 = None\n", - "inout_layer0_node8 = None\n", - "inout_layer0_node9 = None\n", - "inout_layer10_node0 = None\n", - "inout_layer10_node1 = None\n", - "inout_layer10_node10 = None\n", - "inout_layer10_node11 = None\n", - "inout_layer10_node12 = None\n", - "inout_layer10_node13 = None\n", - "inout_layer10_node14 = None\n", - "inout_layer10_node15 = None\n", - "inout_layer10_node2 = None\n", - "inout_layer10_node3 = None\n", - "inout_layer10_node4 = None\n", - "inout_layer10_node5 = None\n", - "inout_layer10_node6 = None\n", - "inout_layer10_node7 = None\n", - "inout_layer10_node8 = None\n", - "inout_layer10_node9 = None\n", - "inout_layer1_node0 = None\n", - "inout_layer1_node1 = None\n", - "inout_layer1_node10 = None\n", - "inout_layer1_node11 = None\n", - "inout_layer1_node12 = None\n", - "inout_layer1_node13 = None\n", - "inout_layer1_node14 = None\n", - "inout_layer1_node15 = None\n", - "inout_layer1_node2 = None\n", - "inout_layer1_node3 = None\n", - "inout_layer1_node4 = None\n", - "inout_layer1_node5 = None\n", - "inout_layer1_node6 = None\n", - "inout_layer1_node7 = None\n", - "inout_layer1_node8 = None\n", - "inout_layer1_node9 = None\n", - "inout_layer2_node0 = None\n", - "inout_layer2_node1 = None\n", - "inout_layer2_node10 = None\n", - "inout_layer2_node11 = None\n", - "inout_layer2_node12 = None\n", - "inout_layer2_node13 = None\n", - "inout_layer2_node14 = None\n", - "inout_layer2_node15 = None\n", - "inout_layer2_node2 = None\n", - "inout_layer2_node3 = None\n", - "inout_layer2_node4 = None\n", - "inout_layer2_node5 = None\n", - "inout_layer2_node6 = None\n", - "inout_layer2_node7 = None\n", - "inout_layer2_node8 = None\n", - "inout_layer2_node9 = None\n", - "inout_layer3_node0 = None\n", - "inout_layer3_node1 = None\n", - "inout_layer3_node10 = None\n", - "inout_layer3_node11 = None\n", - "inout_layer3_node12 = None\n", - "inout_layer3_node13 = None\n", - "inout_layer3_node14 = None\n", - "inout_layer3_node15 = None\n", - "inout_layer3_node2 = None\n", - "inout_layer3_node3 = None\n", - "inout_layer3_node4 = None\n", - "inout_layer3_node5 = None\n", - "inout_layer3_node6 = None\n", - "inout_layer3_node7 = None\n", - "inout_layer3_node8 = None\n", - "inout_layer3_node9 = None\n", - "inout_layer4_node0 = None\n", - "inout_layer4_node1 = None\n", - "inout_layer4_node10 = None\n", - "inout_layer4_node11 = None\n", - "inout_layer4_node12 = None\n", - "inout_layer4_node13 = None\n", - "inout_layer4_node14 = None\n", - "inout_layer4_node15 = None\n", - "inout_layer4_node2 = None\n", - "inout_layer4_node3 = None\n", - "inout_layer4_node4 = None\n", - "inout_layer4_node5 = None\n", - "inout_layer4_node6 = None\n", - "inout_layer4_node7 = None\n", - "inout_layer4_node8 = None\n", - "inout_layer4_node9 = None\n", - "inout_layer5_node0 = None\n", - "inout_layer5_node1 = None\n", - "inout_layer5_node10 = None\n", - "inout_layer5_node11 = None\n", - "inout_layer5_node12 = None\n", - "inout_layer5_node13 = None\n", - "inout_layer5_node14 = None\n", - "inout_layer5_node15 = None\n", - "inout_layer5_node2 = None\n", - "inout_layer5_node3 = None\n", - "inout_layer5_node4 = None\n", - "inout_layer5_node5 = None\n", - "inout_layer5_node6 = None\n", - "inout_layer5_node7 = None\n", - "inout_layer5_node8 = None\n", - "inout_layer5_node9 = None\n", - "inout_layer6_node0 = None\n", - "inout_layer6_node1 = None\n", - "inout_layer6_node10 = None\n", - "inout_layer6_node11 = None\n", - "inout_layer6_node12 = None\n", - "inout_layer6_node13 = None\n", - "inout_layer6_node14 = None\n", - "inout_layer6_node15 = None\n", - "inout_layer6_node2 = None\n", - "inout_layer6_node3 = None\n", - "inout_layer6_node4 = None\n", - "inout_layer6_node5 = None\n", - "inout_layer6_node6 = None\n", - "inout_layer6_node7 = None\n", - "inout_layer6_node8 = None\n", - "inout_layer6_node9 = None\n", - "inout_layer7_node0 = None\n", - "inout_layer7_node1 = None\n", - "inout_layer7_node10 = None\n", - "inout_layer7_node11 = None\n", - "inout_layer7_node12 = None\n", - "inout_layer7_node13 = None\n", - "inout_layer7_node14 = None\n", - "inout_layer7_node15 = None\n", - "inout_layer7_node2 = None\n", - "inout_layer7_node3 = None\n", - "inout_layer7_node4 = None\n", - "inout_layer7_node5 = None\n", - "inout_layer7_node6 = None\n", - "inout_layer7_node7 = None\n", - "inout_layer7_node8 = None\n", - "inout_layer7_node9 = None\n", - "inout_layer8_node0 = None\n", - "inout_layer8_node1 = None\n", - "inout_layer8_node10 = None\n", - "inout_layer8_node11 = None\n", - "inout_layer8_node12 = None\n", - "inout_layer8_node13 = None\n", - "inout_layer8_node14 = None\n", - "inout_layer8_node15 = None\n", - "inout_layer8_node2 = None\n", - "inout_layer8_node3 = None\n", - "inout_layer8_node4 = None\n", - "inout_layer8_node5 = None\n", - "inout_layer8_node6 = None\n", - "inout_layer8_node7 = None\n", - "inout_layer8_node8 = None\n", - "inout_layer8_node9 = None\n", - "inout_layer9_node0 = None\n", - "inout_layer9_node1 = None\n", - "inout_layer9_node10 = None\n", - "inout_layer9_node11 = None\n", - "inout_layer9_node12 = None\n", - "inout_layer9_node13 = None\n", - "inout_layer9_node14 = None\n", - "inout_layer9_node15 = None\n", - "inout_layer9_node2 = None\n", - "inout_layer9_node3 = None\n", - "inout_layer9_node4 = None\n", - "inout_layer9_node5 = None\n", - "inout_layer9_node6 = None\n", - "inout_layer9_node7 = None\n", - "inout_layer9_node8 = None\n", - "inout_layer9_node9 = None\n", - "inout_total_node0 = None\n", - "inout_total_node1 = None\n", - "inout_total_node10 = None\n", - "inout_total_node11 = None\n", - "inout_total_node12 = None\n", - "inout_total_node13 = None\n", - "inout_total_node14 = None\n", - "inout_total_node15 = None\n", - "inout_total_node2 = None\n", - "inout_total_node3 = None\n", - "inout_total_node4 = None\n", - "inout_total_node5 = None\n", - "inout_total_node6 = None\n", - "inout_total_node7 = None\n", - "inout_total_node8 = None\n", - "inout_total_node9 = None\n", - "inout_total_norm0 = None\n", - "inout_total_norm1 = None\n", - "inout_total_norm10 = None\n", - "inout_total_norm11 = None\n", - "inout_total_norm12 = None\n", - "inout_total_norm13 = None\n", - "inout_total_norm14 = None\n", - "inout_total_norm15 = None\n", - "inout_total_norm2 = None\n", - "inout_total_norm3 = None\n", - "inout_total_norm4 = None\n", - "inout_total_norm5 = None\n", - "inout_total_norm6 = None\n", - "inout_total_norm7 = None\n", - "inout_total_norm8 = None\n", - "inout_total_norm9 = None\n", - "is_pos_nonzero_0_0 = None\n", - "is_pos_nonzero_0_1 = None\n", - "is_pos_nonzero_0_10 = None\n", - "is_pos_nonzero_0_11 = None\n", - "is_pos_nonzero_0_12 = None\n", - "is_pos_nonzero_0_13 = None\n", - "is_pos_nonzero_0_14 = None\n", - "is_pos_nonzero_0_15 = None\n", - "is_pos_nonzero_0_2 = None\n", - "is_pos_nonzero_0_3 = None\n", - "is_pos_nonzero_0_4 = None\n", - "is_pos_nonzero_0_5 = None\n", - "is_pos_nonzero_0_6 = None\n", - "is_pos_nonzero_0_7 = None\n", - "is_pos_nonzero_0_8 = None\n", - "is_pos_nonzero_0_9 = None\n", - "is_pos_nonzero_10_0 = None\n", - "is_pos_nonzero_10_1 = None\n", - "is_pos_nonzero_10_10 = None\n", - "is_pos_nonzero_10_11 = None\n", - "is_pos_nonzero_10_12 = None\n", - "is_pos_nonzero_10_13 = None\n", - "is_pos_nonzero_10_14 = None\n", - "is_pos_nonzero_10_15 = None\n", - "is_pos_nonzero_10_2 = None\n", - "is_pos_nonzero_10_3 = None\n", - "is_pos_nonzero_10_4 = None\n", - "is_pos_nonzero_10_5 = None\n", - "is_pos_nonzero_10_6 = None\n", - "is_pos_nonzero_10_7 = None\n", - "is_pos_nonzero_10_8 = None\n", - "is_pos_nonzero_10_9 = None\n", - "is_pos_nonzero_1_0 = None\n", - "is_pos_nonzero_1_1 = None\n", - "is_pos_nonzero_1_10 = None\n", - "is_pos_nonzero_1_11 = None\n", - "is_pos_nonzero_1_12 = None\n", - "is_pos_nonzero_1_13 = None\n", - "is_pos_nonzero_1_14 = None\n", - "is_pos_nonzero_1_15 = None\n", - "is_pos_nonzero_1_2 = None\n", - "is_pos_nonzero_1_3 = None\n", - "is_pos_nonzero_1_4 = None\n", - "is_pos_nonzero_1_5 = None\n", - "is_pos_nonzero_1_6 = None\n", - "is_pos_nonzero_1_7 = None\n", - "is_pos_nonzero_1_8 = None\n", - "is_pos_nonzero_1_9 = None\n", - "is_pos_nonzero_2_0 = None\n", - "is_pos_nonzero_2_1 = None\n", - "is_pos_nonzero_2_10 = None\n", - "is_pos_nonzero_2_11 = None\n", - "is_pos_nonzero_2_12 = None\n", - "is_pos_nonzero_2_13 = None\n", - "is_pos_nonzero_2_14 = None\n", - "is_pos_nonzero_2_15 = None\n", - "is_pos_nonzero_2_2 = None\n", - "is_pos_nonzero_2_3 = None\n", - "is_pos_nonzero_2_4 = None\n", - "is_pos_nonzero_2_5 = None\n", - "is_pos_nonzero_2_6 = None\n", - "is_pos_nonzero_2_7 = None\n", - "is_pos_nonzero_2_8 = None\n", - "is_pos_nonzero_2_9 = None\n", - "is_pos_nonzero_3_0 = None\n", - "is_pos_nonzero_3_1 = None\n", - "is_pos_nonzero_3_10 = None\n", - "is_pos_nonzero_3_11 = None\n", - "is_pos_nonzero_3_12 = None\n", - "is_pos_nonzero_3_13 = None\n", - "is_pos_nonzero_3_14 = None\n", - "is_pos_nonzero_3_15 = None\n", - "is_pos_nonzero_3_2 = None\n", - "is_pos_nonzero_3_3 = None\n", - "is_pos_nonzero_3_4 = None\n", - "is_pos_nonzero_3_5 = None\n", - "is_pos_nonzero_3_6 = None\n", - "is_pos_nonzero_3_7 = None\n", - "is_pos_nonzero_3_8 = None\n", - "is_pos_nonzero_3_9 = None\n", - "is_pos_nonzero_4_0 = None\n", - "is_pos_nonzero_4_1 = None\n", - "is_pos_nonzero_4_10 = None\n", - "is_pos_nonzero_4_11 = None\n", - "is_pos_nonzero_4_12 = None\n", - "is_pos_nonzero_4_13 = None\n", - "is_pos_nonzero_4_14 = None\n", - "is_pos_nonzero_4_15 = None\n", - "is_pos_nonzero_4_2 = None\n", - "is_pos_nonzero_4_3 = None\n", - "is_pos_nonzero_4_4 = None\n", - "is_pos_nonzero_4_5 = None\n", - "is_pos_nonzero_4_6 = None\n", - "is_pos_nonzero_4_7 = None\n", - "is_pos_nonzero_4_8 = None\n", - "is_pos_nonzero_4_9 = None\n", - "is_pos_nonzero_5_0 = None\n", - "is_pos_nonzero_5_1 = None\n", - "is_pos_nonzero_5_10 = None\n", - "is_pos_nonzero_5_11 = None\n", - "is_pos_nonzero_5_12 = None\n", - "is_pos_nonzero_5_13 = None\n", - "is_pos_nonzero_5_14 = None\n", - "is_pos_nonzero_5_15 = None\n", - "is_pos_nonzero_5_2 = None\n", - "is_pos_nonzero_5_3 = None\n", - "is_pos_nonzero_5_4 = None\n", - "is_pos_nonzero_5_5 = None\n", - "is_pos_nonzero_5_6 = None\n", - "is_pos_nonzero_5_7 = None\n", - "is_pos_nonzero_5_8 = None\n", - "is_pos_nonzero_5_9 = None\n", - "is_pos_nonzero_6_0 = None\n", - "is_pos_nonzero_6_1 = None\n", - "is_pos_nonzero_6_10 = None\n", - "is_pos_nonzero_6_11 = None\n", - "is_pos_nonzero_6_12 = None\n", - "is_pos_nonzero_6_13 = None\n", - "is_pos_nonzero_6_14 = None\n", - "is_pos_nonzero_6_15 = None\n", - "is_pos_nonzero_6_2 = None\n", - "is_pos_nonzero_6_3 = None\n", - "is_pos_nonzero_6_4 = None\n", - "is_pos_nonzero_6_5 = None\n", - "is_pos_nonzero_6_6 = None\n", - "is_pos_nonzero_6_7 = None\n", - "is_pos_nonzero_6_8 = None\n", - "is_pos_nonzero_6_9 = None\n", - "is_pos_nonzero_7_0 = None\n", - "is_pos_nonzero_7_1 = None\n", - "is_pos_nonzero_7_10 = None\n", - "is_pos_nonzero_7_11 = None\n", - "is_pos_nonzero_7_12 = None\n", - "is_pos_nonzero_7_13 = None\n", - "is_pos_nonzero_7_14 = None\n", - "is_pos_nonzero_7_15 = None\n", - "is_pos_nonzero_7_2 = None\n", - "is_pos_nonzero_7_3 = None\n", - "is_pos_nonzero_7_4 = None\n", - "is_pos_nonzero_7_5 = None\n", - "is_pos_nonzero_7_6 = None\n", - "is_pos_nonzero_7_7 = None\n", - "is_pos_nonzero_7_8 = None\n", - "is_pos_nonzero_7_9 = None\n", - "is_pos_nonzero_8_0 = None\n", - "is_pos_nonzero_8_1 = None\n", - "is_pos_nonzero_8_10 = None\n", - "is_pos_nonzero_8_11 = None\n", - "is_pos_nonzero_8_12 = None\n", - "is_pos_nonzero_8_13 = None\n", - "is_pos_nonzero_8_14 = None\n", - "is_pos_nonzero_8_15 = None\n", - "is_pos_nonzero_8_2 = None\n", - "is_pos_nonzero_8_3 = None\n", - "is_pos_nonzero_8_4 = None\n", - "is_pos_nonzero_8_5 = None\n", - "is_pos_nonzero_8_6 = None\n", - "is_pos_nonzero_8_7 = None\n", - "is_pos_nonzero_8_8 = None\n", - "is_pos_nonzero_8_9 = None\n", - "is_pos_nonzero_9_0 = None\n", - "is_pos_nonzero_9_1 = None\n", - "is_pos_nonzero_9_10 = None\n", - "is_pos_nonzero_9_11 = None\n", - "is_pos_nonzero_9_12 = None\n", - "is_pos_nonzero_9_13 = None\n", - "is_pos_nonzero_9_14 = None\n", - "is_pos_nonzero_9_15 = None\n", - "is_pos_nonzero_9_2 = None\n", - "is_pos_nonzero_9_3 = None\n", - "is_pos_nonzero_9_4 = None\n", - "is_pos_nonzero_9_5 = None\n", - "is_pos_nonzero_9_6 = None\n", - "is_pos_nonzero_9_7 = None\n", - "is_pos_nonzero_9_8 = None\n", - "is_pos_nonzero_9_9 = None\n", - "max_pos_dst = None\n", - "path_add_individual0_0 = None\n", - "path_add_individual0_1 = None\n", - "path_add_individual0_10 = None\n", - "path_add_individual0_11 = None\n", - "path_add_individual0_12 = None\n", - "path_add_individual0_13 = None\n", - "path_add_individual0_14 = None\n", - "path_add_individual0_15 = None\n", - "path_add_individual0_2 = None\n", - "path_add_individual0_3 = None\n", - "path_add_individual0_4 = None\n", - "path_add_individual0_5 = None\n", - "path_add_individual0_6 = None\n", - "path_add_individual0_7 = None\n", - "path_add_individual0_8 = None\n", - "path_add_individual0_9 = None\n", - "path_add_individual10_0 = None\n", - "path_add_individual10_1 = None\n", - "path_add_individual10_10 = None\n", - "path_add_individual10_11 = None\n", - "path_add_individual10_12 = None\n", - "path_add_individual10_13 = None\n", - "path_add_individual10_14 = None\n", - "path_add_individual10_15 = None\n", - "path_add_individual10_2 = None\n", - "path_add_individual10_3 = None\n", - "path_add_individual10_4 = None\n", - "path_add_individual10_5 = None\n", - "path_add_individual10_6 = None\n", - "path_add_individual10_7 = None\n", - "path_add_individual10_8 = None\n", - "path_add_individual10_9 = None\n", - "path_add_individual1_0 = None\n", - "path_add_individual1_1 = None\n", - "path_add_individual1_10 = None\n", - "path_add_individual1_11 = None\n", - "path_add_individual1_12 = None\n", - "path_add_individual1_13 = None\n", - "path_add_individual1_14 = None\n", - "path_add_individual1_15 = None\n", - "path_add_individual1_2 = None\n", - "path_add_individual1_3 = None\n", - "path_add_individual1_4 = None\n", - "path_add_individual1_5 = None\n", - "path_add_individual1_6 = None\n", - "path_add_individual1_7 = None\n", - "path_add_individual1_8 = None\n", - "path_add_individual1_9 = None\n", - "path_add_individual2_0 = None\n", - "path_add_individual2_1 = None\n", - "path_add_individual2_10 = None\n", - "path_add_individual2_11 = None\n", - "path_add_individual2_12 = None\n", - "path_add_individual2_13 = None\n", - "path_add_individual2_14 = None\n", - "path_add_individual2_15 = None\n", - "path_add_individual2_2 = None\n", - "path_add_individual2_3 = None\n", - "path_add_individual2_4 = None\n", - "path_add_individual2_5 = None\n", - "path_add_individual2_6 = None\n", - "path_add_individual2_7 = None\n", - "path_add_individual2_8 = None\n", - "path_add_individual2_9 = None\n", - "path_add_individual3_0 = None\n", - "path_add_individual3_1 = None\n", - "path_add_individual3_10 = None\n", - "path_add_individual3_11 = None\n", - "path_add_individual3_12 = None\n", - "path_add_individual3_13 = None\n", - "path_add_individual3_14 = None\n", - "path_add_individual3_15 = None\n", - "path_add_individual3_2 = None\n", - "path_add_individual3_3 = None\n", - "path_add_individual3_4 = None\n", - "path_add_individual3_5 = None\n", - "path_add_individual3_6 = None\n", - "path_add_individual3_7 = None\n", - "path_add_individual3_8 = None\n", - "path_add_individual3_9 = None\n", - "path_add_individual4_0 = None\n", - "path_add_individual4_1 = None\n", - "path_add_individual4_10 = None\n", - "path_add_individual4_11 = None\n", - "path_add_individual4_12 = None\n", - "path_add_individual4_13 = None\n", - "path_add_individual4_14 = None\n", - "path_add_individual4_15 = None\n", - "path_add_individual4_2 = None\n", - "path_add_individual4_3 = None\n", - "path_add_individual4_4 = None\n", - "path_add_individual4_5 = None\n", - "path_add_individual4_6 = None\n", - "path_add_individual4_7 = None\n", - "path_add_individual4_8 = None\n", - "path_add_individual4_9 = None\n", - "path_add_individual5_0 = None\n", - "path_add_individual5_1 = None\n", - "path_add_individual5_10 = None\n", - "path_add_individual5_11 = None\n", - "path_add_individual5_12 = None\n", - "path_add_individual5_13 = None\n", - "path_add_individual5_14 = None\n", - "path_add_individual5_15 = None\n", - "path_add_individual5_2 = None\n", - "path_add_individual5_3 = None\n", - "path_add_individual5_4 = None\n", - "path_add_individual5_5 = None\n", - "path_add_individual5_6 = None\n", - "path_add_individual5_7 = None\n", - "path_add_individual5_8 = None\n", - "path_add_individual5_9 = None\n", - "path_add_individual6_0 = None\n", - "path_add_individual6_1 = None\n", - "path_add_individual6_10 = None\n", - "path_add_individual6_11 = None\n", - "path_add_individual6_12 = None\n", - "path_add_individual6_13 = None\n", - "path_add_individual6_14 = None\n", - "path_add_individual6_15 = None\n", - "path_add_individual6_2 = None\n", - "path_add_individual6_3 = None\n", - "path_add_individual6_4 = None\n", - "path_add_individual6_5 = None\n", - "path_add_individual6_6 = None\n", - "path_add_individual6_7 = None\n", - "path_add_individual6_8 = None\n", - "path_add_individual6_9 = None\n", - "path_add_individual7_0 = None\n", - "path_add_individual7_1 = None\n", - "path_add_individual7_10 = None\n", - "path_add_individual7_11 = None\n", - "path_add_individual7_12 = None\n", - "path_add_individual7_13 = None\n", - "path_add_individual7_14 = None\n", - "path_add_individual7_15 = None\n", - "path_add_individual7_2 = None\n", - "path_add_individual7_3 = None\n", - "path_add_individual7_4 = None\n", - "path_add_individual7_5 = None\n", - "path_add_individual7_6 = None\n", - "path_add_individual7_7 = None\n", - "path_add_individual7_8 = None\n", - "path_add_individual7_9 = None\n", - "path_add_individual8_0 = None\n", - "path_add_individual8_1 = None\n", - "path_add_individual8_10 = None\n", - "path_add_individual8_11 = None\n", - "path_add_individual8_12 = None\n", - "path_add_individual8_13 = None\n", - "path_add_individual8_14 = None\n", - "path_add_individual8_15 = None\n", - "path_add_individual8_2 = None\n", - "path_add_individual8_3 = None\n", - "path_add_individual8_4 = None\n", - "path_add_individual8_5 = None\n", - "path_add_individual8_6 = None\n", - "path_add_individual8_7 = None\n", - "path_add_individual8_8 = None\n", - "path_add_individual8_9 = None\n", - "path_add_individual9_0 = None\n", - "path_add_individual9_1 = None\n", - "path_add_individual9_10 = None\n", - "path_add_individual9_11 = None\n", - "path_add_individual9_12 = None\n", - "path_add_individual9_13 = None\n", - "path_add_individual9_14 = None\n", - "path_add_individual9_15 = None\n", - "path_add_individual9_2 = None\n", - "path_add_individual9_3 = None\n", - "path_add_individual9_4 = None\n", - "path_add_individual9_5 = None\n", - "path_add_individual9_6 = None\n", - "path_add_individual9_7 = None\n", - "path_add_individual9_8 = None\n", - "path_add_individual9_9 = None\n", - "path_add_individual_2_0_0 = None\n", - "path_add_individual_2_0_1 = None\n", - "path_add_individual_2_0_10 = None\n", - "path_add_individual_2_0_11 = None\n", - "path_add_individual_2_0_12 = None\n", - "path_add_individual_2_0_13 = None\n", - "path_add_individual_2_0_14 = None\n", - "path_add_individual_2_0_15 = None\n", - "path_add_individual_2_0_2 = None\n", - "path_add_individual_2_0_3 = None\n", - "path_add_individual_2_0_4 = None\n", - "path_add_individual_2_0_5 = None\n", - "path_add_individual_2_0_6 = None\n", - "path_add_individual_2_0_7 = None\n", - "path_add_individual_2_0_8 = None\n", - "path_add_individual_2_0_9 = None\n", - "path_add_individual_2_10_0 = None\n", - "path_add_individual_2_10_1 = None\n", - "path_add_individual_2_10_10 = None\n", - "path_add_individual_2_10_11 = None\n", - "path_add_individual_2_10_12 = None\n", - "path_add_individual_2_10_13 = None\n", - "path_add_individual_2_10_14 = None\n", - "path_add_individual_2_10_15 = None\n", - "path_add_individual_2_10_2 = None\n", - "path_add_individual_2_10_3 = None\n", - "path_add_individual_2_10_4 = None\n", - "path_add_individual_2_10_5 = None\n", - "path_add_individual_2_10_6 = None\n", - "path_add_individual_2_10_7 = None\n", - "path_add_individual_2_10_8 = None\n", - "path_add_individual_2_10_9 = None\n", - "path_add_individual_2_1_0 = None\n", - "path_add_individual_2_1_1 = None\n", - "path_add_individual_2_1_10 = None\n", - "path_add_individual_2_1_11 = None\n", - "path_add_individual_2_1_12 = None\n", - "path_add_individual_2_1_13 = None\n", - "path_add_individual_2_1_14 = None\n", - "path_add_individual_2_1_15 = None\n", - "path_add_individual_2_1_2 = None\n", - "path_add_individual_2_1_3 = None\n", - "path_add_individual_2_1_4 = None\n", - "path_add_individual_2_1_5 = None\n", - "path_add_individual_2_1_6 = None\n", - "path_add_individual_2_1_7 = None\n", - "path_add_individual_2_1_8 = None\n", - "path_add_individual_2_1_9 = None\n", - "path_add_individual_2_2_0 = None\n", - "path_add_individual_2_2_1 = None\n", - "path_add_individual_2_2_10 = None\n", - "path_add_individual_2_2_11 = None\n", - "path_add_individual_2_2_12 = None\n", - "path_add_individual_2_2_13 = None\n", - "path_add_individual_2_2_14 = None\n", - "path_add_individual_2_2_15 = None\n", - "path_add_individual_2_2_2 = None\n", - "path_add_individual_2_2_3 = None\n", - "path_add_individual_2_2_4 = None\n", - "path_add_individual_2_2_5 = None\n", - "path_add_individual_2_2_6 = None\n", - "path_add_individual_2_2_7 = None\n", - "path_add_individual_2_2_8 = None\n", - "path_add_individual_2_2_9 = None\n", - "path_add_individual_2_3_0 = None\n", - "path_add_individual_2_3_1 = None\n", - "path_add_individual_2_3_10 = None\n", - "path_add_individual_2_3_11 = None\n", - "path_add_individual_2_3_12 = None\n", - "path_add_individual_2_3_13 = None\n", - "path_add_individual_2_3_14 = None\n", - "path_add_individual_2_3_15 = None\n", - "path_add_individual_2_3_2 = None\n", - "path_add_individual_2_3_3 = None\n", - "path_add_individual_2_3_4 = None\n", - "path_add_individual_2_3_5 = None\n", - "path_add_individual_2_3_6 = None\n", - "path_add_individual_2_3_7 = None\n", - "path_add_individual_2_3_8 = None\n", - "path_add_individual_2_3_9 = None\n", - "path_add_individual_2_4_0 = None\n", - "path_add_individual_2_4_1 = None\n", - "path_add_individual_2_4_10 = None\n", - "path_add_individual_2_4_11 = None\n", - "path_add_individual_2_4_12 = None\n", - "path_add_individual_2_4_13 = None\n", - "path_add_individual_2_4_14 = None\n", - "path_add_individual_2_4_15 = None\n", - "path_add_individual_2_4_2 = None\n", - "path_add_individual_2_4_3 = None\n", - "path_add_individual_2_4_4 = None\n", - "path_add_individual_2_4_5 = None\n", - "path_add_individual_2_4_6 = None\n", - "path_add_individual_2_4_7 = None\n", - "path_add_individual_2_4_8 = None\n", - "path_add_individual_2_4_9 = None\n", - "path_add_individual_2_5_0 = None\n", - "path_add_individual_2_5_1 = None\n", - "path_add_individual_2_5_10 = None\n", - "path_add_individual_2_5_11 = None\n", - "path_add_individual_2_5_12 = None\n", - "path_add_individual_2_5_13 = None\n", - "path_add_individual_2_5_14 = None\n", - "path_add_individual_2_5_15 = None\n", - "path_add_individual_2_5_2 = None\n", - "path_add_individual_2_5_3 = None\n", - "path_add_individual_2_5_4 = None\n", - "path_add_individual_2_5_5 = None\n", - "path_add_individual_2_5_6 = None\n", - "path_add_individual_2_5_7 = None\n", - "path_add_individual_2_5_8 = None\n", - "path_add_individual_2_5_9 = None\n", - "path_add_individual_2_6_0 = None\n", - "path_add_individual_2_6_1 = None\n", - "path_add_individual_2_6_10 = None\n", - "path_add_individual_2_6_11 = None\n", - "path_add_individual_2_6_12 = None\n", - "path_add_individual_2_6_13 = None\n", - "path_add_individual_2_6_14 = None\n", - "path_add_individual_2_6_15 = None\n", - "path_add_individual_2_6_2 = None\n", - "path_add_individual_2_6_3 = None\n", - "path_add_individual_2_6_4 = None\n", - "path_add_individual_2_6_5 = None\n", - "path_add_individual_2_6_6 = None\n", - "path_add_individual_2_6_7 = None\n", - "path_add_individual_2_6_8 = None\n", - "path_add_individual_2_6_9 = None\n", - "path_add_individual_2_7_0 = None\n", - "path_add_individual_2_7_1 = None\n", - "path_add_individual_2_7_10 = None\n", - "path_add_individual_2_7_11 = None\n", - "path_add_individual_2_7_12 = None\n", - "path_add_individual_2_7_13 = None\n", - "path_add_individual_2_7_14 = None\n", - "path_add_individual_2_7_15 = None\n", - "path_add_individual_2_7_2 = None\n", - "path_add_individual_2_7_3 = None\n", - "path_add_individual_2_7_4 = None\n", - "path_add_individual_2_7_5 = None\n", - "path_add_individual_2_7_6 = None\n", - "path_add_individual_2_7_7 = None\n", - "path_add_individual_2_7_8 = None\n", - "path_add_individual_2_7_9 = None\n", - "path_add_individual_2_8_0 = None\n", - "path_add_individual_2_8_1 = None\n", - "path_add_individual_2_8_10 = None\n", - "path_add_individual_2_8_11 = None\n", - "path_add_individual_2_8_12 = None\n", - "path_add_individual_2_8_13 = None\n", - "path_add_individual_2_8_14 = None\n", - "path_add_individual_2_8_15 = None\n", - "path_add_individual_2_8_2 = None\n", - "path_add_individual_2_8_3 = None\n", - "path_add_individual_2_8_4 = None\n", - "path_add_individual_2_8_5 = None\n", - "path_add_individual_2_8_6 = None\n", - "path_add_individual_2_8_7 = None\n", - "path_add_individual_2_8_8 = None\n", - "path_add_individual_2_8_9 = None\n", - "path_add_individual_2_9_0 = None\n", - "path_add_individual_2_9_1 = None\n", - "path_add_individual_2_9_10 = None\n", - "path_add_individual_2_9_11 = None\n", - "path_add_individual_2_9_12 = None\n", - "path_add_individual_2_9_13 = None\n", - "path_add_individual_2_9_14 = None\n", - "path_add_individual_2_9_15 = None\n", - "path_add_individual_2_9_2 = None\n", - "path_add_individual_2_9_3 = None\n", - "path_add_individual_2_9_4 = None\n", - "path_add_individual_2_9_5 = None\n", - "path_add_individual_2_9_6 = None\n", - "path_add_individual_2_9_7 = None\n", - "path_add_individual_2_9_8 = None\n", - "path_add_individual_2_9_9 = None\n", - "path_add_individual_3_0_0 = None\n", - "path_add_individual_3_0_1 = None\n", - "path_add_individual_3_0_10 = None\n", - "path_add_individual_3_0_11 = None\n", - "path_add_individual_3_0_12 = None\n", - "path_add_individual_3_0_13 = None\n", - "path_add_individual_3_0_14 = None\n", - "path_add_individual_3_0_15 = None\n", - "path_add_individual_3_0_2 = None\n", - "path_add_individual_3_0_3 = None\n", - "path_add_individual_3_0_4 = None\n", - "path_add_individual_3_0_5 = None\n", - "path_add_individual_3_0_6 = None\n", - "path_add_individual_3_0_7 = None\n", - "path_add_individual_3_0_8 = None\n", - "path_add_individual_3_0_9 = None\n", - "path_add_individual_3_10_0 = None\n", - "path_add_individual_3_10_1 = None\n", - "path_add_individual_3_10_10 = None\n", - "path_add_individual_3_10_11 = None\n", - "path_add_individual_3_10_12 = None\n", - "path_add_individual_3_10_13 = None\n", - "path_add_individual_3_10_14 = None\n", - "path_add_individual_3_10_15 = None\n", - "path_add_individual_3_10_2 = None\n", - "path_add_individual_3_10_3 = None\n", - "path_add_individual_3_10_4 = None\n", - "path_add_individual_3_10_5 = None\n", - "path_add_individual_3_10_6 = None\n", - "path_add_individual_3_10_7 = None\n", - "path_add_individual_3_10_8 = None\n", - "path_add_individual_3_10_9 = None\n", - "path_add_individual_3_1_0 = None\n", - "path_add_individual_3_1_1 = None\n", - "path_add_individual_3_1_10 = None\n", - "path_add_individual_3_1_11 = None\n", - "path_add_individual_3_1_12 = None\n", - "path_add_individual_3_1_13 = None\n", - "path_add_individual_3_1_14 = None\n", - "path_add_individual_3_1_15 = None\n", - "path_add_individual_3_1_2 = None\n", - "path_add_individual_3_1_3 = None\n", - "path_add_individual_3_1_4 = None\n", - "path_add_individual_3_1_5 = None\n", - "path_add_individual_3_1_6 = None\n", - "path_add_individual_3_1_7 = None\n", - "path_add_individual_3_1_8 = None\n", - "path_add_individual_3_1_9 = None\n", - "path_add_individual_3_2_0 = None\n", - "path_add_individual_3_2_1 = None\n", - "path_add_individual_3_2_10 = None\n", - "path_add_individual_3_2_11 = None\n", - "path_add_individual_3_2_12 = None\n", - "path_add_individual_3_2_13 = None\n", - "path_add_individual_3_2_14 = None\n", - "path_add_individual_3_2_15 = None\n", - "path_add_individual_3_2_2 = None\n", - "path_add_individual_3_2_3 = None\n", - "path_add_individual_3_2_4 = None\n", - "path_add_individual_3_2_5 = None\n", - "path_add_individual_3_2_6 = None\n", - "path_add_individual_3_2_7 = None\n", - "path_add_individual_3_2_8 = None\n", - "path_add_individual_3_2_9 = None\n", - "path_add_individual_3_3_0 = None\n", - "path_add_individual_3_3_1 = None\n", - "path_add_individual_3_3_10 = None\n", - "path_add_individual_3_3_11 = None\n", - "path_add_individual_3_3_12 = None\n", - "path_add_individual_3_3_13 = None\n", - "path_add_individual_3_3_14 = None\n", - "path_add_individual_3_3_15 = None\n", - "path_add_individual_3_3_2 = None\n", - "path_add_individual_3_3_3 = None\n", - "path_add_individual_3_3_4 = None\n", - "path_add_individual_3_3_5 = None\n", - "path_add_individual_3_3_6 = None\n", - "path_add_individual_3_3_7 = None\n", - "path_add_individual_3_3_8 = None\n", - "path_add_individual_3_3_9 = None\n", - "path_add_individual_3_4_0 = None\n", - "path_add_individual_3_4_1 = None\n", - "path_add_individual_3_4_10 = None\n", - "path_add_individual_3_4_11 = None\n", - "path_add_individual_3_4_12 = None\n", - "path_add_individual_3_4_13 = None\n", - "path_add_individual_3_4_14 = None\n", - "path_add_individual_3_4_15 = None\n", - "path_add_individual_3_4_2 = None\n", - "path_add_individual_3_4_3 = None\n", - "path_add_individual_3_4_4 = None\n", - "path_add_individual_3_4_5 = None\n", - "path_add_individual_3_4_6 = None\n", - "path_add_individual_3_4_7 = None\n", - "path_add_individual_3_4_8 = None\n", - "path_add_individual_3_4_9 = None\n", - "path_add_individual_3_5_0 = None\n", - "path_add_individual_3_5_1 = None\n", - "path_add_individual_3_5_10 = None\n", - "path_add_individual_3_5_11 = None\n", - "path_add_individual_3_5_12 = None\n", - "path_add_individual_3_5_13 = None\n", - "path_add_individual_3_5_14 = None\n", - "path_add_individual_3_5_15 = None\n", - "path_add_individual_3_5_2 = None\n", - "path_add_individual_3_5_3 = None\n", - "path_add_individual_3_5_4 = None\n", - "path_add_individual_3_5_5 = None\n", - "path_add_individual_3_5_6 = None\n", - "path_add_individual_3_5_7 = None\n", - "path_add_individual_3_5_8 = None\n", - "path_add_individual_3_5_9 = None\n", - "path_add_individual_3_6_0 = None\n", - "path_add_individual_3_6_1 = None\n", - "path_add_individual_3_6_10 = None\n", - "path_add_individual_3_6_11 = None\n", - "path_add_individual_3_6_12 = None\n", - "path_add_individual_3_6_13 = None\n", - "path_add_individual_3_6_14 = None\n", - "path_add_individual_3_6_15 = None\n", - "path_add_individual_3_6_2 = None\n", - "path_add_individual_3_6_3 = None\n", - "path_add_individual_3_6_4 = None\n", - "path_add_individual_3_6_5 = None\n", - "path_add_individual_3_6_6 = None\n", - "path_add_individual_3_6_7 = None\n", - "path_add_individual_3_6_8 = None\n", - "path_add_individual_3_6_9 = None\n", - "path_add_individual_3_7_0 = None\n", - "path_add_individual_3_7_1 = None\n", - "path_add_individual_3_7_10 = None\n", - "path_add_individual_3_7_11 = None\n", - "path_add_individual_3_7_12 = None\n", - "path_add_individual_3_7_13 = None\n", - "path_add_individual_3_7_14 = None\n", - "path_add_individual_3_7_15 = None\n", - "path_add_individual_3_7_2 = None\n", - "path_add_individual_3_7_3 = None\n", - "path_add_individual_3_7_4 = None\n", - "path_add_individual_3_7_5 = None\n", - "path_add_individual_3_7_6 = None\n", - "path_add_individual_3_7_7 = None\n", - "path_add_individual_3_7_8 = None\n", - "path_add_individual_3_7_9 = None\n", - "path_add_individual_3_8_0 = None\n", - "path_add_individual_3_8_1 = None\n", - "path_add_individual_3_8_10 = None\n", - "path_add_individual_3_8_11 = None\n", - "path_add_individual_3_8_12 = None\n", - "path_add_individual_3_8_13 = None\n", - "path_add_individual_3_8_14 = None\n", - "path_add_individual_3_8_15 = None\n", - "path_add_individual_3_8_2 = None\n", - "path_add_individual_3_8_3 = None\n", - "path_add_individual_3_8_4 = None\n", - "path_add_individual_3_8_5 = None\n", - "path_add_individual_3_8_6 = None\n", - "path_add_individual_3_8_7 = None\n", - "path_add_individual_3_8_8 = None\n", - "path_add_individual_3_8_9 = None\n", - "path_add_individual_3_9_0 = None\n", - "path_add_individual_3_9_1 = None\n", - "path_add_individual_3_9_10 = None\n", - "path_add_individual_3_9_11 = None\n", - "path_add_individual_3_9_12 = None\n", - "path_add_individual_3_9_13 = None\n", - "path_add_individual_3_9_14 = None\n", - "path_add_individual_3_9_15 = None\n", - "path_add_individual_3_9_2 = None\n", - "path_add_individual_3_9_3 = None\n", - "path_add_individual_3_9_4 = None\n", - "path_add_individual_3_9_5 = None\n", - "path_add_individual_3_9_6 = None\n", - "path_add_individual_3_9_7 = None\n", - "path_add_individual_3_9_8 = None\n", - "path_add_individual_3_9_9 = None\n", - "path_add_total_0 = None\n", - "path_add_total_1 = None\n", - "path_add_total_10 = None\n", - "path_add_total_2 = None\n", - "path_add_total_3 = None\n", - "path_add_total_4 = None\n", - "path_add_total_5 = None\n", - "path_add_total_6 = None\n", - "path_add_total_7 = None\n", - "path_add_total_8 = None\n", - "path_add_total_9 = None\n", - "pos_0_0 = None\n", - "pos_0_1 = None\n", - "pos_0_10 = None\n", - "pos_0_11 = None\n", - "pos_0_12 = None\n", - "pos_0_13 = None\n", - "pos_0_14 = None\n", - "pos_0_15 = None\n", - "pos_0_2 = None\n", - "pos_0_3 = None\n", - "pos_0_4 = None\n", - "pos_0_5 = None\n", - "pos_0_6 = None\n", - "pos_0_7 = None\n", - "pos_0_8 = None\n", - "pos_0_9 = None\n", - "pos_10_0 = None\n", - "pos_10_1 = None\n", - "pos_10_10 = None\n", - "pos_10_11 = None\n", - "pos_10_12 = None\n", - "pos_10_13 = None\n", - "pos_10_14 = None\n", - "pos_10_15 = None\n", - "pos_10_2 = None\n", - "pos_10_3 = None\n", - "pos_10_4 = None\n", - "pos_10_5 = None\n", - "pos_10_6 = None\n", - "pos_10_7 = None\n", - "pos_10_8 = None\n", - "pos_10_9 = None\n", - "pos_1_0 = None\n", - "pos_1_1 = None\n", - "pos_1_10 = None\n", - "pos_1_11 = None\n", - "pos_1_12 = None\n", - "pos_1_13 = None\n", - "pos_1_14 = None\n", - "pos_1_15 = None\n", - "pos_1_2 = None\n", - "pos_1_3 = None\n", - "pos_1_4 = None\n", - "pos_1_5 = None\n", - "pos_1_6 = None\n", - "pos_1_7 = None\n", - "pos_1_8 = None\n", - "pos_1_9 = None\n", - "pos_2_0 = None\n", - "pos_2_1 = None\n", - "pos_2_10 = None\n", - "pos_2_11 = None\n", - "pos_2_12 = None\n", - "pos_2_13 = None\n", - "pos_2_14 = None\n", - "pos_2_15 = None\n", - "pos_2_2 = None\n", - "pos_2_3 = None\n", - "pos_2_4 = None\n", - "pos_2_5 = None\n", - "pos_2_6 = None\n", - "pos_2_7 = None\n", - "pos_2_8 = None\n", - "pos_2_9 = None\n", - "pos_3_0 = None\n", - "pos_3_1 = None\n", - "pos_3_10 = None\n", - "pos_3_11 = None\n", - "pos_3_12 = None\n", - "pos_3_13 = None\n", - "pos_3_14 = None\n", - "pos_3_15 = None\n", - "pos_3_2 = None\n", - "pos_3_3 = None\n", - "pos_3_4 = None\n", - "pos_3_5 = None\n", - "pos_3_6 = None\n", - "pos_3_7 = None\n", - "pos_3_8 = None\n", - "pos_3_9 = None\n", - "pos_4_0 = None\n", - "pos_4_1 = None\n", - "pos_4_10 = None\n", - "pos_4_11 = None\n", - "pos_4_12 = None\n", - "pos_4_13 = None\n", - "pos_4_14 = None\n", - "pos_4_15 = None\n", - "pos_4_2 = None\n", - "pos_4_3 = None\n", - "pos_4_4 = None\n", - "pos_4_5 = None\n", - "pos_4_6 = None\n", - "pos_4_7 = None\n", - "pos_4_8 = None\n", - "pos_4_9 = None\n", - "pos_5_0 = None\n", - "pos_5_1 = None\n", - "pos_5_10 = None\n", - "pos_5_11 = None\n", - "pos_5_12 = None\n", - "pos_5_13 = None\n", - "pos_5_14 = None\n", - "pos_5_15 = None\n", - "pos_5_2 = None\n", - "pos_5_3 = None\n", - "pos_5_4 = None\n", - "pos_5_5 = None\n", - "pos_5_6 = None\n", - "pos_5_7 = None\n", - "pos_5_8 = None\n", - "pos_5_9 = None\n", - "pos_6_0 = None\n", - "pos_6_1 = None\n", - "pos_6_10 = None\n", - "pos_6_11 = None\n", - "pos_6_12 = None\n", - "pos_6_13 = None\n", - "pos_6_14 = None\n", - "pos_6_15 = None\n", - "pos_6_2 = None\n", - "pos_6_3 = None\n", - "pos_6_4 = None\n", - "pos_6_5 = None\n", - "pos_6_6 = None\n", - "pos_6_7 = None\n", - "pos_6_8 = None\n", - "pos_6_9 = None\n", - "pos_7_0 = None\n", - "pos_7_1 = None\n", - "pos_7_10 = None\n", - "pos_7_11 = None\n", - "pos_7_12 = None\n", - "pos_7_13 = None\n", - "pos_7_14 = None\n", - "pos_7_15 = None\n", - "pos_7_2 = None\n", - "pos_7_3 = None\n", - "pos_7_4 = None\n", - "pos_7_5 = None\n", - "pos_7_6 = None\n", - "pos_7_7 = None\n", - "pos_7_8 = None\n", - "pos_7_9 = None\n", - "pos_8_0 = None\n", - "pos_8_1 = None\n", - "pos_8_10 = None\n", - "pos_8_11 = None\n", - "pos_8_12 = None\n", - "pos_8_13 = None\n", - "pos_8_14 = None\n", - "pos_8_15 = None\n", - "pos_8_2 = None\n", - "pos_8_3 = None\n", - "pos_8_4 = None\n", - "pos_8_5 = None\n", - "pos_8_6 = None\n", - "pos_8_7 = None\n", - "pos_8_8 = None\n", - "pos_8_9 = None\n", - "pos_9_0 = None\n", - "pos_9_1 = None\n", - "pos_9_10 = None\n", - "pos_9_11 = None\n", - "pos_9_12 = None\n", - "pos_9_13 = None\n", - "pos_9_14 = None\n", - "pos_9_15 = None\n", - "pos_9_2 = None\n", - "pos_9_3 = None\n", - "pos_9_4 = None\n", - "pos_9_5 = None\n", - "pos_9_6 = None\n", - "pos_9_7 = None\n", - "pos_9_8 = None\n", - "pos_9_9 = None\n", - "pos_dst_0 = None\n", - "pos_dst_1 = None\n", - "pos_dst_10 = None\n", - "pos_dst_2 = None\n", - "pos_dst_3 = None\n", - "pos_dst_4 = None\n", - "pos_dst_5 = None\n", - "pos_dst_6 = None\n", - "pos_dst_7 = None\n", - "pos_dst_8 = None\n", - "pos_dst_9 = None\n", - "pos_src_0 = None\n", - "pos_src_1 = None\n", - "pos_src_10 = None\n", - "pos_src_2 = None\n", - "pos_src_3 = None\n", - "pos_src_4 = None\n", - "pos_src_5 = None\n", - "pos_src_6 = None\n", - "pos_src_7 = None\n", - "pos_src_8 = None\n", - "pos_src_9 = None\n", - "src_0_0 = None\n", - "src_0_1 = None\n", - "src_0_10 = None\n", - "src_0_11 = None\n", - "src_0_12 = None\n", - "src_0_13 = None\n", - "src_0_14 = None\n", - "src_0_15 = None\n", - "src_0_2 = None\n", - "src_0_3 = None\n", - "src_0_4 = None\n", - "src_0_5 = None\n", - "src_0_6 = None\n", - "src_0_7 = None\n", - "src_0_8 = None\n", - "src_0_9 = None\n", - "src_10_0 = None\n", - "src_10_1 = None\n", - "src_10_10 = None\n", - "src_10_11 = None\n", - "src_10_12 = None\n", - "src_10_13 = None\n", - "src_10_14 = None\n", - "src_10_15 = None\n", - "src_10_2 = None\n", - "src_10_3 = None\n", - "src_10_4 = None\n", - "src_10_5 = None\n", - "src_10_6 = None\n", - "src_10_7 = None\n", - "src_10_8 = None\n", - "src_10_9 = None\n", - "src_1_0 = None\n", - "src_1_1 = None\n", - "src_1_10 = None\n", - "src_1_11 = None\n", - "src_1_12 = None\n", - "src_1_13 = None\n", - "src_1_14 = None\n", - "src_1_15 = None\n", - "src_1_2 = None\n", - "src_1_3 = None\n", - "src_1_4 = None\n", - "src_1_5 = None\n", - "src_1_6 = None\n", - "src_1_7 = None\n", - "src_1_8 = None\n", - "src_1_9 = None\n", - "src_2_0 = None\n", - "src_2_1 = None\n", - "src_2_10 = None\n", - "src_2_11 = None\n", - "src_2_12 = None\n", - "src_2_13 = None\n", - "src_2_14 = None\n", - "src_2_15 = None\n", - "src_2_2 = None\n", - "src_2_3 = None\n", - "src_2_4 = None\n", - "src_2_5 = None\n", - "src_2_6 = None\n", - "src_2_7 = None\n", - "src_2_8 = None\n", - "src_2_9 = None\n", - "src_3_0 = None\n", - "src_3_1 = None\n", - "src_3_10 = None\n", - "src_3_11 = None\n", - "src_3_12 = None\n", - "src_3_13 = None\n", - "src_3_14 = None\n", - "src_3_15 = None\n", - "src_3_2 = None\n", - "src_3_3 = None\n", - "src_3_4 = None\n", - "src_3_5 = None\n", - "src_3_6 = None\n", - "src_3_7 = None\n", - "src_3_8 = None\n", - "src_3_9 = None\n", - "src_4_0 = None\n", - "src_4_1 = None\n", - "src_4_10 = None\n", - "src_4_11 = None\n", - "src_4_12 = None\n", - "src_4_13 = None\n", - "src_4_14 = None\n", - "src_4_15 = None\n", - "src_4_2 = None\n", - "src_4_3 = None\n", - "src_4_4 = None\n", - "src_4_5 = None\n", - "src_4_6 = None\n", - "src_4_7 = None\n", - "src_4_8 = None\n", - "src_4_9 = None\n", - "src_5_0 = None\n", - "src_5_1 = None\n", - "src_5_10 = None\n", - "src_5_11 = None\n", - "src_5_12 = None\n", - "src_5_13 = None\n", - "src_5_14 = None\n", - "src_5_15 = None\n", - "src_5_2 = None\n", - "src_5_3 = None\n", - "src_5_4 = None\n", - "src_5_5 = None\n", - "src_5_6 = None\n", - "src_5_7 = None\n", - "src_5_8 = None\n", - "src_5_9 = None\n", - "src_6_0 = None\n", - "src_6_1 = None\n", - "src_6_10 = None\n", - "src_6_11 = None\n", - "src_6_12 = None\n", - "src_6_13 = None\n", - "src_6_14 = None\n", - "src_6_15 = None\n", - "src_6_2 = None\n", - "src_6_3 = None\n", - "src_6_4 = None\n", - "src_6_5 = None\n", - "src_6_6 = None\n", - "src_6_7 = None\n", - "src_6_8 = None\n", - "src_6_9 = None\n", - "src_7_0 = None\n", - "src_7_1 = None\n", - "src_7_10 = None\n", - "src_7_11 = None\n", - "src_7_12 = None\n", - "src_7_13 = None\n", - "src_7_14 = None\n", - "src_7_15 = None\n", - "src_7_2 = None\n", - "src_7_3 = None\n", - "src_7_4 = None\n", - "src_7_5 = None\n", - "src_7_6 = None\n", - "src_7_7 = None\n", - "src_7_8 = None\n", - "src_7_9 = None\n", - "src_8_0 = None\n", - "src_8_1 = None\n", - "src_8_10 = None\n", - "src_8_11 = None\n", - "src_8_12 = None\n", - "src_8_13 = None\n", - "src_8_14 = None\n", - "src_8_15 = None\n", - "src_8_2 = None\n", - "src_8_3 = None\n", - "src_8_4 = None\n", - "src_8_5 = None\n", - "src_8_6 = None\n", - "src_8_7 = None\n", - "src_8_8 = None\n", - "src_8_9 = None\n", - "src_9_0 = None\n", - "src_9_1 = None\n", - "src_9_10 = None\n", - "src_9_11 = None\n", - "src_9_12 = None\n", - "src_9_13 = None\n", - "src_9_14 = None\n", - "src_9_15 = None\n", - "src_9_2 = None\n", - "src_9_3 = None\n", - "src_9_4 = None\n", - "src_9_5 = None\n", - "src_9_6 = None\n", - "src_9_7 = None\n", - "src_9_8 = None\n", - "src_9_9 = None\n", - "src_dst_node0 = None\n", - "src_dst_node1 = None\n", - "src_dst_node10 = None\n", - "src_dst_node11 = None\n", - "src_dst_node12 = None\n", - "src_dst_node13 = None\n", - "src_dst_node14 = None\n", - "src_dst_node15 = None\n", - "src_dst_node2 = None\n", - "src_dst_node3 = None\n", - "src_dst_node4 = None\n", - "src_dst_node5 = None\n", - "src_dst_node6 = None\n", - "src_dst_node7 = None\n", - "src_dst_node8 = None\n", - "src_dst_node9 = None\n", - "[]\n" + "Objective value: 10.0\n", + "Optimal solution found:\n", + "Edge (4,0, 4) is part of the shortest path with value: 1.0\n", + "Edge (2,1, 0) is part of the shortest path with value: 1.0\n", + "Edge (2,2, 1) is part of the shortest path with value: 1.0\n", + "Edge (3,2, 3) is part of the shortest path with value: 1.0\n", + "Edge (2,3, 2) is part of the shortest path with value: 1.0\n", + "Edge (5,4, 0) is part of the shortest path with value: 1.0\n", + "Edge (3,6, 2) is part of the shortest path with value: 1.0\n", + "Edge (1,6, 7) is part of the shortest path with value: 1.0\n", + "Edge (1,7, 3) is part of the shortest path with value: 1.0\n", + "Edge (0,10, 6) is part of the shortest path with value: 1.0\n", + "Source node for src_0: 10\n", + "Source node for src_1: 6\n", + "Source node for src_2: 3\n", + "Source node for src_3: 6\n", + "Source node for src_4: 0\n", + "Source node for src_5: 4\n", + "Destination node for dst_0: 6\n", + "Destination node for dst_1: 3\n", + "Destination node for dst_2: 0\n", + "Destination node for dst_3: 3\n", + "Destination node for dst_4: 4\n", + "Destination node for dst_5: 0\n", + "Position of node (0, 0): 0.0\n", + "Position of node (1, 0): 0.0\n", + "Position of node (2, 0): 3.0\n", + "Position of node (3, 0): 0.0\n", + "Position of node (4, 0): 0.0\n", + "Position of node (5, 0): 1.0\n", + "Position of node (0, 1): 0.0\n", + "Position of node (1, 1): 0.0\n", + "Position of node (2, 1): 2.0\n", + "Position of node (3, 1): 0.0\n", + "Position of node (4, 1): 0.0\n", + "Position of node (5, 1): 0.0\n", + "Position of node (0, 2): 0.0\n", + "Position of node (1, 2): 0.0\n", + "Position of node (2, 2): 1.0\n", + "Position of node (3, 2): 1.0\n", + "Position of node (4, 2): 0.0\n", + "Position of node (5, 2): 0.0\n", + "Position of node (0, 3): 0.0\n", + "Position of node (1, 3): 2.0\n", + "Position of node (2, 3): 0.0\n", + "Position of node (3, 3): 2.0\n", + "Position of node (4, 3): 0.0\n", + "Position of node (5, 3): 0.0\n", + "Position of node (0, 4): 0.0\n", + "Position of node (1, 4): 0.0\n", + "Position of node (2, 4): 0.0\n", + "Position of node (3, 4): 0.0\n", + "Position of node (4, 4): 1.0\n", + "Position of node (5, 4): 0.0\n", + "Position of node (0, 5): 0.0\n", + "Position of node (1, 5): 0.0\n", + "Position of node (2, 5): 0.0\n", + "Position of node (3, 5): 0.0\n", + "Position of node (4, 5): 0.0\n", + "Position of node (5, 5): 0.0\n", + "Position of node (0, 6): 1.0\n", + "Position of node (1, 6): 0.0\n", + "Position of node (2, 6): 0.0\n", + "Position of node (3, 6): 0.0\n", + "Position of node (4, 6): 0.0\n", + "Position of node (5, 6): 0.0\n", + "Position of node (0, 7): 0.0\n", + "Position of node (1, 7): 1.0\n", + "Position of node (2, 7): 0.0\n", + "Position of node (3, 7): 0.0\n", + "Position of node (4, 7): 0.0\n", + "Position of node (5, 7): 0.0\n", + "Position of node (0, 8): 0.0\n", + "Position of node (1, 8): 0.0\n", + "Position of node (2, 8): 0.0\n", + "Position of node (3, 8): 0.0\n", + "Position of node (4, 8): 0.0\n", + "Position of node (5, 8): 0.0\n", + "Position of node (0, 9): 0.0\n", + "Position of node (1, 9): 0.0\n", + "Position of node (2, 9): 0.0\n", + "Position of node (3, 9): 0.0\n", + "Position of node (4, 9): 0.0\n", + "Position of node (5, 9): 0.0\n", + "Position of node (0, 10): 0.0\n", + "Position of node (1, 10): 0.0\n", + "Position of node (2, 10): 0.0\n", + "Position of node (3, 10): 0.0\n", + "Position of node (4, 10): 0.0\n", + "Position of node (5, 10): 0.0\n", + "Position of node (0, 11): 0.0\n", + "Position of node (1, 11): 0.0\n", + "Position of node (2, 11): 0.0\n", + "Position of node (3, 11): 0.0\n", + "Position of node (4, 11): 0.0\n", + "Position of node (5, 11): 0.0\n", + "Position of node (0, 12): 0.0\n", + "Position of node (1, 12): 0.0\n", + "Position of node (2, 12): 0.0\n", + "Position of node (3, 12): 0.0\n", + "Position of node (4, 12): 0.0\n", + "Position of node (5, 12): 0.0\n", + "Position of node (0, 13): 0.0\n", + "Position of node (1, 13): 0.0\n", + "Position of node (2, 13): 0.0\n", + "Position of node (3, 13): 0.0\n", + "Position of node (4, 13): 0.0\n", + "Position of node (5, 13): 0.0\n", + "Position of node (0, 14): 0.0\n", + "Position of node (1, 14): 0.0\n", + "Position of node (2, 14): 0.0\n", + "Position of node (3, 14): 0.0\n", + "Position of node (4, 14): 0.0\n", + "Position of node (5, 14): 0.0\n", + "Position of node (0, 15): 0.0\n", + "Position of node (1, 15): 0.0\n", + "Position of node (2, 15): 0.0\n", + "Position of node (3, 15): 0.0\n", + "Position of node (4, 15): 0.0\n", + "Position of node (5, 15): 0.0\n", + "Source position (src_0): 0.0\n", + "Source position (src_1): 0.0\n", + "Source position (src_2): 0.0\n", + "Source position (src_3): 0.0\n", + "Source position (src_4): 0.0\n", + "Source position (src_5): 0.0\n", + "Destination position (dst_0): 1.0\n", + "Destination position (dst_1): 2.0\n", + "Destination position (dst_2): 3.0\n", + "Destination position (dst_3): 2.0\n", + "Destination position (dst_4): 1.0\n", + "Destination position (dst_5): 1.0\n", + "choose_mid_0_node0 = 1.0\n", + "choose_mid_0_node1 = 1.0\n", + "choose_mid_0_node10 = 0.0\n", + "choose_mid_0_node11 = 0.0\n", + "choose_mid_0_node12 = 1.0\n", + "choose_mid_0_node13 = 1.0\n", + "choose_mid_0_node14 = 1.0\n", + "choose_mid_0_node15 = 1.0\n", + "choose_mid_0_node2 = 0.0\n", + "choose_mid_0_node3 = 1.0\n", + "choose_mid_0_node4 = 1.0\n", + "choose_mid_0_node5 = 1.0\n", + "choose_mid_0_node6 = 1.0\n", + "choose_mid_0_node7 = 1.0\n", + "choose_mid_0_node8 = 1.0\n", + "choose_mid_0_node9 = 1.0\n", + "choose_mid_1_node0 = 0.0\n", + "choose_mid_1_node1 = 0.0\n", + "choose_mid_1_node10 = 0.0\n", + "choose_mid_1_node11 = 0.0\n", + "choose_mid_1_node12 = 0.0\n", + "choose_mid_1_node13 = 0.0\n", + "choose_mid_1_node14 = 0.0\n", + "choose_mid_1_node15 = 0.0\n", + "choose_mid_1_node2 = 0.0\n", + "choose_mid_1_node3 = 0.0\n", + "choose_mid_1_node4 = 0.0\n", + "choose_mid_1_node5 = 0.0\n", + "choose_mid_1_node6 = 0.0\n", + "choose_mid_1_node7 = 0.0\n", + "choose_mid_1_node8 = 0.0\n", + "choose_mid_1_node9 = 0.0\n", + "choose_mid_2_node0 = 0.0\n", + "choose_mid_2_node1 = 0.0\n", + "choose_mid_2_node10 = 1.0\n", + "choose_mid_2_node11 = 1.0\n", + "choose_mid_2_node12 = 0.0\n", + "choose_mid_2_node13 = 0.0\n", + "choose_mid_2_node14 = 0.0\n", + "choose_mid_2_node15 = 0.0\n", + "choose_mid_2_node2 = 1.0\n", + "choose_mid_2_node3 = 0.0\n", + "choose_mid_2_node4 = 0.0\n", + "choose_mid_2_node5 = 0.0\n", + "choose_mid_2_node6 = 0.0\n", + "choose_mid_2_node7 = 0.0\n", + "choose_mid_2_node8 = 0.0\n", + "choose_mid_2_node9 = 0.0\n", + "choose_mid_3_node0 = 0.0\n", + "choose_mid_3_node1 = 0.0\n", + "choose_mid_3_node10 = 0.0\n", + "choose_mid_3_node11 = 0.0\n", + "choose_mid_3_node12 = 0.0\n", + "choose_mid_3_node13 = 0.0\n", + "choose_mid_3_node14 = 0.0\n", + "choose_mid_3_node15 = 0.0\n", + "choose_mid_3_node2 = 0.0\n", + "choose_mid_3_node3 = 0.0\n", + "choose_mid_3_node4 = 0.0\n", + "choose_mid_3_node5 = 0.0\n", + "choose_mid_3_node6 = 0.0\n", + "choose_mid_3_node7 = 0.0\n", + "choose_mid_3_node8 = 0.0\n", + "choose_mid_3_node9 = 0.0\n", + "choose_mid_4_node0 = 0.0\n", + "choose_mid_4_node1 = 0.0\n", + "choose_mid_4_node10 = 0.0\n", + "choose_mid_4_node11 = 0.0\n", + "choose_mid_4_node12 = 0.0\n", + "choose_mid_4_node13 = 0.0\n", + "choose_mid_4_node14 = 0.0\n", + "choose_mid_4_node15 = 0.0\n", + "choose_mid_4_node2 = 0.0\n", + "choose_mid_4_node3 = 0.0\n", + "choose_mid_4_node4 = 0.0\n", + "choose_mid_4_node5 = 0.0\n", + "choose_mid_4_node6 = 0.0\n", + "choose_mid_4_node7 = 0.0\n", + "choose_mid_4_node8 = 0.0\n", + "choose_mid_4_node9 = 0.0\n", + "choose_mid_5_node0 = 0.0\n", + "choose_mid_5_node1 = 0.0\n", + "choose_mid_5_node10 = 0.0\n", + "choose_mid_5_node11 = 0.0\n", + "choose_mid_5_node12 = 0.0\n", + "choose_mid_5_node13 = 0.0\n", + "choose_mid_5_node14 = 0.0\n", + "choose_mid_5_node15 = 0.0\n", + "choose_mid_5_node2 = 0.0\n", + "choose_mid_5_node3 = 0.0\n", + "choose_mid_5_node4 = 0.0\n", + "choose_mid_5_node5 = 0.0\n", + "choose_mid_5_node6 = 0.0\n", + "choose_mid_5_node7 = 0.0\n", + "choose_mid_5_node8 = 0.0\n", + "choose_mid_5_node9 = 0.0\n", + "dst_0_0 = 0.0\n", + "dst_0_1 = 0.0\n", + "dst_0_10 = 0.0\n", + "dst_0_11 = 0.0\n", + "dst_0_12 = 0.0\n", + "dst_0_13 = 0.0\n", + "dst_0_14 = 0.0\n", + "dst_0_15 = 0.0\n", + "dst_0_2 = 0.0\n", + "dst_0_3 = 0.0\n", + "dst_0_4 = 0.0\n", + "dst_0_5 = 0.0\n", + "dst_0_6 = 1.0\n", + "dst_0_7 = 0.0\n", + "dst_0_8 = 0.0\n", + "dst_0_9 = 0.0\n", + "dst_1_0 = 0.0\n", + "dst_1_1 = 0.0\n", + "dst_1_10 = 0.0\n", + "dst_1_11 = 0.0\n", + "dst_1_12 = 0.0\n", + "dst_1_13 = 0.0\n", + "dst_1_14 = 0.0\n", + "dst_1_15 = 0.0\n", + "dst_1_2 = 0.0\n", + "dst_1_3 = 1.0\n", + "dst_1_4 = 0.0\n", + "dst_1_5 = 0.0\n", + "dst_1_6 = 0.0\n", + "dst_1_7 = 0.0\n", + "dst_1_8 = 0.0\n", + "dst_1_9 = 0.0\n", + "dst_2_0 = 1.0\n", + "dst_2_1 = 0.0\n", + "dst_2_10 = 0.0\n", + "dst_2_11 = 0.0\n", + "dst_2_12 = 0.0\n", + "dst_2_13 = 0.0\n", + "dst_2_14 = 0.0\n", + "dst_2_15 = 0.0\n", + "dst_2_2 = 0.0\n", + "dst_2_3 = 0.0\n", + "dst_2_4 = 0.0\n", + "dst_2_5 = 0.0\n", + "dst_2_6 = 0.0\n", + "dst_2_7 = 0.0\n", + "dst_2_8 = 0.0\n", + "dst_2_9 = 0.0\n", + "dst_3_0 = 0.0\n", + "dst_3_1 = 0.0\n", + "dst_3_10 = 0.0\n", + "dst_3_11 = 0.0\n", + "dst_3_12 = 0.0\n", + "dst_3_13 = 0.0\n", + "dst_3_14 = 0.0\n", + "dst_3_15 = 0.0\n", + "dst_3_2 = 0.0\n", + "dst_3_3 = 1.0\n", + "dst_3_4 = 0.0\n", + "dst_3_5 = 0.0\n", + "dst_3_6 = 0.0\n", + "dst_3_7 = 0.0\n", + "dst_3_8 = 0.0\n", + "dst_3_9 = 0.0\n", + "dst_4_0 = 0.0\n", + "dst_4_1 = 0.0\n", + "dst_4_10 = 0.0\n", + "dst_4_11 = 0.0\n", + "dst_4_12 = 0.0\n", + "dst_4_13 = 0.0\n", + "dst_4_14 = 0.0\n", + "dst_4_15 = 0.0\n", + "dst_4_2 = 0.0\n", + "dst_4_3 = 0.0\n", + "dst_4_4 = 1.0\n", + "dst_4_5 = 0.0\n", + "dst_4_6 = 0.0\n", + "dst_4_7 = 0.0\n", + "dst_4_8 = 0.0\n", + "dst_4_9 = 0.0\n", + "dst_5_0 = 1.0\n", + "dst_5_1 = 0.0\n", + "dst_5_10 = 0.0\n", + "dst_5_11 = 0.0\n", + "dst_5_12 = 0.0\n", + "dst_5_13 = 0.0\n", + "dst_5_14 = 0.0\n", + "dst_5_15 = 0.0\n", + "dst_5_2 = 0.0\n", + "dst_5_3 = 0.0\n", + "dst_5_4 = 0.0\n", + "dst_5_5 = 0.0\n", + "dst_5_6 = 0.0\n", + "dst_5_7 = 0.0\n", + "dst_5_8 = 0.0\n", + "dst_5_9 = 0.0\n", + "edge_0_0_1 = 0.0\n", + "edge_0_0_4 = 0.0\n", + "edge_0_10_11 = 0.0\n", + "edge_0_10_14 = 0.0\n", + "edge_0_10_6 = 1.0\n", + "edge_0_10_9 = 0.0\n", + "edge_0_11_10 = 0.0\n", + "edge_0_11_15 = 0.0\n", + "edge_0_11_7 = 0.0\n", + "edge_0_12_13 = 0.0\n", + "edge_0_12_8 = 0.0\n", + "edge_0_13_12 = 0.0\n", + "edge_0_13_14 = 0.0\n", + "edge_0_13_9 = 0.0\n", + "edge_0_14_10 = 0.0\n", + "edge_0_14_13 = 0.0\n", + "edge_0_14_15 = 0.0\n", + "edge_0_15_11 = 0.0\n", + "edge_0_15_14 = 0.0\n", + "edge_0_1_0 = 0.0\n", + "edge_0_1_2 = 0.0\n", + "edge_0_1_5 = 0.0\n", + "edge_0_2_1 = 0.0\n", + "edge_0_2_3 = 0.0\n", + "edge_0_2_6 = 0.0\n", + "edge_0_3_2 = 0.0\n", + "edge_0_3_7 = 0.0\n", + "edge_0_4_0 = 0.0\n", + "edge_0_4_5 = 0.0\n", + "edge_0_4_8 = 0.0\n", + "edge_0_5_1 = 0.0\n", + "edge_0_5_4 = 0.0\n", + "edge_0_5_6 = 0.0\n", + "edge_0_5_9 = 0.0\n", + "edge_0_6_10 = 0.0\n", + "edge_0_6_2 = 0.0\n", + "edge_0_6_5 = 0.0\n", + "edge_0_6_7 = 0.0\n", + "edge_0_7_11 = 0.0\n", + "edge_0_7_3 = 0.0\n", + "edge_0_7_6 = 0.0\n", + "edge_0_8_12 = 0.0\n", + "edge_0_8_4 = 0.0\n", + "edge_0_8_9 = 0.0\n", + "edge_0_9_10 = 0.0\n", + "edge_0_9_13 = 0.0\n", + "edge_0_9_5 = 0.0\n", + "edge_0_9_8 = 0.0\n", + "edge_1_0_1 = 0.0\n", + "edge_1_0_4 = 0.0\n", + "edge_1_10_11 = 0.0\n", + "edge_1_10_14 = 0.0\n", + "edge_1_10_6 = 0.0\n", + "edge_1_10_9 = 0.0\n", + "edge_1_11_10 = 0.0\n", + "edge_1_11_15 = 0.0\n", + "edge_1_11_7 = 0.0\n", + "edge_1_12_13 = 0.0\n", + "edge_1_12_8 = 0.0\n", + "edge_1_13_12 = 0.0\n", + "edge_1_13_14 = 0.0\n", + "edge_1_13_9 = 0.0\n", + "edge_1_14_10 = 0.0\n", + "edge_1_14_13 = 0.0\n", + "edge_1_14_15 = 0.0\n", + "edge_1_15_11 = 0.0\n", + "edge_1_15_14 = 0.0\n", + "edge_1_1_0 = 0.0\n", + "edge_1_1_2 = 0.0\n", + "edge_1_1_5 = 0.0\n", + "edge_1_2_1 = 0.0\n", + "edge_1_2_3 = 0.0\n", + "edge_1_2_6 = 0.0\n", + "edge_1_3_2 = 0.0\n", + "edge_1_3_7 = 0.0\n", + "edge_1_4_0 = 0.0\n", + "edge_1_4_5 = 0.0\n", + "edge_1_4_8 = 0.0\n", + "edge_1_5_1 = 0.0\n", + "edge_1_5_4 = 0.0\n", + "edge_1_5_6 = 0.0\n", + "edge_1_5_9 = 0.0\n", + "edge_1_6_10 = 0.0\n", + "edge_1_6_2 = 0.0\n", + "edge_1_6_5 = 0.0\n", + "edge_1_6_7 = 1.0\n", + "edge_1_7_11 = 0.0\n", + "edge_1_7_3 = 1.0\n", + "edge_1_7_6 = 0.0\n", + "edge_1_8_12 = 0.0\n", + "edge_1_8_4 = 0.0\n", + "edge_1_8_9 = 0.0\n", + "edge_1_9_10 = 0.0\n", + "edge_1_9_13 = 0.0\n", + "edge_1_9_5 = 0.0\n", + "edge_1_9_8 = 0.0\n", + "edge_2_0_1 = 0.0\n", + "edge_2_0_4 = 0.0\n", + "edge_2_10_11 = 0.0\n", + "edge_2_10_14 = 0.0\n", + "edge_2_10_6 = 0.0\n", + "edge_2_10_9 = 0.0\n", + "edge_2_11_10 = 0.0\n", + "edge_2_11_15 = 0.0\n", + "edge_2_11_7 = 0.0\n", + "edge_2_12_13 = 0.0\n", + "edge_2_12_8 = 0.0\n", + "edge_2_13_12 = 0.0\n", + "edge_2_13_14 = 0.0\n", + "edge_2_13_9 = 0.0\n", + "edge_2_14_10 = 0.0\n", + "edge_2_14_13 = 0.0\n", + "edge_2_14_15 = 0.0\n", + "edge_2_15_11 = 0.0\n", + "edge_2_15_14 = 0.0\n", + "edge_2_1_0 = 1.0\n", + "edge_2_1_2 = 0.0\n", + "edge_2_1_5 = 0.0\n", + "edge_2_2_1 = 1.0\n", + "edge_2_2_3 = 0.0\n", + "edge_2_2_6 = 0.0\n", + "edge_2_3_2 = 1.0\n", + "edge_2_3_7 = 0.0\n", + "edge_2_4_0 = 0.0\n", + "edge_2_4_5 = 0.0\n", + "edge_2_4_8 = 0.0\n", + "edge_2_5_1 = 0.0\n", + "edge_2_5_4 = 0.0\n", + "edge_2_5_6 = 0.0\n", + "edge_2_5_9 = 0.0\n", + "edge_2_6_10 = 0.0\n", + "edge_2_6_2 = 0.0\n", + "edge_2_6_5 = 0.0\n", + "edge_2_6_7 = 0.0\n", + "edge_2_7_11 = 0.0\n", + "edge_2_7_3 = 0.0\n", + "edge_2_7_6 = 0.0\n", + "edge_2_8_12 = 0.0\n", + "edge_2_8_4 = 0.0\n", + "edge_2_8_9 = 0.0\n", + "edge_2_9_10 = 0.0\n", + "edge_2_9_13 = 0.0\n", + "edge_2_9_5 = 0.0\n", + "edge_2_9_8 = 0.0\n", + "edge_3_0_1 = 0.0\n", + "edge_3_0_4 = 0.0\n", + "edge_3_10_11 = 0.0\n", + "edge_3_10_14 = 0.0\n", + "edge_3_10_6 = 0.0\n", + "edge_3_10_9 = 0.0\n", + "edge_3_11_10 = 0.0\n", + "edge_3_11_15 = 0.0\n", + "edge_3_11_7 = 0.0\n", + "edge_3_12_13 = 0.0\n", + "edge_3_12_8 = 0.0\n", + "edge_3_13_12 = 0.0\n", + "edge_3_13_14 = 0.0\n", + "edge_3_13_9 = 0.0\n", + "edge_3_14_10 = 0.0\n", + "edge_3_14_13 = 0.0\n", + "edge_3_14_15 = 0.0\n", + "edge_3_15_11 = 0.0\n", + "edge_3_15_14 = 0.0\n", + "edge_3_1_0 = 0.0\n", + "edge_3_1_2 = 0.0\n", + "edge_3_1_5 = 0.0\n", + "edge_3_2_1 = 0.0\n", + "edge_3_2_3 = 1.0\n", + "edge_3_2_6 = 0.0\n", + "edge_3_3_2 = 0.0\n", + "edge_3_3_7 = 0.0\n", + "edge_3_4_0 = 0.0\n", + "edge_3_4_5 = 0.0\n", + "edge_3_4_8 = 0.0\n", + "edge_3_5_1 = 0.0\n", + "edge_3_5_4 = 0.0\n", + "edge_3_5_6 = 0.0\n", + "edge_3_5_9 = 0.0\n", + "edge_3_6_10 = 0.0\n", + "edge_3_6_2 = 1.0\n", + "edge_3_6_5 = 0.0\n", + "edge_3_6_7 = 0.0\n", + "edge_3_7_11 = 0.0\n", + "edge_3_7_3 = 0.0\n", + "edge_3_7_6 = 0.0\n", + "edge_3_8_12 = 0.0\n", + "edge_3_8_4 = 0.0\n", + "edge_3_8_9 = 0.0\n", + "edge_3_9_10 = 0.0\n", + "edge_3_9_13 = 0.0\n", + "edge_3_9_5 = 0.0\n", + "edge_3_9_8 = 0.0\n", + "edge_4_0_1 = 0.0\n", + "edge_4_0_4 = 1.0\n", + "edge_4_10_11 = 0.0\n", + "edge_4_10_14 = 0.0\n", + "edge_4_10_6 = 0.0\n", + "edge_4_10_9 = 0.0\n", + "edge_4_11_10 = 0.0\n", + "edge_4_11_15 = 0.0\n", + "edge_4_11_7 = 0.0\n", + "edge_4_12_13 = 0.0\n", + "edge_4_12_8 = 0.0\n", + "edge_4_13_12 = 0.0\n", + "edge_4_13_14 = 0.0\n", + "edge_4_13_9 = 0.0\n", + "edge_4_14_10 = 0.0\n", + "edge_4_14_13 = 0.0\n", + "edge_4_14_15 = 0.0\n", + "edge_4_15_11 = 0.0\n", + "edge_4_15_14 = 0.0\n", + "edge_4_1_0 = 0.0\n", + "edge_4_1_2 = 0.0\n", + "edge_4_1_5 = 0.0\n", + "edge_4_2_1 = 0.0\n", + "edge_4_2_3 = 0.0\n", + "edge_4_2_6 = 0.0\n", + "edge_4_3_2 = 0.0\n", + "edge_4_3_7 = 0.0\n", + "edge_4_4_0 = 0.0\n", + "edge_4_4_5 = 0.0\n", + "edge_4_4_8 = 0.0\n", + "edge_4_5_1 = 0.0\n", + "edge_4_5_4 = 0.0\n", + "edge_4_5_6 = 0.0\n", + "edge_4_5_9 = 0.0\n", + "edge_4_6_10 = 0.0\n", + "edge_4_6_2 = 0.0\n", + "edge_4_6_5 = 0.0\n", + "edge_4_6_7 = 0.0\n", + "edge_4_7_11 = 0.0\n", + "edge_4_7_3 = 0.0\n", + "edge_4_7_6 = 0.0\n", + "edge_4_8_12 = 0.0\n", + "edge_4_8_4 = 0.0\n", + "edge_4_8_9 = 0.0\n", + "edge_4_9_10 = 0.0\n", + "edge_4_9_13 = 0.0\n", + "edge_4_9_5 = 0.0\n", + "edge_4_9_8 = 0.0\n", + "edge_5_0_1 = 0.0\n", + "edge_5_0_4 = 0.0\n", + "edge_5_10_11 = 0.0\n", + "edge_5_10_14 = 0.0\n", + "edge_5_10_6 = 0.0\n", + "edge_5_10_9 = 0.0\n", + "edge_5_11_10 = 0.0\n", + "edge_5_11_15 = 0.0\n", + "edge_5_11_7 = 0.0\n", + "edge_5_12_13 = 0.0\n", + "edge_5_12_8 = 0.0\n", + "edge_5_13_12 = 0.0\n", + "edge_5_13_14 = 0.0\n", + "edge_5_13_9 = 0.0\n", + "edge_5_14_10 = 0.0\n", + "edge_5_14_13 = 0.0\n", + "edge_5_14_15 = 0.0\n", + "edge_5_15_11 = 0.0\n", + "edge_5_15_14 = 0.0\n", + "edge_5_1_0 = 0.0\n", + "edge_5_1_2 = 0.0\n", + "edge_5_1_5 = 0.0\n", + "edge_5_2_1 = 0.0\n", + "edge_5_2_3 = 0.0\n", + "edge_5_2_6 = 0.0\n", + "edge_5_3_2 = 0.0\n", + "edge_5_3_7 = 0.0\n", + "edge_5_4_0 = 1.0\n", + "edge_5_4_5 = 0.0\n", + "edge_5_4_8 = 0.0\n", + "edge_5_5_1 = 0.0\n", + "edge_5_5_4 = 0.0\n", + "edge_5_5_6 = 0.0\n", + "edge_5_5_9 = 0.0\n", + "edge_5_6_10 = 0.0\n", + "edge_5_6_2 = 0.0\n", + "edge_5_6_5 = 0.0\n", + "edge_5_6_7 = 0.0\n", + "edge_5_7_11 = 0.0\n", + "edge_5_7_3 = 0.0\n", + "edge_5_7_6 = 0.0\n", + "edge_5_8_12 = 0.0\n", + "edge_5_8_4 = 0.0\n", + "edge_5_8_9 = 0.0\n", + "edge_5_9_10 = 0.0\n", + "edge_5_9_13 = 0.0\n", + "edge_5_9_5 = 0.0\n", + "edge_5_9_8 = 0.0\n", + "inout_layer0_node0 = 0.0\n", + "inout_layer0_node1 = 0.0\n", + "inout_layer0_node10 = 0.0\n", + "inout_layer0_node11 = 0.0\n", + "inout_layer0_node12 = 0.0\n", + "inout_layer0_node13 = 0.0\n", + "inout_layer0_node14 = 0.0\n", + "inout_layer0_node15 = 0.0\n", + "inout_layer0_node2 = 0.0\n", + "inout_layer0_node3 = 0.0\n", + "inout_layer0_node4 = 0.0\n", + "inout_layer0_node5 = 0.0\n", + "inout_layer0_node6 = 0.0\n", + "inout_layer0_node7 = 0.0\n", + "inout_layer0_node8 = 0.0\n", + "inout_layer0_node9 = 0.0\n", + "inout_layer1_node0 = 0.0\n", + "inout_layer1_node1 = 0.0\n", + "inout_layer1_node10 = 0.0\n", + "inout_layer1_node11 = 0.0\n", + "inout_layer1_node12 = 0.0\n", + "inout_layer1_node13 = 0.0\n", + "inout_layer1_node14 = 0.0\n", + "inout_layer1_node15 = 0.0\n", + "inout_layer1_node2 = 0.0\n", + "inout_layer1_node3 = 0.0\n", + "inout_layer1_node4 = 0.0\n", + "inout_layer1_node5 = 0.0\n", + "inout_layer1_node6 = 0.0\n", + "inout_layer1_node7 = 1.0\n", + "inout_layer1_node8 = 0.0\n", + "inout_layer1_node9 = 0.0\n", + "inout_layer2_node0 = 0.0\n", + "inout_layer2_node1 = 1.0\n", + "inout_layer2_node10 = 0.0\n", + "inout_layer2_node11 = 0.0\n", + "inout_layer2_node12 = 0.0\n", + "inout_layer2_node13 = 0.0\n", + "inout_layer2_node14 = 0.0\n", + "inout_layer2_node15 = 0.0\n", + "inout_layer2_node2 = 1.0\n", + "inout_layer2_node3 = 0.0\n", + "inout_layer2_node4 = 0.0\n", + "inout_layer2_node5 = 0.0\n", + "inout_layer2_node6 = 0.0\n", + "inout_layer2_node7 = 0.0\n", + "inout_layer2_node8 = 0.0\n", + "inout_layer2_node9 = 0.0\n", + "inout_layer3_node0 = 0.0\n", + "inout_layer3_node1 = 0.0\n", + "inout_layer3_node10 = 0.0\n", + "inout_layer3_node11 = 0.0\n", + "inout_layer3_node12 = 0.0\n", + "inout_layer3_node13 = 0.0\n", + "inout_layer3_node14 = 0.0\n", + "inout_layer3_node15 = 0.0\n", + "inout_layer3_node2 = 1.0\n", + "inout_layer3_node3 = 0.0\n", + "inout_layer3_node4 = 0.0\n", + "inout_layer3_node5 = 0.0\n", + "inout_layer3_node6 = 0.0\n", + "inout_layer3_node7 = 0.0\n", + "inout_layer3_node8 = 0.0\n", + "inout_layer3_node9 = 0.0\n", + "inout_layer4_node0 = 0.0\n", + "inout_layer4_node1 = 0.0\n", + "inout_layer4_node10 = 0.0\n", + "inout_layer4_node11 = 0.0\n", + "inout_layer4_node12 = 0.0\n", + "inout_layer4_node13 = 0.0\n", + "inout_layer4_node14 = 0.0\n", + "inout_layer4_node15 = 0.0\n", + "inout_layer4_node2 = 0.0\n", + "inout_layer4_node3 = 0.0\n", + "inout_layer4_node4 = 0.0\n", + "inout_layer4_node5 = 0.0\n", + "inout_layer4_node6 = 0.0\n", + "inout_layer4_node7 = 0.0\n", + "inout_layer4_node8 = 0.0\n", + "inout_layer4_node9 = 0.0\n", + "inout_layer5_node0 = 0.0\n", + "inout_layer5_node1 = 0.0\n", + "inout_layer5_node10 = 0.0\n", + "inout_layer5_node11 = 0.0\n", + "inout_layer5_node12 = 0.0\n", + "inout_layer5_node13 = 0.0\n", + "inout_layer5_node14 = 0.0\n", + "inout_layer5_node15 = 0.0\n", + "inout_layer5_node2 = 0.0\n", + "inout_layer5_node3 = 0.0\n", + "inout_layer5_node4 = 0.0\n", + "inout_layer5_node5 = 0.0\n", + "inout_layer5_node6 = 0.0\n", + "inout_layer5_node7 = 0.0\n", + "inout_layer5_node8 = 0.0\n", + "inout_layer5_node9 = 0.0\n", + "inout_total_node0 = 0.0\n", + "inout_total_node1 = 1.0\n", + "inout_total_node10 = 0.0\n", + "inout_total_node11 = 0.0\n", + "inout_total_node12 = 0.0\n", + "inout_total_node13 = 0.0\n", + "inout_total_node14 = 0.0\n", + "inout_total_node15 = 0.0\n", + "inout_total_node2 = 2.0\n", + "inout_total_node3 = 0.0\n", + "inout_total_node4 = 0.0\n", + "inout_total_node5 = 0.0\n", + "inout_total_node6 = 0.0\n", + "inout_total_node7 = 1.0\n", + "inout_total_node8 = 0.0\n", + "inout_total_node9 = 0.0\n", + "inout_total_norm0 = 0.0\n", + "inout_total_norm1 = 0.0\n", + "inout_total_norm10 = 0.0\n", + "inout_total_norm11 = 0.0\n", + "inout_total_norm12 = 0.0\n", + "inout_total_norm13 = 0.0\n", + "inout_total_norm14 = 0.0\n", + "inout_total_norm15 = 0.0\n", + "inout_total_norm2 = 1.0\n", + "inout_total_norm3 = 0.0\n", + "inout_total_norm4 = 0.0\n", + "inout_total_norm5 = 0.0\n", + "inout_total_norm6 = 0.0\n", + "inout_total_norm7 = 0.0\n", + "inout_total_norm8 = 0.0\n", + "inout_total_norm9 = 0.0\n", + "is_pos_nonzero_0_0 = 0.0\n", + "is_pos_nonzero_0_1 = 0.0\n", + "is_pos_nonzero_0_10 = 0.0\n", + "is_pos_nonzero_0_11 = 0.0\n", + "is_pos_nonzero_0_12 = 0.0\n", + "is_pos_nonzero_0_13 = 0.0\n", + "is_pos_nonzero_0_14 = 0.0\n", + "is_pos_nonzero_0_15 = 0.0\n", + "is_pos_nonzero_0_2 = 0.0\n", + "is_pos_nonzero_0_3 = 0.0\n", + "is_pos_nonzero_0_4 = 0.0\n", + "is_pos_nonzero_0_5 = 0.0\n", + "is_pos_nonzero_0_6 = 1.0\n", + "is_pos_nonzero_0_7 = 0.0\n", + "is_pos_nonzero_0_8 = 0.0\n", + "is_pos_nonzero_0_9 = 0.0\n", + "is_pos_nonzero_1_0 = 0.0\n", + "is_pos_nonzero_1_1 = 0.0\n", + "is_pos_nonzero_1_10 = 0.0\n", + "is_pos_nonzero_1_11 = 0.0\n", + "is_pos_nonzero_1_12 = 0.0\n", + "is_pos_nonzero_1_13 = 0.0\n", + "is_pos_nonzero_1_14 = 0.0\n", + "is_pos_nonzero_1_15 = 0.0\n", + "is_pos_nonzero_1_2 = 0.0\n", + "is_pos_nonzero_1_3 = 1.0\n", + "is_pos_nonzero_1_4 = 0.0\n", + "is_pos_nonzero_1_5 = 0.0\n", + "is_pos_nonzero_1_6 = 0.0\n", + "is_pos_nonzero_1_7 = 1.0\n", + "is_pos_nonzero_1_8 = 0.0\n", + "is_pos_nonzero_1_9 = 0.0\n", + "is_pos_nonzero_2_0 = 1.0\n", + "is_pos_nonzero_2_1 = 1.0\n", + "is_pos_nonzero_2_10 = 0.0\n", + "is_pos_nonzero_2_11 = 0.0\n", + "is_pos_nonzero_2_12 = 0.0\n", + "is_pos_nonzero_2_13 = 0.0\n", + "is_pos_nonzero_2_14 = 0.0\n", + "is_pos_nonzero_2_15 = 0.0\n", + "is_pos_nonzero_2_2 = 1.0\n", + "is_pos_nonzero_2_3 = 0.0\n", + "is_pos_nonzero_2_4 = 0.0\n", + "is_pos_nonzero_2_5 = 0.0\n", + "is_pos_nonzero_2_6 = 0.0\n", + "is_pos_nonzero_2_7 = 0.0\n", + "is_pos_nonzero_2_8 = 0.0\n", + "is_pos_nonzero_2_9 = 0.0\n", + "is_pos_nonzero_3_0 = 0.0\n", + "is_pos_nonzero_3_1 = 0.0\n", + "is_pos_nonzero_3_10 = 0.0\n", + "is_pos_nonzero_3_11 = 0.0\n", + "is_pos_nonzero_3_12 = 0.0\n", + "is_pos_nonzero_3_13 = 0.0\n", + "is_pos_nonzero_3_14 = 0.0\n", + "is_pos_nonzero_3_15 = 0.0\n", + "is_pos_nonzero_3_2 = 1.0\n", + "is_pos_nonzero_3_3 = 1.0\n", + "is_pos_nonzero_3_4 = 0.0\n", + "is_pos_nonzero_3_5 = 0.0\n", + "is_pos_nonzero_3_6 = 0.0\n", + "is_pos_nonzero_3_7 = 0.0\n", + "is_pos_nonzero_3_8 = 0.0\n", + "is_pos_nonzero_3_9 = 0.0\n", + "is_pos_nonzero_4_0 = 0.0\n", + "is_pos_nonzero_4_1 = 0.0\n", + "is_pos_nonzero_4_10 = 0.0\n", + "is_pos_nonzero_4_11 = 0.0\n", + "is_pos_nonzero_4_12 = 0.0\n", + "is_pos_nonzero_4_13 = 0.0\n", + "is_pos_nonzero_4_14 = 0.0\n", + "is_pos_nonzero_4_15 = 0.0\n", + "is_pos_nonzero_4_2 = 0.0\n", + "is_pos_nonzero_4_3 = 0.0\n", + "is_pos_nonzero_4_4 = 1.0\n", + "is_pos_nonzero_4_5 = 0.0\n", + "is_pos_nonzero_4_6 = 0.0\n", + "is_pos_nonzero_4_7 = 0.0\n", + "is_pos_nonzero_4_8 = 0.0\n", + "is_pos_nonzero_4_9 = 0.0\n", + "is_pos_nonzero_5_0 = 1.0\n", + "is_pos_nonzero_5_1 = 0.0\n", + "is_pos_nonzero_5_10 = 0.0\n", + "is_pos_nonzero_5_11 = 0.0\n", + "is_pos_nonzero_5_12 = 0.0\n", + "is_pos_nonzero_5_13 = 0.0\n", + "is_pos_nonzero_5_14 = 0.0\n", + "is_pos_nonzero_5_15 = 0.0\n", + "is_pos_nonzero_5_2 = 0.0\n", + "is_pos_nonzero_5_3 = 0.0\n", + "is_pos_nonzero_5_4 = 0.0\n", + "is_pos_nonzero_5_5 = 0.0\n", + "is_pos_nonzero_5_6 = 0.0\n", + "is_pos_nonzero_5_7 = 0.0\n", + "is_pos_nonzero_5_8 = 0.0\n", + "is_pos_nonzero_5_9 = 0.0\n", + "max_pos_dst = 3.0\n", + "path_add_individual0_0 = 0.0\n", + "path_add_individual0_1 = 0.0\n", + "path_add_individual0_10 = 0.0\n", + "path_add_individual0_11 = 0.0\n", + "path_add_individual0_12 = 0.0\n", + "path_add_individual0_13 = 0.0\n", + "path_add_individual0_14 = 0.0\n", + "path_add_individual0_15 = 0.0\n", + "path_add_individual0_2 = 0.0\n", + "path_add_individual0_3 = 0.0\n", + "path_add_individual0_4 = 0.0\n", + "path_add_individual0_5 = 0.0\n", + "path_add_individual0_6 = 0.0\n", + "path_add_individual0_7 = 0.0\n", + "path_add_individual0_8 = 0.0\n", + "path_add_individual0_9 = 0.0\n", + "path_add_individual1_0 = 0.0\n", + "path_add_individual1_1 = 0.0\n", + "path_add_individual1_10 = 0.0\n", + "path_add_individual1_11 = 0.0\n", + "path_add_individual1_12 = 0.0\n", + "path_add_individual1_13 = 0.0\n", + "path_add_individual1_14 = 0.0\n", + "path_add_individual1_15 = 0.0\n", + "path_add_individual1_2 = 0.0\n", + "path_add_individual1_3 = 0.0\n", + "path_add_individual1_4 = 0.0\n", + "path_add_individual1_5 = 0.0\n", + "path_add_individual1_6 = 0.0\n", + "path_add_individual1_7 = 0.0\n", + "path_add_individual1_8 = 0.0\n", + "path_add_individual1_9 = 0.0\n", + "path_add_individual2_0 = 0.0\n", + "path_add_individual2_1 = 0.0\n", + "path_add_individual2_10 = 0.0\n", + "path_add_individual2_11 = 0.0\n", + "path_add_individual2_12 = 0.0\n", + "path_add_individual2_13 = 0.0\n", + "path_add_individual2_14 = 0.0\n", + "path_add_individual2_15 = 0.0\n", + "path_add_individual2_2 = 0.0\n", + "path_add_individual2_3 = 0.0\n", + "path_add_individual2_4 = 0.0\n", + "path_add_individual2_5 = 0.0\n", + "path_add_individual2_6 = 0.0\n", + "path_add_individual2_7 = 0.0\n", + "path_add_individual2_8 = 0.0\n", + "path_add_individual2_9 = 0.0\n", + "path_add_individual3_0 = 0.0\n", + "path_add_individual3_1 = 0.0\n", + "path_add_individual3_10 = 0.0\n", + "path_add_individual3_11 = 0.0\n", + "path_add_individual3_12 = 0.0\n", + "path_add_individual3_13 = 0.0\n", + "path_add_individual3_14 = 0.0\n", + "path_add_individual3_15 = 0.0\n", + "path_add_individual3_2 = 0.0\n", + "path_add_individual3_3 = 0.0\n", + "path_add_individual3_4 = 0.0\n", + "path_add_individual3_5 = 0.0\n", + "path_add_individual3_6 = 0.0\n", + "path_add_individual3_7 = 0.0\n", + "path_add_individual3_8 = 0.0\n", + "path_add_individual3_9 = 0.0\n", + "path_add_individual4_0 = 0.0\n", + "path_add_individual4_1 = 0.0\n", + "path_add_individual4_10 = 0.0\n", + "path_add_individual4_11 = 0.0\n", + "path_add_individual4_12 = 0.0\n", + "path_add_individual4_13 = 0.0\n", + "path_add_individual4_14 = 0.0\n", + "path_add_individual4_15 = 0.0\n", + "path_add_individual4_2 = 0.0\n", + "path_add_individual4_3 = 0.0\n", + "path_add_individual4_4 = 0.0\n", + "path_add_individual4_5 = 0.0\n", + "path_add_individual4_6 = 0.0\n", + "path_add_individual4_7 = 0.0\n", + "path_add_individual4_8 = 0.0\n", + "path_add_individual4_9 = 0.0\n", + "path_add_individual5_0 = 0.0\n", + "path_add_individual5_1 = 0.0\n", + "path_add_individual5_10 = 0.0\n", + "path_add_individual5_11 = 0.0\n", + "path_add_individual5_12 = 0.0\n", + "path_add_individual5_13 = 0.0\n", + "path_add_individual5_14 = 0.0\n", + "path_add_individual5_15 = 0.0\n", + "path_add_individual5_2 = 0.0\n", + "path_add_individual5_3 = 0.0\n", + "path_add_individual5_4 = 0.0\n", + "path_add_individual5_5 = 0.0\n", + "path_add_individual5_6 = 0.0\n", + "path_add_individual5_7 = 0.0\n", + "path_add_individual5_8 = 0.0\n", + "path_add_individual5_9 = 0.0\n", + "path_add_individual_2_0_0 = 0.0\n", + "path_add_individual_2_0_1 = 0.0\n", + "path_add_individual_2_0_10 = 0.0\n", + "path_add_individual_2_0_11 = 0.0\n", + "path_add_individual_2_0_12 = 0.0\n", + "path_add_individual_2_0_13 = 0.0\n", + "path_add_individual_2_0_14 = 0.0\n", + "path_add_individual_2_0_15 = 0.0\n", + "path_add_individual_2_0_2 = 0.0\n", + "path_add_individual_2_0_3 = 0.0\n", + "path_add_individual_2_0_4 = 0.0\n", + "path_add_individual_2_0_5 = 0.0\n", + "path_add_individual_2_0_6 = 0.0\n", + "path_add_individual_2_0_7 = 0.0\n", + "path_add_individual_2_0_8 = 0.0\n", + "path_add_individual_2_0_9 = 0.0\n", + "path_add_individual_2_1_0 = 0.0\n", + "path_add_individual_2_1_1 = 0.0\n", + "path_add_individual_2_1_10 = 0.0\n", + "path_add_individual_2_1_11 = 0.0\n", + "path_add_individual_2_1_12 = 0.0\n", + "path_add_individual_2_1_13 = 0.0\n", + "path_add_individual_2_1_14 = 0.0\n", + "path_add_individual_2_1_15 = 0.0\n", + "path_add_individual_2_1_2 = 0.0\n", + "path_add_individual_2_1_3 = 0.0\n", + "path_add_individual_2_1_4 = 0.0\n", + "path_add_individual_2_1_5 = 0.0\n", + "path_add_individual_2_1_6 = 0.0\n", + "path_add_individual_2_1_7 = 0.0\n", + "path_add_individual_2_1_8 = 0.0\n", + "path_add_individual_2_1_9 = 0.0\n", + "path_add_individual_2_2_0 = 0.0\n", + "path_add_individual_2_2_1 = 0.0\n", + "path_add_individual_2_2_10 = 0.0\n", + "path_add_individual_2_2_11 = 0.0\n", + "path_add_individual_2_2_12 = 0.0\n", + "path_add_individual_2_2_13 = 0.0\n", + "path_add_individual_2_2_14 = 0.0\n", + "path_add_individual_2_2_15 = 0.0\n", + "path_add_individual_2_2_2 = 1.0\n", + "path_add_individual_2_2_3 = 0.0\n", + "path_add_individual_2_2_4 = 0.0\n", + "path_add_individual_2_2_5 = 0.0\n", + "path_add_individual_2_2_6 = 0.0\n", + "path_add_individual_2_2_7 = 0.0\n", + "path_add_individual_2_2_8 = 0.0\n", + "path_add_individual_2_2_9 = 0.0\n", + "path_add_individual_2_3_0 = 0.0\n", + "path_add_individual_2_3_1 = 0.0\n", + "path_add_individual_2_3_10 = 0.0\n", + "path_add_individual_2_3_11 = 0.0\n", + "path_add_individual_2_3_12 = 0.0\n", + "path_add_individual_2_3_13 = 0.0\n", + "path_add_individual_2_3_14 = 0.0\n", + "path_add_individual_2_3_15 = 0.0\n", + "path_add_individual_2_3_2 = 1.0\n", + "path_add_individual_2_3_3 = 0.0\n", + "path_add_individual_2_3_4 = 0.0\n", + "path_add_individual_2_3_5 = 0.0\n", + "path_add_individual_2_3_6 = 0.0\n", + "path_add_individual_2_3_7 = 0.0\n", + "path_add_individual_2_3_8 = 0.0\n", + "path_add_individual_2_3_9 = 0.0\n", + "path_add_individual_2_4_0 = 0.0\n", + "path_add_individual_2_4_1 = 0.0\n", + "path_add_individual_2_4_10 = 0.0\n", + "path_add_individual_2_4_11 = 0.0\n", + "path_add_individual_2_4_12 = 0.0\n", + "path_add_individual_2_4_13 = 0.0\n", + "path_add_individual_2_4_14 = 0.0\n", + "path_add_individual_2_4_15 = 0.0\n", + "path_add_individual_2_4_2 = 0.0\n", + "path_add_individual_2_4_3 = 0.0\n", + "path_add_individual_2_4_4 = 0.0\n", + "path_add_individual_2_4_5 = 0.0\n", + "path_add_individual_2_4_6 = 0.0\n", + "path_add_individual_2_4_7 = 0.0\n", + "path_add_individual_2_4_8 = 0.0\n", + "path_add_individual_2_4_9 = 0.0\n", + "path_add_individual_2_5_0 = 0.0\n", + "path_add_individual_2_5_1 = 0.0\n", + "path_add_individual_2_5_10 = 0.0\n", + "path_add_individual_2_5_11 = 0.0\n", + "path_add_individual_2_5_12 = 0.0\n", + "path_add_individual_2_5_13 = 0.0\n", + "path_add_individual_2_5_14 = 0.0\n", + "path_add_individual_2_5_15 = 0.0\n", + "path_add_individual_2_5_2 = 0.0\n", + "path_add_individual_2_5_3 = 0.0\n", + "path_add_individual_2_5_4 = 0.0\n", + "path_add_individual_2_5_5 = 0.0\n", + "path_add_individual_2_5_6 = 0.0\n", + "path_add_individual_2_5_7 = 0.0\n", + "path_add_individual_2_5_8 = 0.0\n", + "path_add_individual_2_5_9 = 0.0\n", + "path_add_individual_3_0_0 = 0.0\n", + "path_add_individual_3_0_1 = 0.0\n", + "path_add_individual_3_0_10 = 0.0\n", + "path_add_individual_3_0_11 = 0.0\n", + "path_add_individual_3_0_12 = 0.0\n", + "path_add_individual_3_0_13 = 0.0\n", + "path_add_individual_3_0_14 = 0.0\n", + "path_add_individual_3_0_15 = 0.0\n", + "path_add_individual_3_0_2 = 0.0\n", + "path_add_individual_3_0_3 = 0.0\n", + "path_add_individual_3_0_4 = 0.0\n", + "path_add_individual_3_0_5 = 0.0\n", + "path_add_individual_3_0_6 = 0.0\n", + "path_add_individual_3_0_7 = 0.0\n", + "path_add_individual_3_0_8 = 0.0\n", + "path_add_individual_3_0_9 = 0.0\n", + "path_add_individual_3_1_0 = 0.0\n", + "path_add_individual_3_1_1 = 0.0\n", + "path_add_individual_3_1_10 = 0.0\n", + "path_add_individual_3_1_11 = 0.0\n", + "path_add_individual_3_1_12 = 0.0\n", + "path_add_individual_3_1_13 = 0.0\n", + "path_add_individual_3_1_14 = 0.0\n", + "path_add_individual_3_1_15 = 0.0\n", + "path_add_individual_3_1_2 = 0.0\n", + "path_add_individual_3_1_3 = 0.0\n", + "path_add_individual_3_1_4 = 0.0\n", + "path_add_individual_3_1_5 = 0.0\n", + "path_add_individual_3_1_6 = 0.0\n", + "path_add_individual_3_1_7 = 0.0\n", + "path_add_individual_3_1_8 = 0.0\n", + "path_add_individual_3_1_9 = 0.0\n", + "path_add_individual_3_2_0 = 0.0\n", + "path_add_individual_3_2_1 = 0.0\n", + "path_add_individual_3_2_10 = 0.0\n", + "path_add_individual_3_2_11 = 0.0\n", + "path_add_individual_3_2_12 = 0.0\n", + "path_add_individual_3_2_13 = 0.0\n", + "path_add_individual_3_2_14 = 0.0\n", + "path_add_individual_3_2_15 = 0.0\n", + "path_add_individual_3_2_2 = 0.0\n", + "path_add_individual_3_2_3 = 0.0\n", + "path_add_individual_3_2_4 = 0.0\n", + "path_add_individual_3_2_5 = 0.0\n", + "path_add_individual_3_2_6 = 0.0\n", + "path_add_individual_3_2_7 = 0.0\n", + "path_add_individual_3_2_8 = 0.0\n", + "path_add_individual_3_2_9 = 0.0\n", + "path_add_individual_3_3_0 = 0.0\n", + "path_add_individual_3_3_1 = 0.0\n", + "path_add_individual_3_3_10 = 0.0\n", + "path_add_individual_3_3_11 = 0.0\n", + "path_add_individual_3_3_12 = 0.0\n", + "path_add_individual_3_3_13 = 0.0\n", + "path_add_individual_3_3_14 = 0.0\n", + "path_add_individual_3_3_15 = 0.0\n", + "path_add_individual_3_3_2 = 1.0\n", + "path_add_individual_3_3_3 = 0.0\n", + "path_add_individual_3_3_4 = 0.0\n", + "path_add_individual_3_3_5 = 0.0\n", + "path_add_individual_3_3_6 = 0.0\n", + "path_add_individual_3_3_7 = 0.0\n", + "path_add_individual_3_3_8 = 0.0\n", + "path_add_individual_3_3_9 = 0.0\n", + "path_add_individual_3_4_0 = 0.0\n", + "path_add_individual_3_4_1 = 0.0\n", + "path_add_individual_3_4_10 = 0.0\n", + "path_add_individual_3_4_11 = 0.0\n", + "path_add_individual_3_4_12 = 0.0\n", + "path_add_individual_3_4_13 = 0.0\n", + "path_add_individual_3_4_14 = 0.0\n", + "path_add_individual_3_4_15 = 0.0\n", + "path_add_individual_3_4_2 = 0.0\n", + "path_add_individual_3_4_3 = 0.0\n", + "path_add_individual_3_4_4 = 0.0\n", + "path_add_individual_3_4_5 = 0.0\n", + "path_add_individual_3_4_6 = 0.0\n", + "path_add_individual_3_4_7 = 0.0\n", + "path_add_individual_3_4_8 = 0.0\n", + "path_add_individual_3_4_9 = 0.0\n", + "path_add_individual_3_5_0 = 0.0\n", + "path_add_individual_3_5_1 = 0.0\n", + "path_add_individual_3_5_10 = 0.0\n", + "path_add_individual_3_5_11 = 0.0\n", + "path_add_individual_3_5_12 = 0.0\n", + "path_add_individual_3_5_13 = 0.0\n", + "path_add_individual_3_5_14 = 0.0\n", + "path_add_individual_3_5_15 = 0.0\n", + "path_add_individual_3_5_2 = 0.0\n", + "path_add_individual_3_5_3 = 0.0\n", + "path_add_individual_3_5_4 = 0.0\n", + "path_add_individual_3_5_5 = 0.0\n", + "path_add_individual_3_5_6 = 0.0\n", + "path_add_individual_3_5_7 = 0.0\n", + "path_add_individual_3_5_8 = 0.0\n", + "path_add_individual_3_5_9 = 0.0\n", + "path_add_total_0 = 0.0\n", + "path_add_total_1 = 0.0\n", + "path_add_total_2 = 0.0\n", + "path_add_total_3 = 1.0\n", + "path_add_total_4 = 0.0\n", + "path_add_total_5 = 0.0\n", + "pos_0_0 = 0.0\n", + "pos_0_1 = 0.0\n", + "pos_0_10 = 0.0\n", + "pos_0_11 = 0.0\n", + "pos_0_12 = 0.0\n", + "pos_0_13 = 0.0\n", + "pos_0_14 = 0.0\n", + "pos_0_15 = 0.0\n", + "pos_0_2 = 0.0\n", + "pos_0_3 = 0.0\n", + "pos_0_4 = 0.0\n", + "pos_0_5 = 0.0\n", + "pos_0_6 = 1.0\n", + "pos_0_7 = 0.0\n", + "pos_0_8 = 0.0\n", + "pos_0_9 = 0.0\n", + "pos_1_0 = 0.0\n", + "pos_1_1 = 0.0\n", + "pos_1_10 = 0.0\n", + "pos_1_11 = 0.0\n", + "pos_1_12 = 0.0\n", + "pos_1_13 = 0.0\n", + "pos_1_14 = 0.0\n", + "pos_1_15 = 0.0\n", + "pos_1_2 = 0.0\n", + "pos_1_3 = 2.0\n", + "pos_1_4 = 0.0\n", + "pos_1_5 = 0.0\n", + "pos_1_6 = 0.0\n", + "pos_1_7 = 1.0\n", + "pos_1_8 = 0.0\n", + "pos_1_9 = 0.0\n", + "pos_2_0 = 3.0\n", + "pos_2_1 = 2.0\n", + "pos_2_10 = 0.0\n", + "pos_2_11 = 0.0\n", + "pos_2_12 = 0.0\n", + "pos_2_13 = 0.0\n", + "pos_2_14 = 0.0\n", + "pos_2_15 = 0.0\n", + "pos_2_2 = 1.0\n", + "pos_2_3 = 0.0\n", + "pos_2_4 = 0.0\n", + "pos_2_5 = 0.0\n", + "pos_2_6 = 0.0\n", + "pos_2_7 = 0.0\n", + "pos_2_8 = 0.0\n", + "pos_2_9 = 0.0\n", + "pos_3_0 = 0.0\n", + "pos_3_1 = 0.0\n", + "pos_3_10 = 0.0\n", + "pos_3_11 = 0.0\n", + "pos_3_12 = 0.0\n", + "pos_3_13 = 0.0\n", + "pos_3_14 = 0.0\n", + "pos_3_15 = 0.0\n", + "pos_3_2 = 1.0\n", + "pos_3_3 = 2.0\n", + "pos_3_4 = 0.0\n", + "pos_3_5 = 0.0\n", + "pos_3_6 = 0.0\n", + "pos_3_7 = 0.0\n", + "pos_3_8 = 0.0\n", + "pos_3_9 = 0.0\n", + "pos_4_0 = 0.0\n", + "pos_4_1 = 0.0\n", + "pos_4_10 = 0.0\n", + "pos_4_11 = 0.0\n", + "pos_4_12 = 0.0\n", + "pos_4_13 = 0.0\n", + "pos_4_14 = 0.0\n", + "pos_4_15 = 0.0\n", + "pos_4_2 = 0.0\n", + "pos_4_3 = 0.0\n", + "pos_4_4 = 1.0\n", + "pos_4_5 = 0.0\n", + "pos_4_6 = 0.0\n", + "pos_4_7 = 0.0\n", + "pos_4_8 = 0.0\n", + "pos_4_9 = 0.0\n", + "pos_5_0 = 1.0\n", + "pos_5_1 = 0.0\n", + "pos_5_10 = 0.0\n", + "pos_5_11 = 0.0\n", + "pos_5_12 = 0.0\n", + "pos_5_13 = 0.0\n", + "pos_5_14 = 0.0\n", + "pos_5_15 = 0.0\n", + "pos_5_2 = 0.0\n", + "pos_5_3 = 0.0\n", + "pos_5_4 = 0.0\n", + "pos_5_5 = 0.0\n", + "pos_5_6 = 0.0\n", + "pos_5_7 = 0.0\n", + "pos_5_8 = 0.0\n", + "pos_5_9 = 0.0\n", + "pos_dst_0 = 1.0\n", + "pos_dst_1 = 2.0\n", + "pos_dst_2 = 3.0\n", + "pos_dst_3 = 2.0\n", + "pos_dst_4 = 1.0\n", + "pos_dst_5 = 1.0\n", + "pos_src_0 = 0.0\n", + "pos_src_1 = 0.0\n", + "pos_src_2 = 0.0\n", + "pos_src_3 = 0.0\n", + "pos_src_4 = 0.0\n", + "pos_src_5 = 0.0\n", + "src_0_0 = 0.0\n", + "src_0_1 = 0.0\n", + "src_0_10 = 1.0\n", + "src_0_11 = 0.0\n", + "src_0_12 = 0.0\n", + "src_0_13 = 0.0\n", + "src_0_14 = 0.0\n", + "src_0_15 = 0.0\n", + "src_0_2 = 0.0\n", + "src_0_3 = 0.0\n", + "src_0_4 = 0.0\n", + "src_0_5 = 0.0\n", + "src_0_6 = 0.0\n", + "src_0_7 = 0.0\n", + "src_0_8 = 0.0\n", + "src_0_9 = 0.0\n", + "src_1_0 = 0.0\n", + "src_1_1 = 0.0\n", + "src_1_10 = 0.0\n", + "src_1_11 = 0.0\n", + "src_1_12 = 0.0\n", + "src_1_13 = 0.0\n", + "src_1_14 = 0.0\n", + "src_1_15 = 0.0\n", + "src_1_2 = 0.0\n", + "src_1_3 = 0.0\n", + "src_1_4 = 0.0\n", + "src_1_5 = 0.0\n", + "src_1_6 = 1.0\n", + "src_1_7 = 0.0\n", + "src_1_8 = 0.0\n", + "src_1_9 = 0.0\n", + "src_2_0 = 0.0\n", + "src_2_1 = 0.0\n", + "src_2_10 = 0.0\n", + "src_2_11 = 0.0\n", + "src_2_12 = 0.0\n", + "src_2_13 = 0.0\n", + "src_2_14 = 0.0\n", + "src_2_15 = 0.0\n", + "src_2_2 = 0.0\n", + "src_2_3 = 1.0\n", + "src_2_4 = 0.0\n", + "src_2_5 = 0.0\n", + "src_2_6 = 0.0\n", + "src_2_7 = 0.0\n", + "src_2_8 = 0.0\n", + "src_2_9 = 0.0\n", + "src_3_0 = 0.0\n", + "src_3_1 = 0.0\n", + "src_3_10 = 0.0\n", + "src_3_11 = 0.0\n", + "src_3_12 = 0.0\n", + "src_3_13 = 0.0\n", + "src_3_14 = 0.0\n", + "src_3_15 = 0.0\n", + "src_3_2 = 0.0\n", + "src_3_3 = 0.0\n", + "src_3_4 = 0.0\n", + "src_3_5 = 0.0\n", + "src_3_6 = 1.0\n", + "src_3_7 = 0.0\n", + "src_3_8 = 0.0\n", + "src_3_9 = 0.0\n", + "src_4_0 = 1.0\n", + "src_4_1 = 0.0\n", + "src_4_10 = 0.0\n", + "src_4_11 = 0.0\n", + "src_4_12 = 0.0\n", + "src_4_13 = 0.0\n", + "src_4_14 = 0.0\n", + "src_4_15 = 0.0\n", + "src_4_2 = 0.0\n", + "src_4_3 = 0.0\n", + "src_4_4 = 0.0\n", + "src_4_5 = 0.0\n", + "src_4_6 = 0.0\n", + "src_4_7 = 0.0\n", + "src_4_8 = 0.0\n", + "src_4_9 = 0.0\n", + "src_5_0 = 0.0\n", + "src_5_1 = 0.0\n", + "src_5_10 = 0.0\n", + "src_5_11 = 0.0\n", + "src_5_12 = 0.0\n", + "src_5_13 = 0.0\n", + "src_5_14 = 0.0\n", + "src_5_15 = 0.0\n", + "src_5_2 = 0.0\n", + "src_5_3 = 0.0\n", + "src_5_4 = 1.0\n", + "src_5_5 = 0.0\n", + "src_5_6 = 0.0\n", + "src_5_7 = 0.0\n", + "src_5_8 = 0.0\n", + "src_5_9 = 0.0\n", + "src_dst_node0 = 1.0\n", + "src_dst_node1 = 0.0\n", + "src_dst_node10 = 1.0\n", + "src_dst_node11 = 0.0\n", + "src_dst_node12 = 0.0\n", + "src_dst_node13 = 0.0\n", + "src_dst_node14 = 0.0\n", + "src_dst_node15 = 0.0\n", + "src_dst_node2 = 0.0\n", + "src_dst_node3 = 1.0\n", + "src_dst_node4 = 1.0\n", + "src_dst_node5 = 0.0\n", + "src_dst_node6 = 1.0\n", + "src_dst_node7 = 0.0\n", + "src_dst_node8 = 0.0\n", + "src_dst_node9 = 0.0\n", + "[(4, 0, 4), (2, 1, 0), (2, 2, 1), (3, 2, 3), (2, 3, 2), (5, 4, 0), (3, 6, 2), (1, 6, 7), (1, 7, 3), (0, 10, 6)]\n", + "[[(0, 0), (0, -0.5)], [(0, -0.5), (0.2, -0.5)], [(0.2, -0.5), (0.2, 1)]]\n", + "Edge: (0, 4), Start: (0, 0), End: (0, -0.5)\n", + "Edge: (0, 4), Start: (0, -0.5), End: (0.2, -0.5)\n", + "Edge: (0, 4), Start: (0.2, -0.5), End: (0.2, 1)\n", + "[[(0, 0), (-0.5, 0)], [(-0.5, 0), (-0.5, 0.2)], [(-0.5, 0.2), (1, 0.2)]]\n", + "Edge: (0, 1), Start: (0, 0), End: (-0.5, 0)\n", + "Edge: (0, 1), Start: (-0.5, 0), End: (-0.5, 0.2)\n", + "Edge: (0, 1), Start: (-0.5, 0.2), End: (1, 0.2)\n", + "[[(1, 0.2), (2.5, 0.2)], [(2.5, 0.2), (2.5, 0)], [(2.5, 0), (2, 0)]]\n", + "Edge: (1, 2), Start: (1, 0.2), End: (2.5, 0.2)\n", + "Edge: (1, 2), Start: (2.5, 0.2), End: (2.5, 0)\n", + "Edge: (1, 2), Start: (2.5, 0), End: (2, 0)\n", + "[[(2, 0), (2, -0.5)], [(2, -0.5), (2.2, -0.5)], [(2.2, -0.5), (2.2, 1)]]\n", + "Edge: (2, 6), Start: (2, 0), End: (2, -0.5)\n", + "Edge: (2, 6), Start: (2, -0.5), End: (2.2, -0.5)\n", + "Edge: (2, 6), Start: (2.2, -0.5), End: (2.2, 1)\n", + "[[(2, 0), (3.5, 0)], [(3.5, 0), (3.5, 0.2)], [(3.5, 0.2), (3, 0.2)]]\n", + "Edge: (2, 3), Start: (2, 0), End: (3.5, 0)\n", + "Edge: (2, 3), Start: (3.5, 0), End: (3.5, 0.2)\n", + "Edge: (2, 3), Start: (3.5, 0.2), End: (3, 0.2)\n", + "[[(3, 0.2), (3, -0.30000000000000004)], [(3, -0.30000000000000004), (3.2, -0.30000000000000004)], [(3.2, -0.30000000000000004), (3.2, 1.2)]]\n", + "Edge: (3, 7), Start: (3, 0.2), End: (3, -0.30000000000000004)\n", + "Edge: (3, 7), Start: (3, -0.30000000000000004), End: (3.2, -0.30000000000000004)\n", + "Edge: (3, 7), Start: (3.2, -0.30000000000000004), End: (3.2, 1.2)\n", + "[[(2.2, 1), (2.2, 2.5)], [(2.2, 2.5), (2, 2.5)], [(2, 2.5), (2, 2)]]\n", + "Edge: (6, 10), Start: (2.2, 1), End: (2.2, 2.5)\n", + "Edge: (6, 10), Start: (2.2, 2.5), End: (2, 2.5)\n", + "Edge: (6, 10), Start: (2, 2.5), End: (2, 2)\n", + "[[(2.2, 1), (3.7, 1)], [(3.7, 1), (3.7, 1.2)], [(3.7, 1.2), (3.2, 1.2)]]\n", + "Edge: (6, 7), Start: (2.2, 1), End: (3.7, 1)\n", + "Edge: (6, 7), Start: (3.7, 1), End: (3.7, 1.2)\n", + "Edge: (6, 7), Start: (3.7, 1.2), End: (3.2, 1.2)\n" ] }, { "data": { - "image/png": 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" ] @@ -2960,16 +1967,91 @@ "output_type": "display_data" }, { - "ename": "ValueError", - "evalue": "max() arg is an empty sequence", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[28], line 384\u001b[0m\n\u001b[1;32m 370\u001b[0m highlight_edges_with_colors \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 371\u001b[0m (\u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m9\u001b[39m): \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mred\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 372\u001b[0m (\u001b[38;5;241m11\u001b[39m, \u001b[38;5;241m3\u001b[39m): \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mblue\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 373\u001b[0m (\u001b[38;5;241m5\u001b[39m, \u001b[38;5;241m7\u001b[39m): \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgreen\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 374\u001b[0m }\n\u001b[1;32m 376\u001b[0m draw_folded_torus_noc(\n\u001b[1;32m 377\u001b[0m mesh_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m4\u001b[39m,\n\u001b[1;32m 378\u001b[0m G_NoC\u001b[38;5;241m=\u001b[39mG_NoC,\n\u001b[1;32m 379\u001b[0m highlight_edges_with_colors\u001b[38;5;241m=\u001b[39mconvert_edge_list_to_highlight_dict(edge_list),\n\u001b[1;32m 380\u001b[0m title\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFolded Torus NoC (4x4)\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 381\u001b[0m )\n\u001b[0;32m--> 384\u001b[0m \u001b[43mplot_nx4x4_grid_with_highlighted_edges\u001b[49m\u001b[43m(\u001b[49m\u001b[43medge_list\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/Documents/projects/wk_LinProg/LinProg_Scripts/LinProg_lib.py:415\u001b[0m, in \u001b[0;36mplot_nx4x4_grid_with_highlighted_edges\u001b[0;34m(highlighted_edges)\u001b[0m\n\u001b[1;32m 412\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mplot_nx4x4_grid_with_highlighted_edges\u001b[39m(highlighted_edges):\n\u001b[1;32m 413\u001b[0m \n\u001b[1;32m 414\u001b[0m \u001b[38;5;66;03m# Determine the number of layers based on the input\u001b[39;00m\n\u001b[0;32m--> 415\u001b[0m num_layers \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43medge\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43medge\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mhighlighted_edges\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 417\u001b[0m \u001b[38;5;66;03m# Create a 3D grid graph\u001b[39;00m\n\u001b[1;32m 418\u001b[0m G \u001b[38;5;241m=\u001b[39m nx\u001b[38;5;241m.\u001b[39mDiGraph()\n", - "\u001b[0;31mValueError\u001b[0m: max() arg is an empty sequence" + "data": { + "image/png": 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", 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F1ymu5TySAql+9erZ8HVtOPBs2VKoYGHDt+6IR2VFhUqK96hzeqDO9NXLvtR3q1bqxDPPjbkcmURDmpvLCVOm6qhTx9WZVrhjh56YcYtOPvcCHXnKOGX17RdzWXKJWJqbyfKyUlWGK9Spc+c60+c8dr+i0ahGnHhyg8t6VNUf3Ma1ZS3g8ypa2PDrb858WqHdRdpZsFWStHj+e9q5NV+SNH7yVCV5kvTHqy5WcVGhzrnyOi1Z+EGd5XtmH6TBI0bFXHd07/hAbY1lUmo8l4pGdc3Jo3Tc+LOVPXCwfJ38+m7VCs1/5UX5O6fpvOtujLleMomGNPezsv/Qw9R/6GF1lqk+HZo9cHDNvSljIZeIpbmZLC4s1C9+NFYnTJioPrkDJElf/Wehvlj4gUaceLKOPGVcg+t2ayY90agL7w4naVdpWPO/297g69eOOUrbNm+M+dpj738qSbru1KMbXP6HEy/QT//0QIOvn3xQd9d99Retq7FMSo3nMiOrh/751zv09acfa9umPJWXlSojs4cOO+5EnXftjfWeDVobmUQszf2sjJW5go15uu7Uoxt8Nmht5BL7am4mU9PS9OQdv9GqpV9oV8EWRSoj6nlQjk4680c6e+q16uDdf97cmEnXlrVINKo31mxtlRvjNsab5NGEgT2UFOPZoThwkUlYRC5hDZl0zrWPm0ryeJQb8Md5H+2W45HUP+B33Y5G6yOTsIhcwhoy6Zxry5pU9Utv614elZQb8LfxqHALMgmLyCWsIZPOuLqs+b0dlJMe3zc4W0pOeif5va79XgZaGZmEReQS1pBJZ1xd1iRpWGaafMlt8zZ8yUkalpnWJmPBvcgkLCKXsIZMxs/1Zc2bnKSRvQJtMtbIXgF52yhYcC8yCYvIJawhk/Fz75bX0iM1RcOzWrcxD89KU4/UlFYdA4mDTMIicglryGR8EqKsSdKAjNRW2+HDs9I0ICO1VdaNxEUmYRG5hDVksnGuvc9aQ7YWl2lJflCllZFmr8u39xCt2xs52heZhEXkEtaQyYYlXFmTpHBlRMu3FWlDYYnj54dWz5+T3knDMtNcfY4bdpBJWEQuYQ2ZjC0hy1q1ULhC64MhrQuGau6UvO/Or/2zN8mj/gG/cgN+1369F7aRSVhELmENmawroctatUg0qsKyCgVLw1X/ikP6Pi9P/bKzFUj1K+DzKuDzKj2lgyvvbAz3IZOwiFzCGjJZJXGOEe5HksejDJ9XuQG/RvRM18F+acPCt3SwXxrRM125Ab8yfN6E3tGwhUzCInIJa8hklQOirAEAALgVZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZ5oNBpt741obZFoVIVlFQqWhqv+FYf0fV6e+mVnK5DqV8DnVcDnVXpKByV5PO29uTgAkElYRC5hDZmsktBlLRSu0LpgSOuDIYUjVW/TI6n2G679szfJo9yAX/0Dfvm9Hdp4a3EgIJOwiFzCGjJZV0KWtXBlRMu3FWlDYUm9nduY6vlz0jtpWGaavMmcKUbzkUlYRC5hDZmMLeHK2tbiMi3OD6qsMtLsdfmSkzSyV0A9UlNaYMtwoCKTsIhcwhoy2bCEKmtrdxVraUFRi693eFaaBmSktvh6kfjIJCwil7CGTO5fwhwjbK0dLUlLC4q0dldxq6wbiYtMwiJyCWvIZOMSoqxtLS5rtR1dbWlBkbYWl7XqGEgcZBIWkUtYQybj4/qyFq6MaHF+sE3GWpIfVLgFzqUjsZFJWEQuYQ2ZjJ/ry9rybUUqb6MdULr3WyrA/pBJWEQuYQ2ZjJ+rb0ZSHK7QhsKSuOffvGGdXnjoHq1Y8rn2FO5S9159dOKZ5+qcqdcqpZM/rnVsKCzRwd06J+R9XNB8TjO59utleu6BP+m/Xy5WNBrV4MNHasrNv1HukEPjXgeZRGMaymVJcbFefepRrV72pdYs/0p7CoO6/q77NeZHF9abd+Pa1frfu2do5RefqYO3o44YfYouv/X3Su/aLeaY5BL709xMrl72pea/Mlurl36h71atUGVFheau3LzfMd2cSVcfWVsfDCne+xVvz9+kWy+YoFVffaHxl1yuK351uwYfPlIvPvxX3f/zn8Q9pmfvuEAsTjK57ptl+s0lE7U173tdcP3PdP71Nyn/u/X63ZRJ2rRuTdxjkkk0pqFc7t61U3MevV8b163WQYMPaXD5HVs267eTz9WW7zfoxzfeqrOvuFZfLPxAt0+9UOHy8pjLkEvsT3Mz+cXCD/TBS8/J4/GoR99+cY3p5ky6r17uFYlGtT4YivuGeQtfnaviokLdMWue+v1gsCRp7IWTFY1EteDVOdpTGFTn9ECj64lKWhcMaUj3Lgn9aAs45zSTzz/0F3X0+XT3C6+pS0ZXSdLosybphtNP0Kz7/6RbHn4yrvWQSezP/nKZkZWlJxd9pYzMLK1ZvlS/PH98zHXMfeJhlZaEdM/ct5XZu68kaeBhh+v2qRdp/iuzNfbCyfWWIZdoSEtkctzFl2ni1dcrxddJf7/9Nm3esK7Rcd2cSdceWSssq6h5BEU8QsW7JUmB7t3rTA9kZSkpKUkdvB3jXlc4UvWsMqA2p5lcsfhTDTv2xJqiJkkZWT009MhjtWTB+yopjv/r5mQSDdlfLr0dU5SRmdXoOv7v3Tc08oen1RQ1SRp+3EnqndNfH7/9WoPLkUvE0hKZDHTPVIqvk+Ox3ZpJ15a1YGnY0fyHHnWcJOnRX/9c61d8re35m/SfN1/Vu8//Q2dMuVI+f3zXrDV1fCQ+p5kIl5crJcVXb3rHTp1UES5X3uqVrTo+DgzNzcWOrfkq3LFdAw89rN5rAw8bofXfftOq4yPxtHcm2nv8pnDtadBgadjRc8NGnHiyLp5+i+Y+8ZA+//DdmumTrp2uH9/4S0dje+TOnY3W5TSTvXMHaNXSJaqsrFRycrKkqgK3etkXkqQdW7fEPTaZREOc5nJfuwoKJEmBzB71XsvIzNKewl0Kl5fJ27H+Y33IJWJpbiabw62ZdG1ZK62sdLyjM/tk65BRx+iYsRPUJZChJQvf18tPPKRA90ydMXlq3OuJSgoWh5Sf784LFdE6giFnHz6n//gy/e33t+rRX/9cE6/6iaKRiF56/AEFt1X9cSwvK417XWQSDXGay31V59Dbsf6lIt6UqoJWXloas6yRS8TS3Ew2R1RV/cFtXFvWKh1cGyRJ/35jnh7/3c165O1/q1vP3pKkY8aeoWgkopn33qkTJ0ysc+1QY77Py9NHC99ytA1IbDmjx6tLr+y45x930aXanr9Zrz39mBbMmy1JGnDocJ1z5U809/EHHZ+aJ5OIxWku99Vx76n6WN/6DJdV3RW+o6/+6fxq5BL7am4mm8tpf7DAtWUtOcnZNznefv5Z5Q45tKaoVTtyzDjNf2W21q34WsOPOynu9fXLztbYadMcbQMS28qQtMvhdauX3HSrzpl6rfLW/Ff+zmk6aPAQzbrvbklS75wBjtZFJhFLU3JZW0ZW1cXewW1b6722a1uBOqdnxDyqVo1cYl/NzWRzOe0PFri2rPmSkx2d8y7cvk2pMW7NUVFRde464uCwqEdSINWvXj3T414GiW/LlkIFC+O/dUe1zukBDRl5dM3Pyz5ZpG49e6lP/4Fxr4NMoiFNzWW1bj16Ka1rN635elm919Ys+1K5Q4Y2uCy5RCzNzWRzeFTVH9zGtd8GDfi8jnZ0r5z+Wv/t19q8fm2d6f9+Y56SkpJ00KAhca8rund8oDanmYzlP2++qjXLv9KZl16tpKT4/+9JJtGQlsjlMWMnaMmC97Q9f1PNtGWfLNLmDet07OlnNrgcuUQsLZHJpnJrJl17ZM3pL/ucK3+iLxfN128mn6vxl1yhLoEMLV7wvr786EOdev6P1bVHz1YdH4nPaSa++fz/NOfR+3T48aPVOZCh1Uu/0Icvv6gRJ56sCZde1erj48DQWC7enPm0QruLtLOg6jTn4vnvaefWfEnS+MlTldolTZOu+ak+eft1zbjsfE2YcqVKQyG9+vRj6jdoSMxHUzkZHweelshkwaaN+ui1lyRJa7+pOur70mMPSJK69+6rH55zXpPHt8gTjUbdd6Wdqu6A/MaarY5uQrp62Zd68ZF7tX7F19oT3KWsPtn64cQLNPGqnyi5Q/y91Zvk0YSBPVx3B2S0LqeZ3PL9Bv3tD7/S+m+Xq6S4WFl9s/XDiefrrMuvifnNu/0hk2hIY7m8dsxR2rZ5Y8zXHnv/U2X1rboQ/PvV/9Uzf/p9zbNBR44+RZf9coYC3TMbHJtcIpaWyOTXn36sGZfFLmRDjzxWt/9zbszX3JpJ15Y1Sfp6W5FW7yxu08OpHkmDuqZqaGZaG44KtyCTsIhcwhoy6Yxrr1mTpP4Bf5uf945Kyg04u6UCDhxkEhaRS1hDJp1xdVnzezsoJ935s8GaIye9k/xe117qh1ZGJmERuYQ1ZNIZV5c1SRqWmSZfctu8DV9ykoa58PAp2haZhEXkEtaQyfi5vqx5k5M0slegTcYa2SsgbxsFC+5FJmERuYQ1ZDJ+7t3yWnqkpmh4Vus25uFZaeqR2vBduoHayCQsIpewhkzGJyHKmiQNyEhttR0+PCtNAzJSW2XdSFxkEhaRS1hDJhvn6lt3xLK1uExL8oMqrYw0e12+vYdo3d7I0b7IJCwil7CGTDYs4cqaJIUrI1q+rUgbCkscPT9UUs38OemdNCwzzdXnuGEHmYRF5BLWkMnYErKsVQuFK7Q+GNK6YKjmTsn77vzaP3uTPOof8Cs34Hft13thG5mERTFzWVGhaHKy5KlKpEcecok2w2dlXQld1qpFolEVllUoWBqu+lcc0vd5eeqXna1Aql8Bn1cBn1fpKR1c9wgKuBOZhEV1cjlnrkrLK1SZkqLwSScpkNaFXKLN8VlZJfHqZwxJHo8yfF5l7H14a35+SB8tfEtjp01Tr57p7bx1OBCRSVhUJ5fPPS0tWCBJyl+7llyiXfBZWSVxTugCAAAkIMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADOvQ3hsAADAiEpHeeENav17auLFmsv+ZZ6T+/aVzz5XS09tv+4ADFGUNAFDlxRelH/+43uT0P/6x6n988IH0z3+28UYB4DQoAKBKJLL/16PRttkOAHVQ1gAAVSZNkvr0afj16dPbblsA1KCsAQCq+HzSr34V+7UJE6Qjj2zb7QEgibIGAKjtyitjH12bMaPttwWAJMoaAKC2GEfXSk8+maNqQDvyRKOJf8VoJBpVYVmFgqXhqn/FIX2fl6d+2dkKpPoV8HkV8HmVntJBSR5Pe28uDgBkEhbV5HJ3SMEnnlRp126q7NhRlYcfrrS+fcgl2hyflVUSuqyFwhVaFwxpfTCkcKTqbXok1X7DtX/2JnmUG/Crf8Avv5e7mqDlkUlYFDOXkYiiHo+09w8guURb4rOyroQsa+HKiJZvK9KGwpJ6O7cx1fPnpHfSsMw0eZM5U4zmI5OwiFzCGjIZW8KVta3FZVqcH1RZZSP3C4qDLzlJI3sF1CM1pQW2DAcqMgmLyCWsIZMNS6iytnZXsZYWFLX4eodnpWlARmqLrxeJj0zCInIJa8jk/iXMMcLW2tGStLSgSGt3FbfKupG4yCQsIpewhkw2LiHK2tbislbb0dWWFhRpa3FZq46BxEEmYRG5hDVkMj6uL2vhyogW5wfbZKwl+UGFW+BcOhIbmYRF5BLWkMn4uf77rcu3Fam8iTvgpccf1PMP/FnZPxisB16f3+j8pXu/pXJEz0CTxsOBId5Mfv3px5px2XkxX7v7hdc16PCRja6DTCJeTj8r132zTC8+cq9WfvG5ystK1SP7IJ12/iWacOlVjS5LLhGPeDP58K03asG82Q2+/reFS9StR6/9rsPtmXR1WSsOV2hDYUmTlt2xZbNefuIh+fx+R8ttKCzRwd06J+R9XNB8TcnkGVOu1MBhh9eZ1vOgnLiXJ5NojNNcfvXvBbr7usuVe8ihOu+6G+Xzp2pL3gbt2Jof9zrIJfbHSSbHXjhZhx13Yp1p0WhUf/v9L5XZJ7vRolbNzZl03xbXsj4YcnwflmrP3nO7Bg0fqUhlpYqCO+NezrN33KGZaU0YFYmuKZk8ZOTROvb0M5s8JplEY5zkMrRntx6+dbpG/vAU/eLBvyspqWlXy5BL7I+TTA4eMUqDR4yqM23Fkk9VVlKik878UdxjujmTrr1mLRKNan0w1KSi9s3n/6dP3nlDV/zqD46XjUpaFwwpkjh3PEELaU4mS/bsUWVFRZPGJZPYH6e5XPSvVxTcvk0/vvFWJSUlqTQUUiTi/FITcomGNOezstqif82Tx+PRiWeeG/cybs6ka8taYVlFzSMonKisrNRTd/xGp573Yx00eEiTxg5Hqp5VBtTW1Ew+cttNmjxqkC4anqvfXXqe1ixf6ngdZBINcZrLZR8vkr9zF+3Ymq+fnn6CLjlioKaMGqQnfn+rystKHY1NLhFLUz8rq1WEw/r4rdc0eMQoZfXNdrSsWzPp2tOgwdJwk5Z794V/aNvmjZrxvy82e/wMn7dZ60BicZrJDl6vjhk7QUeMHqO0jK7KW7NKrz39uH47+Vzd+fyr6n/IMMfjk0nsy2ku879br8rKCv35+it0yqSLdcnPbtM3n32sN2c+reKiQv3svsccj08uUVtT/35X++rfC7Q7uEsnnhX/KdB9x3dbJl1d1pxeG7R710698NBfdf51Nyq9a7cmj+1R88OGxOM0kwcfcaQOPuLImp+PHDNOx447Uz875xTNuu9u/fbJ5+Iem0yiIU5zWRoqVllJicZedKmu/M0dkqRjxp6hinBY7774T130/25W75z+ca2LXCKWpvz9rm3Rv15RB69Xx59+luNl3ZpJ15a10spKxzv6uQfvUedAQOMnT23W2FFJweKQ8vNDzVoPEksw1PQPn2q9DsrVkWPG6dP33lJlZaWSk5PjWo5MoiFOc9nR55MknTBhYp3pJ5x5rt598Z9a9dWSuMsauUQszfmsLCku1ucfvqPhx49Wl4yujpePqqo/uI1ry1qlw/Pdmzes0/uzZ+qKX/1Buwq21kwvLy9TZTisgo156tS5s7oEMuJa3/d5efpo4VuOtgGJLWf0eHXp5ez6iVi69+qtinC5ykpC8nfuEvdyZBKxOM1l18weylv9XwW6da8zPb1b1dmIPUWFjsYnl9hXcz4rP/vg7apvgTbxFKjkvD9Y4NqylpzkcTT/zq1bFIlE9NSdv9VTd/623uvXnXq0Jlx6labedntc6+uXna2x06Y52gYktpUhaVcLXLe6Ne97dUzxyed39vBhMolYnOay/9DDtPTjj7SzYIv69B9YM736P3LTHR7NIJfYV3M+Kxe9/rJ8/lQdOWZsk8d32h8scG1Z8yUnOzrn3W/QYN3yyFP1pj//4D0qKd6jqbfdrp7ZOXGtyyMpkOpXr57p8W4uDgBbthQqWBj/19ELd+6od+3khpXfaPH8dzXixJMd3d+KTKIhTnN53Piz9MrfH9EHLz2vYcecUDP9/TnPKblDBw096ri4xyaXiMVpJqsV7tyhZZ8s0gkTJiqlk7Mb2lfzqKo/uI1ry1rA51XUwdH4tIxuOvrU8fWmv/Hsk5IU87WGRPeOD9TmNJP33XStOvp8GjxilNK7dtfGtav03uyZ6ujrpMk//7WjsckkGuI0l/0PGaYxky7Sh3NfUGVlhYYeeay+/uwTffL26/rRtJ+qa4+eca+LXCIWp5ms9p83X1VlRYVOdHAj3H25NZOuLmsH8viwx2kmjjplnBb96xW9/r9/U0nx7qr/oDjtDF1w/c/U66DcVh8fB4am5OKa3/9Zmb366MOXX9Rn77+t7r376opf/UFnXnZ1m4yPxNbUTCx6/RWld+te79FTbTV+e/JEoy68la+q7oD8xpqtzbqxXlN5kzyaMLCHkjzuO++N1kMmYRG5hDVk0jnXPsEgyeNRbsCvtv51eyT1D/hdt6PR+sgkLCKXsIZMOufasiZV/dLbupdHJeUGmnZhIxIfmYRF5BLWkElnXF3W/N4Oyknv1KZj5qR3kt/r2kv90MrIJCwil7CGTDrj6rImScMy0+RLbpu34UtO0rDMtDYZC+5FJmERuYQ1ZDJ+ri9r3uQkjewVaJOxRvYKyNtGwYJ7kUlYRC5hDZmMn3u3vJYeqSkantW6jXl4Vpp6pKa06hhIHGQSFpFLWEMm45MQZU2SBmSkttoOH56VpgEZzh79A5BJWEQuYQ2ZbJxr77PWkK3FZVqSH1RpZaTZ6/LtPUTr9kaO9kUmYRG5hDVksmEJV9YkKVwZ0fJtRdpQWOLo+aGSaubPSe+kYZlprj7HDTvIJCwil7CGTMaWkGWtWihcofXBkNYFQzV3St5359f+2ZvkUf+AX7kBv2u/3gvbyCQsIpewhkzWldBlrVokGlVhWYWCpeGqf8UhfZ+Xp37Z2Qqk+hXweRXweZWe0sGVdzaG+5BJWEQuYQ2ZrJI4xwj3I8njUYbPq9yAXyN6putgv7Rh4Vs62C+N6Jmu3IBfGT5vQu9o2EImYRG5hDVkssoBUdYAAADcirIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDBPNBqNtvdGtLZINKrCsgoFS8NV/4pD+j4vT/2ysxVI9Svg8yrg8yo9pYOSPJ723lwcAMgkLCKXsIZMVknoshYKV2hdMKT1wZDCkaq36ZFU+w3X/tmb5FFuwK/+Ab/83g5tvLU4EJBJWEQuYQ2ZrCshy1q4MqLl24q0obCk3s5tTPX8OemdNCwzTd5kzhSj+cgkLCKXsIZMxpZwZW1rcZkW5wdVVhlp9rp8yUka2SugHqkpLbBlOFCRSVhELmENmWxYQpW1tbuKtbSgqMXXOzwrTQMyUlt8vUh8ZBIWkUtYQyb3L2GOEbbWjpakpQVFWruruFXWjcRFJmERuYQ1ZLJxCVHWthaXtdqOrra0oEhbi8tadQwkDjIJi8glrCGT8XF9WQtXRrQ4P9gmYy3JDyrcAufSkdjIJCwil7CGTMbP9d9vXb6tSOVx7oBweZleeOgvWvjqXBUXFeqgwUN08fRbNPz40XEtX7r3WypH9Aw0Y4uR6JxksqS4WK8+9ahWL/tSa5Z/pT2FQV1/1/0a86ML41qeTCJe8eZyzfKvNP+V2fr6s4+1bVOeugQy9IPhI/Xj6beod+6AuMYil4hHvJn8fvV/NfuRe7X2m2UKbi9Qiq+T+g4cpHOmXqcjx4yNayy3Z9LVR9aKwxXaUFgS91d7H771Rr3+zN904lnn6orbbldSUpLuvGaKViz5NO4xNxSWKBSuaNoGI+E5zeTuXTs159H7tXHdah00+JAmjUkm0RgnuXzl7/+j/3vvTR12zAmaetvtOu2CyVqx+P9086Rx+n7VyrjHJJfYHyeZ3LZ5o0qK9+jkiedr6m1/1Hk/uUmS9KefXK53X5wZ95huzqSrvw369bYird5ZHNfOXr3sS916wQRdevNvdc6V10mSystKddNZY5TetZvueuH1uMb0SBrUNVVDM9OavuFIWE4yKVUd7d1TWKiMzCytWb5Uvzx/vKMjaxKZROOc5HLlF59rwKHD5e3YsWba5g3r9LOzT9Gx4yZo+l8eiWtMcon9cfpZua/KykrdMmmcysvK9PBbi+Jaxs2ZdO2RtUg0qvXBUNw7+pN3/qWk5GSdduHkmmkdU3w6ZdLF+u9XS7Q9f1Nc64lKWhcMKeLejotW4jSTkuTtmKKMzKxmjUsmsT9Oc3nwEUfWKWqS1Dunv7IHDtLGtavjHpdcoiFN+azcV3Jysrr17K3Q7vi/nODmTLq2rBWWVdQ8giIe61d8rd45/eXv3KXO9IGHHb739W/iXlc4UvWsMqA2p5lsSWQSDWmJXEajUQV3bFeXjK6OliOXiKWpmSwNhVS0a4e2fL9Brz/zN325aL6GHXOCo3W4NZOu/YJBsDTsaP5d2wqUkdmj3vTqabsKtjoeP8PndbQMEpvTTLbG+GQS+2qJXH70+svauTVfF/2/XzRpfHKJ2pqayWf//Ae9++I/JUlJSUk6+rQzdNVv72zS+G7LpKvLmpPnhpWXlqrDPof2JcmbUvUoivKy0rjH9qj9/zDDHqeZbElkEg1pbi43rlutJ2+/TYMPH6kfTrzA0bLkErE0NZMTLrtKx4yboF0FW/XxW68rEqlURdhZvtyaSdeWtdLKSkc7uqPPp4ry8nrTw2VVN8rrmOKLe11RScHikPLzQw62AIkuGGqfoiaRSTSsObncta1Ad11zqfxduugXD/5dycnJjpYnl4ilqZns2/8H6tv/B5KkH048X7dPvUh3X3eZ/jT7DXk8nrjWEVVVf3Ab15a1SofnuzMys7Rz65Z603dtqzr9mZFV/xTp/nyfl6ePFr7laBkktpzR49WlV3a7jU8mEUtTc1m8u0h3TrtExUVFumPWK+rao2eTxieX2FdLfVYeM+5MPTHjFm1ev1Z9+g+Mezmn/cEC15a15KT4WnS1nIOH6utPP1Zoz+46XzJYvfRLSVLukKGO1tcvO1tjp01ztAwS28qQtKsdr1slk4ilKbksLyvV3dddps0b1mnG0y8qe+CgJo9PLrGvlvqsrL58KbRnt6PlnPYHC1xb1nzJyY7OeR877ky99vTjeu/FmTX3WQuXl+nDV17UD4Yfoe69+sQ9tkdSINWvXj3THW83EteWLYUKFjbv6+hNRSbREKe5rKys1H03XatVXy3RL//nfzV4xKgmj00uEYvTTBbu2K70bt3rTKsIh7Vw3hx19PnUd0D8/zHhUVV/cBvXlrWAz6toYfzzDxp+hI49/SzNuv9uFe7crp79crVg3mxt25Snn9xxr6Oxo3vHB2pzmslqb858WqHdRdq59xvJi+e/p51b8yVJ4ydPVWqXxm/gSCbREKe5fPbPf9DnH76rUSefpj2FQS18bW6d10efPSnudZFLxOI0k4/PuEUle/bokFFHq2uPngpu36aPXn9Zm9at0WW/nKFOqalxr8utmXR1WXPq//35QT3/YB8tfG2uigurng36q8f+oaFHHtMm4yOxNTUTrz39uLZt3ljz86fvvalP33tTknTSWZPiKmvNGR+JzWkuNuy95+Ti+e9p8fz36r3upKw1ZXwkPqeZOH782fpg7vN654V/aHdwlzqldlb/ocM05Re/1pFjxrX6+Ba49nFTkWhUb6zZ2i43IfUmeTRhYA8lxfntExwYyCQsIpewhkw659onGCR5PMoN+NXWv26PpP4Bv+t2NFofmYRF5BLWkEnnXFvWpKpfelv38qik3IC/jUeFW5BJWEQuYQ2ZdMbVZc3v7aCc9E5tOmZOeif5va691A+tjEzCInIJa8ikM64ua5I0LDNNvuS2eRu+5CQNy4zvYm8cuMgkLCKXsIZMxs/1Zc2bnKSRvQJtMtbIXgF52yhYcC8yCYvIJawhk/Fz75bX0iM1RcOzWrcxD89KU4/UlFYdA4mDTMIicglryGR8EqKsSdKAjNRW2+HDs9I0ICP+m+4BEpmETeQS1pDJxrn2PmsN2VpcpiX5QZVWRpq9Lt/eQ7Rub+RoX2QSFpFLWEMmG5ZwZU2SwpURLd9WpA2FJY6eHyqpZv6c9E4alpnm6nPcsINMwiJyCWvIZGwJWdaqhcIVWh8MaV0wVHOn5H13fu2fvUke9Q/4lRvwu/brvbCNTMIicglryGRdCV3WqkWiURWWVShYGlawNKzSykpVRqJKTvLIl5ysgM+rgM+r9JQOrryzMdyHTMIicglryGSVA6KsAQAAuFXinNAFAABIQJQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMo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", 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cdGrC5cgkGtPSXBZNnqJDjhtfb1rJ1q16cOr1OvbUM3XwuPHK67NfwmXJJRJpaSarKisUjVSrc5cu9abPun+a4vG4Ro45ttFlParpD27j2rIW9PsUL2n885enP6rw9lJt27RRkjRvzhvatnG9JGnCpCnyerz6fxefo7LSEp1y0RWa/+5b9Zbvld9Xg0aOTrju+M7xgV01lUmp6VwqHtdlx47WERNOVv6AQfJ3DuibpYs15/mnFeiSpdOvuCbheskkGtPS78p+ww5Qv2EH1Fum9nRo/oBBdc+mTIRcIpGWZrKspES//NHxOqpoovYt7C9J+uKDd/XZu29p5JhjdfC48Y2u262Z9MTjLnw6nKTiiojmfLOl0c8vH3uINq9bm/Cz+9/8WJJ0xXGHNrr8MRPP1E9vv7vRz4/t28N1t/6ibTWVSanpXObk9dTjf75FX378oTZ/t0ZVlRXKye2pA44Yo9Mvv6bBu0F3RSaRSEu/KxNlbtPaNbriuEMbfTforsgldtfSTGZmZenhW27S0gWfqXjTBsWiMfXqW6Dvn/QjnTzlcnXy7Tlvbsyka8taLB7XS8s3tsmDcZvi83pUNKCnvAneHYq9F5mEReQS1pBJ51z7uimvx6PCYCDJ52i3Ho+kfsGA63Y02h6ZhEXkEtaQSedcW9akmr/09u7lcUmFwUA7jwq3IJOwiFzCGjLpjKvLWsDXSQXZyd3B2VoKsjsr4HPtfRloY2QSFpFLWEMmnXF1WZOk4blZ8qe1z6/hT/NqeG5Wu4wF9yKTsIhcwhoymTzXlzVfmlejegfbZaxRvYPytVOw4F5kEhaRS1hDJpPn3i3fRc/MDI3Ia9vGPCIvSz0zM9p0DKQOMgmLyCWsIZPJSYmyJkn9czLbbIePyMtS/5zMNlk3UheZhEXkEtaQyaa59jlrjdlYVqn560OqiMZavC7/zkO0bm/k6FhkEhaRS1hDJhuXcmVNkiLRmBZtLtXqknLH7w+tnb8gu7OG52a5+hw37CCTsIhcwhoymVhKlrVa4Ui1VoXCWhkK1z0pefedv+vPPq9H/YIBFQYDrr29F7aRSVhELmENmawvpctarVg8rpLKaoUqIjV/ysL6ds0a7Zefr2BmQEG/T0G/T9kZnVz5ZGO4D5mEReQS1pDJGqlzjHAPvB6Pcvw+FQYDGtkrW4MD0up3X9HggDSyV7YKgwHl+H0pvaNhC5mEReQS1pDJGntFWQMAAHAryhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwzzxeDze0RvR1mLxuEoqqxWqiNT8KQvr2zVrtF9+voKZAQX9PgX9PmVndJLX4+nozcVegEzCInIJa8hkjZQua+FItVaGwloVCisSq/k1PZJ2/YV3/dnn9agwGFC/YEABX6d23lrsDcgkLCKXsIZM1peSZS0SjWnR5lKtLilvsHObUjt/QXZnDc/Nki+NM8VoOTIJi8glrCGTiaVcWdtYVql560OqjMZavC5/mlejegfVMzOjFbYMeysyCYvIJawhk41LqbK2orhMCzaVtvp6R+RlqX9OZquvF6mPTMIicglryOSepcwxwrba0ZK0YFOpVhSXtcm6kbrIJCwil7CGTDYtJcraxrLKNtvRtRZsKtXGsso2HQOpg0zCInIJa8hkclxf1iLRmOatD7XLWPPXhxRphXPpSG1kEhaRS1hDJpPn+rK2aHOpqtppB1TsvEsF2BMyCYvIJawhk8lz9cNIyiLVWl1SnvT861av1FP33KHF8z/VjpJi9ei9r8acdKpOmXK5MjoHklrH6pJyDe7eJSWf44KWc5rJFV8u1BN3367/fj5P8Xhcgw4cpcnX3aTCIfsnvQ4yiaY0lsvysjK98Mh9Wrbwcy1f9IV2lIR05R+naeyPzmow79oVy/T326ZqyWefqJMvXQcdPU4X3PB7ZXfrnnBMcok9aWkmly38XHOen6llCz7TN0sXK1pdrWeXrNvjmG7OpKuPrK0KhZXs84q3rP9ON5xZpKVffKYJ516gC399swYdOEpP3/tnTfvFT5Ie07NzXCARJ5lc+dVC3XTuRG1c863OvPLnOuPKa7X+m1X63eTT9N3K5UmPSSbRlMZyub14m2bdN01rVy5T30FDG11+64Z1+u2kU7Xh29X68TU36OQLL9dn776lm6ecpUhVVcJlyCX2pKWZ/Ozdt/TWM0/I4/GoZ5/9khrTzZl0X73cKRaPa1UonPQD89594VmVlZbolhmztd/3BkmSjj9rkuKxuN55YZZ2lITUJTvY5HriklaGwhrSo2tKv9oCzjnN5JP3/I/S/X7d9tS/1DWnmyTp6B+epqtOOEozpt2u6+99OKn1kEnsyZ5ymZOXp4fnfqGc3DwtX7RAvzpjQsJ1PPvgvaooD+uOZ19V7j59JEkDDjhQN085W3Oen6njz5rUYBlyica0RibHn3O+Jl5ypTL8nfXQzTdq3eqVTY7r5ky69shaSWV13SsokhEu2y5JCvboUW96MC9PXq9XnXzpSa8rEqt5VxmwK6eZXDzvYw0/fExdUZOknLyeGnbw4Zr/zpsqL0v+dnMyicbsKZe+9Azl5OY1uY7/vP6SRh3zg7qiJkkjjvi+9inopw9f/Vejy5FLJNIamQz2yFWGv7Pjsd2aSdeWtVBFxNH8+x9yhCTpvt/8QqsWf6kt67/TBy+/oNef/KdOnHyR/IHkrllr7vhIfU4zEamqUkaGv8H09M6dVR2p0pplS9p0fOwdWpqLrRvXq2TrFg3Y/4AGnw04YKRWff1Vm46P1NPRmejo8ZvDtadBQxURR+8NGznmWJ1z9fV69sF79Onbr9dNP+3yq/Xja37laGyP3Lmz0bacZnKfwv5aumC+otGo0tLSJNUUuGULP5Mkbd24IemxySQa4zSXuyvetEmSFMzt2eCznNw87SgpVqSqUr70hq/1IZdIpKWZbAm3ZtK1Za0iGnW8o3P3zdfQ0YfpsOOL1DWYo/nvvqnnHrxHwR65OnHSlKTXE5cUKgtr/Xp3XqiIthEKO/vyOeHH5+tvv79B9/3mF5p48U8Uj8X0zAN3K7S55h/HqsqKpNdFJtEYp7ncXW0OfekNLxXxZdQUtKqKioRljVwikZZmsiXiqukPbuPashZ1cG2QJL3/0mw98Lvr9NdX31f3XvtIkg47/kTFYzFNv/NWjSmaWO/aoaZ8u2aN3nv3FUfbgNRWcPQEde2dn/T8488+T1vWr9O/Hr1f78yeKUnqv/8InXLRT/TsA39xfGqeTCIRp7ncXfrOU/WJ7vqMVNY8FT7d3/B0fi1yid21NJMt5bQ/WODaspbmdXYnx6tPPqbCIfvXFbVaB48drznPz9TKxV9qxBHfT3p9++Xn6/hLL3W0DUhtS8JSscPrVs+99gadMuVyrVn+XwW6ZKnvoCGacddtkqR9Cvo7WheZRCLNyeWucvJqLvYObd7Y4LPizZvUJTsn4VG1WuQSu2tpJlvKaX+wwLVlzZ+W5uicd8mWzcpM8GiO6uqac9cxB4dFPZKCmQH17pWd9DJIfRs2lChUkvyjO2p1yQ5qyKhD635e+NFcde/VW/v2G5D0OsgkGtPcXNbq3rO3srp11/IvFzb4bPnCz1U4ZFijy5JLJNLSTLaERzX9wW1cezdo0O9ztKN7F/TTqq+/1LpVK+pNf/+l2fJ6veo7cEjS64rvHB/YldNMJvLByy9o+aIvdNJ5l8jrTf4/TzKJxrRGLg87vkjz33lDW9Z/Vzdt4UdztW71Sh1+wkmNLkcukUhrZLK53JpJ1x5Zc/qXfcpFP9Hnc+fopkmnasK5F6prMEfz3nlTn7/3to4748fq1rNXm46P1Oc0E199+h/Nuu8uHXjk0eoSzNGyBZ/p7eee1sgxx6rovIvbfHzsHZrKxcvTH1V4e6m2bao5zTlvzhvatnG9JGnCpCnK7Jql0y77qT569UVNPf8MFU2+SBXhsF549H7tN3BIwldTORkfe5/WyOSm79bqvX89I0la8VXNUd9n7r9bktRjnz465pTTmz2+RZ54PO6+K+1U8wTkl5ZvdPQQ0mULP9fTf71TqxZ/qR2hYuXtm69jJp6piRf/RGmdku+tPq9HRQN6uu4JyGhbTjO54dvV+tsffq1VXy9SeVmZ8vrk65iJZ+iHF1yW8M67PSGTaExTubx87CHavG5tws/uf/Nj5fWpuRD822X/1T9u/33du0FHHT1O5/9qqoI9chsdm1wikdbI5Jcff6ip5ycuZMMOPlw3P/5sws/cmknXljVJ+nJzqZZtK2vXw6keSQO7ZWpYblY7jgq3IJOwiFzCGjLpjGuvWZOkfsFAu5/3jksqDDp7pAL2HmQSFpFLWEMmnXF1WQv4Oqkg2/m7wVqiILuzAj7XXuqHNkYmYRG5hDVk0hlXlzVJGp6bJX9a+/wa/jSvhrvw8CnaF5mEReQS1pDJ5Lm+rPnSvBrVO9guY43qHZSvnYIF9yKTsIhcwhoymTz3bvkuemZmaERe2zbmEXlZ6pnZ+FO6gV2RSVhELmENmUxOSpQ1Seqfk9lmO3xEXpb652S2ybqRusgkLCKXsIZMNs3Vj+5IZGNZpeavD6kiGmvxuvw7D9G6vZGjY5FJWEQuYQ2ZbFzKlTVJikRjWrS5VKtLyh29P1RS3fwF2Z01PDfL1ee4YQeZhEXkEtaQycRSsqzVCkeqtSoU1spQuO5Jybvv/F1/9nk96hcMqDAYcO3tvbCNTMIicglryGR9KV3WasXicZVUVitUEan5UxbWt2vWaL/8fAUzAwr6fQr6fcrO6OS6V1DAncgkLCKXsIZM1kidY4R74PV4lOP3qTAY0Mhe2RockFa/+4oGB6SRvbJVGAwox+9L6R0NW8gkLCKXsIZM1tgryhoAAIBbUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMMwTj8fjHb0RbS0Wj6ukslqhikjNn7Kwvl2zRvvl5yuYGVDQ71PQ71N2Rid5PZ6O3lzsBcgkLCKXsIZM1kjpshaOVGtlKKxVobAisZpf0yNp11941599Xo8KgwH1CwYU8HVq563F3oBMwiJyCWvIZH0pWdYi0ZgWbS7V6pLyBju3KbXzF2R31vDcLPnSOFOMliOTsIhcwhoymVjKlbWNZZWatz6kymisxevyp3k1qndQPTMzWmHLsLcik7CIXMIaMtm4lCprK4rLtGBTaauvd0RelvrnZLb6epH6yCQsIpewhkzuWcocI2yrHS1JCzaVakVxWZusG6mLTMIicglryGTTUqKsbSyrbLMdXWvBplJtLKts0zGQOsgkLCKXsIZMJsf1ZS0SjWne+lC7jDV/fUiRVjiXjtRGJmERuYQ1ZDJ5rr+/ddHmUlU1cwc888Bf9OTdf1L+9wbp7hfnNDl/xc67VA7qFWzWeNg7JJvJLz/+UFPPPz3hZ7c99aIGHjiqyXWQSSTL6Xflyq8W6um/3qkln32qqsoK9czvqx+cca6Kzru4yWXJJZKRbCbvveEavTN7ZqOf/+3d+eres/ce1+H2TLq6rJVFqrW6pLxZy27dsE7PPXiP/IGAo+VWl5RrcPcuKfkcF7RcczJ54uSLNGD4gfWm9epbkPTyZBJNcZrLL95/R7ddcYEKh+6v06+4Rv5ApjasWa2tG9cnvQ5yiT1xksnjz5qkA44YU29aPB7X337/K+Xum99kUavl5ky6b4t3sSoUdvwcllqP3XGzBo4YpVg0qtLQtqSX8+wcd1huVjNGRaprTiaHjjpUh59wUrPHJJNoipNchnds1703XK1Rx4zTL//ykLze5l0tQy6xJ04yOWjkaA0aObretMXzP1Zlebm+f9KPkh7TzZl07TVrsXhcq0LhZhW1rz79jz567SVd+Os/OF42LmllKKxY6jzxBK2kJZks37FD0erqZo1LJrEnTnM599/PK7Rls358zQ3yer2qCIcVizm/1IRcojEt+a6sNfffs+XxeDTmpFOTXsbNmXRtWSuprK57BYUT0WhUj9xyk447/cfqO2hIs8aOxGreVQbsqrmZ/OuN12rS6IE6e0Shfnfe6Vq+aIHjdZBJNMZpLhd+OFeBLl21deN6/fSEo3TuQQM0efRAPfj7G1RVWeFobHKJRJr7XVmrOhLRh6/8S4NGjlZen3xHy7o1k649DRqqiDRrudef+qc2r1urqX9/usXj5/h9LVoHUovTTHby+XTY8UU66OixysrppjXLl+pfjz6g3046Vbc++YL6DR3ueHwyid05zeX6b1YpGq3Wn668UONOO0fn/vxGffXJh3p5+qMqKy3Rz++63/H45BK7au6/37W+eP8dbQ8Va8wPkz8Fuvv4bsukq8ua02uDthdv01P3/FlnXHGNsrt1b/bYHrU8bEg9TjM5+KCDNfigg+t+PnjseB0+/iT9/JRxmnHXbfrtw08kPTaZRGOc5rIiXKbK8nIdf/Z5uuimWyRJhx1/oqojEb3+9OM6+2fXaZ+Cfkmti1wikeb8+72ruf9+Xp18Ph15wg8dL+vWTLq2rFVEo4539BN/uUNdgkFNmDSlRWPHJYXKwlq/Ptyi9SC1hMLN//Kp1btvoQ4eO14fv/GKotGo0tLSklqOTKIxTnOZ7vdLko4qmlhv+lEnnarXn35cS7+Yn3RZI5dIpCXfleVlZfr07dc04sij1TWnm+Pl46rpD27j2rIWdXi+e93qlXpz5nRd+Os/qHjTxrrpVVWVikYi2rR2jTp36aKuwZyk1vftmjV6791XHG0DUlvB0RPUtbez6ycS6dF7H1VHqlRZHlagS9eklyOTSMRpLrvl9tSaZf9VsHuPetOzu9ecjdhRWuJofHKJ3bXku/KTt16tuQu0madAJef9wQLXlrU0r8fR/Ns2blAsFtMjt/5Wj9z62wafX3HcoSo672JNufHmpNa3X36+jr/0UkfbgNS2JCwVt8J1qxvXfKv0DL/8AWcvHyaTSMRpLvsNO0ALPnxP2zZt0L79BtRNr/2f3GyHRzPIJXbXku/KuS8+J38gUwePPb7Z4zvtDxa4tqz509IcnfPeb+AgXf/XRxpMf/Ivd6i8bIem3HizeuUXJLUuj6RgZkC9e2Unu7nYC2zYUKJQSfK3o5ds29rg2snVS77SvDmva+SYYx0934pMojFOc3nEhB/q+Yf+qreeeVLDDzuqbvqbs55QWqdOGnbIEUmPTS6RiNNM1irZtlULP5qro4omKqOzswfa1/Kopj+4jWvLWtDvU9zB0fisnO469LgJDaa/9NjDkpTws8bEd44P7MppJu+69nKl+/0aNHK0srv10NoVS/XGzOlK93fWpF/8xtHYZBKNcZrLfkOHa+xpZ+vtZ59SNFqtYQcfri8/+UgfvfqifnTpT9WtZ6+k10UukYjTTNb64OUXFK2u1hgHD8LdnVsz6eqytjePD3ucZuKQceM199/P68W//03lZdtr/ofiByfqzCt/rt59C9t8fOwdmpOLy37/J+X23ldvP/e0PnnzVfXYp48u/PUfdNL5l7TL+Ehtzc3E3BefV3b3Hg1ePdVe43ckTzzuwkf5quYJyC8t39iiB+s1l8/rUdGAnvJ63HfeG22HTMIicglryKRzrn2DgdfjUWEwoPb+6/ZI6hcMuG5Ho+2RSVhELmENmXTOtWVNqvlLb+9eHpdUGGzehY1IfWQSFpFLWEMmnXF1WQv4Oqkgu3O7jlmQ3VkBn2sv9UMbI5OwiFzCGjLpjKvLmiQNz82SP619fg1/mlfDc7PaZSy4F5mEReQS1pDJ5Lm+rPnSvBrVO9guY43qHZSvnYIF9yKTsIhcwhoymTz3bvkuemZmaERe2zbmEXlZ6pmZ0aZjIHWQSVhELmENmUxOSpQ1Seqfk9lmO3xEXpb65zh79Q9AJmERuYQ1ZLJprn3OWmM2llVq/vqQKqKxFq/Lv/MQrdsbOToWmYRF5BLWkMnGpVxZk6RINKZFm0u1uqTc0ftDJdXNX5DdWcNzs1x9jht2kElYRC5hDZlMLCXLWq1wpFqrQmGtDIXrnpS8+87f9Wef16N+wYAKgwHX3t4L28gkLCKXsIZM1pfSZa1WLB5XSWW1QhWRmj9lYX27Zo32y89XMDOgoN+noN+n7IxOrnyyMdyHTMIicglryGSN1DlGuAdej0c5fp8KgwGN7JWtwQFp9buvaHBAGtkrW4XBgHL8vpTe0bCFTMIicglryGSNvaKsAQAAuBVlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhnng8Hu/ojWhrsXhcJZXVClVEav6UhfXtmjXaLz9fwcyAgn6fgn6fsjM6yevxdPTmYi9AJmERuYQ1ZLJGSpe1cKRaK0NhrQqFFYnV/JoeSbv+wrv+7PN6VBgMqF8woICvUztvLfYGZBIWkUtYQybrS8myFonGtGhzqVaXlDfYuU2pnb8gu7OG52bJl8aZYrQcmYRF5BLWkMnEUq6sbSyr1Lz1IVVGYy1elz/Nq1G9g+qZmdEKW4a9FZmEReQS1pDJxqVUWVtRXKYFm0pbfb0j8rLUPyez1deL1EcmYRG5hDVkcs9S5hhhW+1oSVqwqVQrisvaZN1IXWQSFpFLWEMmm5YSZW1jWWWb7ehaCzaVamNZZZuOgdRBJmERuYQ1ZDI5ri9rkWhM89aH2mWs+etDirTCuXSkNjIJi8glrCGTyXP9/a2LNpeqKskdEKmq1FP3/I/efeFZlZWWqO+gITrn6us14sijk1q+YuddKgf1CrZgi5HqnGSyvKxMLzxyn5Yt/FzLF32hHSUhXfnHaRr7o7OSWp5MIlnJ5nL5oi805/mZ+vKTD7X5uzXqGszR90aM0o+vvl77FPZPaixyiWQkm8lvl/1XM/96p1Z8tVChLZuU4e+sPgMG6pQpV+jgsccnNZbbM+nqI2tlkWqtLilP+tbee2+4Ri/+428a88NTdeGNN8vr9erWyyZr8fyPkx5zdUm5wpHq5m0wUp7TTG4v3qZZ903T2pXL1HfQ0GaNSSbRFCe5fP6h/9V/3nhZBxx2lKbceLN+cOYkLZ73H1132nh9u3RJ0mOSS+yJk0xuXrdW5WU7dOzEMzTlxv+n039yrSTp9p9coNefnp70mG7OpKvvBv1yc6mWbStLamcvW/i5bjizSOdd91udctEVkqSqygpd+8Oxyu7WXX986sWkxvRIGtgtU8Nys5q/4UhZTjIp1Rzt3VFSopzcPC1ftEC/OmOCoyNrEplE05zkcslnn6r//iPkS0+vm7Zu9Ur9/ORxOnx8ka7+n78mNSa5xJ44/a7cXTQa1fWnjVdVZaXufWVuUsu4OZOuPbIWi8e1KhROekd/9Nq/5U1L0w/OmlQ3LT3Dr3GnnaP/fjFfW9Z/l9R64pJWhsKK7dpx43Fp5UqpzP13nKD5nGZSknzpGcrJzWvRuAkzKUmbN0sbNrRo3XA/p7kcfNDB9YqaJO1T0E/5AwZq7YplSY+bMJfhsLRiRdLrQGpqznfl7tLS0tS91z4Kb0/+5oRGvytdwLVlraSyuu4VFMlYtfhL7VPQT4EuXetNH3DAgTs//yrpdUViNe8qUzwuvf66dOSRUv/+0kEHSdFo0utBanGaydZUl0lJWrZMOv98qVcvqbBQWrCgQ7YJNrRGLuPxuEJbt6hrTjdHy9XlsrRUuuUWqU8facAAadq0Fm0P3K25mawIh1VavFUbvl2tF//xN30+d46GH3aUo3XU+650EdfeYBCqiDiav3jzJuXk9mwwvXZa8aaNzsb/7Avl/PJq6aOP/m/i0qXS6tU1xQ17HaeZbPXxv12rnFt/L02fLsV2XrRbUSG99540YkSHbhs6Tmvk8r0Xn9O2jet19s9+6Xz8Z2cr56eXScXF/zfx9dela69t8XbBnZqbycf+9Ae9/vTjkiSv16tDf3CiLv7trc0aP8fva9Y2dBRXlzUn7w2rqqhQp90O7UuSL6PmVRRVlRVJj+2pjij0xtv1i1qthx6SevRIel1IHaHhh8izX3/Fve1/wNpTXa3QM7Okf/6z4YdvvSVVuvsZQ2i+luZy7cplevjmGzXowFE6ZuKZjpb1RCIKLV9Zv6hJNZeN/PnPzdoeuF9zM1l0/sU6bHyRijdt1IevvKhYLKrqiLPi51HH/491c7i2rFVEo47Od6f7/aquqmowPbLzH7H0DH/S64qndVJFj0auM/rTnxxsFVJJxf/+XfG+Azpk7Hhamip65Cb+8IUXav5gr9SSXBZv3qQ/XnaeAl276pd/eUhpaWmOlo93auS7culS6brrmrVNcL/mZrJPv++pT7/vSZKOmXiGbp5ytm674nzdPvMleTyepNYRV01/cBvXXrMWdXi+Oyc3T8WbG57qrJ2Wk9fwFGmjPB5FM1Lj5bBoPdH0dCnJL4xWRybRiObmsmx7qW699FyVlZbqpoeeULeevZwPTi6RQGt9Vx42/iQtX/SF1q1ydtOK0/5ggWuPrKV5ne3ogsHD9OXHHyq8Y3u9mwyWLfhcklQ4ZFjyK4vHldbIaaWSW29VLK9ld/fBnWJDh9TcdNIRhS0el7c68UWz4bPPVuW4ce28QbCiObmsqqzQbVecr3WrV2rqo08rf8DA5g3eyHdlZNgw7bjmmuatE67XWt+VtZcvhXdsd7Sc0/5ggWvLmj8tzdE1a4ePP0n/evQBvfH09LrnrEWqKvX280/reyMOUo/e+yY9tsfjkf+4sdKkSdITT/zfxdySss85p+YOPOx1um4o0daSlt2O3lwej0edTzxB+sMfpLvukkpK6j4LHHWUAhdf3AFbBQuc5jIajequay/X0i/m61f/+3cNGjm62WN7PB75RxwgDR4sLfm/B+r6+vZVDpncaznNZMnWLcruXv9a8OpIRO/OnqV0v199+if/PxMe1fQHt3FtWQv6fYqXND1frYEjDtLhJ/xQM6bdppJtW9Rrv0K9M3umNn+3Rj+55U5HY8clBXvmSo8/Lt10U80t6U8+KR11lFRQ4GhdSB1OM1nr5emPKry9VNt23pE8b84b2rZxvSRpwqQpyuza9AMc45KCWV2k3/1O+tnPpHvuke6+W0pPl044wflGIWU4zeVjf/qDPn37dY0+9gfaURLSu/96tt7nR598WtLriksK7j9E+vJLaebMmu/KpUulH/84+Q1CynGayQemXq/yHTs0dPSh6tazl0JbNuu9F5/TdyuX6/xfTVXnzMyk1xXfOb7buPYNBsUVEc35ZoujZaoqK/TkX+7Qey8+p7KSmneDnv2z6zVyzDGOxz+2b4/6t/5GIlJamtQBdwLChuZkUpIuH3uINq9bm/Cz+9/8WHl98pNaT4NMxuM1uUxwFzT2Hk5z+bvJp+mrTxPc6b7Ts0vWORq/QS6rqsjkXs5pJt9/abbeevZJfbt0ibaHitU5s4v6DRuuEydN0cFjxzsev0EmXcC1ZS0Wj+ul5Rs75CGkPq9HRQN6yttRF5PDJDIJi8glrCGTzrn2MJDX41FhMKD2/uv2SOoXDLhuR6PtkUlYRC5hDZl0zrVlTar5S2/vXh6XVBgMtPOocAsyCYvIJawhk864uqwFfJ1UkN25XccsyO6sgM+192WgjZFJWEQuYQ2ZdMbVZU2ShudmyZ/WPr+GP82r4blN35mHvRuZhEXkEtaQyeS5vqz50rwa1TvYLmON6h2Ur52CBfcik7CIXMIaMpk89275LnpmZmhEXts25hF5WeqZyWtTkBwyCYvIJawhk8lJibImSf1zMttsh4/Iy1L/nOQfugdIZBI2kUtYQyab5trnrDVmY1ml5q8PqSIaa3rmJvh3HqJ1eyNHxyKTsIhcwhoy2biUK2uSFInGtGhzqVaXlDt6f6ikuvkLsjtreG6Wq89xww4yCYvIJawhk4mlZFmrFY5Ua1UorJWhcN2Tknff+bv+7PN61C8YUGEw4Nrbe2EbmYRF5BLWkMn6Urqs1YrF4yqprFaoIqJQRUQV0aiisbjSvB7509IU9PsU9PuUndHJlU82hvuQSVhELmENmayxV5Q1AAAAt0qdE7oAAAApiLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBhlDUAAADDKGsAAACGUdYAAAAMo6wBAAAYRlkDAAAwjLIGAABgGGUNAADAMMoaAACAYZQ1AAAAwyhrAAAAhlHWAAAADKOsAQAAGEZZAwAAMIyyBgAAYBhlDQAAwDDKGgAAgGGUNQAAAMMoawAAAIZR1gAAAAyjrAEAABhGWQMAADCMsgYAAGAYZQ0AAMAwyhoAAIBh/x/e59fMMLLkIgAAAABJRU5ErkJggg==", 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plot saved to graph_plot.pkl\n" ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ @@ -3282,7 +2364,7 @@ "\n", "\n", "# status = model.solve(GUROBI_CMD(threads=26, options=[(\"IIS\", 1), (\"IISFile\", \"/home/sfischer/Documents/projects/wk_LinProg/LinProg_Scripts/infeasible.ilp\")]))\n", - "status = model.solve(GUROBI_CMD(threads=26, timeLimit=600))\n", + "status = model.solve(GUROBI_CMD(threads=26, timeLimit=60))\n", "# status = model.solve(GUROBI(Threads=26, TimeLimit=600,ImprovementTime=30))\n", "\n", "# status = model.solve(GUROBI_CMD(threads=26))\n", @@ -3361,7 +2443,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -3459,7 +2541,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -3615,7 +2697,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, "outputs": [], "source": [ diff --git a/LinProg_Scripts/PE_graph.graphml b/LinProg_Scripts/PE_graph.graphml index 9272411..55f4777 100644 --- a/LinProg_Scripts/PE_graph.graphml +++ b/LinProg_Scripts/PE_graph.graphml @@ -8,21 +8,87 @@ - 5052 - 70 - 302 + 106 + 1191 + 14 True False + + 60 + 265 + 14 + False + False + + + 172 + 1924 + 5 + False + False + - 6032 - 478 - 302 + 62 + 274 + 28 + False + False + + + 142 + 2554 + 5 + False + False + + + 199 + 7716 + 5 + False + False + + + 240 + 12630 + 2 False True - - 302 + + 38 + 3028 + 3 + False + False + + + 56 + + + 35 + + + 14 + + + 5 + + + 14 + + + 5 + + + 5 + + + 12 + + + 3 diff --git a/LinProg_Scripts/PE_graph.pkl b/LinProg_Scripts/PE_graph.pkl index a4325b99f5563d53f302ff0a3d031de889163799..3b432190065ada0dc375370aa81e5043bf54874a 100644 GIT binary patch literal 782 zcmZXS&u-H|5XJ+xX%e@Q+6zzx5DI_NOC%1JIG`XT5QkCW)~n_0F5QGAjyyJ{he{xE zXr&bwmS^C?d+-802xm@w>$NLO_%yq}nQy-F&ZqEu5Ok`~+*+&RG|S(AoQP%0tau{l zCwaQj)@;3;zpkQh_TaNUw__7|a&AqOtTUOSMeT5|OPomKLVxk1MsZM?b=b zvRX?^0~2sA?1c#=7xuEG5CXbS&vbm$yQa5kpm#3y03i0@C%~62fT#g|52gTnu434L zT@Stj{Oz?XMjreEcyPB34n6n-aQp<|dL?yH($s@T0Ka2^pzcwcFiGX28Qr-z(Yxim zU`tP#t7!-Z^*)W*jeual)i4BmI7P@p!WCn8PjFZ>LCf5)hu8x@eEuF zVf9T!n_S7ZE9&Umm4PvZ`VRH={jzEs>Y?u#>wE0l(yoS6_akVeAJSAGRMXR;evB4- zNz$xHB2uAMlAwzTtHx%(VOQ%TvRr+bt5ddS=Y?FPLaoKwF)nPqM&?G67T7ho=9!6< zJWic6++mU?s5PSMEV@|_@_!R>pGF@p!FB!jmzgRi5sw1*`=F(qpXP=Pl??G%v8 z9@ey+%#vb|ImN{wfzlq<_~O#! effect_comp: + more_factor = "noc_factor" + less_factor = "comp_factor" + ratio = effect_noc / effect_comp if effect_comp != 0 else float('inf') +else: + more_factor = "comp_factor" + less_factor = "noc_factor" + ratio = effect_comp / effect_noc if effect_noc != 0 else float('inf') + +print(f"{more_factor} impacts the objective value {ratio:.2f} times more than {less_factor}.") +# ...existing code... +impact_summary = f"{more_factor} x{ratio:.2f} > {less_factor}" # Pivot the data to create a matrix for the heatmap heatmap_data = df.pivot_table( index="noc_factor", @@ -33,14 +70,23 @@ sns.heatmap( cmap="viridis", cbar_kws={'label': 'Max Delay'} # Add colorbar label ) -plt.title("Max Delay Heatmap\n(Pearson: noc={:.2f}, comp={:.2f} | Spearman: noc={:.2f}, comp={:.2f})".format( - pearson_corr['objective_value']['noc_factor'], - pearson_corr['objective_value']['comp_factor'], - spearman_corr['objective_value']['noc_factor'], - spearman_corr['objective_value']['comp_factor'] -)) +plt.title( + "Max Delay Heatmap\n" + "Pearson: noc={:.2f}, comp={:.2f} | Spearman: noc={:.2f}, comp={:.2f}\n" + "Regression: noc={:.2f}{} , comp={:.2f}{} | R²={:.2f}".format( + pearson_corr['objective_value']['noc_factor'], + pearson_corr['objective_value']['comp_factor'], + spearman_corr['objective_value']['noc_factor'], + spearman_corr['objective_value']['comp_factor'], + model.params['noc_factor'], + f" ← ({ratio:.2f})" if more_factor == "noc_factor" else "", + model.params['comp_factor'], + f" ← ({ratio:.2f})" if more_factor == "comp_factor" else "", + model.rsquared + ) +) plt.xlabel("comp_factor") plt.ylabel("noc_factor") plt.tight_layout() -plt.savefig("/home/sfischer/Documents/projects/wk_LinProg/optimization_results/inception70/NoOpt_heatmap.png") +plt.savefig("/home/sfischer/Documents/projects/wk_LinProg/optimization_results/inception70/Opt_5x_heatmap.png") plt.show() \ No newline at end of file diff --git a/LinProg_Scripts/Task_LinProg.ipynb b/LinProg_Scripts/Task_LinProg.ipynb index 812aa41..1241e61 100644 --- a/LinProg_Scripts/Task_LinProg.ipynb +++ b/LinProg_Scripts/Task_LinProg.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 188, + "execution_count": 577, "metadata": {}, "outputs": [], "source": [ @@ -300,7 +300,7 @@ }, { "cell_type": "code", - "execution_count": 189, + "execution_count": 578, "metadata": {}, "outputs": [], "source": [ @@ -488,7 +488,7 @@ }, { "cell_type": "code", - "execution_count": 190, + "execution_count": 579, "metadata": {}, "outputs": [], "source": [ @@ -506,7 +506,7 @@ }, { "cell_type": "code", - "execution_count": 191, + "execution_count": 580, "metadata": {}, "outputs": [ { @@ -514,76 +514,76 @@ "output_type": "stream", "text": [ "Node Attributes:\n", - "Node 0: {'delay_comp': 6, 'delay_mem': 1078, 'delay_send': 285, 'src': True, 'dst': False}\n", - "Node 1: {'delay_comp': 56, 'delay_mem': 38, 'delay_send': 277, 'src': False, 'dst': False}\n", - "Node 2: {'delay_comp': 112, 'delay_mem': 75, 'delay_send': 554, 'src': False, 'dst': False}\n", + "Node 0: {'delay_comp': 4, 'delay_mem': 1078, 'delay_send': 285, 'src': True, 'dst': False}\n", + "Node 1: {'delay_comp': 34, 'delay_mem': 38, 'delay_send': 277, 'src': False, 'dst': False}\n", + "Node 2: {'delay_comp': 67, 'delay_mem': 75, 'delay_send': 554, 'src': False, 'dst': False}\n", "Node 3: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 4: {'delay_comp': 83, 'delay_mem': 223, 'delay_send': 205, 'src': False, 'dst': False}\n", + "Node 4: {'delay_comp': 50, 'delay_mem': 223, 'delay_send': 205, 'src': False, 'dst': False}\n", "Node 5: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 342, 'src': False, 'dst': False}\n", - "Node 6: {'delay_comp': 16, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 7: {'delay_comp': 78, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", - "Node 8: {'delay_comp': 16, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 9: {'delay_comp': 43, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 10: {'delay_comp': 43, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 11: {'delay_comp': 78, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", + "Node 6: {'delay_comp': 10, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 7: {'delay_comp': 47, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", + "Node 8: {'delay_comp': 10, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 9: {'delay_comp': 26, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 10: {'delay_comp': 26, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 11: {'delay_comp': 47, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", "Node 12: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 388, 'src': False, 'dst': False}\n", - "Node 13: {'delay_comp': 114, 'delay_mem': 1329, 'delay_send': 95, 'src': False, 'dst': False}\n", + "Node 13: {'delay_comp': 69, 'delay_mem': 1329, 'delay_send': 95, 'src': False, 'dst': False}\n", "Node 14: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 95, 'src': False, 'dst': False}\n", "Node 15: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 16: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 17: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 18: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 19: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 20: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 21: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 16: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 17: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 18: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 19: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 20: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 21: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 22: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 23: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 23: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 24: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 25: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 26: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 27: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 28: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 29: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 30: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 25: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 26: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 27: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 28: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 29: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 30: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 31: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 32: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 32: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 33: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 34: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 35: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 36: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 37: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 38: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 39: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 34: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 35: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 36: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 37: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 38: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 39: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 40: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 41: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 41: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 42: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 43: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 44: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 45: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 46: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 47: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 48: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 43: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 44: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 45: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 46: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 47: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 48: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 49: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 50: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 50: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 51: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 52: {'delay_comp': 108, 'delay_mem': 5311, 'delay_send': 45, 'src': False, 'dst': False}\n", - "Node 53: {'delay_comp': 26, 'delay_mem': 296, 'delay_send': 95, 'src': False, 'dst': False}\n", - "Node 54: {'delay_comp': 133, 'delay_mem': 1550, 'delay_send': 110, 'src': False, 'dst': False}\n", - "Node 55: {'delay_comp': 42, 'delay_mem': 2067, 'delay_send': 30, 'src': False, 'dst': False}\n", + "Node 52: {'delay_comp': 65, 'delay_mem': 5311, 'delay_send': 45, 'src': False, 'dst': False}\n", + "Node 53: {'delay_comp': 16, 'delay_mem': 296, 'delay_send': 95, 'src': False, 'dst': False}\n", + "Node 54: {'delay_comp': 80, 'delay_mem': 1550, 'delay_send': 110, 'src': False, 'dst': False}\n", + "Node 55: {'delay_comp': 25, 'delay_mem': 2067, 'delay_send': 30, 'src': False, 'dst': False}\n", "Node 56: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 45, 'src': False, 'dst': False}\n", "Node 57: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 119, 'src': False, 'dst': False}\n", - "Node 58: {'delay_comp': 32, 'delay_mem': 1575, 'delay_send': 45, 'src': False, 'dst': False}\n", - "Node 59: {'delay_comp': 16, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", - "Node 60: {'delay_comp': 25, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", - "Node 61: {'delay_comp': 33, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", - "Node 62: {'delay_comp': 16, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", - "Node 63: {'delay_comp': 21, 'delay_mem': 1034, 'delay_send': 23, 'src': False, 'dst': False}\n", - "Node 64: {'delay_comp': 25, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", - "Node 65: {'delay_comp': 29, 'delay_mem': 1406, 'delay_send': 26, 'src': False, 'dst': False}\n", - "Node 66: {'delay_comp': 33, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", + "Node 58: {'delay_comp': 20, 'delay_mem': 1575, 'delay_send': 45, 'src': False, 'dst': False}\n", + "Node 59: {'delay_comp': 10, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", + "Node 60: {'delay_comp': 15, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", + "Node 61: {'delay_comp': 20, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", + "Node 62: {'delay_comp': 10, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", + "Node 63: {'delay_comp': 13, 'delay_mem': 1034, 'delay_send': 23, 'src': False, 'dst': False}\n", + "Node 64: {'delay_comp': 15, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", + "Node 65: {'delay_comp': 18, 'delay_mem': 1406, 'delay_send': 26, 'src': False, 'dst': False}\n", + "Node 66: {'delay_comp': 20, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", "Node 67: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 119, 'src': False, 'dst': False}\n", - "Node 68: {'delay_comp': 11, 'delay_mem': 526, 'delay_send': 15, 'src': False, 'dst': False}\n", - "Node 69: {'delay_comp': 11, 'delay_mem': 0, 'delay_send': 15, 'src': False, 'dst': True}\n", + "Node 68: {'delay_comp': 7, 'delay_mem': 526, 'delay_send': 15, 'src': False, 'dst': False}\n", + "Node 69: {'delay_comp': 7, 'delay_mem': 0, 'delay_send': 15, 'src': False, 'dst': True}\n", "1078\n" ] } @@ -601,7 +601,7 @@ }, { "cell_type": "code", - "execution_count": 192, + "execution_count": 581, "metadata": {}, "outputs": [], "source": [ @@ -690,7 +690,7 @@ }, { "cell_type": "code", - "execution_count": 193, + "execution_count": 582, "metadata": {}, "outputs": [], "source": [ @@ -777,7 +777,7 @@ }, { "cell_type": "code", - "execution_count": 194, + "execution_count": 583, "metadata": {}, "outputs": [], "source": [ @@ -836,7 +836,7 @@ }, { "cell_type": "code", - "execution_count": 195, + "execution_count": 584, "metadata": {}, "outputs": [], "source": [ @@ -883,12 +883,12 @@ }, { "cell_type": "code", - "execution_count": 196, + "execution_count": 585, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -899,10 +899,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 196, + "execution_count": 585, "metadata": {}, "output_type": "execute_result" } @@ -973,7 +973,7 @@ }, { "cell_type": "code", - "execution_count": 197, + "execution_count": 586, "metadata": {}, "outputs": [ { @@ -981,76 +981,76 @@ "output_type": "stream", "text": [ "Node Attributes:\n", - "Node 0: {'delay_comp': 6, 'delay_mem': 1078, 'delay_send': 285, 'src': True, 'dst': False}\n", - "Node 1: {'delay_comp': 56, 'delay_mem': 38, 'delay_send': 277, 'src': False, 'dst': False}\n", - "Node 2: {'delay_comp': 112, 'delay_mem': 75, 'delay_send': 554, 'src': False, 'dst': False}\n", + "Node 0: {'delay_comp': 4, 'delay_mem': 1078, 'delay_send': 285, 'src': True, 'dst': False}\n", + "Node 1: {'delay_comp': 34, 'delay_mem': 38, 'delay_send': 277, 'src': False, 'dst': False}\n", + "Node 2: {'delay_comp': 67, 'delay_mem': 75, 'delay_send': 554, 'src': False, 'dst': False}\n", "Node 3: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 4: {'delay_comp': 83, 'delay_mem': 223, 'delay_send': 205, 'src': False, 'dst': False}\n", + "Node 4: {'delay_comp': 50, 'delay_mem': 223, 'delay_send': 205, 'src': False, 'dst': False}\n", "Node 5: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 342, 'src': False, 'dst': False}\n", - "Node 6: {'delay_comp': 16, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 7: {'delay_comp': 78, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", - "Node 8: {'delay_comp': 16, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 9: {'delay_comp': 43, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 10: {'delay_comp': 43, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", - "Node 11: {'delay_comp': 78, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", + "Node 6: {'delay_comp': 10, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 7: {'delay_comp': 47, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", + "Node 8: {'delay_comp': 10, 'delay_mem': 42, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 9: {'delay_comp': 26, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 10: {'delay_comp': 26, 'delay_mem': 116, 'delay_send': 137, 'src': False, 'dst': False}\n", + "Node 11: {'delay_comp': 47, 'delay_mem': 223, 'delay_send': 194, 'src': False, 'dst': False}\n", "Node 12: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 388, 'src': False, 'dst': False}\n", - "Node 13: {'delay_comp': 114, 'delay_mem': 1329, 'delay_send': 95, 'src': False, 'dst': False}\n", + "Node 13: {'delay_comp': 69, 'delay_mem': 1329, 'delay_send': 95, 'src': False, 'dst': False}\n", "Node 14: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 95, 'src': False, 'dst': False}\n", "Node 15: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 16: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 17: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 18: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 19: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 20: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 21: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 16: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 17: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 18: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 19: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 20: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 21: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 22: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 23: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 23: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 24: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 25: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 26: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 27: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 28: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 29: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 30: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 25: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 26: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 27: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 28: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 29: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 30: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 31: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 32: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 32: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 33: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 34: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 35: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 36: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 37: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 38: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 39: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 34: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 35: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 36: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 37: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 38: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 39: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 40: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 41: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 41: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 42: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 43: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 44: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 45: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 46: {'delay_comp': 9, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", - "Node 47: {'delay_comp': 19, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", - "Node 48: {'delay_comp': 29, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 43: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 44: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 45: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 46: {'delay_comp': 6, 'delay_mem': 100, 'delay_send': 32, 'src': False, 'dst': False}\n", + "Node 47: {'delay_comp': 12, 'delay_mem': 223, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 48: {'delay_comp': 18, 'delay_mem': 333, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 49: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 50: {'delay_comp': 13, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", + "Node 50: {'delay_comp': 8, 'delay_mem': 149, 'delay_send': 48, 'src': False, 'dst': False}\n", "Node 51: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 189, 'src': False, 'dst': False}\n", - "Node 52: {'delay_comp': 108, 'delay_mem': 5311, 'delay_send': 45, 'src': False, 'dst': False}\n", - "Node 53: {'delay_comp': 26, 'delay_mem': 296, 'delay_send': 95, 'src': False, 'dst': False}\n", - "Node 54: {'delay_comp': 133, 'delay_mem': 1550, 'delay_send': 110, 'src': False, 'dst': False}\n", - "Node 55: {'delay_comp': 42, 'delay_mem': 2067, 'delay_send': 30, 'src': False, 'dst': False}\n", + "Node 52: {'delay_comp': 65, 'delay_mem': 5311, 'delay_send': 45, 'src': False, 'dst': False}\n", + "Node 53: {'delay_comp': 16, 'delay_mem': 296, 'delay_send': 95, 'src': False, 'dst': False}\n", + "Node 54: {'delay_comp': 80, 'delay_mem': 1550, 'delay_send': 110, 'src': False, 'dst': False}\n", + "Node 55: {'delay_comp': 25, 'delay_mem': 2067, 'delay_send': 30, 'src': False, 'dst': False}\n", "Node 56: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 45, 'src': False, 'dst': False}\n", "Node 57: {'delay_comp': 0, 'delay_mem': 0, 'delay_send': 119, 'src': False, 'dst': False}\n", - "Node 58: {'delay_comp': 32, 'delay_mem': 1575, 'delay_send': 45, 'src': False, 'dst': False}\n", - "Node 59: {'delay_comp': 16, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", - "Node 60: {'delay_comp': 25, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", - "Node 61: {'delay_comp': 33, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", - "Node 62: {'delay_comp': 16, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", - "Node 63: {'delay_comp': 21, 'delay_mem': 1034, 'delay_send': 23, 'src': False, 'dst': False}\n", - "Node 64: {'delay_comp': 25, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", - "Node 65: {'delay_comp': 29, 'delay_mem': 1406, 'delay_send': 26, 'src': False, 'dst': False}\n", - "Node 66: {'delay_comp': 33, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", + "Node 58: {'delay_comp': 20, 'delay_mem': 1575, 'delay_send': 45, 'src': False, 'dst': False}\n", + "Node 59: {'delay_comp': 10, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", + "Node 60: {'delay_comp': 15, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", + "Node 61: {'delay_comp': 20, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", + "Node 62: {'delay_comp': 10, 'delay_mem': 788, 'delay_send': 23, 'src': False, 'dst': False}\n", + "Node 63: {'delay_comp': 13, 'delay_mem': 1034, 'delay_send': 23, 'src': False, 'dst': False}\n", + "Node 64: {'delay_comp': 15, 'delay_mem': 1206, 'delay_send': 26, 'src': False, 'dst': False}\n", + "Node 65: {'delay_comp': 18, 'delay_mem': 1406, 'delay_send': 26, 'src': False, 'dst': False}\n", + "Node 66: {'delay_comp': 20, 'delay_mem': 1608, 'delay_send': 30, 'src': False, 'dst': False}\n", "Node 67: {'delay_comp': 1, 'delay_mem': 0, 'delay_send': 119, 'src': False, 'dst': False}\n", - "Node 68: {'delay_comp': 11, 'delay_mem': 526, 'delay_send': 15, 'src': False, 'dst': False}\n", - "Node 69: {'delay_comp': 11, 'delay_mem': 0, 'delay_send': 15, 'src': False, 'dst': True}\n", + "Node 68: {'delay_comp': 7, 'delay_mem': 526, 'delay_send': 15, 'src': False, 'dst': False}\n", + "Node 69: {'delay_comp': 7, 'delay_mem': 0, 'delay_send': 15, 'src': False, 'dst': True}\n", "\n", "Edge Attributes:\n", "Edge from 0 to 1: {'flits': 285}\n", @@ -1209,12 +1209,210 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 587, + "metadata": { + "tags": [ + "parameters" + ] + }, + "outputs": [], + "source": [ + "param1 = 1\n", + "param2 = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 588, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Edge from 0 to 1: {'flits': 285}\n", + "Edge from 1 to 2: {'flits': 277}\n", + "Edge from 2 to 3: {'flits': 554}\n", + "Edge from 2 to 4: {'flits': 554}\n", + "Edge from 3 to 5: {'flits': 137}\n", + "Edge from 4 to 5: {'flits': 205}\n", + "Edge from 5 to 6: {'flits': 342}\n", + "Edge from 5 to 8: {'flits': 342}\n", + "Edge from 6 to 7: {'flits': 137}\n", + "Edge from 7 to 12: {'flits': 194}\n", + "Edge from 8 to 9: {'flits': 137}\n", + "Edge from 9 to 10: {'flits': 137}\n", + "Edge from 10 to 11: {'flits': 137}\n", + "Edge from 11 to 12: {'flits': 194}\n", + "Edge from 12 to 13: {'flits': 388}\n", + "Edge from 12 to 14: {'flits': 388}\n", + "Edge from 13 to 15: {'flits': 95}\n", + "Edge from 14 to 15: {'flits': 95}\n", + "Edge from 15 to 16: {'flits': 189}\n", + "Edge from 15 to 17: {'flits': 189}\n", + "Edge from 15 to 19: {'flits': 189}\n", + "Edge from 15 to 22: {'flits': 189}\n", + "Edge from 16 to 24: {'flits': 48}\n", + "Edge from 17 to 18: {'flits': 32}\n", + "Edge from 18 to 24: {'flits': 48}\n", + "Edge from 19 to 20: {'flits': 32}\n", + "Edge from 20 to 21: {'flits': 48}\n", + "Edge from 21 to 24: {'flits': 48}\n", + "Edge from 22 to 23: {'flits': 189}\n", + "Edge from 23 to 24: {'flits': 48}\n", + "Edge from 24 to 25: {'flits': 189}\n", + "Edge from 24 to 26: {'flits': 189}\n", + "Edge from 24 to 28: {'flits': 189}\n", + "Edge from 24 to 31: {'flits': 189}\n", + "Edge from 25 to 33: {'flits': 48}\n", + "Edge from 26 to 27: {'flits': 32}\n", + "Edge from 27 to 33: {'flits': 48}\n", + "Edge from 28 to 29: {'flits': 32}\n", + "Edge from 29 to 30: {'flits': 48}\n", + "Edge from 30 to 33: {'flits': 48}\n", + "Edge from 31 to 32: {'flits': 189}\n", + "Edge from 32 to 33: {'flits': 48}\n", + "Edge from 33 to 34: {'flits': 189}\n", + "Edge from 33 to 35: {'flits': 189}\n", + "Edge from 33 to 37: {'flits': 189}\n", + "Edge from 33 to 40: {'flits': 189}\n", + "Edge from 34 to 42: {'flits': 48}\n", + "Edge from 35 to 36: {'flits': 32}\n", + "Edge from 36 to 42: {'flits': 48}\n", + "Edge from 37 to 38: {'flits': 32}\n", + "Edge from 38 to 39: {'flits': 48}\n", + "Edge from 39 to 42: {'flits': 48}\n", + "Edge from 40 to 41: {'flits': 189}\n", + "Edge from 41 to 42: {'flits': 48}\n", + "Edge from 42 to 43: {'flits': 189}\n", + "Edge from 42 to 44: {'flits': 189}\n", + "Edge from 42 to 46: {'flits': 189}\n", + "Edge from 42 to 49: {'flits': 189}\n", + "Edge from 43 to 51: {'flits': 48}\n", + "Edge from 44 to 45: {'flits': 32}\n", + "Edge from 45 to 51: {'flits': 48}\n", + "Edge from 46 to 47: {'flits': 32}\n", + "Edge from 47 to 48: {'flits': 48}\n", + "Edge from 48 to 51: {'flits': 48}\n", + "Edge from 49 to 50: {'flits': 189}\n", + "Edge from 50 to 51: {'flits': 48}\n", + "Edge from 51 to 52: {'flits': 189}\n", + "Edge from 51 to 53: {'flits': 189}\n", + "Edge from 51 to 56: {'flits': 189}\n", + "Edge from 52 to 57: {'flits': 45}\n", + "Edge from 53 to 54: {'flits': 95}\n", + "Edge from 54 to 55: {'flits': 110}\n", + "Edge from 55 to 57: {'flits': 30}\n", + "Edge from 56 to 57: {'flits': 45}\n", + "Edge from 57 to 58: {'flits': 119}\n", + "Edge from 57 to 59: {'flits': 119}\n", + "Edge from 57 to 62: {'flits': 119}\n", + "Edge from 57 to 67: {'flits': 119}\n", + "Edge from 58 to 69: {'flits': 45}\n", + "Edge from 59 to 60: {'flits': 23}\n", + "Edge from 60 to 61: {'flits': 26}\n", + "Edge from 61 to 69: {'flits': 30}\n", + "Edge from 62 to 63: {'flits': 23}\n", + "Edge from 63 to 64: {'flits': 23}\n", + "Edge from 64 to 65: {'flits': 26}\n", + "Edge from 65 to 66: {'flits': 26}\n", + "Edge from 66 to 69: {'flits': 30}\n", + "Edge from 67 to 68: {'flits': 119}\n", + "Edge from 68 to 69: {'flits': 15}\n", + "Edge from 0 to 1: {'flits': 285}\n", + "Edge from 1 to 2: {'flits': 277}\n", + "Edge from 2 to 3: {'flits': 554}\n", + "Edge from 2 to 4: {'flits': 554}\n", + "Edge from 3 to 5: {'flits': 137}\n", + "Edge from 4 to 5: {'flits': 205}\n", + "Edge from 5 to 6: {'flits': 342}\n", + "Edge from 5 to 8: {'flits': 342}\n", + "Edge from 6 to 7: {'flits': 137}\n", + "Edge from 7 to 12: {'flits': 194}\n", + "Edge from 8 to 9: {'flits': 137}\n", + "Edge from 9 to 10: {'flits': 137}\n", + "Edge from 10 to 11: {'flits': 137}\n", + "Edge from 11 to 12: {'flits': 194}\n", + "Edge from 12 to 13: {'flits': 388}\n", + "Edge from 12 to 14: {'flits': 388}\n", + "Edge from 13 to 15: {'flits': 95}\n", + "Edge from 14 to 15: {'flits': 95}\n", + "Edge from 15 to 16: {'flits': 189}\n", + "Edge from 15 to 17: {'flits': 189}\n", + "Edge from 15 to 19: {'flits': 189}\n", + "Edge from 15 to 22: {'flits': 189}\n", + "Edge from 16 to 24: {'flits': 48}\n", + "Edge from 17 to 18: {'flits': 32}\n", + "Edge from 18 to 24: {'flits': 48}\n", + "Edge from 19 to 20: {'flits': 32}\n", + "Edge from 20 to 21: {'flits': 48}\n", + "Edge from 21 to 24: {'flits': 48}\n", + "Edge from 22 to 23: {'flits': 189}\n", + "Edge from 23 to 24: {'flits': 48}\n", + "Edge from 24 to 25: {'flits': 189}\n", + "Edge from 24 to 26: {'flits': 189}\n", + "Edge from 24 to 28: {'flits': 189}\n", + "Edge from 24 to 31: {'flits': 189}\n", + "Edge from 25 to 33: {'flits': 48}\n", + "Edge from 26 to 27: {'flits': 32}\n", + "Edge from 27 to 33: {'flits': 48}\n", + "Edge from 28 to 29: {'flits': 32}\n", + "Edge from 29 to 30: {'flits': 48}\n", + "Edge from 30 to 33: {'flits': 48}\n", + "Edge from 31 to 32: {'flits': 189}\n", + "Edge from 32 to 33: {'flits': 48}\n", + "Edge from 33 to 34: {'flits': 189}\n", + "Edge from 33 to 35: {'flits': 189}\n", + "Edge from 33 to 37: {'flits': 189}\n", + "Edge from 33 to 40: {'flits': 189}\n", + "Edge from 34 to 42: {'flits': 48}\n", + "Edge from 35 to 36: {'flits': 32}\n", + "Edge from 36 to 42: {'flits': 48}\n", + "Edge from 37 to 38: {'flits': 32}\n", + "Edge from 38 to 39: {'flits': 48}\n", + "Edge from 39 to 42: {'flits': 48}\n", + "Edge from 40 to 41: {'flits': 189}\n", + "Edge from 41 to 42: {'flits': 48}\n", + "Edge from 42 to 43: {'flits': 189}\n", + "Edge from 42 to 44: {'flits': 189}\n", + "Edge from 42 to 46: {'flits': 189}\n", + "Edge from 42 to 49: {'flits': 189}\n", + "Edge from 43 to 51: {'flits': 48}\n", + "Edge from 44 to 45: {'flits': 32}\n", + "Edge from 45 to 51: {'flits': 48}\n", + "Edge from 46 to 47: {'flits': 32}\n", + "Edge from 47 to 48: {'flits': 48}\n", + "Edge from 48 to 51: {'flits': 48}\n", + "Edge from 49 to 50: {'flits': 189}\n", + "Edge from 50 to 51: {'flits': 48}\n", + "Edge from 51 to 52: {'flits': 189}\n", + "Edge from 51 to 53: {'flits': 189}\n", + "Edge from 51 to 56: {'flits': 189}\n", + "Edge from 52 to 57: {'flits': 45}\n", + "Edge from 53 to 54: {'flits': 95}\n", + "Edge from 54 to 55: {'flits': 110}\n", + "Edge from 55 to 57: {'flits': 30}\n", + "Edge from 56 to 57: {'flits': 45}\n", + "Edge from 57 to 58: {'flits': 119}\n", + "Edge from 57 to 59: {'flits': 119}\n", + "Edge from 57 to 62: {'flits': 119}\n", + "Edge from 57 to 67: {'flits': 119}\n", + "Edge from 58 to 69: {'flits': 45}\n", + "Edge from 59 to 60: {'flits': 23}\n", + "Edge from 60 to 61: {'flits': 26}\n", + "Edge from 61 to 69: {'flits': 30}\n", + "Edge from 62 to 63: {'flits': 23}\n", + "Edge from 63 to 64: {'flits': 23}\n", + "Edge from 64 to 65: {'flits': 26}\n", + "Edge from 65 to 66: {'flits': 26}\n", + "Edge from 66 to 69: {'flits': 30}\n", + "Edge from 67 to 68: {'flits': 119}\n", + "Edge from 68 to 69: {'flits': 15}\n" + ] + }, { "data": { - "image/png": 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vHe+01XZJkpGvvJjGjb9ds8Ka60wrkyTJgu07ZIU1181bL78ww/mqpzMfv05tbW3OOuusbLfddllppemfIgMAAAAAQMOhUAIAAAAAAA3Y9ddfn3feeSennXZaqaP8opdffjkbbLBBysvLM2LEiKy66qqljlQv1RWnr7DRZsF2SZJWbRf43vGWbdsmSb75enxaL9Tu/459f8136yZ+PX625ePXufvuuzNy5Mgcc8wxpY4CAAAAAEA9pVACAAAAAAAN1NSpU3PyySdnxx13zBprrFHqOD/r8ccfz0YbbZTFFlssw4cPzxJLLFHqSPVWWaEwXeuW6vhtIWfM6M+/d3zs6FFJkpat22Tx5VZMRWXlD9Z8e96ozN+67WzLx8wrFos544wzsummm2adddYpdRwAAAAAAOophRIAAAAAAGigrrjiinzyySc55ZRTSh3lZ91xxx3ZYostsv766+eJJ57IggsuWOpI9VpF+fQVNjbYYuskyWN33vq944/ecUvKKyrScd0NMl/z5lmjy+/z9ssv5ON335m25uP/vJO3X34hq23YeYbzVU5nPmbe0KFD88orr+TYY48tdRQAAAAAAOqxQrForjgAAAAAADQ0EydOzFJLLZVu3brl2muvLXWcn3TZZZfloIMOys4775zrrrsujRo1KnWkeu+VUePz3rhJmZ4bQJf2OSyP33VbNthi63RcZ/28/twzeWbo/dn+rwdnt8OOSZJ89O+ROfpPW2a+Zs3TbY8/J0kG33hNamtrct6gh9O23SLTna2QZMlWTbN6u5Yz8cqYXp07d05NTU1GjBiRgokwAAAAAAD8BIUSAAAAAABogM4666yccMIJGTlyZJZYYolSx/mBYrGYE088Maeeemp69eqVCy64IGVlBq9Pj/fHT8pLn4+frrU11dW5+4p+efzugRn7xags0L5Dtth172y1V4/vrXv3X6/lxvNPz8hXXkyhUJaV19swex55fNovsdQM51tr4ZZZvGXTGT6P6fPUU0+lS5cuue+++7L11luXOg4AAAAAAPWYQgkAAAAAADQw48aNy5JLLpldd901l156aanj/EBtbW0OOOCAXHnllTnzzDPTu3dvUxZmwPgp1Xnsgy9LHeMnbbLEAmnZuLLUMeZZ3bp1y8cff5xXXnlFCQsAAAAAgJ9VUeoAAAAAAADAnHX++ednypQp6dOnT6mj/MCUKVOy66675r777ss111yTffbZp9SR5jotGlekPMXUpv6VcCrKCmnRyO2p2eXll1/OkCFDcssttyiTAAAAAADwi3ySDAAAAAAADcgXX3yRiy66KAcffHDat29f6jjfM27cuHTt2jVDhgzJoEGDlElmUG1tbe6+++78buONc/c1VyT1bEh9IcmSLZumzLSZ2ebMM8/M0ksvnR133LHUUQAAAAAAmAsolAAAAAAAQANy1llnpVAopHfv3qWO8j2fffZZNtpoo7z22mt59NFHs/XWW5c60lxj3LhxOe+887L00kune/fuqaury9YbrpPUs+JGMcmSrZqWOsY86+23386dd96Zo446KhUVpsAAAAAAAPDLfJoMAAAAAAANxMcff5xLL700Rx99dNq2bVvqONO888472WyzzVJdXZ3hw4enY8eOpY40V3j77bfTr1+/XH/99amqqsrOO++cXr16Za211kqSDP/oq3wxqSr1YU5JIcmCTRuleSO3pmaXs88+OwsvvHD22muvUkcBAAAAAGAuYUIJAAAAAAA0EKeddlqaNWuWww47rNRRpnnhhRey4YYbpkmTJhkxYoQyyS8oFot56KGHssUWW2SFFVbInXfemSOOOCIffvhhbrjhhmllkiRZaYEW9aJMknw7nWSlBVqUOsY868MPP8yNN96YI444Io0bNy51HAAAAAAA5hIKJQAAAAAA0AC8++67ufrqq3P00Udn/vnnL3WcJMkjjzyS3/3ud1lqqaUyfPjwLLbYYqWOVG9NnDgx/fv3z0orrZTNN988o0aNynXXXZcPP/wwJ510UhZeeOEfnNNmvkZZrk2zEqT9oeXaNEub+RqVOsY867zzzsv888+fv/71r6WOAgAAAADAXEShBAAAAAAAGoCTTjopCyywQA488MBSR0mS3Hbbbdlyyy3TuXPnPPbYY2nbtm2pI9VLH3zwQY466qh06NAhBx10UDp27Jhhw4blxRdfzF577fWL0yhWbNsizSrLU5hDef9XIUnzyvKs2NZ0ktll9OjRueqqq9KrV680b9681HEAAAAAAJiLKJQAAAAAAMA87l//+lduuummHHfccWnatGmp46Rfv37ZZZddsvPOO+fee+9Ns2b1Y4pGfVEsFjN8+PDssMMOWWqppTJgwID85S9/yX/+85/ceeed6dy5cwqF6auIlJcVsm771pnO5bNcoZCs0751ystKVWmZ9/Xt2zfl5eU56KCDSh0FAAAAAIC5TKFYLBZLHQIAAAAAAJh9unfvnpdeeilvv/12GjVqVLIcxWIxxx13XM4444wcccQROfvss1NW5tlX35k6dWoGDhyYvn375qWXXsryyy+fXr16ZY899vjVkydGT5yapz8ekzl5U6iQZMMObbJQs5+fosLMGz9+fBZbbLHst99+Oeecc0odBwAAAACAuUxFqQMAAAAAAACzzwsvvJC777471157bUnLJDU1Nfnb3/6Wq6++Oueee26OOOKIkmWpb0aNGpXLL788/fv3z6hRo7L55ptnyJAh2WyzzWZZ4WahZo2zYYc2GfHJmBSLme3FkrJCssGiyiSz22WXXZapU6fm0EMPLXUUAAAAAADmQiaUAAAAAADAPGzzzTfP+++/n9dffz0VFaV5ztTkyZOz8847Z/Dgwbnmmmuyxx57lCRHffPSSy+lb9++ue2221JRUZG99torPXv2zAorrDDb9hw7pTrPfTo2E6trZ9sezSvLs0771mndpHK27UEyadKkLLHEEunevXv69+9f6jgAAAAAAMyFTCgBAAAAAIB51FNPPZWHHnooAwcOLFmZZOzYsdlmm23y0ksv5b777ssWW2xRkhz1RU1NTe6999707ds3Tz31VBZbbLGcfvrp2XfffdO6devZvn/rJpXZdIkF8+ZXEzJyzMQUMmumlXx3neXaNMuKbVukvKwwC67Kz7n66qszZsyYHHnkkaWOAgAAAADAXMqEEgAAAAAAmAcVi8VstNFGmTBhQl588cWUlZXN8QyffPJJNt9883z66ad58MEHs956683xDPXF2LFjc/XVV+fiiy/Ohx9+mM6dO6dXr17ZdtttS1b2GTO5Km98OSGjJ1XNdLHku/MWatooKy3QIm3mazRrQ/Kjqqqqsswyy2SjjTbKjTfeWOo4AAAAAADMpUwoAQAAAACAedDDDz+cp556Kg888EBJyiRvvfVWunbtmmKxmOHDh2fFFVec4xnqg7feeiv9+vXL9ddfn5qamuy8887p1atX1lxzzVJHS5v5GqXTb9rmm6qavDduUt4bPyk1dd/WSn6qYPLfxyvKClmyZdMs2appmjdyy2lOuvnmm/PRRx/l6KOPLnUUAAAAAADmYiaUAAAAAADAPKZYLGadddZJo0aN8vTTT6dQKMzR/Z977rl069Yt7dq1y0MPPZQOHTrM0f1Lra6uLg8//HD69u2boUOHpl27dtl///3zt7/9Le3atSt1vJ9UVyxmQlVNxk2pztgp1Rk/tTrVtcXUFYspKxRSWV5Iy8aVad2kMq2aVKZFo4qUzeG/WyS1tbXp2LFjVlxxxQwaNKjUcQAAAAAAmIt5XBQAAAAAAMxjBg0alBdffDFPPPHEHC+TDB06NN27d8/qq6+e+++/P23atJmj+5fSN998kxtuuCH9+vXL22+/nTXXXDPXX399dtpppzRu3LjU8X5RWeHbwkjLxpVZvGWp0/BTBg0alLfffjs33HBDqaMAAAAAADCXM6EEAAAAAADmIbW1tVl11VXTvn37PPLII3N075tuuin77LNPNt988wwcODBNmzado/uXygcffJBLLrkkV111Vb7++utst912OeSQQ7LhhhvO8UIP87ZisZi11lorbdu2nePvbwAAAAAA5j0mlAAAAAAAwDzk1ltvzRtvvJFrr712ju57wQUX5PDDD88+++yTK6+8MhUV8/YtiGKxmOHDh+eiiy7KPffck/nnnz89evTIgQcemMUXX7zU8ZhHPfTQQ3n55Zfz+OOPlzoKAAAAAADzABNKAAAAAABgHlFdXZ0VVlghK6+8cu699945smexWEzv3r1z7rnn5uijj84ZZ5wxT0/lmDp1am677bb07ds3L7/8clZYYYX07Nkze+65Z5o1a1bqeMzjunTpkqqqqjzzzDPz9PsMAAAAAIA5Y95+PBgAAAAAADQg11xzTd57770MGjRojuxXXV2dHj165Prrr8+FF16YQw45ZI7sWwqff/55Lr/88vTv3z+jR4/OFltskaFDh+YPf/hDysrKSh2PBuCpp57KU089lXvvvVeZBAAAAACAWcKEEgAAAAAAmAdMnjw5yy67bLp06ZJbbrlltu83ceLE/OlPf8ojjzyS6667Lrvuuuts37MUXnzxxfTt2ze33XZbKisrs/fee+fggw/OCiusUOpoNDDdunXLRx99lFdffVWJCQAAAACAWcKEEgAAAAAAmAf0798/n3/+eU4++eTZvtdXX32VrbbaKv/85z/zwAMPZLPNNpvte85JNTU1ueeee9K3b98MHz48iy++eM4888zsu+++adWqVanj0QC9/PLLGTJkSG6++WZlEgAAAAAAZhkTSgAAAAAAYC43YcKELLXUUvnjH/+YAQMGzNa9Pvroo3Tt2jVffPFFBg8enHXWWWe27jcnjR07NldddVUuueSSfPjhh+nSpUt69eqVbbbZJhUVntFF6ey000554YUX8vbbb/u7CAAAAADALOMTZwAAAAAAmMv17ds3X3/9dY4//vjZus8bb7yRrl27pry8PE8//XSWW2652brfnPLmm2+mX79+ueGGG1JTU5NddtklvXr1yhprrFHqaJCRI0fmjjvuyOWXX65MAgAAAADALGVCCQAAAAAAzMXGjBmTpZZaKnvttVf69u072/Z55plnsuWWW6ZDhw4ZOnRo2rdvP9v2mlmTJk1K06ZNkyTFYjGFQuEn19bV1eWhhx5K375989BDD6Vdu3Y54IADst9++6Vdu3ZzKjL8on333TdDhgzJe++9l8aNG5c6DgAAAAAA85CyUgcAAAAAAABm3rnnnpvq6uoce+yxs22PBx98MJtssklWXnnlDBs2rN6VSfr165c111wzu+6667RSzU+VSYrFYkaPHp2VVlop3bp1y5dffpkbbrghH3zwQU444QRlEuqVDz/8MDfccEOOOOIIZRIAAAAAAGY5hRIAAAAAAJhLff755+nXr1969eo124oQ119/fbbddtt07do1Dz30UFq1ajVb9plZRx99dC677LL8+c9/TocOHXLSSSflwAMPzNdff53k2wLJfysUCllooYWy/fbbZ/jw4Xn++eezxx57+LI+9dL555+f+eefP3/9619LHQUAAAAAgHlQRakDAAAAAAAAM+fMM89MZWVljjzyyFl+7WKxmHPPPTe9e/dOjx49ctlll6WiovS3FaqqqtKoUaMkyccff5z77rsvPXr0yEEHHZQk6datW/bee++svvrq6dGjx49OKikWiznjjDPmaG6YUaNHj86AAQPSu3fvNG/evNRxAAAAAACYB5lQAgAAAAAAc6EPP/wwl19+eY444oi0bt16ll67rq4uRxxxRHr37p3jjz8+V1xxRcnLJNdee2023XTTHHjggenfv3+S5Msvv8wnn3ySLbbYYtq6bt26pVOnTrn//vszcuTIJD8+pQTqu759+6asrCwHH3xwqaMAAAAAADCPUigBAAAAAIC50CmnnJL5558/vXr1mqXXraqqyp577pkLL7wwF198cU455ZSSFTCKxWLuvvvuLL/88jn77LPTqVOnNGnSJAceeGCuuuqqLL300qmpqZlWHJkyZUqSZK+99sq7776b559/PokCCXOf8ePH55JLLsn++++fNm3alDoOAAAAAADzKIUSAAAAAACYy7zzzju57rrrcuyxx6ZFixaz7LrffPNNttlmm9x+++257bbbctBBB82ya8+sd955JwcccECef/75nHTSSbn44ouz4YYbZtiwYWnUqFE23njjaRNLvpuisu2226auri7//ve/U1dXV8r4MFP69++fKVOm5LDDDit1FAAAAAAA5mGlnU8PAAAAAADMsBNPPDELL7xw9t9//1l2zS+//DJbbrll3njjjQwZMiSbbLLJLLv2zCoUCtlrr73SrFmz7xVn2rVrlx133DGNGzfOn/70p/To0SPvvfdellxyyVRXV6eysjKrr756XnrppZSVlaWuri5lZZ6xxdxh0qRJueCCC/LnP/85iyyySKnjAAAAAAAwD1MoAQAAAACAuchrr72WW2+9NZdffnmaNGkyS675wQcfpGvXrhk7dmyefPLJrLnmmrPkurPCwgsvnCQpFos555xzctFFF+Xrr7/O2LFj88UXX2SttdZK586dc8ghh+Tee+9NZWVlJk2alM8++yxLL710kiiTMFe55pprMmbMmBx55JGljgIAAAAAwDyuUCwWi6UOAQAAAAAATJ9tt902r7/+et56661UVlb+6uu9/vrr6dq1a5o0aZKHHnooyyyzzCxIOetNmDAhRx99dFZaaaWst956uffee/Pggw+mW7du2XHHHbPeeutliy22yP77758XX3wxV155ZQYOHJi111671NFhulVVVWWZZZbJRhttlBtvvLHUcQAAAAAAmMcplAAAAAAAwFziH//4R9Zbb73ceOON2X333X/19YYPH56tt946iy++eIYOHTptGsjcYrfddsvUqVNz55135u67784tt9yS119/PUly6qmnZscdd0yxWEyhUChxUpg+1113XfbZZ5+8/vrr6dixY6njAAAAAAAwj1MoAQAAAACAucQf/vCHfPrpp3nttddSXl7+q6513333Zaeddsp6662Xe+65Jy1btpxFKX+9HyuB/Pex2traJMn666+fxRZbLHfeeee0NZ9++mkWXXTRORsYZoHa2tp07NgxK6ywQu65555SxwEAAAAAoAEoK3UAAAAAAADglz3xxBN59NFHc+qpp/7qMsnVV1+d7bbbLltttVWGDBlSb8ok7733Xk4//fT82LOwCoVCqqurkyRTpkzJ+eefn0aNGuWYY4753jplEuZWgwYNyttvv/2Dv9MAAAAAADC7mFACAAAAAAD1XLFYzIYbbpiqqqo8//zzP5jeMSPXOfPMM9OnT5/sv//+ufjii391OeXXKhaLGTZsWPr27Zt77703LVu2zPDhw7Piiit+73UWi8X06dMnY8aMyd13350FF1wwJ510UnbccccSpodZo1gsZq211kqbNm3y6KOPljoOAAAAAAANREWpAwAAAAAAAD9v8ODBeeaZZzJ06NCZLpPU1dXlkEMOycUXX5yTTz45xx9//Exfa1aYMmVKbrvttlx00UV59dVXs+KKK+ayyy7L7rvvnmbNmv1gfaFQyCabbJI777wzt9xySzbddNMSpIbZ4+GHH87LL7+cxx57rNRRAAAAAABoQEwoAQAAAACAeqyuri5rrbVWWrRokSeffHKmSiBTp07NXnvtlTvuuCOXXXZZ9ttvv9mQdPp89tln6d+/fy6//PJ88cUX6datWw455JBsuummJS24QClttNFGmTp1ap555hnvAwAAAAAA5hgTSgAAAAAAoB67884788orr2TYsGEz9UXzCRMmZPvtt8+wYcNyxx13ZPvtt58NKX/ZCy+8kL59+2bgwIFp1KhR9tlnnxx88MFZbrnlSpIH6ovhw4dn2LBhuffee5VJAAAAAACYo0woAQAAAACAeqqmpiYrr7xyllxyyQwZMmSGzx89enS6deuWd955J/fee2823njjWR/yZ9TU1OTuu+9O3759M2LEiCyxxBI5+OCD8+c//zmtWrWao1mgvtpyyy3z4Ycf5tVXX01ZWVmp4wAAAAAA0ICYUAIAAAAAAPXUTTfdlLfffjs333zzDJ/73nvvZbPNNss333yTYcOGZbXVVpsNCX/cmDFjMmDAgFx66aX56KOPsvHGG2fQoEHZeuutU15ePsdyQH33yiuvZPDgwbnpppuUSQAAAAAAmONMKAEAAAAAgHpi6tSp+fe//52VVlopVVVVWX755bPWWmvlrrvumqHrvPrqq9l8883TvHnzPPTQQ1lqqaVmU+Lve+ONN9K3b9/ceOONqaury6677ppevXrN0TILzE122mmnPP/88xk5cmQqKjwHDgAAAACAOcsn0wAAAAAAUE8MHDgwe+21Vzp16pR11lknH374YQYPHjxD13jyySezzTbbZNlll83gwYOz0EILzaa036qrq8uQIUPSt2/fPPLII1lkkUVy7LHHZr/99suCCy44W/eGudnIkSNzxx13pH///sokAAAAAACUhE+nAQAAAACgnhg/fnwKhUKeeeaZDB8+PIssskimTJky3efffffd2XXXXdOpU6cMGjQoLVq0mG1ZJ0yYkOuvvz79+vXLO++8k3XWWSc33XRTdtxxxzRq1Gi27QvzirPPPjsLL7xw9tprr1JHAQAAAACggSordQAAAAAAAOBbNTU1KSsrS21tbZJk9OjRWWuttdKzZ89fPPeKK67IjjvumD/+8Y958MEHZ1uZ5L333sthhx2WDh065JBDDskaa6yRESNG5B//+Ed22203ZRL4CaNHj07//v3z1Vdf5aOPPsqNN96Yww8/PE2aNCl1NAAAAAAAGiiFEgAAAAAAqCeqq6u/9+u6urok+dmSRrFYzCmnnJK//e1vOfDAA3PLLbekcePGszRXsVjM3//+92y33XZZZpllcv311+eAAw7Ie++9l4EDB2b99ddPoVCYpXvCvObee+/NAQcckA4dOmTbbbdN06ZNs99++5U6FgAAAAAADZhCCQAAAAAA1BM1NTUpFotJkvLy8jRt2jS33nprzjvvvCRJbW1t/vnPf05bX1tbm4MOOignnnhiTj/99PTt2zdlZbPuo/8pU6bk2muvzRprrJHf/e53GTlyZPr375+PPvooZ555Zn7zm9/Msr1gXldeXp7k2/fVyy+/nAkTJuSwww7Lu+++W+JkAAAAAAA0VBWlDgAAAAAAAPOSumIxE6bWZOzU6oybUp1xU6tTU1tMXbGYskIhFeWFtGpcmVZNKtO6cWVaNK5I2f9N9/j666+nTSVZc801M3DgwCy55JLTrn3RRRfliCOOyFVXXZXdd989u+++e+6+++4MGDAgf/nLX2bZa/j000/Tv3//XHHFFfniiy+y1VZb5bzzzssmm2xiEgnMpMrKyu/9uq6uLgMGDMhjjz2W//znPyVKBQAAAABAQ6ZQAgAAAAAAs8A3VTV5b9ykvDd+Umrqvp0yUkhS/JG1YydXTzteUVbIki2bZslWTfPOO+8kSQ455JCcc8453/sCerFYTP/+/ZMkPXr0SN++ffPOO+/k7rvvzrbbbjtLXsPzzz+fvn37ZuDAgWnSpEn22WefHHzwwVl22WVnyfWhIfvfQsl3U4guvvjiEiUCAAAAAKChKxSLxR+7lwUAAAAAAEyHMZOr8saXEzJ6UtVPFkh+yXfntaxIaj99L5t13uAHa55++ul06tTpe8cuueSSHHjggTMTe5rq6uoMGjQoF110UZ555pksueSS6dmzZ/bZZ5+0bNnyV10b+P/uuuuu7LDDDkmSsrKyrLjiirnvvvuy1FJLlTgZAAAAAAANVVmpAwAAAAAAwNyotq6Y17/4On//8Kt8MakqycyVSf77vK9rkm8WWjKvf/F1auu+f7Wrrroq5eXl035dVlaWY445Jq+//vpM7fnVV1/lrLPOylJLLZWddtopTZo0yT333JN33nknhxxyiDIJzGJ1dXXT/nv33XfPc88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"text/plain": [ "
" ] @@ -1247,9 +1445,9 @@ "Gurobi Optimizer version 12.0.1 build v12.0.1rc0 (linux64 - \"Ubuntu 24.04.2 LTS\")\n", "Copyright (c) 2025, Gurobi Optimization, LLC\n", "\n", - "Read LP format model from file /tmp/e238715edea14657bc0028d36a114def-pulp.lp\n", - "Reading time = 0.08 seconds\n", - "OBJ: 123791 rows, 45084 columns, 334023 nonzeros\n", + "Read LP format model from file /tmp/112d441dab3c4dc894cc2bf3321a97f9-pulp.lp\n", + "Reading time = 0.07 seconds\n", + "OBJ: 123791 rows, 45084 columns, 334004 nonzeros\n", "\n", "Using Gurobi shared library /home/sfischer/Software/gurobi12.0.1_linux64/gurobi1201/linux64/lib/libgurobi.so.12.0.1\n", "\n", @@ -1260,57 +1458,47 @@ "TimeLimit 1200\n", "Threads 20\n", "\n", - "Optimize a model with 123791 rows, 45084 columns and 334023 nonzeros\n", - "Model fingerprint: 0x755eceea\n", - "Variable types: 2689 continuous, 42395 integer (41345 binary)\n", + "Optimize a model with 123791 rows, 45084 columns and 334004 nonzeros\n", + "Model fingerprint: 0xb0ed6e36\n", + "Variable types: 2689 continuous, 42395 integer (41835 binary)\n", "Coefficient statistics:\n", - " Matrix range [1e+00, 1e+04]\n", + " Matrix range [1e+00, 2e+05]\n", " Objective range [1e+00, 1e+00]\n", " Bounds range [1e+00, 1e+00]\n", - " RHS range [1e+00, 2e+04]\n", + " RHS range [1e+00, 5e+05]\n", "Presolve removed 121060 rows and 44745 columns\n", "Presolve time: 0.02s\n", "Presolved: 2731 rows, 339 columns, 5778 nonzeros\n", "Variable types: 189 continuous, 150 integer (150 binary)\n", - "Found heuristic solution: objective 647.0000000\n", + "Found heuristic solution: objective 296.0000000\n", "Performing another presolve...\n", - "Presolve removed 70 rows and 70 columns\n", + "Presolve removed 1064 rows and 91 columns\n", "Presolve time: 0.00s\n", "\n", - "Root relaxation: objective 5.510000e+02, 126 iterations, 0.00 seconds (0.01 work units)\n", + "Root relaxation: objective 2.430000e+02, 152 iterations, 0.00 seconds (0.00 work units)\n", "\n", " Nodes | Current Node | Objective Bounds | Work\n", " Expl Unexpl | Obj Depth IntInf | Incumbent BestBd Gap | It/Node Time\n", "\n", - " 0 0 551.00000 0 4 647.00000 551.00000 14.8% - 0s\n", - " 0 0 629.00000 0 5 647.00000 629.00000 2.78% - 0s\n", - " 0 0 645.00000 0 7 647.00000 645.00000 0.31% - 0s\n", - " 0 0 646.00000 0 7 647.00000 646.00000 0.15% - 0s\n", - " 0 0 646.00000 0 7 647.00000 646.00000 0.15% - 0s\n", - " 0 0 646.00000 0 7 647.00000 646.00000 0.15% - 0s\n", + "* 0 0 0 243.0000000 243.00000 0.00% - 0s\n", "\n", - "Cutting planes:\n", - " Gomory: 2\n", - " Implied bound: 1\n", - " MIR: 8\n", - "\n", - "Explored 1 nodes (238 simplex iterations) in 0.13 seconds (0.22 work units)\n", + "Explored 1 nodes (347 simplex iterations) in 0.05 seconds (0.14 work units)\n", "Thread count was 20 (of 28 available processors)\n", "\n", - "Solution count 1: 647 \n", + "Solution count 2: 243 296 \n", "\n", "Optimal solution found (tolerance 1.00e-04)\n", - "Best objective 6.470000000000e+02, best bound 6.470000000000e+02, gap 0.0000%\n", + "Best objective 2.430000000000e+02, best bound 2.430000000000e+02, gap 0.0000%\n", "\n", - "Wrote result file '/tmp/e238715edea14657bc0028d36a114def-pulp.sol'\n", + "Wrote result file '/tmp/112d441dab3c4dc894cc2bf3321a97f9-pulp.sol'\n", "\n", - "objective: 647.0\n", - "[(0, 16), (0, 20), (16, 20), (16, 24), (20, 24), (24, 28), (24, 32), (28, 32), (32, 36), (32, 40), (36, 40), (40, 44), (40, 48), (44, 48), (48, 52), (48, 56), (52, 56), (56, 60), (56, 64), (56, 68), (60, 64), (60, 68), (64, 68)]\n" + "objective: 243.0\n", + "[(0, 4), (4, 10), (4, 11), (11, 17), (10, 11), (17, 35), (35, 53), (53, 62), (62, 53)]\n" ] }, { "data": { - "image/png": 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UqWc/zmgwnxwyJF00zq/fmhAcxHsdmQqFgm655Ra1t7erqalJDQ0Ndo8EAAAAAAAGGEFfAAAAAECfmKaplpaWqoHejo6O8rr6+vqq7byhUEgOh8PGHQAAAGCoKBaLvQZ0qwV6c7lcxXkMw6gI6X6yVfeTwV2/3z8qH5e25kv61zdTg36/3zg/opBneIekh4qOjg5t3bpVPp9PmzdvltfrtXskAAAAAAAwgAj6AgAAAACqSqfTVcO8yWRSpmlKktxudznM2z3QG4vFeLIZAABglCkUCjVbdmuFdwuFQsV5DMPoU8tuIBCQz+eTYRg27Hp42vfrdr2WyA1Kq68haW7Mq2sm1w/CvY0eJ06c0Pbt2zV58mStX79+VIbWAQAAAAAYLQj6AgAAAMAoViwWlUqlegR5u44zmUx5XSgU6hHi7TpuaGggUAEAADDCWJalfD5fM6hb67hYLFacy+l01gzo1rrd6/XyGHOA5UqmfvTLlDqL1sCGfS1TPof0jTlxeZ0EUfvbe++9p9tvv12LFi3SihUr7B4HAAAAAAAMEIK+AAAAADDCWZaljo6Oimbe5uZmtbS0qOvHQq/X2yPM2xXojUajcrvdNu8CAAAAn4ZlWcrlcn1q2U2n0+V3cOjO5XL1qWU3EAjI7XYT2h2ijrTlddd7bQN+P/lf/FSfv+Bcfe5zn+PvwgB48cUX9eCDD+rqq6/W0qVL7R4HAAAAAAAMAJfdAwAAAAAA+kehUKho5e36yOVykk69DXIkElE8HtfMmTN7tPMGg0GeeAcAABjCLMtSNput2bJbLbibyWSqhnbdbnePQG5dXZ3Gjh3ba3CXF3+NLFMbPLryrKAeOdY5YPdx5cSA2mefoyeeeEIffvihvvjFL8rn8w3Y/Y1GCxcuVCKR0P79+xUOhzVjxgy7RwIAAAAAAP2MRl8AAAAAGEYsy1Jra2vVQG9ra2t5XSAQ6NHK2/XfSCQip9Np4w4AAAAgSaZp1mzTrXZ7JpNRJpNRtUv6Xq+3IpR7usZdl4seEJzy4smMHjnWKUNSfzxh1HWeq84K6sIxfknSO++8oz179sjv92vt2rVqbGzsh3tCF8uytGvXLr333nvavHmzxo8fb/dIAAAAAACgHxH0BQAAAIAhKJfLlUO8n2znLRaLkiSn06loNFo10Ov3+23eAQAAwOhRKpUqQrmnC+5ms9mq5/L5fGcc1u065oVc+KyOtOX10Pvt6ixanynsa0gKugytPLteUxs8PX4tlUpp165dam5u1qpVqzRv3rzPNDN6KhQKuuWWW9Te3q6mpiY1NDTYPRIAAAAAAOgnBH0BAAAAwCamaaqlpaVqoLejo6O8rq6urhzi7R7oDYfDcjgcNu4AAABg5CkWi1XbdHs7zuVyVc9VK6Db2+08voNdsiVTT3zYqVcTuT63+3atnxfz6vKJQXmd1f8eFwoF7d27V6+88ooWLlyoq6++mnbpftTR0aGtW7fK5/Np8+bN8nq9do8EAAAAAAD6AUFfAAAAABhg6XS6Isjb3NysZDIp0zQlSW63uxzk/WSglydnAQAAPp1CodCnlt10Oq1CoVBxHsMw+tyy6/P5CO1iWGrNl/RKc1YvN2eVLZ16Cskhyey2pvvnPqehBXGf5sd9CnnOrF36pZde0t69e9XY2Kg1a9YoFAr15xZGtRMnTmjbtm06++yztX79er4OAQAAAAAwAhD0BQAAAIB+UCqVlEwmqwZ6M5lMeV0oFKraztvQ0CDDMGzcAQAAwNBlWVaP0O6ZBneLxWLFuRwOR59adgOBgLxeL4/VMOqULEsnMyUdTxd1PF1UZ9FU0bTkchgKuhxqDLjUGHBpjN8p56f49/HRRx9p165dyufzuvHGGzVt2rQB2MXo9O6772rnzp1avHixrrnmGrvHAQAAAAAAnxFBXwAAAAA4Q5ZlqaOjo0eIt+s4lUqp68crr9fbI8TbdRyNRuV2u23eBQAAgL0sy1Iul+tTy24mk1GpVKo4l8vlqtqm21tw1+PxENoFhoh0Oq17771X7777ri677DJ97nOf499nP3nhhRf00EMP6eqrr9bSpUvtHgcAAAAAAHwGBH0BAAAA4BMKhULVMG8ikVAul5N06u2bI5FIRTNvPB5XMBjkyWkAADAqWJalbDbbp5bdTCYj0zQrzuV2u/vUshsIBHgRFTACmKapp59+Wk899ZSmT5+uL37xi/L5fHaPNSI8/PDDevbZZ7V+/XpNnz7d7nEAAAAAAMCnRNAXAAAAwKhkWZba2trKQd7ugd7W1tbyOr/fX9HMG4vFFI1G5XQ6bdwBAABA/zJNU5lMpmZYt1pwN5PJqNolZo/HUzWg21tw1+Vy2bBrAEPFO++8oz179sjv92vt2rVqbGy0e6Rhz7Is7dq1S++99542b96s8ePH2z0SAAAAAAD4FAj6AgAAABjRcrlcRZC367hYLEqSnE6notFoRZg3FospEAjYvAMAAIC+K5VKVdt0a7XsptNpZbPZqufy+XwVodzTHfOCKACfRiqV0q5du9Tc3KxVq1Zp3rx5do807BUKBd1yyy1qb29XU1OTGhoa7B4JAAAAAAD0EUFfAAAAAMOeaZpqaWmpGujt6Ogor6urq6vazhsOh+VwOGzcAQAAQG3FYrFqq25vwd1cLlf1XNVCub217Pr9fh4nARhUhUJBe/fu1SuvvKKFCxfq6quvpvH7M2pvb9fWrVsVCAS0efNmeTweu0cCAAAAAAB9QNAXAAAAwLCRTqcrWnkTiYSSyaRKpZIkyeVyVbTydh17vV6bdwAAAEa7QqHQp5bdTCajfD5fcR7DMGq26dYK7vp8PkK7AIaNl156SXv37lVjY6PWrFmjUChk90jD2scff6zt27fr7LPP1vr16/l+AAAAAADAMELQFwAAAMCQUiqVlEwmq7bzZjKZ8rpQKFQR5I3H42poaJBhGDbuAAAAjAaWZZVDu30J7haLxYpzORyOPrXsBgIBeb1eHvMAGPE++ugj7dq1S/l8XqtXr9Y555xj90jD2rvvvqudO3dq8eLFuuaaa+weBwAAAAAAnCGCvgAAAAAGnWVZ6uzsLAd5uwd6U6mUun5M8Xg8VZt5Y7GY3G63zbsAAAAjhWVZyuVyNcO6tY673lGgO6fTWTWg21tw1+PxENoFgBrS6bT27Nmjw4cP67LLLtOll17K18zP4IUXXtBDDz2kq6++WkuXLrV7HAAAAAAAcAYI+gIAAAAYMIVCQclksqKZN5FIKJfLSTr1ttORSKRqO28wGOQJXAAA0CeWZSmbzfapZTeTycg0zYpzud3uilDu6YK7brebxy8A0M9M09RTTz2lp59+WtOnT9cXv/hF+Xw+u8cath5++GE9++yzWr9+vaZPn273OAAAAAAA4DQI+gIAAAD4TCzLUltbW0Uzb3Nzs1pbW8vr/H5/1XbeaDQqp9Np4w4AAMBQZZpmObRbrVm36/NPtu1Wu+Tp8Xj61LLr9/t5BwEAGGLeeecd7dmzR36/X2vXrlVjY6PdIw1Lpmlq9+7deu+997R582aNHz/e7pEAAAAAAEAvCPoCAAAAOCO5XK4izNv1USgUJEkOh0PRaLRqoDcQCNi8AwAAYKdSqVQRyj1dy24mk6l6Lp/P16eWXb/fL5fLNcg7BgAMhFQqpV27dqm5uVmrVq3SvHnz7B5pWMrn87r11lvV3t6upqYmNTQ02D0SAAAAAACogaAvAAAAgDLTNNXS0lK1nbejo6O8rq6uriLIG4/HFQ6H5XA4bNwBAAAYDMVisaJF93TB3VwuV/Vc1UK6tY67PufxBgCMboVCQXv37tUrr7yiRYsWafny5byg41Nob2/X1q1bFQgEtHnzZnk8HrtHAgAAAAAAVRD0BQAAAEahTCZTDvJ2D/Qmk0mVSiVJksvlKod5uwd6Y7GYfD6fzTsAAAD9pVAo1GzZrXWcz+crzmMYRp9adgOBgHw+H6FdAMCnYlmWXnrpJe3bt0+NjY1as2aNQqGQ3WMNOx9//LG2b9+uKVOmaN26dXxfBgAAAABgCCLoCwAAAIxQpVJJqVSqaqA3nU6X14VCoartvA0NDTIMw8YdAACAvrAsS4VCoWqbbq2W3Uwmo0KhUHEuh8NRs1m3VnDX5/Px2AEAMOg++ugj7dq1S4VCQTfeeKPOOeccu0cadt59913t3LlTixcv1jXXXGP3OAAAAAAA4BMI+gIAAADDmGVZ6uzsrAjyNjc3K5VKqevhvsfj6dHI2/3Y7XbbvAsAAPBJlmUpn8/XbNmtFd7taubvzul09qllNxAIyOPxENoFAAwb6XRae/bs0eHDh3XZZZfp0ksv5ftYH73wwgt66KGHdPXVV2vp0qV2jwMAAAAAALoh6AsAAAAMA4VCQclkskeYtyvQm8vlJJ16u+xwOFw10FtXV8eTnAAA2MSyLGWz2ZpB3VrHpmlWnMvlclUN6PYW3HW73TwOAACMeKZp6qmnntLTTz+tGTNm6IYbbpDP57N7rGHlwIEDeu6557R+/XpNnz7d7nEAAAAAAMC/I+gLAAAADBGWZamtra1qO29ra2t5nd/vr2jljcfjikQicrlcNu4AAICRzzRNZbPZXlt2q91W7RKcx+OpCOWe7pgmfgAAenfo0CHde++98vv9WrduncaNG2f3SMOGaZravXu33nvvPW3ZskWNjY12jwQAAAAAAETQFwAAABh0uVyuR4i3e0NvoVCQJDkcDkWjUcXj8fJ/uwK9gUDA5h0AADAymKbZ55bdTCZT9Vxer7dPLbt+v58X6AAAMEBSqZR27dql5uZmrVq1SvPmzbN7pGEjn8/rlltuUUdHh5qamtTQ0GD3SAAAAAAAjHoEfQEAAIABYJqmWltby0He7oHe9vb28rq6uroerbxd/w2Hw3I4HDbuAACA4aVUKp02oPvJQG82m616Lr/fXzWkWyu46/f75XQ6B3nHAACgN4VCQXv37tUrr7yiRYsWafny5bzI5gy1t7dr69atCgQC2rx5szwej90jAQAAAAAwqhH0BQAAAD6DTCZTEeRtbm5WMplUqVSSJLlcrnKYt3ugNxaLyefz2bwDAACGnmKxWLNlt1Z4N5/PV5zHMIyKdt3eWnYDgYB8Ph8vtgEAYISwLEsvvfSS9u3bp8bGRq1Zs0ahUMjusYaFjz/+WNu3b9eUKVO0bt06Hh8BAAAAAGAjgr4AAADAaZRKJaVSqR7tvMlkUs3NzUqn0+V1DQ0NPUK8XcehUEiGYdi4AwAA7GFZlgqFQs2gbq3jQqFQcS6Hw9EjlHsmwV2fz8f3YAAAoA8//FC7d+9WoVDQjTfeqHPOOcfukYaFd999Vzt37tTixYt1zTXX2D0OAAAAAACjFkFfAAAAQKeCSJ2dnVXbeVOplLoeNns8nopW3ng8rmg0yltZAgBGNMuylM/n+9Sym8lkVCwWK87ldDorQrmnO/Z6vYR2AQDAp5ZOp7Vnzx4dPnxYl112mS699FIeW5yB559/Xnv37tU111yjJUuW2D0OAAAAAACjEkFfAAAAjCrFYrFHiLf7cS6Xk3Tqbb7D4XCPMG9XoLeuro4nAgEAw55lWcrlcjVbdmsFd03TrDiXy+XqU8tuIBCQ2+3m+ykAABh0pmnqySef1M9+9jPNmDFDN9xwg3w+n91jDXkHDhzQc889p/Xr12v69Ol2jwMAAAAAwKhD0BcAAAAjjmVZam9vLwd5uwd6W1payuv8fn/Vdt5IJCKXy2XfBgAA6APLsqqGcntr2U2n06p2Scjj8VRt0+0tuOt2u23YNQAAwKd36NAh3XvvvfL7/Vq3bp3GjRtn90hDmmma2rVrlw4fPqwtW7aosbHR7pEAAAAAABhVCPoCAABg2Mrn81WbeROJhAqFgiTJ4XAoGo32CPJ2/TcQCNi8AwAAejJNs2oo93TB3Wq8Xm9FKLfWcdfnvNAFAACMFqlUSrt27VJzc7NWrVqlefPm2T3SkJbP53XLLbeoo6NDTU1NamhosHskAAAAAABGDYK+AAAAGNJM01Rra2vVdt729vbyumAwWNHMG4vFFIlE5HA4bNwBAGC0KpVKfW7ZzWazVc/l8/n61LLr9/vldDoHeccAAADDS6FQ0N69e/XKK69o0aJFWr58OS986kV7e7u2bt2qQCCgzZs3y+Px2D0SAAAAAACjAkFfAAAADAmZTKZqO28ymVSpVJIkuVwuRaPRqoFen89n8w4AACNZsVjsU8tuOp1WPp+vOI9hGPL7/WfUsts90MuLVgAAAAaGZVl66aWXtG/fPjU2NmrNmjUKhUJ2jzVkffzxx9q+fbumTJmidevW8TgVAAAAAIBBQNAXAAAAg6ZUKimVSlUN9KbT6fK6hoaGqmHeUCgkwzBs3AEAYCQoFApVg7q9BXcLhULFeQzD6FPLbiAQkM/n43sZAADAEPThhx9q9+7dKhQKuvHGG3XOOefYPdKQ9e6772rnzp1asmSJrr76arvHAQAAAABgxCPoCwAAgH5lWZbS6XQ5yNs90JtKpWSapiTJ4/H0CPF2HUejUd76EQBwRizLUj6f71PLbiaTUbFYrDiX0+ms2aZbK7jr9XoJ7QIAAIwg6XRae/bs0eHDh3XZZZfp0ksv5fFeDc8//7z27t2ra665RkuWLLF7HAAAAAAARjSCvgAAAPhUisViOcDbvZk3kUgom81KOtV0GA6HK5p54/G46urqeLIMAFBmWZZyuVyfWnbT6XT5BSTduVyuilBureOuzz0eD9+XAAAAINM09eSTT+pnP/uZZsyYoRtuuEE+n8/usYakAwcOyO126/LLL7d7FAAAAAAARjSCvgAAAKjJsiy1t7dXbedtaWkpr/P5fBXNvLFYTNFoVC6Xy74NAABsYVmWMplMzbButeBuJpOpGtp1u919atkNBAJyu9027BoAAAAjyaFDh3TvvfcqEAho7dq1GjdunN0jDTmWZfFiOQAAAAAABgFBXwAAACifz1cEebuOC4WCJMnhcCgajZbDvN0DvYFAgCd2AGCEMk2zZpturduz2ayqXW7wer01Q7q1Gnd5wQgAAADskkqldNdddymRSOjaa6/V3Llz7R5p2LAsS5ZlyeFw2D0KAAAAAADDHkFfAACAUcI0TbW2tlYN9La3t5fXBYPBqu28kUiEJ2cAYJgrlUpVW3V7C+5ms9mq5/L5fL0GdKsFep1O5yDvGAAAAPhsCoWCHnroIb366qtatGiRrr76ah7X9lE2m5XP57N7DAAAAAAAhi2CvgAAACNMNpstB3m7B3oTiYRKpZIkyeVyKRqNVg308sQLgNEgn8/rxIkTOnnypDo6OnT++ecrGo3q0Ucf1X333adkMqkTJ07o61//ur70pS8NyVbZYrHYp5bdTCajXC5X9VzVArq1mne7jnnxBwAAAEYLy7L04osvav/+/WpsbNTatWvV0NBg91hDTqlU0jvvvKOnn35apmnqiSee0Lx58/T0008rFArprrvusntEAAAAAACGpaH3TCUAAABOq1QqKZVKVQ3zdnZ2ltc1NDQoFotp8uTJuvDCC8uB3lAoJMMwbNwBANjrBz/4gX7yk5+osbFR+XxeF198sf70T/9UoVBIF1xwgSZOnKi6ujr9zd/8jTKZjL7yla/IsqwB+9pZKBT61LKbTqdVKBQqzmMYRkUod9y4cb227Pp8PkK7AAAAQC8Mw9CiRYs0fvx47dq1S//n//wfrV69WlOnTrV7tCHl8OHDWr9+vaZMmaJvfetbmjVrlj744AOlUikVi0WdOHFCY8eOtXtMAAAAAACGHRp9AQAAhijLspROp6u286ZSKZmmKUnyeDzlVt7uzbyxWEwej8fmXQDA0PTyyy9r0qRJisfjamtr0+rVq7Vy5Ur90R/9UY91n//853XppZfqb/7mb84o6GtZlvL5fM2wbq3jYrFYcS6Hw9Gnlt1AICCv18sLOQAAAIABlE6ndc899+jIkSO6/PLLdckll/AYvJu//du/1WOPPabHH39cr7zyir797W/r0ksv1de//nVNnjxZr732mubOnWv3mAAAAAAADCs0+gIAANisWCwqmUz2CPJ2HWez2fK6cDiseDyuc889t0egt76+nieUAKCPFixYUD42DEORSKQctn399dd188036+GHH9aSJUv07W9/u7yuS1tbm55++umqgd5SqVRxf06ns0cgNxAIKBaLVYR1ux97PB6+vgMAAABDTCAQ0Je//GU9+eSTeuyxx3Ts2DHdcMMN8vl8do9mq64XRv7Zn/2Zjh07poULF6qhoUErVqzQ7/3e78nn8+kb3/iG9uzZox/96Ee67rrr7B4ZAAAAAIBhg0ZfAACAQWBZltrb2yuaeZubm9XS0lJe5/P5ejTydh1Ho1G5XLxGCwAGwrZt23TPPffoX/7lXzRlyhR9/PHHeuutt5RKpXTgwAE1NjbqL//yL3s0+ra2turOO++sGtCt1rrrdrsJ7QIAAAAjzNtvv617771XwWBQa9eu1bhx4+weaUj4+7//e/33//7fNXfuXD355JNKJBL62te+prPOOkvTpk3TLbfcom3btunCCy+0e1QAAAAAAIYFgr4AAAD9KJ/PV7Tydn3k83lJp96KPRKJVA30BgIBgmAAcBqmaSqTyVRt0/3kcWNjo1asWFHzXL/4xS/03e9+V1/96le1cePGHmFeSTpw4ID+7u/+Tg888IAaGhoGY3sAAAAAhpFkMqldu3YpkUjo2muv1dy5c+0eyVY//elP9b3vfU9/+Id/qGeeeUZ//Md/rDfeeEM33XST/vmf/1nXX3+97rrrLt188826//77+TkLAAAAAIAzQNAXAACgj0zTVGtra9Uwb1tbW3ldMBisCPLG43GFw2E5nU4bdwAAQ0epVCqHcmsFdz95ezabrXoun89X0aY7YcIELVmypOr6Dz74QH/yJ3+iZcuW6Q/+4A/K83T/Gn3nnXfqL/7iL3To0KGKEDAAAAAASFKhUNBDDz2kV199VYsWLdLVV189qq/9vP7665ozZ45yuZy8Xq8kaceOHdq2bZuefPJJuVwuPf7445o2bZrOPvtsm6cFAAAAAGDoI+gLAABQQzabLQd5PxnoLZVKkiSn01kO834y0Ovz+WzeAQAMrmKxeEYtu92Pc7lc1XN1BXa7B3drHXd97nA4znjWtrY2fe1rX9OHH36oH/3oR3r55Zfl8/n0+c9/Xt/85jfldruVTCZVKpX0ne98R5dddll//TEBAAAAGIEsy9KLL76o/fv3q7GxUWvXrh3VbbV33nmnnn32Wf3gBz9QoVCQ2+3Wxo0btWHDBl177bV2jwcAAAAAwLBC0BcAAIxqpVJJLS0tVQO9nZ2d5XX19fXlEG/3QG8oFOpTsAwAhotCodCnlt1MJqN8Pl9xHsMwqoZyewvu+ny+Af/a+sorr2jZsmW64oorJEkNDQ2aOXOm/uRP/kS33XabwuGwxowZo7POOktTp04d0FkAAAAAjBwffvihdu3apWKxqNWrV4/anydSqZSWL1+u73znO1q9erUk6fOf/7z+5E/+RNdcc43N0wEAAAAAMLwQ9AUAACOeZVlKp9MVQd7m5malUimZpilJcrvdVcO8sVhMHo/H5l0AwKdjWVY5tFutWbdWeLdYLFacy+Fw9Lll1+fzyTAMG3YOAAAAAPZIp9O65557dOTIEV1++eW65JJLRuXPRb/85S+1YcMG3XjjjXr44YfV3NysF154QXV1dXaPBgAAAADAsELQFwAAjBjFYlHJZLJqoDebzZbXhcPhqoHe+vr6UfmkC4Dhw7Is5XK5mkHdWselUqniXE6nsyKUW6t5t+vD4/HwdRIAAAAAzoBpmnryySf1s5/9TDNmzNANN9wgn89n91iD7uDBg3r77bf1q1/9Sn/1V38lj8cj0zR5hywAAAAAAPqAoC8AABhWLMtSe3t71TBva2uruh7a+Hy+ilbeeDyuaDQql8tl8y4A4NTXs2w226eW3UwmU24h787tdtcM6da63e12E9oFAAAAgAH29ttv695771U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"text/plain": [ "
" ] @@ -1335,6 +1523,11 @@ " mesh_y=4\n", " router_num=mesh_x*mesh_y\n", "\n", + " noc_factor=param1\n", + " comp_factor=param2\n", + " # noc_factor=0.5\n", + " # comp_factor=0.1\n", + "\n", "\n", "\n", " # ======================================================================\n", @@ -1345,6 +1538,23 @@ " # G =CreateNetworkXGraphManuelParallel()\n", "\n", " G=CreateNetworkXGraph()\n", + "\n", + "\n", + " for node, atr in G.nodes(data=True):\n", + " G.nodes[node]['delay_send'] = math.ceil(atr['delay_send'] * noc_factor)\n", + " G.nodes[node]['delay_comp'] = math.ceil(atr['delay_comp'] * comp_factor)\n", + "\n", + "\n", + " for u, v, attrs in G.edges(data=True):\n", + " print(f\"Edge from {u} to {v}: {attrs}\")\n", + "\n", + "\n", + " for u, v, attrs in G.edges(data=True):\n", + " G[u][v]['flits'] = math.ceil(attrs['flits'] * noc_factor)\n", + "\n", + " for u, v, attrs in G.edges(data=True):\n", + " print(f\"Edge from {u} to {v}: {attrs}\")\n", + "\n", " # Draw the graph\n", " plt.figure(figsize=(32, 14))\n", " pos = nx.spring_layout(G) # Layout for positioning\n", @@ -1407,20 +1617,19 @@ " # task_map[task][f\"t_map_{router}\"].setInitialValue(0)\n", " # task_map[task][f\"t_map_{router}\"].fixValue() \n", "\n", + " # 5x optimal mapping\n", + " manual_task_groups = [\n", + " [0, 1, 2, 3],\n", + " [10, 8, 9],\n", + " [11, 12, 13, 14, 15, 16, 7],\n", + " [17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34],\n", + " [35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52],\n", + " [4, 5, 6],\n", + " [53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 66, 67, 68, 69],\n", + " [62, 63, 64]\n", + " ]\n", "\n", - " # manual_task_groups = [\n", - " # list(range(0, 16)),\n", - " # # list(range(3, 6)),\n", - " # # list(range(6, 13)),\n", - " # # list(range(13, 16)),\n", - " # # list(range(16, 25)),\n", - " # # list(range(25, 34)),\n", - " # # list(range(34, 43)),\n", - " # # list(range(43, 52)),\n", - " # # list(range(52, 58)),\n", - " # # list(range(58, 70)),\n", "\n", - " # ]\n", "\n", " # manual_task_groups = [\n", " # list(range(0, 16)), # 16 elements: 0-15\n", @@ -1440,16 +1649,16 @@ " # list(range(68, 70)), # 2-4 elements: 68-71 (adjust if you only want up to 70: use range(68, 71))\n", " # ]\n", "\n", - " # # Assign each group to a router index\n", - " # for router, task_group in enumerate(manual_task_groups):\n", - " # for task in G.nodes:\n", - " # if task in task_group:\n", - " # task_map[task][f\"t_map_{router}\"].setInitialValue(1)\n", - " # task_map[task][f\"t_map_{router}\"].fixValue()\n", - " # else:\n", - " # task_map[task][f\"t_map_{router}\"].setInitialValue(0)\n", - " # task_map[task][f\"t_map_{router}\"].fixValue()\n", - " # ======================================================================\n", + " # Assign each group to a router index\n", + " for router, task_group in enumerate(manual_task_groups):\n", + " for task in G.nodes:\n", + " if task in task_group:\n", + " task_map[task][f\"t_map_{router}\"].setInitialValue(1)\n", + " task_map[task][f\"t_map_{router}\"].fixValue()\n", + " else:\n", + " task_map[task][f\"t_map_{router}\"].setInitialValue(0)\n", + " task_map[task][f\"t_map_{router}\"].fixValue()\n", + " # # ======================================================================\n", " # Number of tasks per router\n", " # ======================================================================\n", " # for router in range(router_num):\n", @@ -1530,12 +1739,13 @@ "\n", "\n", " # remove memory delay as it is saved in PE\n", - " # task_constraints.append(tR0_start + t_comp + t_mem <= tR0_end)\n", - " task_constraints.append(task_vars[task][\"t_start\"] + task_vars[task][\"t_comp\"] <= task_vars[task][\"t_end\"])\n", - " # task_constraints.append(t_start + t_comp <= t_end)\n", + " # task_constraints.append(task_vars[task][\"t_start\"] + task_vars[task][\"t_comp\"] <= task_vars[task][\"t_end\"])\n", + " task_constraints.append(task_vars[task][\"t_start\"] + task_vars[task][\"t_comp\"] +task_vars[task]['t_send'] <= task_vars[task][\"t_end\"])\n", + "\n", " # Predecessor constraints\n", " for pre in predecessors:\n", - " task_constraints.append(task_vars[pre]['t_end'] + task_vars[pre]['t_send'] <= task_vars[task][\"t_start\"])\n", + " # task_constraints.append(task_vars[pre]['t_end'] + task_vars[pre]['t_send'] <= task_vars[task][\"t_start\"])\n", + " task_constraints.append(task_vars[pre]['t_end']<= task_vars[task][\"t_start\"])\n", " # Constraint for first task\n", " if task==0:\n", " # remove memory delay as it is saved in PE\n", @@ -1552,7 +1762,7 @@ " # task_constraints.append(t_send_total<=110)\n", " task_constraints.append(t_send_total >= lpSum(t_send_list))\n", "\n", - " M = 1e4\n", + " M = 25e4\n", "\n", " # ======================================================================\n", " # If the successor of a task is in the same PE the sending delay is 0/the normal sending delay condition does not apply\n", @@ -1691,7 +1901,7 @@ "\n", " # task_constraints.append(PE_delay[router] <= 20615) #all layers inception \n", "\n", - " # task_constraints.append(PE_delay[router] <= 280) \n", + " # task_constraints.append(PE_delay[router] <= 243) \n", " \n", "\n", "\n", @@ -1711,7 +1921,6 @@ " # Objective function\n", " # model += task_vars[18]['t_end']\n", " model += max_router_delay\n", - " # 11431.00000000\n", "\n", " #optimize: minimize the traffic I have by minimizing t_send_total while having optimal time per PE\n", " # model+=t_send_total\n", @@ -1734,10 +1943,11 @@ "\n", " import os\n", " import pickle\n", - "\n", + " import csv\n", + " \n", " # Set your subfolder and filename here\n", " subfolder = \"inception70\"\n", - " filename = \"No_mem_fast3x_noParallel.pkl\"\n", + " filename = f\"No_mem_Fullopt_5x_NoC{noc_factor}_Comp{comp_factor}.pkl\"\n", "\n", " # Create the full path\n", " results_dir = f\"/home/sfischer/Documents/projects/wk_LinProg/optimization_results/{subfolder}\"\n", @@ -1756,6 +1966,16 @@ " nx.write_graphml(G, \"Task_graph.graphml\")\n", "\n", "\n", + " csv_path = os.path.join(results_dir, \"resultsLinProg.csv\")\n", + " row = [noc_factor, comp_factor, model.objective.value()]\n", + " write_header = not os.path.exists(csv_path)\n", + " with open(csv_path, mode='a', newline='') as csvfile:\n", + " writer = csv.writer(csvfile)\n", + " if write_header:\n", + " writer.writerow([\"noc_factor\", \"comp_factor\", \"objective_value\"])\n", + " writer.writerow(row)\n", + "\n", + "\n", " # Combine nodes and create a new graph + graph figure\n", " import re\n", " mappings = {}\n", @@ -1835,6 +2055,13 @@ "if __name__ == \"__main__\":\n", " Graph2LinProgDynamicMap()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/LinProg_Scripts/Task_graph.graphml 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Vf3//WldxhoWFyc/Pz+u55H6/R9kLd3gVsDYIQwrsFqWYaT28bup0Oo8ZPhcWFlZqExISUuvjFxoaWiV8BgAAAAAAVRGwAgAAAGhwxcXFlcLSowPAnJwcORwO9/lWq9WjbXB9UYvUkV2sA/9c0fgBq6ToS05QUM8Yn/RdWlpaa4CdnZ2t0tJS9/mGYVR67KtbARwUFEQ9WAAAAABAq8ceUQAAAAC8UrHuaU23NdU9DQsLU5s2baqEdyEhIU0W3NnCAxTYPVpFGw5LrsYb1xLqp8ATon3Wv5+fn6KjoxUdXf0YpmmqqKioxu/hnj17lJOTI5frfw9KxXqwNW1FTD1YAAAAAMDxjhWsAAAAQBMyTbNZrQh0uVzKy8urdfVpfn5+pTZBQUGVArejAzi73S6r1dpEV+SZ4u1ZSn9lXeMNaEhhZ7RX2GnJjTdmHVSsB1tToH50PdjAwMBj1sGlHiwAAAAAoCUjYAUAAAB8pLS0VAcPHlRQUFCVVYRz5szRjBkz9Mknn+j0009vlPmYpqnCwsJaw7KcnJwqdU9rC8vqWve0OTry/iYVrD7k+62CDckWE6T4m06SYWv5NU/L68HWFsrXVA+2plC+serBulwunXXWWYqMjFRycrLatWun8ePHKyUlRTk5OQoLC/P5HAAAAAAALQ8fGwYAAADqKCMjQ7t27VJaWpp2796tU089VSeffLJOP/10HTlyRBaLRcHBwZo1a5bGjh0rqSzkdDqdeumll9S5c2dlZ2c32HyKi4tr3O61urqnFovFHWhFRkaqXbt2VQJUX9U9bY4iJnRU0eZMufJLfR6yRl3Y9bgIV6Wy+rkRERGKiIio8ZySkpJKgWvFn81t27ZVqQdrsVhkt9trDfYboh7svn37tHLlSj344IPKz8/Xtm3bdPDgQUVERKht27bq0KGDQkNDFR8frzvuuEODBg2q1N7lcjVKEAwAAAAAaF4IWAEAAIA66t27t+Lj49W9e3clJCRo6NChslgs2r59u5577jlNnDix0vnl2wHffffduvHGGzV79mxlZGTI4XAcc8tUh8PhXiVY0+rToqKiSm3sdrs7lIqPj68SUjVl3dPmyBJkU/TF3ZT+f+slp+8S1vBxHeSfZPdZ/82Rv7+/YmJiFBMTU+395fVga/rZrqkebG2rYMPDw+Xv71/rvHbv3q3OnTvr2muvrXR8zZo16tSpkxYuXKiSkhLt379fycnJ7rkahqHi4mLdf//9evnll/Xdd9+pb9++9XuQAAAAAAAtBgErAABAIzJLXSrZm6uSvXkq3ZsnZ3aJTIdLhs0ia5i//BJD5Z8UKv/EUBl+zbtmJaQ2bdro5ZdfVv/+/SsdT0hIcK9qO3z4sCIiImS1WmUYhnbs2KFt27bp7rvv1nfffaeMjIwa+1+0aJG2bt1aa93TsLAwpaSkVAmWWkLd0+YooEOEov/UXYdn/yG5zAZfyRo2up3sQxMbttPjgGEYCgoKUlBQkNq0aVPtOaZpKi8vr9ptiNPT07V161bl5eVVahMYGKjw8HBFRETooosuqtLnvn37tGrVKk2dOlVdu3bVeeedpx49emjHjh3y9/dXXFycrFar2rVr555Debj60Ucf6dNPP9XQoUMrBb9ovpwuUxsP5Gjdnmyt25uttMMFKnI4ZbNYFBnsp56J4eqZGK6+SREKDz4+tj4HAAAA4BsErAAAAI2gNL1A+csPKH/lAZnFTslQ2X8V35O3SPqtrP6j4W9RSP82Cjmlrfxig5tm0jimyMhIvf/++9qzZ4+Ki4t12mmnKT4+XjExMbrmmmsUGxurqKgoXX755Zo4caLCwsL0yiuvaNq0aYqKilJ0dLQOHTqknTt3KjU1tUog6u/vr/j4eHXu3LnKSr1jrcxD3QV1i1LM5T115J0NchU66h+yWiTJUMSEDgo9NaEBZtg6GYYhu90uu92uxMTqQ+qK9WArroKtKQA95ZRTNG/ePLlcLs2fP1+vvPKKHn/8cTmdTu3Zs0cDBgxQTEyM7rzzTo0cOdK94vvVV1/Vjh079MADD+g///mP7PbWtSK5pcnIK9b7q3brrZ926kBOsSTJZjHkcP3vyW0xpK9+PyinacpqMTSuZxtdOqi9+rWLZKU/AAAAgCoM0zR9XF0IAACg9XIVlCpz/jYVrk4vC1m8WeT03/ODescq4uyOsoawmqa5ueuuu/Tdd9+pW7duKigoUHx8vGbOnCmr1arCwkJ17dpVK1as0M0336wrrrhC06ZN05AhQ5Senq6UlBRt2LBBGRkZOu+88/TPf/5TqampTX1JqMBVUKrMedtU+Fsdnr9S2YcoTMkvMVRRF3aVXxwflmjOCgsLdcYZZ+iKK67Q9OnTlZeXp9DQUP3f//2fFi5cqFmzZqlPnz5655139Pvvv+uOO+7QwoUL9emnn+qxxx5TUlJSU18CjlLicOlfi7fq+e+2ymWacnnx7ofVYsjpMtU3OUKPn99HneJCfTdRAAAAAC0OASsAAICPFG44rMwPN8tVUM8VcEZZbcjI8zorqEf19QvhG06n070CLi4uTsHBlQOy/Px8hYSESCoLZy655BKlpqbq8ccfl8vlcm8TfP3118vpdOrFF1/UZ599JpfLpV69eumHH37Q3Llz9fLLLys2Nta9/Sial6LNmcr9Ya+Kt2R6FrRaDMllyhYfLPuQRAWfFC/Dyve1uXE4HO6tuyWptLRU/fr106xZs3T++edXej72799fd911l0aOHKnRo0dr/PjxeuCBB3T33XerpKREjz32mPv5Xs40TW3fvt298pxV543rj305uvm91dpyMK9eL8FWiyHDkO4Y01VXDukgi4XnMgAAAAC2CAYAAPCJ3B/2Kvvz7e4VbPViSq4Chw7P3qCwM9srbERyQ0yx1Suv51hxG9GK/5+Tk1OpnuPkyZN1wgknVApRysNVqawmavv27bVv3z5Jcp+3du1aZWRkaNy4cZKks846y90mPT1d+fn5ysjIUGxsLOFqMxXYJVKBXSLlOFyo/F8PqWRXjkp258osclY+0WaRf0KI/JPtCuodK/8UO9/TZqywsFB/+tOfVFhYqI4dO+rw4cMaOnSoTjrpJG3dulWxsbEKDw/XL7/8ouzsbLVr105FRUUaOXKkvv76a82dO1e7du1ScXGx/Pz8dM899ygsLMzdf0FBgd5++23310FBQe4aydXdhoWFUTe5gSzZnK6r3lolh8us90uw87/LXh/6YqPW7cnWkxf2lZ/VcoxWAAAAAI53rGAFAABoYO5w1UfCx7aXfTgha21M01RRUVG1oWn5bU5OTqW6jH5+fpWCjoo1T8PDwxUZGVkl/Dhy5Ii2bNmi4uJi/fzzz/r111916623qqCgQDNmzFBwcLAsFosmT56su+66yz030zRlsVgqrXJFy2Kaply5pXIVO9x1k61hATJY3daipKWlaefOndq5c6ccDoemTJmikpISXXzxxdqzZ49sNpvsdrtmzJih8847r8oq1MmTJ2vAgAG68MILlZKSUilQN01TWVlZVT7AUfHroqKiSv2FhoZWqbdc8evQ0FBC+2P4cWuGpv17hZymqYZ+t8MwpHE92+rZKSfKynMdAAAAaNUIWAEAABpQ4aYjOvz67z4fJ/rS7grqHu3zcZqrkpKSGledlt+Wlpa6z7dYLJXCiuoC1MDAQK+Di59++kk333yzkpOTlZCQoLFjx2rcuHHKzc1VTk6O2rZtS4AKtGC5ubnKzs5211c1TdP9wQyr1aozzzxT06ZN05QpU+rUf11/l9X2YZC6/C47Xuw+UqDRT32vYoerwcPVim4c2Um3ntHVdwMAAAAAaPYIWAEAABqIq9ChA0+skiu/tP7bAtfmvzVZ28zsJ0uwX62nHjlyRNu2bVO/fv1azBvu5XVP67Lqq6btN1n1BcBXSktL5edX++/iujJNU4WFhbX+PszNza1xNX51t+Hh4T6bry9s3LhRQUFBateuXa3nuVymprz6s1alZbq39fUViyF9et0Q9UoK9+k4AAAAAJovAlYAAIAGcuSDzSr49aBvw9VyhhTUN1bRF3ar9m6Xy6Wff/5ZixYtUnh4uK699tpmUduvurqnR99WrHsqSYGBgbVumUndQgCtmcvlUn5+fq2rYI/+vVpbPdjw8HDZ7fZm83t17ty5WrNmjU466SSNHj1agYGB1Z739s9pmjV3faPMyWox1D46WAtuGiZ/G7sUAAAAAK0RASsAAEADcBwp0oFHVzb6uG1m9pMtJqjSsUOHDmnevHnau3evBg4cqJEjR1apG+gLFeue1rTlZXV1T2t7kz8sLKxR5g4AxzOHw+He7rim1bBH7wxgt9tr/P3cmPVgTdPUqlWr9M033yggIEBnnXWWunTpUumcUqdLpzz8rQ7nlfh8PhU9N+VETeiT0KhjAgAAAGgeCFgBAAAaQPbCHcr9fk/jrF4tZ0ihQxIVMb6DpLKtdZcuXaolS5YoKipKEydOVHJycoMNV7FWYE1v0HtS97RigNqaawUCQHNSUlJS6+/37OxsORwO9/kV68HWtMNAQ/6Oz8rK0meffaZt27apV69eOvPMMxUcHCxJWrh+v2a8/WuDjOMpiyGdlBKpD68d1KjjAgAAAGgeCFgBAADqyXS6tO9vy2UWOY598n+9tXquZq+eqz3ZByRJXWJSdfOgaTqt4ylejW0EWJXwl1O0/9ABffrpp0pPT9fgwYM1fPhw2Ww2j/txOp3u1U01bTFZWFhYqU1oaGiNq07Dw8MVEhIii4WtEwHgeFBeD7a2Ld5rqgdbUwDrbT1Y0zS1du1aLVy4UBaLRePGjVP37t019bXl+nn7YdW19Gr2zx8o6/s3ZT95oqJGXe1V269vGabO8fa6DQwAAACgxSJgBQAAqKeSvXk69Nxqr9p8vfVHWQ2LUiOTZEr6YP1Cvbz8XS2Y/n/qGpvqVV87+hVr0R8/KT4+XhMnTlTbtm0r3V9e97S2VUk11T2tbXvI5lKfDwDQPLhcrmO+3uTn51dqExQUVOvrTXX1YPPy8vTFF19ow4YN6ty1m+5ba5ejjulq8f7NSv/0EVn8gxSY0turgNWQdP/EHpo2qH2dxgYAAADQcnm+rAEAAADVKt2bd+yTjjK60+BKX9857CrNXj1Xq/f97lXAasrUgXVp6n9Kf6WmpmrPnj36448/qqwsqriiyGazuVcQxcbGqmPHjlVWFFH3FADgrYpbwyclJVV7TsV6sEe/VqWlpSknJ8ejerA9e/ZUQkKC5v/wqxyu0DrN11VSqIz5jyv6zBuU/dN/6nC9htbtza7T2AAAAABaNgJWAACAeirZl1dWjK2Oq2ecLqc+27hYhaVFOimxp1dtXTIV5QjV0hUrtGLFClksFtntdndgmpSUVGVLxqCgIOqeAgCahM1mU2RkpCIjI2s8p7i4uMZtiA8ePFipHuxeR7TKCqB7/7p25OsXFdSxv4La961TwOp0mVq9K8vrdgAAAABaPgJWAACAenLmlNQpXN2Qvk2TZv9ZxY4ShfgH6dVz/q4uMe296sMqi0KNQPXq1Ut9+vRRamoqdU8BAC1aQECAYmNjFRsbW+39pmnq0KFD+vXXX7Xpl0MySssiVm/k//G9Sg5sU9tpT9Vrrhl5xfVqDwAAAKBlImAFAACoJ9PpOvZJ1egYlaKFl/2fcovz9cWmxbrl84f0wcXPeR2yhoeGacm2VVq3bp3i4+PVu3dv9erVS3a7vU7zAgCgOSopKdGGDRu0du1abd++XTabTSH2HrLkG3J6kbA6ctJ15NtXFX/h32TY6rclvqOO/wYAAAAA0LIZpmnWbS87AAAASJIyZv+hot8P17ufKf+5Re0iEvTPM2/3ql1RG4scZ0YrOztbO3bs0JYtW2Sapjp06KDevXurW7du1FQFALRILpdLO3bs0Nq1a7VhwwaVlpYqOTlZnTp1UmxsrN75NV1z1ud6tZFEweZlSv/kH5JRYccH0yXJkAxDKTM/kWGxetRXRJCffvvrGd5dFAAAAIAWjxWsAAAA9WQN869XDdZyLtOlYmepd23kUlrGPi197xv3MT8/PwUEBGjv3r3atm2brFarEhISNGjQIMXExCg8PFx+fn71misAAL7gdDqVm5urrKwsLV++XNu3b1dJSYn7tc1qtWr37t3avXu3JCnNES2XmerVGIHt+qjt5c9XOnb4i2fkF52ksIHneRyuSlJ8WKBXYwMAAAA4PhCwAgAA1JN/YqjyvQxX//n9yxrRYaASw+KVV1KgT//4Rst2/aa3L3jcq34ssmjAWUPVv/tY5eTkKDs7W9nZ2crJyVFOTo4OHz6szMxM7d69W++99567XVBQkMLDwxUWFlbtrd1ul9Xq+RvMAAAci2maysvLq/b1qvzrvLy8Sm2sVquioqIUHR3tfo2q+Hq1v9DQD8/+6NU8LAHB8o9tX+mY4RcgS6C9yvHa2CyGTkyJ8GpsAAAAAMcHAlYAAIB68kv0vtZpRn6mbvnsIR3KPyx7QIhOiO2oty94XMNS+3vdV0CSXf5hdoWFhSkpKanacxwOh3Jzcyu9oV1+m5aWppycHBUVFVVqY7fb3W9iV/emdkhIiAzD8Hq+AIDjj2maKioqqhKeHn3rcv2vZqnNZnO/tsTGxqpjx45VXmuOtcW9Pcwlf6tFJU1QC9XpMtUzMbzRxwUAAADQ9KjBCgAAUE+m09T+h5bLle/d9r4NwRJsU9t7B8qwWo598jEUFxfXuqooJydHDofDfb7Vaq0Uvh59Gx4eroCAAEJYADgOlJaWVgpLq3udKC393+ugYRg1vj6U3wYFBTXIa8Rlr6/Qki0ZctZzq/66WDxzhNrHhDT6uAAAAACaFitYAQAA6smwGgo9ta1yvt0lNeZ7u4YUMrBtg4SrkhQQEKDY2FjFxsZWe79pmiosLKx2ZVJmZqZ7JWzFz+/5+/vXGsCGhYVRDxYAmlh53dPaAtTCwsJKbUJCQty/yzt27Fjld3toaKgsloZ5fTqWS09tr0Wb0htlrHJWQzqlYzThKgAAANBKEbACAAA0gJABbcoC1sYed2CbRhvLMAwFBwcrODhYbdu2rfYcl8ulvLy8at+kP3DggDZv3qz8/PxKbcrrwda0yol6sABQd6ZpKj8/v9Zte3Nzcyu1CQgIcP9eTkxMVPfu3Sv9Xg4LC5PN1nzeThjWJVZtwwO1P7vo2Cc3EKcpTTu1faONBwAAAKB5YYtgAACABpI1b5vylu1rnFWsRlmoG3lO50YYrGE5HI4qb/AfvVKquLjYfb5hGAoNDa11FWxT1oOdOXOmfvrpJ8XHx+vFF19UmzZlofeWLVsUExOjyMjIJpkXgMbhcDiaLGw8uu5pdbc5OTlyOp3uNjabrcrv0KO/DggIaJLrqY9PVu/RLe+taZSxrBZD3drYNe/6IbJa2AYfAAAAaI2az0dOAQAAWriwM9ur8I/DcmYX+zZkNSSL3V/h41J9OIjv2Gw2RUVFKSoqqsZziouLawxgDxw4oOzs7EqBQXk92JrCAl/VgzVNU6NHj1b37t11yy23uLfQzMvL04033qj09HQ5nU516tRJr732msLDw5WVlaUPP/xQHTp0UEpKihISEhQcHNyg8wLQMEpLS5WRkeFetV9SUqKHHnpIq1atUnZ2tkpKSnTVVVfpyiuv9Nn4R/8ePPq2pKTEfX553dPy33uJiYlVPpTSUHVPm5tJfRM1b80+Ldns+1qshqSnL+xLuAoAAAC0YqxgBQAAaEDF27OV/upan69ijbmypwI7td6VkaZpqqCgoMbAITs7W7m5uVXqwdYWwNanHuyaNWt0+eWX69tvv1VERESl+/Lz8/X4448rIyNDzz33nPbs2aNZs2YpLy9Phw4d0pYtWxQSEqKtW7fW5yEBUAdHjhzRtm3btGfPHjkcDk2ePFmGYSg/P18XX3yxNmzYoJCQEM2YMUPXXHONJOmkk07S2LFjdemllyopKUkhIXWrwVle97Smlfw11T2tra51Y9Y9bY4O5hRp9JPfK6/YIV9mrHeP7aZrhnf03QAAAAAAmj1WsAIAADSggA7hijyvizI/3OyzMSLO7dSqw1WpbJVWSEiIQkJClJCQUO05LperxvDiwIED2rRpkwoKCiq1CQ4OrnEb4vj4ePn7+1da+WWapgzD0IYNG2S32xUYGOi+r6CgQIZhyGq16siRI9qyZYskKSkpSW+88YakspW6t912mzsIdrlcrTocaUlKHC7tPJyv3CKHTNNUoJ9VqTEhCgngT6yWwuFw6KqrrtKhQ4eUmpqq7OxsrV27Vg888IBefPFFpaSkaO7cucrJyVHnzp01cOBA9e3bV+3bt9fQoUPVtWvXWvt3Op06cOBAjR8CycvLq/QhkPK6p2FhYUpISNAJJ5xQJUhtTnVPm6P4sEC9efkAXfTKzyp1unwSsk4ZkKyrh3Vo+I4BAAAAtCj8dQYAANDAQvrFS5IyP/pvyNoQb/AaZf1EnNtJoQPaNkCHxz+LxeIOSJOTk6s9p2I92KMDkJ07d7q3AJWkCy64QF27dq12a82dO3eqTZs28vf3dx9bvXq1Zs6cqfXr1+uiiy7Sv//9b0lloYvT6ZS/v79mz56tNWvWuO87HrftPJ6s25OtD3/ZrVVpmdp0IFeOo9IbQ1JKdLBOTonU+N5tNaJrHFuINmM2m0233XabBg0aJEnasWOHhg0bppkzZ+qDDz7QvffeK8MwFB4erjPPPFMLFixQ3759FRISoltuuUX333+/IiMjdeutt2rEiBFVVsAXFxfrtddek1S2jXl5SBodHa3U1NRqtzFH/Z2YEqk5V52iS/+9XEWlrgbdLviSU1L04MSe/K4GAAAAQMAKAADgCyH94mWLDtSR9zfJmVXPmqyGZA0LUOQFXRTYMaKhpgh5Vg+2qKhIOTk5CgsLq7K6tHwF6/bt29WmTRv3ClTTNDV48GAtW7ZMv/76q5566int3r1bCQkJMgxD/v7+OnTokD7//HMNGzZMnTt3ZvVqM2Wapuav3a9Xvt+m9ftyZLUYNQY2pqS0wwXak1moj1fvVZvwQF02qL2mDWqvQD9r404cHhk0aJCcTqesVquys7OVlJSknJwcSWUBabnu3bvrwIEDys/P14wZM5SRkaETTzxRGzdu1O23366ZM2fqkksucf9OkMpWxF911VUKDw9XcHAwoVwjOrldpL64cahmfrBGK3dm1qsvq8VQgM2i+yf00Pn9kvg+AgAAAJAk8Q4OAACAjwSkhiv+lpMVOiih7F9d3r4na5T9F3pqguJvO5lwtYkEBgYqLi6u0va/5coD0ZycHPXp08e9fWf5G/Aul0snnXSS9u/fr1WrVkkqWzUrSa+++qqCgoI0ZcqUSm3QfOzPLtSl/16hG99drT/2l4VunqyGKz/nQHaR/rlwo8Y+vUSrd9Uv5IHvWK1l4ffTTz+twYMHKzk5WZGRkdq+fbv7nMjISHfd58GDB+vss89WSkqKzjjjDA0aNEiLFi2qtu+EhASFhITw/G4C7aJD9N7Vp+qBiT0U7F/2Pfbm21C++nxY5xh9e9twXdA/me8jAAAAADdWsAIAAPiQxd+qiAkdZR+RrPyVB5S3bL9cuSX/vdOQTLNs2Zuhsnd+/xvMWEL9FHpqgkL6t5E1zL/G/tG0XnrpJb366qtavXq1tmzZonXr1umWW27R77//rvbt26tLly7atm2b1q9fr7vvvluS3NsIz5kzR7fffrt69uwpqfqA9dtvv1V6enq1NWHtdjsrXn3o6z8O6qb/rFaxwyVJda7laJrSriOFOvfFn3TrqC66fmQnQhofMU3THYIeveW30+nUhRdeWGPbV199Vfv379ftt98uqWzF6m+//ea+v7i4WIcPH65S89k0TWVnZyslJcUn14T6sVgMTRvUXuf3S9Knv+3T6z/u0OaDeZIkm8WQyzRl/vc12GqUrU43JQX5WXVBvyRdcko7dY63N+k1AAAAAGieCFgBAAAagdXur7CRKbKPSJYjo1Cle/NUsjdPztwSmQ6XDJtF1lA/+SXZ5Z8YKltMkAxqNzZ7V1xxhUaNGqV9+/Zpy5Yt2rRpk/z9/fXRRx9pzZo1cjgcCgwM1OOPP65hw4a5291zzz1KSkrSuHHjau0/MDBQDodDO3bsqFQPVioLZO12uztwPTqAZVvSuvv0t7265b3f3J9/qC+nWdbLE19vVmZBqf5y1gl8X+qgfLvuigHq0V87nU73+Var1f1ciIiIqLR9b0WrVq3Sl19+qYceekg9evSQJI0bN05PPPGEPv/8c40cOVIbN25U165dJUkrV67UPffcI4vFokOHDumUU07RfffdJ4mV6M1VsL9NUwak6KL+ydqfXaR1e7O1fm+20g4XqNjhlM1qUXiQn3okhKlXYri6trErwMa23gAAAABqZpim2RDvGQAAAACoRkFBgYKDgysdu+OOOzRy5EideeaZHvdjmqaKi4srrcw7OmQ6OmCy2WyVwtejb8PDwxUQENBg13o8WLTxkK54c2WdV6x64qbTO+uW0V18N0AL5HA4av3ZrukDBrX9bHvyAYN9+/bpggsuUEBAgG6++WZ99913SkhI0O23364FCxbo3nvvVW5urgYPHqwXXnhBISEhSk9P19KlS9WhQwclJiYqJibG1w8PAAAAAKCZIWAFAAAAjhOmaSo/P7/WkCovL08V/wQICAiodRVsWFiYu7bs8S4jr1gjH1+s3CJHg6xcrc17V5+igR2ifTxK8+ByuZSbm1vl57LibUFBQaU2wcHBtf5cNtQW2UuXLtW5556rCRMmKDAwUCkpKerdu7fGjh0rSTWuegUAAAAAtG4ErAAAAEAr4nQ6K4Vd1d0eHXaFhITUulIwNDS02daD3bhxoxYsWKAzzjhD3bt3rzEsM01TM97+Rd9sOCSnL5evSrIaUpvwIH196zAF+9ccXu/bt0+fffaZUlNTNXr0aJ/Oqa4q1j2tKdjPzc2tFOr7+/tXCkyPDlDDwsLk5+fXhFcFAAAAAEDtCFgBAAAAVFJaWloleD06hK2pHmx1IWxYWFiT1YMtKirSvHnztGHDBnXr1k3jxo2T3W6vct7iTYc0/fWVjTYviyFdf1on3XpG1yr3lZaWavHixVq2bJni4+N17rnnKjY2ttHmVlH5ttQ1hfE5OTlyOBzu8yvWPa3pNjAwsEmuBQAAAACAhkLACgAAAMArFevB1ha8VVcPtqZVsGFhYT6tB/vHH3/oiy++kMPh0JgxY9S3b99Kge+0f6/Q0q0ZPl+9WlFEkJ+W33u6AmxW97G0tDTNmzdP2dnZGjFihE499VRZrdZaeqk7h8NRY5Be/nVxcbH7fMMwFBoaWuvq05CQELbUBQAAAAAc9whYAQAAADS48nqwx9o6tqLyerC1bR1bn3qwhYWF+vLLL7VmzRp16NBBEyZMUEREhHYdLtDwxxZ5VXc1a+k7yv7x3UrHbFFJSrzqJa/m9MxFfXV230QVFxfrm2++0apVq5ScnKyJEycqJibGq74qcrlcysvLqzUEz8/Pr9QmODj4mFtB+yrsBQAAAACgJSFgBQAAANAkjq4He3QAm52drcLCwkptQkJCat1+1pN6sFu2bNFnn32mwsJCnX766VqZH6Unv94sbxavZi19RwWbflT8hf/430GLRdbgcI/7sBjSsC6xmjU0Sp999pkKCgp0+umnq3///rVeQ3nd05rq6NZW97S64Lr8lrqnAAAAAAB4hoAVAAAAQLNVWlpa4wrM8jCxtLTUfb7FYnHXg60pTAwKClJJSYl7xehPlp7aXBAob/4yylr6jgq2/KyEy56r1/UFW01d4PeLOnb834ra4uLiGmvflt9WV/e0pq2Xw8PDFRAQwNa9AAAAAAA0EAJWAAAAAC2WaZoqKiqqdRVsTk6OXC6Xu43NZnOHj1arVf9YH6IC07vVm1lL31HOio9lCQiRYfWTf2I3RQ6fJltYnNfXcEvHw4oJtlZb91RSpcC4ulvqngIAAAAA0LgIWAEAAAAc1yrWgz16JejeQ4f19O5kr/ss3LZKrtIi+UUlypl3RNk/vitH3mElXP6CLAHBXvV1btQ+9U8OrXb1qd1up+4pAAAAAADNjK2pJwAAAAAAvmQYhkJDQxUaGqrExETl5eVp/fr1SktL0/70I5K8D1iDOvb73xdxqQpI6Ko9L16u/I1LZe9zhld9ZeYV6ODBfMXFxalbt26KiYnxej4AAAAAAKDxELACAAAAOO6VlpZq06ZNWrt2rbZu3SrDMNSlSxdN7Heq3nt/V737twSGyi8qUY6sfV63HXnaSEXk7dTKlSu1dOlSJSQkqHfv3urZs6dCQkLqPTcAAAAAANCw2CIYAAAAwHHJNE2lpaVp9erV2rhxo0pKShQZGanY2FgFBQWpoKBA6Zk5eqoOWwQfzVVSqL0vXqbwwRcrrN9Er9pOjjmgPvH+Cg0NlcPh0OHDh3Xo0CFJUseOHXXiiSeqS5custn4fCwAAAAAAM0Bf6EDAAAAaLFcLleN9VV37dql/Pz8SudnZmaqqKjIXeO0U/tkRRwylFXs3edOM7/7PwV1GiBbeJwcuUeUvfQdybAopPtwr6+hX5dEWYtzdfjwYWVnZysvL89939atW7V161bZbDalpqZWW6c1LCyMOq0AAAAAADQiAlYAAAAAzZJpmiosLHSHpuXBacWvc3Nz5XK53G38/Pzc4WO7du0UEBCgpKQkRUREuMNIf3//SuPMO7JKX/9xUC4vMlZHboYy5j8mZ2GOrEHhCkjqrjZ/ekLW4HCvrjEi2E8XThgtwzDcx5xOp3Jzc93XuH//fmVlZcnlcmn37t3KyclRYWFhpX5CQ0MrBa4VA9jw8HCFhoZWGgMAAAAAANQdWwQDAAAAaBIlJSWVVp0eHaDm5OSotLTUfb7FYnEHhjXdBgYGeh0k/mvxVj3+5SavAtaGYDGkEV3j9O/p/b1uW1JSUulxqm4Fb3WPXU2PW10fOwAAAAAAWiMCVgAAAAANzul0VgkAj74tKiqq1KZ8FWZNKzF9tQpzT2aBhj66SE3xl9ELF5+k8b3bNni/pmmqqKio2uC1YpB99Orf6oLXiseOXv0LAAAAAEBrRMAKAAAAwCumaSovL6/W1acV64hKUlBQUK2rJ+12e5PWEb3ijZVavDldzkZcxhoV7K/l954uP6ul0casqGL92uPl+wgAAAAAQGMgYAUAAADgVteVj7XV/2wJKx9/3Jqhqa8tb7TxDEO6+fQuumlU50Ybsy7KVyLXtA1xc1qJDAAAAABAYyFgBQAAAHzENE3t3r1bUVFRCg0NVWlpqZ599ll99dVXys/PV1hYmP7+97/rpJNOarQ5VazdWVOA2lprd94w51d9se6AnD7+E8liSMmRwfrylmEK9Gv5qz2PrqVbXW1Yh8PhPt9XtXTrwuVyaerUqbJYLEpJSVHPnj01ZcoUWSxNs6oYAAAAANAy2Jp6AgAAAEBLlZ6erl27dmnXrl3Ky8vTBRdcoICAAPf9L730kq677jp98MEHOu+88+Tn56ecnBzdcsst6ty5s9auXauzzjpLO3bsqNSuro5ebVjdbWFhYaU25asNw8LC1KlTpyqrT1vTasMHz+6ppVszlFVY6tN6rKYpPXVR3+MiXJUkf39/xcbGKjY2ttr7TdNUYWFhjdsQ79q1S7m5uTWuiq6pJqyfn1+9526apq699lplZGRoy5Yt+uyzzxQQEKDJkye7758zZ46effZZ/fvf/1aPHj1kmqbWrVunwMBAJSUlKTg4uN7zAAAAAAC0LKxgBQAAAOpo0qRJys3NVZs2bWSxWBQREaEnnnhC/v7+ysvL03nnnae8vDxdf/31uuCCC2S1WpWenl4piIqIiNCKFSvUpUuXWscqr3taU0hVXb3MwMDAWrdqDQsLo17mUZZuydC011fI5TLlqz+U7jizq/48opOPem+ZKtaDrenDAdXVg61ta+q61IN9+umn9dZbb+nXX3+Vy+XS8uXLdemll8put+vZZ5/VkCFDlJGRoWuuuUa7du2Sw+FQ+/bt9dprryk6OrohHxIAAAAAQDNGwAoAANCISp0ubTqQq/V7s7Vub7YO5hSrxOGUv82quLAA9UwIV++kcHVtY5eflS0qmzun0+kOcA4cOKAePXpoyZIl6tGjhy699FJdfvnleu2119S3b19df/31CgwMrNTuk08+0YsvvqhXXnlF7du3r9L/smXLtGnTJnfAdPQKv9q27W0JdU+bq4Xr9+u6Oat9ErL+eURH3T6ma6tZFdyQHA6HcnNzq2w/XDGEPboerN1uV1hYmGJjY3X22WdX2+/69ev13HPPqaCgQKZpaujQobrmmms0b948zZ8/X6eeeqq++OIL3X///erZs6dyc3OVnp6uDh06SJJmzZqlXbt26a233pJpmnxvmzPTlA5vk/atlvb/JmXulEoLJatNCoqS2vSWEvpKbftI/iFNPFkAAAAAzRlbBAMAADSCvVmFenf5Lr29PE1ZBWX1LW0WQw7X/+Ibm8XQu65dMiWFB/lp6sAUXTwwRUmRbD/ZXFmtVu3atUurV6/WvHnzNGPGDHXt2lWrV6+WzWZT//799dVXXykvL88drpaWlsrPz09HjhzR448/rquuukrt27evEsyUfx0WFqakpKQq4WlQUBBBjo+c2bOt/j3dphvm/Kr8EqecrvrFrFaLIdM0dffYE3TVsA4NNMvWx2azKTIyUpGRkTWeU14P9ujgtbaVrG3bttX48eP18ccfKyAgQFdccYV+/PFHff3115o2bZry8/NVWlrq3grYbrfLbre7PygRGhqqnTt3Sipbicuq8GaoMEta8x9p+UtS5o6yYxY/yeWQyj9GYVilte9Jpkuy+ku9L5T6X1kWuAIAAADAUVjBCgAA4EO5RaV6+IsNenflblkkOb34l5fVkFymdH6/JM06q7vCAutfbxANpzwAfe+99zR37lwdPHhQvXv31o033qjZs2crJSVFl112me666y5t2LBBV1xxhYYNG6aIiAg5HA5NmzZNUVFReu6555r6UlCD9Nxi3fPJOn39x0FZ/vt89EZ5/N05PlRPXdhXPRLCG3yOaFhTpkxRt27dtG/fPnXq1Em33367Xn75Zf3+++96+umnZbFY5HA4ZLOVfVZ56dKlevjhh3XGGWfopptuksvlksXC7gPNhssp/fSctPghyVHy34MePpEttrIAtv1Q6eznpcj2vpolAAAAgBaIgBUAAMBHftiSrpkfrFF6brHXwUxFFkOKDg3QY5N7a0TXuIabII7JNE13XcjY2Nhjbrl722236ffff1dkZKTmz5+vxMREd/upU6fq3nvvVXJysp5//nn99ttveu211+R0OpWTk1Prqjw0HdM09fUfB/XqD9u1cmemrBbjmCtay89pFx2sywenasqAFPnbCN2am5KSEpWWliok5H9bwZ544okaMGCASktLtWDBAkVERCgzM1OmaWrmzJmaMWOG7Ha7JGnRokWaNWuWzjnnHM2cObPaMfbs2aPQ0NA61YNFPaVvkj6+Rtq/un79WKxlq13P+HvZilZ2DgAAAAAgAlYAAACfmP1zmu6bu15GHVa9Vad89dz9E7pr+uDU+ncImaapoqKiStuIHl3bMTc3V06nU5J06aWXKjW19sf+H//4hz799FMtXbpU+/fvV7t27bRs2TI9+OCDev3119WmTRstW7ZMgwcPVmJiotq3b6+DBw9q+PDhevXVVxvjslEPWw7m6sNf9+iXtEz9vjdHhaXOSvdbLYa6xIWqb0qkJvRuq1M7RrONczOWn5+vadOmKScnR506dVJpaakyMjL08ssvKy7ufx9mOe+88xQeHq4LL7xQw4cPV2BgoN5//309+eSTuuuuuzRp0qRq+3c4HPrHP/4hSTIMQ6GhodXWTC6/DQkJ4eeloexcKr1zvuQolkznsc/3VN9LpInPloWuAAAAAFo1AlYAAIAG9vbPaZo1d73P+idk9UxpaWmlsLS6ILWkpMR9fnm90/LA4+iap7GxsbJare4AxDRNHThwQFu3bpXT6dTatWv1448/6k9/+pPOOussd7+bNm3SI488ojvuuEPdunVTRkaGvvzyS/Xr10/R0dGKiYlp9McG9edymdqTWai8YodcpqlAP6uSo4IUYCN4aUl2796t7du3a9euXcrOztbFF1+sqKgouVwuSZLFYtHIkSM1depUXXHFFZLKVqr/61//0vz58zVq1Kga+zZNUxkZGZV+Bx39O8nhcLjPt1qttf4OCg8PV0BAACHssaQtk96aWLa9r+lq4M4Nqc9F0tn/ktgKGgAAAGjVCFgBAAAa0I9bM3TJa8s9rfBWZ29c1r9VbxfsdDqVm5tbJayo+HVhYWGlNiEhIZXCiqPDi9DQUK9rJ65YsUK33HKL2rRpo4SEBA0fPlyTJ09uyEsF0MR2794tf39/xcXFyTAMTZw40R2elpSUyOl0asGCBWrbtq1X/ZqmqcLCwlo/BJKTk6OKf7L7+/vXGsCGhYXJz68V1+vO3iO9MFAqLfBBuFrByFnSsNt91z8AAACAZo+AFQAAoIHkFTs06onvdSi3qEG2Ba6JxZCiQvz13cwRCgus/Y307Oxs7dixQ3369Gkxq54q1j2tafvevLy8SqFDQEBAtUFDxSDCZrM14VUBOF4dPnxYkZGRXn9AwxMul0t5eXm1hrD5+fmV2gQHB1f5PVjx/+12u0/m6itbt25VUFCQEhMTaz/RNKXZ50g7l0iuBtwWuDoWq3T1EqlNT9+OAwAAAKDZImAFAABoIPd+sk7vrtjl03C1nMWQJp+cpEcn96n2ftM0tWrVKn3zzTcKCQnRddddJ6u16bcuNU1TxcXFVWqdVlx9mpOT4657Kkk2m61KSHD01wEBAU14VQDQdBwOR7U1pCv+Xi0uLnafbxiG7HZ7jbVgw8PDFRwc3Gw+lPPRRx9p/fr1GjhwoEaOHCl/f//qT/x1tjTv+saZlGGVYrtK1/wgWfnwDgAAANAaEbACAAA0gH1ZhRr8yHdqzH9ZGZKW3HGakqOCKx0/fPiw5s+fr7S0NJ100kkaPXq0AgMDG2VOFeue1vRGf3V1T2t7oz8oKKjZvNEPAC1RTR9sqXhb8YMtFevB1vTBlsZ6XXG5XPr555+1aNEihYaGasKECerQocNRJzmlJ7tLeQcaZU5uF7wldT+7cccEAAAA0CwQsAIAADSAJ77apBcWbW2U1avlrIZ01bCOumtsN0llb0IvW7ZMixcvlt1u14QJE5Samtpg47lcLuXm5tb6Jn1BQUGlNiEhIbWGp3WpewoAaFimaaqgoKDWrdlzc3OrrQdb09bs4eHhDbo1+5EjRzRv3jylpaXpxBNP1BlnnPG/kHfjF9J/pjTYWB4xrFLKqdJlnzfuuAAAAACaBQJWAACAenI4Xer/j2+UWVDqXbvcDGUtfkOF23+R6SiWLaKtosfdrIC2nT3uIyzQplWzRivzcLrmzZun/fv3u7dR9POrvT5rRRXfXK/pDfaj31wvr3ta3cqm8lvqngLA8aH8QzY17U6QnZ1d5UM2wcHBta6C9bYerGma+uWXX/T1118rICBA48ePV9euXaW3zpF2fC+ZntVedbpM3b+4WG+vK9WBPFMJdkPT+/hr1jB/73dMuH6VFOP56zYAAACA4wMBKwAAQD39vi9b459d6lUbZ1Ge9r9+owJTest+4lhZgsPlyNwnW0Rb+UW29aqvv5wSoH3rlik6OloTJ05UUlJSlXOKiopqfVP86LqnVqu1xlWn5f9P3VMAQEUV68FW92Gd6raJt9vttX5Yp7p6sNnZ2fr888+1ZcsW9epxgs75488yXJ5/yOmhH4r15LISvTkpUD3irFq1z6nLPi3UP0YG6MaB3ry2GdK4x6QBV3nRBgAAAMDxgCUFAAAA9bR+b7bXbXJ+/lC2sBjFjL/Zfcwvok0dRjf17a9bdMkpJ6tLly7KyMjQ9u3bvXpDOyEhoUqQWt0b2gAA1MZmsykqKkpRUVE1nlPbB3727dtX5QM/Nput2lrd/fv3V0pKijb/8IlX4aok/bTbqbO72jS+S9lOD+0jLHp3falW7HV5d8EWq7T/N+/aAAAAADguELACAADU0/q9ObJZDDm8KMBauHW5AlNPUvrch1W0e72sodGynzhO9r5nejW2IVMZziCtXLlSK1eulFR5S8bU1NR6b8kIAEBDCQwMVGBgoOLi4qq9v7Yt6w8fPqwdO3ZU2rK+j7lbpiRvPhI0KNmqV34p0ebDTnWJtmrNAaeW7nLqyTMCvbsYl0Pas8q7NgAAAACOCwSsAAAA9XQot8ircFWSSrMOqHT1FwrrP0nxp16g4v1blPntKzKsfgrtdbrH/ZiyqNgSqN69e6tPnz5KSUmh7ikAoMUyDEMhISEKCQlRQkJCtee4XC4dPHhQa9asUdiatXIVGrLK89fhu4b4K6fYVLfn82W1SE6X9I+RAZra2/Pa5W55B71vAwAAAKDF4903AACAeipxeLmloCSZpgLadFLk8GmSJP/4jirNSFPub194FbBKUkBwqDZtWq+1a9cqMTFRffr0UY8ePRQcHOz9vAAAaKYcDoc2bdqktWvXauvWrZKkSZGBshRZJdPhcT/v/+7QO+tKNee8IPWItei3A07d/GWxEuyGpvX1925STu+2JwYAAABwfCBgBQAAqCd/m/fb7VpDI+UXk1LpmF90sgo2/eh1X0lt43Xb1DHavHmz1qxZowULFmjhwoXq0qWLevfurc6dO7OqFQDQIpmmqV27dmnt2rX6/fffVVxcrMTERI0ZM0Y9e/ZU8C8vSosWyosFrLr96yLdNThAF/UsW7HaK96qtGxTDy8t8T5gtdZh1SsAAACAFo932gAAAOopzh7odQ3WgMTuKj2yp9Kx0iN7ZQurviZdTWwWQ3H2APn5+alHjx7q0aOH8vPztX79eq1Zs0bvv/++AgMD1aNHD51xxhny9/fyjWMAAJqAaZr68ccf9csvvygrK0vh4eEaMGCAevfurZiYmP+dGNqmrBaqFwpKJctRRVuthuTlbv//HT++Do0AAAAAtHQErAAAAPXUMzHM6xqsYf3P1oG3b1f2svcV3G2ISvZvVt6ahYoac71X/Thdpnomhlc6FhISooEDB2rgwIFKT093b6V4+PBhtW3b1qv+AQBoCk6nUxs2bFBqaqq7xrhhGFVPbNvH674ndLHpHz8UKyXcUI84q1bvd+rJn0t0eV8vV6NabFJSP6/HBwAAANDyGaZp1uUzmgAAAPiv3/dla/yzS71uV7B1hbK+f1OlmftkC49XWP9Jsvc90+t+Pr1usPokR3jdDgCAFs/pkB5qKzlLPG6SW2zqL4uK9cnGUh3KN5VgNzSlp5/uGx4gf2s1IW6NDGncY9KAq7yfNwAAAIAWjYAVAACgnhxOl/r/4xtlFpQ2+thhgTatmjW6TnVgAQA4Lrx1jrTje8l0Nv7Y16+SYjo3/rgAAAAAmhTvxAEAANSTzWrRJae0q1LPzdeshnTxwHaEqwCA1m3AVY0frhpWqd0QwlUAAACgleLdOAAAgAYwZUCKGntbEJcpTR2Y0sijAgDQzHQZI9nbNO6YplMaeHXjjgkAAACg2SBgBQAAaAAJEUGa0j+50VaxWgxp8slJSo4KbpwBAQBorixW6bR7G288wyrFdZe6jm+8MQEAAAA0KwSsAAAADeTucSco1h7g85DVYkhRIf6adVZ33w4EAEBLceKfpA6nlYWtvmZIOvcVyWrz/VgAAAAAmiUCVgAAgAZiD/TTE+f3lenjvYJdpvTY+X0UHuTn24EAAGgpDEM6+3nJFigZPn6rY/jdUptevh0DAAAAQLNGwAoAANCAhnSO0d8m9fTpGPdP6K7Tusb5dAwAAFqc8CRp6oeSxeajkNWQel8kDb3NB30DAAAAaEkIWAEAABrYJae0098m9ZQhNdh2weX93D+hu6YPTm2YTgEAON60GyT96ZOylawNvV1w36nS2S9IFt5KAQAAAFo7wzR9vYkdAABA6/TDlnTd9v4aZeQVy1WPf3FZDCk6JECPnd9bI1i5CgDAsaVvlj6+Wtq/up4dWSSbv3TG36X+V5ZtRQwAAACg1SNgBQAA8KHcolI9/MUGvbtytwzJq6DVapSdf36/JM06q7vCAqm5CgCAxzZ/JX14mVSSV79++l4sjXtc8g9pmHkBAAAAaPEIWAEAABrB3qxCvbt8l97+OU1ZhaWSJJvFkKNC4lrx6/AgP00dmKIpA1KUHBXcJHMGAKBFcjqkBXdIq/6vrBar6apff4ZFCkuULn5fiu/eMHMEAAAA0KIRsAIAADSiUqdLmw7kav3ebK3dm6303GIVlzoV4GdVTGiAeiWGq3dSuLrE2+Vvo8YbAABecZZKH0yTNn4hqQHf7jCskn+wdOk8KfGkhusXAAAAQItEwAoAAAAAAFo+0yyru7ruAzVouFrOsEoBodKV30oxnRu+fwAAAAAtBssiAAAAAABAy/fbHGnd+/JJuCpJplMqziur6+p0+GYMAAAAAC0CASsAAEATmzFjRrXHly5dqptuuqmRZwMAQAuUs09acLskw7fjmE7pwHrpx6d9Ow4AAACAZo2AFQAAoIl9/vnn1R7v0KGD5s2b18izAQCgBVp4t+Qoks9Wr1ZiSosfkrJ2NcJYAAAAAJojW1NPAAAAoLU7ePCgUlNTqxw3DENpaWlNMCMAAFqQ7L3ShnmS6Wq8MU1Jq16XRv218cYEAAAA0GwQsAIAADSx6Ohoffrpp009DQAAWqZf35S3WwPnFpv6y6JifbKxVIfyTZ3YxqpnzgxU/0SrZx2YTmnVv6URd0m2AO/nDAAAAKBFI2AFAABoYna7Xb17927qaQAA0DKtfqcs8PTClfMLtf6QS7PPCVKC3aK315Zo1Ox8/fHnUCWGeVhNqShL2vad1HWs93MGAAAA0KJRgxUAAKCJffvtt8rOzm7qaQAA0PIUHJFy9njVpLDU1Ed/OPToqAANa2dTpyiL7h8RqE5RFr24qsTzjiw2ae+vXk4YAAAAwPGAgBUAAKCJTZ48WQUFBVWO5+TkaMyYMU0wIwAAWoh9q71u4nBJTlMKtFXeVjjIZmjpLi9Wwrqc0t5fvB4fAAAAQMtHwAoAANDEioqK1LZtW/fX06ZNkySFhYXp4MGDTTUtAACav/SNkuHdWxv2AEOnJln1tyXF2pfrktNl6u21JVq2x6n9eaYXPZnSwfXezRcAAADAcYGAFQAAoIkZRuUVNIsWLarxPgAAUEFJvtcBqyTNPidIpqTEJ/MU8PdcPbu8RFN6+sni7ctuaaHXYwMAAABo+WxNPQEAAIDWLi4uTnPnztWkSZM0e/ZsGYahN954QxEREQoLC2vq6QEA0HyZ3qw4/Z+OURZ9Pz1E+SWmcopNtbVbdOGHBeoQ6W1YW7fxAQAAALRsBKwAAABN7PHHH9dZZ52liy++WKeddpq++OIL/elPf5LL5dIbb7zR1NMDAKD58g+RTFedm4f4GwrxN5RZaOrLrQ49OjrQuw78gus8NgAAAICWi4AVAACgifXu3Vu7du1SZmamIiMjJUm//vprE88KAIAWILZbnQLWL7c6ZErqGm3R1iMu3f51kbrFWHVZXz8vejGkuO5ejw0AAACg5SNgBQAAaCbKw9WKjhw5oqioqCaYDQAALUBC3zo1yy42dfe3RdqTYyoqyNB5J9j0j5GB8rN6UYTVYpUST67T+AAAAABaNsM061iwBAAAAD534oknavXq1U09DQAAmq8nukm5+5tm7IvmSN3GN83YAAAAAJqMpaknAAAA0NoNGTJE//d//6f8/Pwq9xmGFytpAABojfpeLBnWxh83IEzqeHrjjwsAAACgyRGwAgAANLGrr75ab775ptq2basrr7xSP/30U1NPCQCAluPk6XWqw1ovhrVsXL/Axh0XAAAAQLNAwAoAANDELr30Ui1ZskSrVq1STEyMJk+erO7du+uJJ56odlUrAACoICJF6jaurCZqY+p3eeOOBwAAAKDZoAYrAABAM+NyufT555/rtdde04IFC1RSUtLUUwIAoHnL2iU9P0ByFDbCYIY0/A7ptHsaYSwAAAAAzREBKwAAQDOWlZWliIiIpp4GAADN36p/S5/d4tsxDKsU00W6Zolk8/ftWAAAAACaLbYIBgAAaMYIVwEA8NDJl0knTJQMH73VYVjKaq5O/jfhKgAAANDKsYIVAACgEZkul47s36tD27fq4I6tysvMlMvhkMVmU0hEpOJTOyq+Q2dFJiTI0ti15AAAaOkcxdK7F0vbv5NMV8P1a1glW4D0p7lSysCG6xcAAABAi0TACgAA0AjyszK17ruv9NuXnyk/K1OSZLFaZbpcMk1ThmHIsFjkcjolScHhEeo7Zrx6jRyj0Mioppw6AAAti6NEmn+jtOZdSYaker7tYVikkDjp4vekhL4NMEEAAAAALR0BKwAAgA+VFhdp6X9ma/XC+ZJpypt/ehmGIRmG+owep6EXT5N/YJAPZwoAwHHmj3nSJ9dIpQX166fn+dJZT0qBYQ0zLwAAAAAtHgErAACAj+zZ+LsWPPeEcg+nexWsHs0wDIVGRWvsdbcquUfvBpwhAADHqSM7pLnXSruW1a8fwyL5BUljH5X6TpUMo2HmBwAAAKBFI2AFAADwgfWLv9GXLz0jwzBkuupfA84wLDJNl0ZffYN6nz6mAWYIAMBxavdK6e1zylauupwN12+/K6Vxj0kWS8P1CQAAAKBFImAFAABoYOsXf6MvX3zaZ/2Pvvp69T79TJ/1DwBAi7VnlfTGWZKzRDIbMFwtd9J0acLTrGQFAAAAWjk+dgkAANCA9vyxXl++9IxPx/j6leeVtu43n44BAECLk3tAevtc34WrkvTrG9JPz/qmbwAAAAAtBgErAABAAyktKtIXLzwhw8erWgzDooX/ekolhQU+HQcAgBbDNKV5N0rFeb4LV8t9+6B0aKNvxwAAAADQrBGwAgAANJAf/vOm8g5nNEjN1dqYpkv5mZn6/u3XfToOAAAtxtr3pS1f+j5clSSZ0idXN2x9VwAAAAAtCgErAABAA8g7cli/LfxMjVXe3jRdWvvtQuVkHGqU8QAAaLZcTunbBxp3vP1rpM0LG29MAAAAAM0KASsAAEADWPvtl5KPtwY+mmEYWvvNl406JgAAzc7Wb6WcvY07pmGVVrzSuGMCAAAAaDZsTT0BAACAls7ldGrNV597tTXwPz77TpkFhVWOD+rYTuee3NOjPkyXS2u+/kKnTp4iq41/1gEAWqmVr5YFnjVsD7wkzaHHfirRL/uc2p9n6pMLgzSpm5/7ftM09dfFxXr111JlFZkanGzVi+MD1TnaWvOYplPavlg6vE2K7tjAFwQAAACgueOdOAAAgHo6vGeXCnKyvWpz06jBclXYTvhATp5e+X65eie39aqforxcZezaqfgOnbxqBwDAccHpKAs6a6m9ml9iqk+8RZf39dO571f9cNOjP5bo2eUlenNSkFIjLfrLomKNebtAf1wXqkBbbbtTGGVjE7ACAAAArQ5bBAMAANTTwe1bvW4TGhigsKBA938b9h1UdGiwOsZGNcr4AAAcFzI2S86SWk8Z29lPfx8ZqHNO8Ktyn2maenp5iWYNC9DZ3fzUO96qtyYFaV+uqbkbHbWPbbFK+3+rx+QBAAAAtFQErAAAAPV0cMc2Way1bCN4DA6nS7+k7dWA9skyvKzjarFaCVgBAK3X/jX1ar4jy9SBPFOjOvxvg6/wQEMDk6xatrvmVbGSJJdD2rOqXuMDAAAAaJkIWAEAAOop78hhuZzHeBO2Fuv3HVBRqUP9UpO8butyOpWXebjOYwMA0KLl7pMsda9+dCCvrH56fEjlDzjFhxg6kO9BbfXc/XUeGwAAAEDLRcAKAABQT87S0nq1X7F9t7q2iVV4UGCd2jtKat8aEQCA45ajiV8DnfX7NwAAAACAlomAFQAAoJ6sfnVfOXMkv0BbDmVoYIfkeoxftaYcAACtgrV+r4FtQsveFjmYb1Y6fjDfVJsQD94ysfAaDAAAALRGBKwAAAD1FBIRWecarCt37FFoQIBOaBtXp/YWq1UhEVF1agsAQIsXGl9WC7WOUiMMtQk19O32//WRU2xq+R6nTk324LU9NLbOYwMAAABoueq+3AIAAACSpLjUjnWqweoyTa3cuUf92ifJaqnb595cTqeKLDYdPHhQsbGxstSxHwAAWqS2fY55Sl6Jqa1H/ldPdUemS78dcCoqyFBKuEU3D/TX338oVudoi1IjLPrLomIl2A1N6naMt0wsNimpf32vAAAAAEALRMAKAABQT/GpnerUbsvBDGUVFGpAalK9xl+/I02/vfSSAgIClJycrJSUFKWkpCgxMVE2G//cAwAcx+JOKNum11VzLdRV+5w67c0C99e3flUsqVjT+vjpjUlBumOwv/JLTV09v0hZRaaGpFi18JJgBdqM2sd2OaW2fRvmOgAAAAC0KIZpmuaxTwMAAEBNnA6HXrx6qorz8xt9bP+gIF35rzd18NAh7dq1S7t27dLu3btVUlIiq9WqhIQEJScnq127dkpOTlZQUFCjzxEAAJ96c4K080fJ9H43iXr783IprlvjjwsAAACgSbGkAQAAoJ6sNpv6jBqrlfM/lulyHbtBAzEsFvU6/UwFBQerffv2at++vSTJ5XLpUIXAde3atfrpp58kSbGxse4VrikpKQoPD5dhHGOFDgAAzVn/q6QdSxp3TMMqJfUjXAUAAABaKQJWAACABtB71Fit+PTDRh3TdLnUZ/TYKsctFovatGmjNm3aaMCAATJNU1lZWe7ANS0tTb/88oskKSwsrFLgSh1XAEBLcyiqn6xFFkUFuNRonxkyndLAaxppMAAAAADNDQErAABAAwiPi1ePEaP0x5LvGmUVq2GxqOugYYpsk3Dscw1DkZGRioyMVJ8+fSRJBQUF2r17tzt0/eOPP+RyuajjCgBoUZYtW6abbrpJNw85WRcHrmycQQ2rFN1R6jahccYDAAAA0OxQgxUAAKCBFOXn6fVbZqgwJ1s+/SeWYSgo1K7Lnn5ZQaH2BumytLRUe/fupY4rAKDF+PDDD3XnnXfqxRdf1BmjRunXmxPVN6pIFvn4g06GRbrqOynhRN+OAwAAAKDZImAFAABoQDtWr9LH/7zf5+Ocfftf1KnfQJ/1f3Qd17S0NOXl5UmijisAoHn47bffFBQUpK5du0qS3n7+H5p88DEFWCVDvnqrw5CG3S6NvNdH/QMAAABoCQhYAQAAGtgvn3+qxW+96rP+h029TP0nnuez/qtzdB3XXbt2KSMjQxJ1XAEA3skuzlZWcZacLqf8rf6KC46Tv9Xfo7ZOp1N5eXmyWCyy2+3uY1arVStWrNCnT9+qv3fdIMN0SQ2+ktWQuk+SJv+fZLE2cN8AAAAAWhICVgAAAB/45fO5WvzWa5JhSA3xz63/9jP04ukacPbk+vfXAI6u47pv3z7quAIAqsgsytT8bfP1y8FftC5jndIL0yvdbzWs6hDRQX1i+2hE0ggNSRwiazUB5vbt2zX9/9m77/ioCuxt4M+90/ukh1R6r4oUFSzYaYoFWQt2V0VWXV2x/SxrZV9dV9fVtevauyAqFlRABaT3DimEkD693/v+EWfMJDOThGRS4Pnuh53MzG0TIZO5zz3nXHEFevXqhR07duDbb7+FyWSCLMuRTgpDhgzBvbOOxyx8DoSCgBxqvxcy9HzgvP8CClX7bZOIiIiIiLolBqxERERESbJnzUosfv5f8LqckKXDr6IRRBEavQFnXH8z+o05vh2PsH1xjisRETW0o2YHXt/yOr7e9zVCcgiCIECS478fKgQFQnIImfpMzBo4C38a+CfoVXoAwNdff4177rkH11xzDS688EL86U9/wty5czFlyhQAgN/vh1qtxvvvv493330XbzxxOyzf3Q5Ubgfa0i5YUNTPXJ10HzB+DitXiYiIiIgIAANWIiIioqTyOB344fX/YtuyHyGIYquC1vDyA4+fiFOv+jN0JnPyDjQJOMeViOjo5A/58cKGF/DKplcgCAJCh1FFKkJEhj4Dj5z4CMb2GIsbb7wRkydPxuTJkyHLMk444QRceOGFsFgsuOqqqyLrffzxx3j++efx0UcfwWrUA8ufApb+A5Cl+j8tPgAlIAWB3GOBc18AMvq3+jUQEREREdGRiwErERERUQeoKTuAjd99iY3ff4OA1wMIAgRBiApcBVGELMuALEOl1WLYKWdg+OlnIy03vxOPvP1wjisR0ZGv2F6MOUvmYL9tP+S2VI6iPmSVIOGSQZfglhG3QKvRoq6uDrNmzYJSqcTFF1+Mhx56CFOmTMGTTz4ZWa+mpgapqal/bMhZCaz7H7DqRcBx8PeNqwAp8McygghAqG8pLCrqZ60edy1QMK6+TT8REREREVEDDFiJiIiIOlDQ78ehfXtwaO9uHNq7C86aagQDfihVahhTUpHVuy+yevdDZu8+UKk1nX24Scc5rkRER449dXtwxddXwOF3HFbVajwCBJxeeDqemPgEpKCEb775JtIaePXq1bj44ouxatUqWK3WxBfnSCHg0Bbg4HqgbD1QsxcIuAGFGtCnAT2GAz1GArnHALqUdjt+IiIiIiI68jBgJSIiIqIug3NciYi6pwPOA5i1aBbsPnu7hqthAgRM7T0VD5/4cFRL+W+//RZvvvkm3njjDXY+ICIiIiKiDsOAlYiIiIi6LM5xJSLq+iRZwuVfXY7NVZuTEq429MiJj2Ban2kAgM8//xwPPvgg7rzzTsycOTOp+yUiIiIiImqIASsRERERdRuc40pE1PW8tfUtPPHbE0nfjwABOqUOH579Ib799FvMnz8f//vf/zBmzJik75uIiIiIiKghBqxERERE1K1xjisRUeepdFfirI/Pgl/yd8j+FIICeZ48vDTtJeh0Olit1g7ZLxERERERUUM8w0RERERE3Zper8eAAQMwYMAAAE3nuC5fvjwpc1xffPFF+P1+nHLKKRgyZEh7vRwiom7lo10fISgHO2x/ITmEIk0RBLMAq8HaYfslIiIiIiJqiBWsRERERHRES8Yc12AwiOeeew7vv/8+NmzYgF27diEnJwcA4PP5oFQqoVAokvq6iIg6W1AK4rQPT0O1tzruMq4dLlR9WQVPkQfBuiAKbi6A+Vhz5HnbahtqfqiBd78XIVcIfR7sA11h4otfREHEdcOvw00jb2q310JERERERNQarGAlIiIioiOaKIrIzs5GdnY2xowZ02SOa1FREdasWQOg6RzXzMzMmIGrIAj4y1/+grS0NLz33nuRFpUbNmzA66+/jsWLFyM7OxuzZs3Ctdde25Evl4iow6wqX5UwXAUAySdBW6BFysQUFD9bHPN5Q38DLGMsKHutrEX7lWQJn+76lAErERERERF1GgasRERERHRUEQQBKSkpSElJwYgRIwA0neO6detWSJKEq666Cnl5eU1CVlEUAQALFy7EiBEjoNfrAQD3338/cnNzsXXrVnz77bd46623cMIJJ2Dw4MFR63s8nja1JyYi6go2V22GQlAgJIfiLmMaboJpuCnu8yknpAAA/JWtm+F6yH0I1Z5qpOnSWrUeERERERFRexA7+wCIiIiIiDpbeI7r6aefjquvvhrz5s3D7NmzkZubm7Bl8JYtWzBu3DgA9a2It27diksuuQQAcPrpp6O4uBi//vorgPrWwQCwadMmnHXWWTjhhBNw4MCBJL8yIqLk2Vy1GZ05dWhr9dZO2zcRERERER3dGLASERERETWiUqnQs2fPSKVqY4IgoKioCG63O1KdKssy+vbti5KSEgBAaWkpVq9eDYPBAADQaDRYvHgx/t//+39QKBQYM2ZM3O0TEXUH22u2Q4LUKfsWBRG763Z3yr6JiIiIiIjYIpiIiIiI6DDs2rULvXr1Qm5uLgBAoVDg0UcfxQ033ICXX34Zubm5sFqtyMzMBAAsX74cjz76KJ577jk8/fTTyM3NRXp6eme+BCKiNnEH3J22b1EQ4Q523v6JiIiIiOjoxoCViIiIiKgVli1bhueffx6rVq3CkCFDoFarAQDBYBAjR46MtAR+/PHHceDAAQwYMAALFizAJ598go8//hhpaWmw2WzIzs6GSqXqzJdCRNQmMjqvPTBkQJI7p3qWiIiIiIiIASsRERERUSsce+yxuOCCC5Ceno5ff/0VFosFW7duxebNm+H1enHeeedh48aN+Oabb3D22WfDbDbjjTfewNKlS3HqqaeioqICKpUKI0eOBFA/u5Wtgomoq5NlGU6nE7W1tairq0NdXR0Q6MTjgQydUtd5B0BEREREREc1BqxERERERK2g1+sxY8YMzJgxAwDg8/mg0Wjw22+/4eWXX8Ydd9yBXr164aqrrsJ5550Hg8GAV199Fd988w1++eUXfPbZZzh48CBEUcRTTz0VaSEMAKFQCA6HAxaLBYIgdNZLJKKjkCzL8Hq9kQC1YZBaW1sLm82GYDAYWV6v1yMlPQV20Z5wuyFvCP5D/sh9f5UfniIPFEYF1GlqBJ1BBKoDCNbVb9tfXr+s0qKEyhq/yj8kh9DH0qctL5mIiIiIiOiwCbIsd2JPHyIiIiKiI095eTmys7NjPjd37lykpKRg2rRpGDZsWKTFsCRJ2LNnD9555x2YzWYUFBRE/mRkZLDKlYjazO/3R4Wmjb/2+XyRZdVqNaxWK1JSUmC1Wpt8rdFo8Nz65/DSxpcQkkNx9+nc5sT+J/Y3edx6ghV51+ahdlktDrxyoMnzGdMzkHVeVsLX890F3yHLkHgZIiIiIiKiZGAFKxERERFRO4sXrtbW1kKWZRQUFODYY4+Nek4URRQWFuLiiy9GcXExiouLsXXrVkiSBI1Gg/z8/EjgmpubC6WSv8oTUbRQKASbzRa3CtXtdkeWVSgUkbA0Ly8Pw4YNiwpSdTpds5X0Q9OGJgxXAcA4yIihrw+N+3zKhBSkTEhp3QsFYNVYkanPbH5BIiIiIiKiJGAFKxERERFRBwsGgy0KSAOBAA4cOIDi4mKUlJSgpKQEPp8PCoUCOTk5yM/PR2FhIfLz86HTcRYh0ZFOlmU4HI64AarD4UD4I74gCDCbzXGrUE0mU5tbkftCPpzy/ilwBBzt8fJaTCEocMmgS3DHcXd06H6JiIiIiIjCGLASEREREXUTkiShoqIiUuFaXFwMh6M+2MjIyIhqK8w5rkTdjyzLcLvdUeFpwxDVZrMhFPqjYtRgMMRt4WuxWKBQKJJ+zE+tfgpvbn2z2UrW9vbFeV+g0FzYofskIiIiIiIKY8BKRERERNRNybKMurq6qMC1qqoKACJzXMNVrpzjSkc7p9MJpVIJrVbbqcfh8/niBqh1dXXw+/2RZTUaTcwANXyrUqk68ZXUK3GUYMonUyBB6pD9KQQFxmSPwYtnvNgh+yMiIiIiIoqFASsRERER0RHE7XajpKQkEriWlZVxjisdFcLBZVZWVpPn/vvf/+Kmm27C+++/j/PPPx+yLCetwjsYDEa17W0YntbW1sLj8USWVSqVcVv4Wq3WbtP6+9/r/o0XN74IGck/vaASVfhk2ifoaemZ9H0RERERERHFw4CViIiIiOgI1pI5ruHQtbuEOXR0kmUZxcXFqKiowPDhw6HRaAAAP/74I2677TYEg0H06NEDc+fOxeTJkyFJEkRRhN1ux4QJEzB48GBMmjQJ11xzTZuOQ5Ik2O32mDNQ6+rqIm27gfo5qBaLJW4VqsFgOCJaeQdCAVyw8AIU2YuS3ir4jtF34PIhlyd1H0RERERERM1hwEpEREREdBThHFfqjmRZxrXXXotvvvkGpaWl2Lp1KwYOHAi73Y4TTjgBr7zyCsaMGYNt27bhlFNOwY4dO2CxWAAAd999N4YNG4bvv/8eAwYMwK233pqweluWZbhcrpjhaXgOqiT90Q7XZDLFrUI1m81HTWvuHTU7cNlXl8EX8kGS279dsCiIGNdjHP4z6T9QiMmfLUtERERERJQIe4IRERERER1FRFFEdnY2srOzMWbMmCZzXIuKirBmzRoAR+8cV1mWESgpgXfLFni3bkWwqhpyIABBrYYqOwvaIUOgHTIEyqwsBtAdRBAEXHnllXjhhRcwatQo1NbWAgBqamrgdDoxaNAgAMCgQYMQDAaxYMECXHbZZTh48CDWrFmDefPmYfPmzXC5XFAoYodzDocDb775Jurq6hAMBiOP63S6SGDao0ePJmEqW23XG5A6AC+c9gKu//Z6+CV/u4asoiBiZMZIPH3K0wxXiYiIiIioS+AnQSIiIiKio5ggCEhJSUFKSgpGjBgBoOkc161btx4Vc1yDVVWo++hj1L7zDoIVFfUPKpWALNf/CYepofoWqOqePZFy2aWwTJ8OhdHYSUd99Bg/fjxEUYRGo0FxcTHGjx+PgoICSJKETz75BLNnz8ZPP/0ElUqF7du3AwCefvpp3HzzzTCbzdDpdNi5cycWL16MiRMnQq/XR21fr9ejd+/eUS18rVZrpBUxNe+YrGPw6pmvYs6SOajz1bU5ZBUgQIaMk/NOxhMTn4BWqW2nIyUiIiIiImobtggmIiIiIqKEjvQ5rpLLhYp//hO1775XH6RKLQyFfg9cBbUa6X++HmnXXANBpUrikR7dwjNVp02bhokTJ+L2228HAHz//fd4/fXX8dtvv+Gcc87Bhg0bcNxxx+GOO+7A1KlTsWfPHmRnZ6O8vBxutxtTp07F448/joKCgk5+RUcum8+GJ1Y9gYV7F0IUxMMKWhWCAlqFFveMuwdTek9htTgREREREXUpDFiJiIiIiKhVjqQ5rq6Vq1A2704ED1W0PFiNRRCg6d8fOfPnQzugf/sd4FFKluUmf2/CAevcuXMRCoXw9NNPQ/V7oO10OqHX6yGKIv785z9Dr9fjqaeewooVKyAIAkaMGIGlS5firbfewt13342BAwciFArFbRdM7WP5geV4edPLWHNoDRSCAiE5lHD5cMWqVqHF9L7Tcd3w65Cpz+ygoyUiIiIiImq5I6efFxERERERdYjm5rgWFxd3yhxXr9cLjUbT4kC39t13Uf7Q3+srUdsSrgKALMO3ezf2X3ABcp/5F0ynnNK27R3hZFmGx+NBXV0damtro27r6uqg1WpxzTXXRK0T/u86fPhwfPfdd5Fw1e/3w/h7i+YlS5aguroas2bNAgCMGzcusn5mZiYMBkNkfivD1eQ7MfdEnJh7IvbU7cHHuz7Gb+W/YXftbgTlYJNlLWoLhqYPxSn5p2BKnykwqAydcMREREREREQtwwpWIiIiIiJqd43nuJaVlSV1jqssy3j66afRo0cPnHfeec3Ozax55x0ceujvbd5vE4IACALynvv3UR+y+v3+uAFqbW0t/H5/ZFmNRhM19zQtLQ2jR4+Oud2nnnoK8+fPx5/+9Cf07t0bs2fPxkUXXYRdu3bBYrFg7ty5mD17dqQKNlY1LHWeQCiAvba9sPlsCEpBaJQa5BpzkaXP4n8nIiIiIiLqNhiwEhERERFR0nXEHNddu3bho48+gtVqxaxZs2C1WmMu5/zpJ5Rc/+c2vJpmCAIEpRI9P/oQ2gEDkrefThYKhaIC08Zfu93uyLIKhSIqQG34dUpKCrRabbPhWjAYxMyZM7Fz507069cP2dnZmDhxIi6++GIcPHgQGRkZkbCeoSoRERERERElEwNWIiIiIiLqcMma41pRUYF3330XgUAAM2fORH5+ftTzIZsNe84+B6HaWiCZH4UUCmj69EGvjz+C8Hsr21gkScLKlSvhdrsxadKk5B3PYZAkCQ6HI26AarfbI8sKggCLxdIkPA1/bTQaGXgSERERERHREYMBKxERERERdbrGc1xLSkpQWVkJIHqOa0FBATIzMxPOcXW73Xj//fdx4MABTJ06FSNGjIg8d+DOebAvXNj2mastIQhIv3kOMm68MebT1dXV+Pzzz1FSUoJTTz0VEyZMSP4xNSDLMtxud9wWvjabDVKD75PRaIxbhWo2mznTlIiIiIiIiI4aDFiJiIiIiKhLaukc15ycHKgaVYmGQiF88cUXWL9+PY4//nhMmjQJgf1F2HvOOR36GgSNBv1+Xg6F0Rh5TJZlrFy5Et9//z1MJhOmT5+OwsLCpOzf6/UmbOMbCAQiy2q12qjwtHGY2vh7TERERERERHS0YsBKRERERETdQmvnuMqyjBUrVuCbb77BgAEDMGH3btjffQ8IhTruoAUBWffeg9RLLgEA1NTUYMGCBSgqKsKYMWMwadIkqNXqw958MBiMCkwbh6herzeyrFKpjDsD1Wq1QqvVtvnlEhERERERER0NGLASEREREVG31NI5rqFQCN9+8QXO/uBDKBtUbDa22u3GqzXV2OL1oTIUxDM5uTjNZAIABGQZz1RVYqnThdKAH0ZRgfEGPW7LyECmMkFlpyBAXViIXl8uwurVq/Hdd9/BYDBg+vTp6NmzZ4teo81mi1uF6nQ6I8uKohhzDmr41mAwcA4qERERERERUTtgwEpEREREREeERHNc8212jP/yy4TrL3U6sc7jwRCtFnPLDkQFrI5QCLeUHcAFFisGajWwhyQ8WnEIkgx82IKgdN1NN2JXTQ1Gjx6N008/PVK1KssynE5n3CpUm82Ghh/ZTCZT3CpUk8mUcDYtEREREREREbUPBqxERERERHREkmUZZWVl2LhxI4KffII+y5dDaOGnn8E7tkcFrLFs8ngws7gI3/Xug5xm5pOuPv105M04DxqNJipAraurQzAYjCyn0+niBqgWiwVKpbJlL4CIiIiIiIiIkoafzomIiIiI6IgQbhlcVFQUqWINt9A96VAFIIiALLXb/hySBAGAuZmqUUkQoCsrw9KlS6FWqyOBaZ8+faJCVKvVCo1G027HR0RERERERETJwYCViIiIiIi6LbfbjTVr1kRaAvt8PigUCuTk5GDEiBEoKChAfn4+Dl15FTxS+4WrPknCU5UVOMdkhlGhaHZ5o9eLQYMGYcSIEejbty8ULViHiIiIiIiIiLomBqxERERERNRtbdu2Db/88gvy8vJwwgknoKCgADk5OVA1atkr+Xztts+ALOO2sjLIAO7Pymp2eVEQkJWWir1VVXjvvfeg0+kwePBgDB06FIWFhRAEod2OjYiIiIiIiIiSjwErERERERF1W8ceeyyOOeaYmCGlLMvweDyw2WzwhULtsr/6cPUAyoIBvJZf0KLqVRmAzmjCjBkz4Pf7sWPHDmzZsgVr1qyByWTC0KFDMXToUPTo0YNhKxEREREREVE3wICViIiIiIi6JZ/PB7vdDpvNFvc2GAwCAI53u5EDIPG01MTC4WqR34/X8wtgbWGbX1mWsa2sDBv/+18AgFqthsViQW5uLnw+H1avXo1ff/0VZrMZ5513HnJzc5tU4BIRERERERFR18GAlYiIiIiIupxgMAiHwwGbzRY3QPV6vVHrGI1GWCwWWCwWZGVlwWw2R+7DaoX9xZeABJWsLklCsd8fuX8gEMA2rxcWhQIZSiVuKTuAbV4v/pObhxCAyt/DW4tCAXWCylNRljH+0ksweuzYqNdjt9shSRJUKhUCgQDsdjveeOMNAIBer48cf+Nbi8UCk8kEUWxLXExEREREREREh0uQZVnu7IMgIiIiIqKjhyRJcDqdcatObTYbXC5X1Do6na7ZwFGRoKLUuWwZSq69LuFxrXK7cEVJSZPHzzWbcVN6Ok7fuzfmeq/n52OM3pBw230Wfw11YWHc54PBYNTrj/W98TWYIysIAkwmU8LviV6vZ8thIiIiIiIioiRgwEpERERERO0mPPe0cVjY8L7D4YAkSZF1VCpVJBxsGBA2DA3VanWbjitkt2PXCSdCDgTa+hJbTZGRgX5Lf2pz2On1epttiRxqUKGrUCiafD8b39dqtW19eURERERERERHHbYIJiIiIiKiFvP7/U2qTRsHqOG5pwAgimJUsJefn98kQNVqtUmvtFSYzTBPmQzbgoUJ2wS3O1FE6iV/apfXp9VqodVqkZmZGfN5WZbhdrtjVsFWV1dj3759cDgcaHiNbXgebKwq2PCtUsmPjUREREREREQNsYKViIiIiIgAAKFQqElY2rhCMt7c03jVp0ajscu0qfVs2oT9F17UsTtVKNDvxx+gzMjo2P3GIUlSZLZtvJDc7XZHraPX6xNWwXIeLBERERERER1tGLASEREREXUAWZY7NWiUZRlOpzNhsOZ0OqPW0Wq1CYM1s9mccO5pV1R01dVwr1zZMVWsogjrzJnocf//JX9f7SgQCMQM2hve9/v9keXD82ATBe2dPQ9WkiRccsklEEURBQUFGDp0KGbNmsVgmIiIiIiIiA4LA1YiIiIiojYKBAKoqKhAeno6NBoNAKCsrAy33norysrK4HQ6cdlll+G2225Lyv5lWYbX640ZnjYMxxrPPY3XEra95p52RYGyMuyZPBmyx9v8wm0hilBmZKD3okVQGA3J3VcnaDgPNt5M2IbzYJVKZVT4GiuEDf/bSYZQKISff/4ZVVVV2LVrF9avX4+LLroI06dPx2uvvYZnnnkGer0eWVlZmD9/Pvr37w+g/t92aWkpsrKyoNfrk3Z8RERERERE1L0wYCUiIiIiakZlZSWKi4tRXFwMh8OBmTNnQqPRYPXq1bjxxhsRDAYhCALOPPNM/P3vf4dCocCcOXOQk5OD888/H2azGcOHD8fixYtxzDHHtHr/fr+/SYDVuKowEAhElhdFMVJRGG+2pk6n6zKtezta7Ycfovy+5FeVFrz2Kgzjxyd9P12RLMtwuVwJq2CdTmfUPFiNRpOwCtZsNrfbPNgnn3wSX3zxBV599VWMHj0aW7duRTAYxLvvvoulS5diwYIFsNvteOmll/Duu+9CkiQoFAo8+OCDOOecc9rlGIiIiIiIiKj7ap9Pp0REREQUkyzLCNXUQPZ6AYUCotEIhdHY2YdFrXTttdfC4XAgOzsboihi5cqVeO655zBnzhzcf//9mDx5MoD6YPPyyy/HwIEDsWDBAjz22GMYMGAAACA9PT1mRagkSc1WAno8nqh1jEZjJHTq06dPk4pAg8HA1qcJWC+4AP7de1DzxhtJ20fWffceteEqUN822Gg0wmg0IicnJ+YyoVAo0ra68d/5srIybN++vck8WIPBkLDy2mQyxb1wYPPmzXj22WfhdrsRCoVw7bXXoq6uDjk5OTAajTAYDEhNTcW6desAAD///DP++9//4ueff0ZGRgY++OADPPLIIzj99NOhUqna9xtGSROy2SC53YAsQ9DpoLBaj9qLS4iIiIiIqP0wYCUiIiJqZ55Nm+BYvBiejRvh3byl/sRuA8qsLOhGjIBu1ChYpk6BMj29k46UWurjjz+OzBotLy9H//798eijj+LAgQOorKyEJEnYuHEjzjzzzEib01deeQVPPfUUHnnkEezZswd/+ctfkJeXF7VdSZKwfft2fPjhh5HHwnNPzWYz8vLymlTxmUymdqviO1oJgoDMeXcCQPuGrIIAyDKy7rkHqZdc0n7bPUIpFIrI3+94wvNgY1Vv79u3r8k82BtuuAGZmZkxt9WjRw9MnjwZn376KXQ6Hc4991yEQiGcfPLJyM3NhdFoxLhx4/Dxxx8DADIzMzF8+HCsWLECU6dORVlZGSRJYrjaxflLSmBbuBCeDRvh3bgRodraqOdFiwW6YcOgGz4c5imToendu5OOlIiIiIiIujO2CCYiIiJqB3IwCNuChaj535vwbdsOKJVAMBh/hXB1oSDAdMYZSLvyCuiGD++Yg6XDUlxcjHXr1mHBggXIysrCQw89hK1bt2LOnDnYuXMnXC4X/vznP+OWW25Bbm4uVqxYgddffx0XXnghxo8fj4suughDhgzBI488EhWQut1uHDx4MBKgHolzT7sqWZZh+/hjlD/yCGR/AGgwM7TVRBEKqxU9HnkYplNOab+DpIRkWYbP54sEr717927RBQgzZszABRdcgNLSUhw8eBD33HMPysvLcd9992H27Nk499xzUVVVhcceewzvv/8+6urqMHHiRDz99NPo378/ZFlmFWQX41y2HDVvvA7Xz7/Uv8dKEhDvdIcg1C8TCkF/3HFInX05jJMm8b8pERERERG1GPuGEREREbWRb88e7J95MQ7efTd8O3bWP5goXAXqT/xKEhAKwfHNN9g/82KUP/Jok2pX6nzh6xF//fVXvPfee9i3bx9cLheqqqqwY8cOjBw5EkVFRXA4HNi/fz/+/ve/AwDeeustWK1WTJo0CXq9HhdffDHKysqwb9++qO3r9Xr06dMHGRkZDFc7mCAIsF5wAfosWgT92LH1D/5eqdxivy9vnjIZfb5cxHC1gwmCAK1Wi6ysLPTv3z9muOr3++FyuaIe27FjB+x2O5YuXYqTTjoJ6enpGDp0KKxWK1asWAEAuOuuu2AymVBSUgKn0wmVSoWvv/46sl/qGoI1NSj9yy0oufZauH5dUR+qhkLxw1Xgj2UAuNeuRemcm1Fy/fUIHKrooKMmIiIiIqLujr3FiIiIiNqg5q23cejxx/84kStJrd/I7yd5a99+G87vv0fec/+GdtCgdjxKaiwUCsHhcDSZ+5iXl4ehQ4dGzS8NBykzZ87EzJkzAQBz5szB448/juzsbOh0ukhb4DPPPBOffvopgPo5qb/88ktkOwcPHoTdbkefPn066mVSC6lyclD46ivwbNyImnfegf2LRfUXSSgU9f+2G/67bvCYoNPBesEFSJl1MduMdmGBQACzZ8+G3W5H3759EQgE0K9fP5x77rl47733UFlZGVl2/fr1uPLKKwEAixYtwiuvvBL5GTB06FCUlpbCbrfDbDZH1vnll18ijzVs6W00GjkLOcmcy3/Ggb/+FZLTWf/A4VSh/76O6+dfsPecc9DjsUdhPuOMdjxKIiIiIiI6EjFgJSIiIjpMlc88g6r/PN9+G5QkBMrLsf9Pl6DglVegP2ZU+237KCLLMlwuV8yZjeH7Docjah2tVguz2YyUlJQWBSIZGRlYtWoVRo4cGZmf6nA4sH37dmRlZQEArrzySlRVVWH06NGQZRlGoxGPPfYYA5cuTDd8OHKHD0f2XXfVz1DesgWezZsRrKiEHAhAVKuhzMmBbugQaIcMhW74MIh6fWcfNjXDYDDgn//8J/bu3Yvi4mLYbDbMmjULaWlp+Mc//oG5c+fi+eefhyiKOO6443DRRRcBAE499VQsW7YMQ4cORX5+Pr766itcc8010Df6b+5wOLBnzx7Y7faoebCiKMJkMkUC18YBrMVigU6nYzXsYbIv/gYHbrstcSvg1giFILlcOPCXWyA9/HdYzz+/7dskIiIiIqIjFmewEhERER2GqpdeQuWTTyVn46IIQatFz3fehnbgwOTso5tqPG+xYfVpwxA11KCKSalURgUasW7DFajx9lleXo7du3cjFAph48aN+Pnnn3HVVVfhuOOOwyOPPIKFCxfCaDRi4MCB+Mc//oHc3FwAQE1NDUpLS5GTk4P09PSkf3+I6PA4HA4cPHgQ2dnZkerUQ4cOYe7cuSgqKoLdbsf06dNxzz33wGg0xtyGLMvwer0xfy41/JklNaiIbu7nE+cyx+Zctgwl1/+5PlhNxikNQUDuU0/CfPbZ7b9tIiIiIiI6IjBgJSIiImol99p1KLrkkuSc1A0TRajy8tB74QKICcK/I00gEGgSRjS+bVghJghCVGVYrHCiPSrEVq1ahVtvvRXZ2dnIycnBxIkTceGFFwKon++oVCpZmUp0hAsGgzFnvLZGwwr7eD/j4lXYx/sZZzKZ2nxc3Umwqgp7zj6nvi1wst6HBQGCWo3ei76AOi8vOfsgIiIiIqJujQErERERUStIXi/2Tp2GwIEDhzdvtTUEAWlXX4XM229PuNiePXuwZMkSnHnmmSgoKEjuMbVBeO5pvLa9NpsNHo8nah2DwZCwvSZnHBLRkSbWjOjGPy8b/6w0Go0Jq/S7+s/KTZs2Ye3atTjjjDPQo0ePuMvJsozSm2+G84cfD2/eamsoFNCPGoWCN9+A0IW/d0RERERE1DkYsBIRERG1QsW//oXqF/6b3OrVhgQBvT77DNoB/Zs85fV6sXjxYqxfvx49e/bEhRde2GQ2YEeJNfe08a3T6UTDXz01Gk1UYNo4QDWbzUdVVRYRUUv5/f4mF6g0vh8IBCLLN54H27gK1mw2d+o82JqaGnzwwQeoqKjACSecgJNOOinmz3/HkiUovfGmDj22Ho89But553boPomIiIiIqOtjwEpERETUQpLPh10nToDUqH1jUikUsMyYgZy/PxT18Pbt27Fo0SL4/X6cccYZOOaYY5J2Yrzh3NN4J/NjzT2NFZg2vJ9o7ikRER2+xvNg4138EmsebKKuAcmcBxsKhbB8+XIsXboUqampmDZtGvLz86OWKbr0MrjXrk1+B4kwQYCmb1/0WvB5p4XPRERERETUNTFgJSIiImoh2+efo+zOeQmXWe1249Waamzx+lAZCuKZnFycZjJFnv93VSW+cjhQHghAJQgYrNXiL+kZGKHTxd2moFaj3/JlUJjNcLlc+Oqrr7Blyxb069cPU6ZMgdlsbtPrajj3NF6A2pq5p2azGXq9niejiYi6MFmW4XQ643YdCHceaEir1SYMYM1mMxQKRZuOq6KiAgsWLMCBAwcwZswYTJo0CWq1Gr49e7B38pSE6zb3HtzQA+Xl+MBWh3kZmbg8NTXhdgvffQf6UaMO+zUREREREdGRhz3XiIiIiFqo7uNPAFFMWDnjliQM0Ggxw2LF3LIDTZ7vqVbjnsws5KtU8Moy3qytwbWlJfi6V2+kxmmHKwcCsH+9GCUDB+Drr78GAMyYMQNDhw5tNsSUJCkyyy9eBZPb7Y5ax2AwRE6W9+rVq0krya4+y4+IiJonCAJMJhNMJhNyc3NjLtNwHmzj947S0lJs3bq1VfNgw+8hid67MjMzcdVVV2HlypVYsmQJdu7cialTp8L42eeAQpFw9mpz78Fh3zkc2OD1ILMlbegVCtg+/YwBKxERERERRWHASkRERNQCsiTBs3Fjs20JJxqNmGg0xn1+itkSdf/OjEx8bLNhh8+H8fFO9CpEbP70UywZOABDhgzB2WefDYPB0KT6KNYMvnhzT81mM3JycjBo0KAmJ8E595SIiABAoVDAarXCarXGXSY8DzZWF4Q9e/bEnAfbXBcEnU6H8ePHY8CAAVi4cCH+97//YcqKldAnCFeB5t+DAeBQIIBHKg7hxbx83FBa0vw3IRSqb0tMRERERETUAM+eEREREbWAv6gIstfbvtuUZXxgq4NJFDEw0TzSYAiqffsweMZ5UCgU+Oijj2LOPVUoFJEKobS0tEj1acMT15x7SkRE7UmtViM9PR3p6ekxnw/Pg43Xhr6kpKTJPFiVShVV9dqvb1+oP/yozccqyTLmlR/EVamp6NeK90P/3r2QfD6IfA8lIiIiIqLfMWAlIiIiagHfzl3ttq0fnU78tewAvLKMDKUSL+flI6WZqlGTzYaS4mJYU1JgsViQk5PTZP4d554SEVFXIwgCdDoddDodsrOzYy4T7sgQq5V9VVUVPCUlUAaDbT6Wl2tqoABwqTWldStKEvx790I7aFCbj4GIiIiIiI4MDFiJiIiIWkByOtttW2P0enzSsxfqQiF8aKvDbQfL8F5BIdIShKyiLMPrdMJUUIChQ4eib9++UCgU7XZMREREnaXhPNiwQCCA7du3Y8OGDXA6HG3exxavF/+rrcHHPXse1sVIksvV5mMgIiIiIqIjBwNWIiIiohaRm1+khfSiiEK1GoUARuh0OGvvHnxss+G6tLSE6508cSI27tiB9957D3q9HkOHDsXw4cORk5PDylUiIur2ZFnG/v37sXHjRmzduhV+vx8FBQWYOGEi8OVXbdr2GrcbNaEQJu3ZE3ksBGB+ZQXerK3Bd336Jj62ZmawExERERHR0YUBKxEREVELCFpt0rYtA/DLiU/cygD2l5UhLy8PhYWFqKmpwaZNm7Bq1SqkpqZi5MiRGDZsGKxWa9KOk4iIKBkqKyuxYcMGbNy4EQ6HA0ajEb169UJKSgp8Ph927y/CsDbuY5rFgvEGQ9Rj15aWYJrZjPMslmbXF3W6Nh4BEREREREdSRiwEhEREbWApnfvFi3nkiQU+/2R+wcCAWzzemFRKGBVKPDf6mqcajQiXalEXSiEd2prcSgYxJkmc8LtBtPSIIgiSktLYbfb4fF4Is/V1NRgyZIlWLJkCTIzM9GrV6+o2awWiwVGo5FVrkRE1GkkSYLD4YDNZouasbpr1y7U1dVFLet0OrFjxw4YDIb697H0NMgKBYRQKOE+Er0H56hUsDZqra8EkK5Qopda0+zxq3v1avFrJSIiIiKiIx8DViIiIqIW0PTtCyiVQDCYcLktXg+uKCmJ3H+isgIAcK7ZjPuzsrHP78NfymyoDYVgFRUYqtPif/kF6KdJcHJXoUDa8cdj1qxZkYf8fn/k5LTdbkd1dTVKS0sRCoWwZ88e2Gw2BAKByPKiKMJsNkcC18a3FosFWq2WISwREbWaLMtwuVxR70uNbx0OB2T5j3b7Go0GFosFBoMBqampyM/PR0pKStT7k7LBbPJ9H38C75YtCY8j0Xvwoz1yDvv1qfLyoDAaD3t9IiIiIiI68jBgJSIiImoBQaWCtn9/eLduTbjcGL0BWwcMjPv8M7l5rd+5LEM3dEjUQ2q1Gunp6UhPT4+zigyv19ukUih8W1JSArvdDqnBTDmVSpUwgDWbzVCr1a0/fiIi6ta8Xm/k/SP8XtL4fqhBdalCoYi8b6SlpcXsrKBJdGFRDLoRI+Ddvh1IUMXa3HtwY83NXQUAKBTQjRzZ4m0SEREREdHRgQErERERUQuZp02Fd9s2oEEFTkcxnXlmq5YXBAE6nQ46nQ7Z2dkxl5EkCS6XKyp4DX9dWVmJ3bt3w+l0Rq2j1WqjTpI3DmDNZjMUjVowEhFR1xUIBGIGpg3v+xu03RUEASaTKfJzv0ePHk3CU71e3+4dEcyTz0HtO++06zZbJBSC+ZxzOn6/RERERETUpQmy3AlnCImIiIi6oZDNhl0TJkJucKI56RQKGE8+GfnP/bvj9tlAKBSKeeK94a3X641ax2g0xqyC5TxYIqKO1XDuabz2vW63O2odvV6f8EIak8kEURQ7/LXIsoy9U6bAv3dfh17opMzMRN8flkDgxUNERERERNQAK1iJiIiIWkhhscA8bRpsn36asEVhuwqFkHrZpR2zrxgUCgVSUlKQkpISdxm/3x+zCtZut2PXrl2w2WwINphdG54HG+/kPefBEhE1T5ZluN3umD9/4809VavVkZ+3PXr0wMCBA5v8PFapVJ34quITBAGpl89G+f33d+ROkXLZpQxXiYiIiIioCVawEhEREbVCsKoKe84+B5LTmfwKGoUCptNOQ96/nk7ufpJMlmV4PJ6E7ScdDkeTebCJAtiuMA928+bNePrpp5GWloYhQ4bg0ksvhSiKcLlcMBgMnXpsRHT4AoEAysvLoVAokJOT02nH4fP54nYOCN82nnsaq217w/tarbbTXk97kINB7J95cbOzWNuFQgFVbi56L1wAsZXzYomIiIiI6MjHgJWIiIiolexffokDt/01uTsRBIhmM/p89SWUqanJ3VcXIEkSnE5n3BDBZrPB5XJFraPT6eK2IbZYLDCZTEmbB7t9+3ZceOGFuPnmm+F0OrFy5UpccsklOP300zF69Gj4/X6kp6cjIyMD11xzDaZNm5aU4yCi1pMkCRs2bMC+fftgs9lw2WWXAQCuuOIKrF27FlqtFlqtFtdddx2uuOKKpBxDMBhM2HrdbrfD5/NFlg/PPY33M89sNsNgMBwVlf++3bux99zzgAadEZJCENDzvXehGzEiufshIiIiIqJuiS2CiYiIiFrJdPbZsCxdBtvnnyevilUQkPPE40dFuAr80TbYbDYjLy8v5jLBYDAyS7BxEFFcXAy73R53Hmy8QOJw58H++OOPyMjIwHXXXQcA+Pbbb3Hvvffi+OOPR2ZmJh599FEUFBSguLgY6enprf+GEFHSfPzxx/jPf/4T+Vnz22+/4T//+Q/Ky8tx880344YbbmjT9sNzTxNV7ceaexr+2dSzZ8+YF4x0xtzTrkjTty+y7pqHQ39/OKn7yZh7M8NVIiIiIiKKiwErERERUSsJgoAef38IIYcdziU/tG/I+nvYl/PYozCdfHL7bfcIoFQqm50H6/P54lbBlpeXw263x50HG6ulZnp6eswqWLfbHRXmbt26FZIkYfny5VCpVMjKykJubi5yc3Pb95tAHSZQUQHvli3wbtmKUE015EAAgkoNZVYWtEOHQDt4MJQJ/i5S1zV37lwsXLgQo0ePBgAUFBRg9uzZ6NGjB9RqNTweD1wuV8xW5LIsIxgMoqqqKm71aby5p2azGdnZ2RgwYECTiz266tzTrir1kksQstlQ9cyzydn+7MuR9uc/J2XbRERERER0ZGCLYCIiIqLDJAeDOHj/A7B9/HF9MNrWX6sUCghKJXKeeALms85sn4OkKOF5sInactrt9kg4ctttt8FkMjXZTlFRER5++GE4nU6MHDkSixYtgtVqxbnnnotnnnkGfr8f2dnZmDt3Ls4999wOfpV0uEI2G+o+/RS1b7+DQElJ/YMKxR//vgUBkKT6PwA0gwYi9dJLYT7nHIg6XSceObWU3W7HqaeeiieffBInnXQSAKBv37645pprsGfPHnz//ffQ6/VISUnBzJkzMWvWLKSlpUVtY//+/XjjjTcA/DH3NFG7co1Gc1S07u0MNW++iUOPP1H/b7OtM1lFEZBlpN90E9JvupH/zYiIiIiIKCEGrERERERt5PjuOxy89z6EHI7DO8H7e3ijG30sch5/HOo4LXKpY4TnwdpsNuTl5cU9yb5//358++236NmzJ55//nnk5ubirrvuQlZWFhQKBRYuXIgXXngBd9xxB05mNXKXJnm9qPr3v1Hz5v8gBwL1D7bkY5IoApIE0WBA+k03IXX25RCSNPeX2s8ll1wCtVqN8847DwcOHMDzzz+PSZMm4cILL0ReXh4KCgpQWlqKCy+8EJMnT8a9994LWZYjPwv8fj8qKythsViOmrmnXZlnyxaU/e1O+PfuPfwLnUQRqpwc5Mx/AvpjjmnfAyQiIiIioiMSA1YiIiKidhCsrUXV88+j7qOPIbvdLatoVSiAUAiqwkKkX3sNLDNmQOCMvW7B4/FA16Bicfz48bjyyisjM1lDoRAUCgVOPPFEXHTRRZg7d25UQLNixQoAiKp0Y1DTOTzr1+PA3+6sr1ht40cj7bBhyHniCWh692qno6OWanhhRLgi3WAwYESMGZpOpxNvvvkmFi1ahAsvvBCrVq1CdXU13n//fQD1856VSiXuu+8+bNq0CZ999hkkSeIM1C5M9vtR8+abqHnjTQQrKyPvrwn9foGEIiUFKZdcgrSrr2IlOhERERERtRgDViIiIqJ2JLndsC1aBPtXX8G7aTMkhyPmcqrcXOiOPRbW88+HfsxxDNa6mYcffhjLli1DVlYWbDYbhg8fjttvvx0HDx5EdnY2rFYrqqurMXz4cLzyyis466yzotZ/9dVXUVZWhlCDAICtRjte3aef4eA999Tf+b3tb5v83uY7//n/wHD88W3fHgFofWtvAFCpVBg4cCBmzJjR7Pb/9re/oaamBi+//HIkXN27dy8eeOABDB48GPPmzYu6QIK6LjkYhPOnn2D77HN41q+vD1tjUKSmQjdiOCzTpsE0aRKERrN2iYiIiIiImsOAlYiIiChJZFlGsKwMvv37Ift8gChCYTJB078/FDHmelL3UVlZia1bt2LXrl0wGo24+OKLAQDTp0/Hnj17oNVqodFocNFFF+H666+HVqttsg1ZluF2uyMhUcOgKHzf4XBEhUZqtTpm8NrwMZVK1WHfh+6s7uOPcfCee9t/w6IIiCLy//sCjCec0P7bPwL5fL6E/w7sdjuCwWBkeVEUm/z9b3xfq9XGDUQ9Hg/WrVsHl8uFn3/+GTt37sRjjz0Gu92OCy64IFJNfsYZZ+Cxxx7rqG8DJUGwpga+XbshuV2ADIh6HTR9+kCZkdHZh0ZERERERN0cA1YiIiIionbmcDhQXV2NwsLCNlW9NWx7Gq9yz+VyRa2j1+sTVsGaTKajvtWp65dfUHz1NW1uCRyXKEJQKtHr00+g6dMnOfvoJoLBIBwOR8K/w16vN2odk8mU8O9wW9tp19bW4q9//SsOHjyInj17YubMmTj55JPh9XpRU1OD7Ozso/7fCBERERERESXGgJWIiIiIqBsLBoNNQqvGAZbP54ssLwgCjEZjwuq/7jgPdvfu3SgoKIC6mVafIacTe88+B8Hq6vZpCxyPQgHtwIHo+f57EJTKhIu6XC5UVVWhsLAweceTBOELABJVnza+AECn08X9exe+AEChUHTSKyIiIiIiIiJqGQasRERERERHOJ/Pl7CC0GazxZwHG6uCMHwbq+1xZ/H7/XjyySeh1+sxdepU9O7dO+6yZff9H2wff5zccLWBjL/ehvRrr435nCzL2LRpE77++mvodDrMmTOnywTbDeeexgtQHQ4HpAbfR5VKFbfqNByoNheAExEREREREXUHDFiJiIiIiI5y4XmwzYVpjefBJqqC7eh5sDU1NVi4cCH279+PkSNH4swzz2wSAvuLi7HnjDM77JgAQNDp0H/5MogGQ9TjdrsdX3zxBXbt2oUhQ4bg7LPPhqHRMsnk9/sTVj3bbLa4c08The5dJSAmIiIiIiIiSiYGrERERERE1CxJkuBwOBK2g3W73VHr6PX6ZtvBtuesS1mWsXbtWnz77bdQqVSYPHkyBg4cGHn+0Px/oOaNN4AG1bodIfuBB5By8cwWHWN7CIVCcdtGh+83nnvaXNtoo9HI8JSIiIiIiIjodwxYiYiIiIioXTScBxurItJms8Hv90eWFwQBJpMpbktZi8UCvV7f6mDPbrdj0aJF2LlzZ6Q6VKdUYtcJJ0JyOuOut9rtxqs11dji9aEyFMQzObk4zWSKPH/3wTJ8ZrdHrXOi3oAX8/PjH4wgQN27F/osWhRVZTtq1CicccYZrW61LMsynE5nwpbPzkavUafTxa065dxTIiIiIiIiotZjwEpERERERB3G6/XGnQMb/rrxPNhEbWktFgs0Gk2T/ciyjM2bN+Orr74CAJxdWAjl/Q8kPLalTifWeTwYotVibtmBmAFrVSiER7J7RB5TCwIsLQgnbU89ie/XrYPRaIw7J1aWZXi93oThqd1ujzv3NFZAzbmnRERERERERO2PASsREREREXUZDefBxgsZG8+D1Wg0cQNYlUqFX3/9FcFPPsWI9eshtPDjz+Ad22MGrHZJwr9z81r9upZNnIDc6dMxatQoeDyeuK8tEAhE1gnPPU0ULnPuKREREREREVHHU3b2ARAREREREYUJggCDwQCDwYCcnJyYy4Tnwcaqfj148CC2b9/eZB7seFsdZABtjSJ/c7tx4u5dMIsKjNXr8ZeMDFibqWCVBAEZNhtWr16N1atXRx4Pzz01m83o27dvk+pTzj0lIiIiIiIi6poYsBIRERERUbciimIkjIwnEAjAbrejoqIC27Ztg3HJEohtbN5zosGI00wm5KlUKPYH8HRVJa4vLcE7BYVQNBOEmnx+HHPMMRg0aBDS0tJgNps595SIiIiIiIiom2LASkRERERER5RgMIhdu3Zh48aN2LVrFwCgUBDbvN1zzObI1/01WgzQaHDmvr1Y5XZjvMEQdz0BgBgMYu3atdiwYQN69OiBXr16IS8vD2q1GiqVKuYfUWz7MRMRERERERFR+2PASkRERERE3Z4syygpKcGGDRuwdetWeL1e5OTkYNKkSejRowfcK1e2+z7z1WqkKBQoDvgxHvEDVhlAQJahVCoRDAZRWlqK0tLSZrcvimKT0FWpVLbosdY8L4oiWxETERERERERtQIDViIiIiIi6pZCoRBqamqwbNky7N69Gx6PBwqFAiqVCmq1GuXl5SgrKwMAHO/xIgdAe9aElgcCqAuFkKFs/mOVW6VCMBgEAOj1emi1WoRCITidToRCIRgMBuTl5WHAgAGRIDYYDCIQCDT5E37c7/fD5XI1eTz8R25hS2RBEFoUyCYKalsS8iqVSga5REREREREdERgwEpERERERF2OLMtwuVyw2WyoqqrCoUOHUF1dDZvNBpfLBa/XGwksGwqFQhAEAVqtFqmpqbBYLEhLS0OPkATx44+BUCjuPl2ShGK/P3L/QCCAbV4vLAoFLAoF/lNVhTNMJqQrFSj2B/BkZQUKVCqcqI9fvQoAoixjzMUzMWLMGNjtdthsNthsNtjtdqhUKtTV1cHlcmHHjh3YsWMHBEGA2WyG2WyGxWJpcmuxWKDT6RKGlbIsQ5KkmAFtvEA20fMejyfuOpIkteC/aL22hLWtqdRlkEtERERERETJxICViIiIiIg6lCzL8Hq9sNvtqKurQ1VVFSorK1FbWwu73Q6PxwOfzxd3fY1GA6PRCJPJhJSUFGRkZCA7OxsZGRkwmUwxZ5c6NRqUfPBBwuPa4vXgipKSyP0nKisAAOeazfi/rGzs9Pnwud0GeyiETKUSJxgMuDk9A+oWzEpNHzsWml694n4/fD5fVPDa8PbAgQOw2+0INQiHlUplVODaMJAN39doNFAoFNBqtc0eX1uEQqFmq21bGuQ6nc6464QShOONDRkyBCNGjEB6ejr8fj8cDgc8Hk/k75bf749sszUhbuNlOCeXiIiIiIjo6CTILe0bRURERERE1AKBQCAqIKysrERVVRVsNhucTie8Xm/cqkdRFCMBqsViQWpqKjIzM5GZmYmUlBQYDIbDqk4M1dVh54kTgBhVr8mmSEtFv2XLILQhjGtY0du4CjZ83+FwRK2j1WoTVsGaTCYoW9DeuKuQJClm+Nr4MYvFgoKCAsiyHPm7Ev77JghC1N+fUCgEt9sNm82Gurq6yJ+G399EYb9CoWj1DNzWhrgqlQoKhSK531wiIiIiIiJqFQasRERERETUYqFQCA6HIxLqhStQa2pq4HA44HK5YrbuDVMoFNDr9TCZTLBarcjIyEBGRgZSU1NhtVqh1WqT1t71wB1/g/3LLxO2CW53ooj0G29Expybkr6rxv9tGgewNpsNHo8nah2DwZCwCtZoNB51VZoNg9nw/VAoFAlwfT4fvF4vbDYb3G533ErdllTvtlTjObktaZ/c2uA3HOSyvTIREREREVHzGLASERERERGA2FWStbW1kdmnDocjYTUfUD9js2H1aXp6OtLS0mC1WmGxWKDRaDro1TTlXrcORbP+1LE7FUX0/eEHqLIyO3a/cTSuLm58a7PZooI/URRhMpniBrAtmQdLsTUOblszE7c16/j9frTmY397VuMmmqfLvzNERERERNSdMWAlIiIiIjoKxJvzWVtbG5l96nK5mg1itFptpPo0LS0N6enpkfDUYrFApVJ10CtqPVmWUXz5bLjXru2YKlZRhOX8Gcj5+9+Tv6920nA+brwqWLvdHtXiWalUxmxD3DCMVavVnfiqgNtvvx2//PILsrKy8PzzzyM7OxsAEAwG4XK5YLFYOvX4ki0c5B5OiNvceg2fa82c3ETha3uEuOHnjrYKbCIiIiIi6hgMWImIiIiI2igYDEIQhMicxNraWjz88MPYtWsXQqEQHnvsMQwfPjypxxAIBGJWI9bV1aG2thZOp7NJ615BEKICVUEQoNfrYTabkZaWhtTUVKSkpEQCVLPZ3O1nQfpLS7F38hTIzVTitpkoQpGaij5ffQmFyZTcfXWwhpXO8aphWzIPtnEYm6y/W7Is45tvvsGBAwdw6623Yv369ejVqxe8Xi+eeeYZvP322xBFEWazGU8//TRGjRoFAPB6vVizZg0yMzORl5cHnU6XlOM7ksSbk3s4YW2ixxO1IW9MoVAkraVywz8McpPnxx9/xLx587Bq1Sq88MILuO666wAAdXV1+Mc//oEdO3ZAFEVccsklmDp1auS/xbfffov9+/dDrVbj1FNPRX5+fme+DCIiIiI6wjBgJSIiIiJqRnl5OQ4ePIj+/fvDYDAAALZv3445c+bAZrPB7/dj9uzZuO222wAAd9xxB0KhEKZOnYpAIIAbb7wRq1evhtVqPaz9S5IEh8PRJNAKB6h2ux1erzdqnXD7zYa/7ofbvVqt1ibhqdVqPWrmbda88w4OPZT8qtL8l16EccKEpO+nKwrPg23897VhNWzjebBGozFhFazBYGjT388NGzbgqquuwjfffIO0tDQsW7YMU6dORXV1NRQKBV555RW89tprWL58Oaqrq/H4449jzZo18Pl8UCgUePHFFzFw4MC2fmuoHciyfFhBbaLAtq1zckVRbHF75MMNcZVK5VE5J3fnzp0wmUy44IILcPHFF+Omm26CKIq47LLLkJ2djYkTJ8LlcuHf//43Hn30UUycOBH//e9/sWTJEqSmpsJms8FsNuOBBx6IVK8TEREREbWVsrMPgIiIiOhI5/cGEfRLEEUBKo0CCtWRH2AdSf72t79hwYIF2LlzJ3766SdM+D0w+8tf/oLZs2djypQpUKlUMJvNmDx5MgYMGIDnnnsOmzdvRu/evQEAOTk5+N///ocbbrgBSmX0r+DhasBYIVRdXR1sNluT1r2iKEIQhCbtOJVKJcxmc8zw1Gq1Qq/XH3Un5mNJmTULvl27Uffuu0nbR+addx614SpQXzUY/nsXj9/vj9l+2GazYc+ePQnnwcabCRtrHqwsyxAEAdu2bYPJZIJer49sb+jQodi/fz/69OkDv9+PyspKAMCXX36Jzz77DLt27QIAvPXWW5gzZw6+++47SJJ0VFyI0JUJghAJHZsT9IcQ8IcAGVBqFFCpW14p3XhObltC3EAgALfbHXf5ll773vC1H05Y29JK3a40J7dv374QRRFarTby7xeor2x96KGHMHXqVADAnDlzIv+GH330Ufzzn//EjBkzAABjx47F0qVLcdFFF3X8CyAiOkqFghICvhCkkAylWoRKc/RdJERERzYGrERERETtrPqAE3vWVaJivx2H9tvhdTaogBEAS4YO2b0tyO5tQd9jM6E1dN2ZlQTMnDkT8+fPx/jx41FbWxsJV5YtW4brr78eKSkpqKqqwnHHHRc5QZ6eno6ff/45ErAeOnQIK1euxGWXXRYVOEmShO3bt+PDDz+MPNaw1XDjNpgajSZSfRoOThvearVanrRoAUEQkH3fvYAkoe7999tzw4AsI/P2vyLtyivab7tHKLVajfT0dKSnp8d8PjwPNl4VbElJSZN5sDfccAMyMzNjbm///v3Izs6OhHL9+vXDqFGjMHr0aADAySefjM8//zyybEFBQWRdnU6HUCiE8vJyVsB1ca46H3b+dgiH9ttxaJ8NzproduAGqwZZvczI6mlG32MzYU6P3/pZEAQolUoolcqktoiWZRmSJLVbJa7X6427TsN/L8053CC3uRC38TItfd9yu93QarWRCxzefvtt3H333XjnnXfgdDpxww034KSTTgJQX0XfcPazXq/HmjVrMHXqVLb7JiJKEr8niN1rK3Bwjw2H9tpQd8iNhtcPafRKZPasfw/uNSIdmYXmzjtYIqJ2wICViIiIqB3IkozdayuwcUkJyvfaIYio/zDZuCBFBmwVHtirvNixohzLPtiJ/mOyMeLUfKTnGTvj0KkZ4XmMRqMRJSUlkRO7X3zxBR5++GHccsstOHToEO68885IUPTQQw/hyy+/xPvvvw+LxYKePXvCbDbDbrdHBayiKEbdNxgMkaq/xtWnFosl6mQxtY0gish+4H5o+vZFxT/+ATkUAhpVBLeKQgHRYECPhx6E+ayz2u9Aj2KCIECn00Gn08UNNWVZhtPpjASwqampMZcRBAF79+6N2s6DDz6IlJQU1NbWwuFw4NJLL8Wvv/6KgQMHYty4cVi3bh0+/vhjjBs3Dh9++CEqKyths9mQnZ0d2SZ1HWW76rDh+2Ls21AVeSxWUairzod96yuxb30lfv10DwqHpmH4qXkoGJzWgUcbLXxhjUKhgFarTeq+Gge5bWmn7HK54q7Tmjm54RC7f//+OO+88+Iu5/f7oypYv/rqK0yYMAHHHXcctm/fjnXr1sH3+3ztW265Be+//z5KSkqg1+tRVFSEYcOGtbhSmIiIWq623IWNS0qx/deDCAYkCKIAWWr689bnDqJkaw1Kt9di9Zf7kVFgwvBT8tB/TBZEBbuDEFH3w4CViIiIqI1slW589/o2lO+xIXy+XW6mQCT8gVMKytixohzbfz2IY84oxHFTekKpann7Quo4eXl5OHDgQCRYqaurw+DBg/Hqq68iPz8f5513Hh5++GE8/fTTuOKKKzBq1Cjs2bMHp59+Ov71r39h+/btMUOirKwszJkzBxaLpUn7YEouQRCQetmlME6cgLK77oZn7VpAoWhd0Pr78qZTT0H2Aw9AmdZ5Ic3RSBAEmEwmmEwm5ObmxlwmfFGE3W7H8ccfD6VSCVmW8fPPP+ORRx4BAJhMJmRlZWH37t0IhUI4/fTTUVdXhxdeeAELFiyAy+XC+PHjI/9GGa52HT53AMs/2IXtK8rrT+i2ID9ruEzx1moUba5G71EZOGnWAOjNR/aFLKIoQqPRQKPRJHU/siy3OsRtbk653++PXGhUVlaGL774Al999RXy8vIAACNGjMBvv/2G3Nxc3H777Xj55Zfx22+/Yfjw4Rg4cCDy8vIiHSIaeuONN2JW3ra0nXLjP+E2/kRER7pQSMK6xUVY9cV+AH98xo0VrjYUfr6qxIHv39iGDUtKcNqVg5GWwwuOiah74RkcIiIiojbY+nMZlr67E1L4w+RhFEaEP2Cu/aYIe9dV4Kw/D+OHyySTZRlut7vJ3Mfc3FwMGjQo5nzFgoIC7N27F4FAAGq1Gj/++CNSUlLQs2dPAMC0adOwaNEi2O12mM1mjBgxAiNGjAAA7Ny5E7169YJarUYoFIo6watQKJDGUK5TqQsLUfj2W/CsXo2at96G49tvAUkClMr6sLXhP2xBAEQRCIUgqNWwTJ+OlFkXQzt4cOe9AErohRdewEsvvYR169Zh9+7dWLduHf7xj38gOzsbO3bswBlnnAGVSoXly5fj1ltvjfz7vPDCC3HhhRcCAGbMmIH8/Hzk5OQ02f6qVatgt9sjc2DDM2HZsjv5DuysxeKXNkda8Td3QjeW8AVR+zZU4sCOWpx25WD0HBa7bTW1nCAIUKvV7dJ5oeF7clZWFoD6iyJ2794d1fLYZrNFVQBfc801uOaaawAA//znP/G3v/2tSbAcCoVgMpkQCATg9/sjVbmxQuHDmZPbXCh7uCGuSqWCQsFZhkTUeexVHnz5wiZUlzoPexvhH6vVB5z44OHfMH5GH4yYlM+fbUTUbTBgJSIiIjpMa77ejxWf7W2/DcqArcqDT/6xBtNvGcWZNG3g9XojoWnj2/DXoQZViuGKHkmSMGTIkKhthT/gDxo0CGvXro2cLNbr9Vi6dGlkudLSUigUCpjNZhw6dAgvv/wyVqxYgYqKCowbNw7/93//B1mWY1bPUOcTBAH6446D/rjjEKyuhnvtWni3bIF302YEKyogBQIQNRqocnpAO3QodEOHQnfMMVCYTJ196NSMq6++GqeddhrKysqwa9cu7NixAwDwzDPP4KabbsL//vc/+Hw+TJ8+HRdccAEAYNGiRaipqUH//v2xYcMG7N+/H/Pnz485u7GyshK7d+9uMg9WpVJFQteGwWv4a7PZzLbfbbB/YxW++u8myJJ8WBc3NSZLgM8TxJf/2YjTrhqM/sdx1m5XMW/ePLz//vsoKirC9OnTYbVasX79ejzwwAO4/PLLkZ2dDa/XiwkTJmD8+PEAgI8++gh79uyB0WjEpk2bcMopp0TmszakUCgwY8aMZo8h3pzcw2237PF44q5zOHNykxXihp9n2EFEDdUcdOGzJ9fC6w60y/ZkCZAh4+ePdsNt92P8eX34c4eIugVB5gAKIiIiolbbsKQEyz/YlZRtCwKg0ipw/h2jkZpjSMo+urNgMNgkLG18G57BBtQHZ1qtNtK2L9y20Ov1Rp3E1Gq1GDx4MKZOnRpzvy+//DLuvfde3HDDDcjLy8N5552H2267DatXr4YoisjLy8O//vUv9OvXDy6XC0uWLIHP50OfPn3Qv39/GAz8b0nUVTkcDqjV6kh125dffom33noLBw4cQI8ePfD4449HqtXjkSQJLpcr5gUd4ftOZ3SVh06niwpcG1fBmkwmXpQRQ+mOWiz81/pI94j2JgjAWdcPQ++RGUnZPrWex+OBz+eDy+WC2+1Gv3794PV68dtvv8Fut8Pr9WLixInIyKj/b7Z48WIsXrwYDocDPXv2xLx587rNv6VQKBQ3rG3tzNxE64Ra0Q6/YQibKJCN91xLQ95YHUSIqGuxV3nw0ROr4XUFmh2Lc7iOm9ILY6b0Ss7GiYjaEQNWIiIiolY6tN+Oj55YDSTxtyhBBKyZesy8dwwUyqPnZJMkSXA4HHHDCZvNBrfbHbWORqOBVquNzEYMhULw+XzweDxRy+n1elitVlit1kh40fB+w7aCDYVCIVx88cXYvHkzCgsLkZ6ejrFjx+Lmm2+GzWaDy+VCdnY2TwoSUbNCoVDc6vrwrdfrjVrHaDRGVb82roY1Go1HVZWHx+nH2/evgN8dbJfK1XiUahF/emAcTKmx3xuIujtJkloVyCZaJtE6wWCwxcekUCgOu+q2Net0l7CdqKuRJBmfzF+DimLHYbXlb41pt4xE/sDUpO6DiKitGLASERERtUIoIOG9v6+ErcqTtCt2Gxp9Tk+MndY74TJFRUX44YcfMGnSJOTn5yf/oA5Tw7mn8YIFh8MRNeNMpVJBr9dDrVZDFMXIyUCPx9MkhDCZTJGwtOFt+GuVStXRL5mIqNX8fn/CKlibzRYVWIiimLAK1mw2d/l5sFu2bMH69etx+umnIzMzM+Gyi1/ejD1rK5L+HiyIAnIHWDFt7sgu/b0j6upkWW5VIHs4IW74T0uJotjqELe55WMtwzm5dKRZ/10xfv5od9L3IwiA3qLBnx4YC7WWEw6JqOviTygiIiKiVlj7TRHqKj1JrV5taM1X+9FvdFbMVsE+nw/ff/89fvvtN+Tl5SE1tXOv8PX5fAlDAbvdHhUKKBQKGAyGSPWpyWSCXq+Hz+eD2+2Gz+dDIBCAzWaLBAjxqk8tFgurEYjoiKBWq5GRkRFpddqYLMvweDxxf9YWFxfD4XDEnAebaCZsZ16EkpWVhdraWrz44ouYMGECTjzxxJg/04u2VGP36ooOOSZZklG6rRa7fjuE/mM4j5XocAmCEAkck0mWZYRCoXYLcd1ud8zl/X4/WlOr0p4hbqIWzAxyKdkcNV78+umeDtmXLANumw+rFuzDiRf165B9EhEdDlawEhEREbVQKCDhtXnL4XO1vNVZWwmigCEn5uCkPw2Ienz37t344osv4Ha7ceqpp2LMmDFJbVHbcO5pvJP6jeeeGo1G6HQ6qNVqKBSKqNmnLpcLfr8/srxCoYgbnlqtVphMJrbgJSJqIUmS4HQ643YLCLc3b0in08Wsgg3fJnsebDAYxE8//YSff/4ZmZmZmDZtGnJycqKW+eyf61C2q7ZDOkgAAAQgPdeImfeO6aAdElF3EA5yDyfEbUlL5bbOyU1GiBt+jr+PH3neeOMNSJKE008/HXl5eXGXW/HZHqz9pqjj3oMBKFUirpx/ItQ61ogRUdfEgJWIiIiohXb+Vo5vX9macJndZRvx3Yb3UVy1C3Z3Na4940GM6HVi5Pk5/50Uc71zx16H00bOjPlcww+WHo8HixcvxoYNG9CrVy9MnToVKSkph/+i8MeJ+Fjhafi28Yl4vV4Po9EYqT4VBAGhUAh+vx9utxsOhyPqpJBarY7butdqtcJgMPDKeyKiDhQMBuFwOGL+zA/fxmrFnqgKtj1+lh88eBALFizAoUOHcPzxx+Okk06CSqVC3SE33r5/RcJ1m3sPtrtr8PnKl7CtdA08fif6Zg/HhSfOQaYl/gllALhg3mhk9TS36XUREbVWvDm5LQ1sW/r44czJbUlV7eGEuOHn2Zmm4xQVFeHLL79ERUUFBg8ejEmTJjXpjNTchcaL172DDfuW41BdMVQKDXpnD8b0sdchy1o/vsbltWPR6jewvXQ1ap0VMOqsGN7zBEwZfQV0GmPC45t4cX8MOznx+zQRUWfh5R9ERERELbR1+UEIQn3Lonh8QQ9y0/pg/MCz8dI39zd5/tHLPoy6v6V4Fd756f9hZO8JcbcZDEjYs64CSLHhyy+/RCAQwNSpUzFq1KhmT2SHW0kmOoFut9ujWp2p1WqYzeZIiGqxWCLzs8LVp3a7HW63O7JOuPLJarUiPz+/SZDa1ef/EREdbZRKJVJSUhJepOPz+eJWwR46dKjJPFiFQhEVvsaaCavRaBK+H/To0QPXXHMNfvnlF/z000/Yvn07pk2bhrK1AQiiAFmK/yac6D1YlmW8uPj/oBCVuP7Mh6BVG7Bk44d49os7cO9Fr0Kj0sXcpiAK2P7LQQasRNThRFGEWq2GWq1O6n5izcltTdVtw+e9Xi8cDkfc5VtKFMU2hbUtrdTlnFygsLAQ119/PTZu3IglS5bgueeew+jRo3HSSSdBr9cDqG/Rn6iL0+6yjZg4ZBoKMwYiJIewcNUr+Peiv0XeX23uatjc1Thv3PXITumJGuchvLfsn7C5qnDNGQ8kPL6ty8sYsBJRl8WAlYiIiKgFZEnGoX22hOEqAAwpGIshBWPjPm/WR18NvKnoZ/TLGYl0c06cNepP7v7y3XqUyr9hwIABOOecc2A215/obXjyu3HL3nhzT81mc2TeqcViiVSfBgKBSBhbXV2NqqqqyHoGgyESlhYWFjapQtVoNIm/MURE1O1oNJoWzYONdRFPbW0tioqK4l7E0zh4bfiYSqXChAkTMHDgQCxYsACvvfYa8vzHQ5YSVzQleg+usJVif8U23HPhK+iR2hMAMHPCLbj7zQuxZvcSHD9ocuzXKMko213X/DeLiKib6qw5uYcb4gYCgUjXnHjLtrRhY/i1t7Z1cnPLN16mq8/JFUURI0eOxJAhQ7BixQosX74cGzZswAknnIBx48bh0D47RFGAFOcip5smPx51/9KT/4a73jwfJZW70DdnOHJSe+HaBkFqhiUHU4+7Gm8ueQwhKQSFGP/9vbrMiWAgBKWKVc1E1PUwYCUiIiJqAVuVB0F/+w6csbtrsLl4JS47+c6Ey8mSDFdlCENOGgKNRoMvvvii2faNRqMR+fn5kdmnwWAQfr8/0g6yuLg4so4gCDCZTLBarUhJSUGvXr2i2vlaLJakn3AhIqLuRxAE6PV66PV69OjRI+YyidrQHzp0CDt37ozZhj4cuGZnZ0On06NmmYy2nJoOhuorp5SKPyrBREGEUqHCnvLNcQNWAKgtdyMUkKBQcfYgEdHhEgQBSqUSSqUSOl3srgHtQZZlSJLU5hA3fN/r9cZdXpJa/vmwvUPceM+3JcgNX+B0zDHHYOnSpfjxxx+xevVqZDiPjRuuxuL117+v67WmBMs4oVXrE4arACBLQHWpC1m92EmCiLoeBqxERERELVB9wNnu21y58xtoVXqM7BW/PXCYGNBhz+6tsKZYYTabkZubi549e0IQBMiyDL/fH6kiqqqqQmlp6R/rimIkKM3MzES/fv2iqk/NZjPnHBERUVKIohhpGxxPMBiM2YEhfEGQrcoNk5zVpuPIthYgxZiJBatexqyJt0Kt1OKHTR+hzlUJm7sm4bqyJKP2kAvpefFPFBMRUdcgCAIUCgUUCgW0Wm1S9xUryD2cdsvBYDBhRW4oFGrxMTWek3u4IW6/fv2Qm5uL9evXo3anByJadsGtJEv46Jfn0Dt7KHJSe8Vcxumx4au1byW8uKmh6gNOBqxE1CUxYCUiIiJqAb+n5R9qW2rFjq8xuu8kqJTNz1USIMLn86O2thZVVVVRbX+VSmUkLM3JycHgwYOjZqAajUaIIqtuiIioa1IqlUhNTUVq6h9t9IPBIHbt2oWNGzei9qArwdoto1Aoce0ZD+Ltn/4f/vb6uRAFEQNyj8Xg/DEAmq/K8Xvb//cAIiLq3kRRhEajSfq4FEmSooLZww1xG87Jjfd8LGly/HE2jX2w/BkcrNmPW6f/K+bzHr8Lz399N3qkFGLysbOb3Z4gAH5v/PmvRESdiQErERERUQu0dI5PS+0+uBGH6kpw5Wn3tXid1JRUON0OBINB6HQ69OvXD6NGjUJhYWGXnulDRETUErIso7S0FBs3bsTmzZvh9XrRo0cPjB9/PLZ+7m1+A80oyOiPuy54ER6fE0EpCJPOin98ehMK0vs3f2ytaI1IRETUnkRRhFqthlrd/IW5bREeLRMOXfft24e1a9fCfbBl63+w/BlsLlqBW6b9EynGpvPbvX43/vPlPGhVelx7xkNQKFoQTQj1bYKJiLoiBqxERERELaBUt28F6K/bv0J+en/kpfVp8To3zbkREIADBw5ETj5v3LgR2dnZGD58OIYNGwaj0diux0lERJRstbW12LhxIzZu3IiamhqYzWYce+yxGDFiBDIyMlBX4cbWz1e02/50mvr3ygpbKYord2LK6CubXUepZit9IiI6sgmCAFEUsXv3bvz6668oLy9HVlYWlCoRodjFrQDqg9kPf34WG/Ytx1+mPYV0c9O57B6/C88tuhNKhRrXn/n3FnVxqt92+38WJyJqLwxYiYiIiFogJcvQouV8AQ8qbQci96sd5Sit2g29xoRUU/38OI/fhXV7l+K88X9u8f5NaVoIYn2Val5eHvLy8nDmmWdG2id+//33+Pbbb3HmmWdi7NixrXhlREREnWfx4sVYsWIF1Go1Bg8ejClTpkRmjIeZ0rQQFQKkUOIq0ubeg9fu+QlGnQWpxkyU1ezDRz8/h+E9T8Cg/NHNHqc1S3/4L5KIiKiL8/l8WLNmDVauXAm73Y4+ffrgsssuQ69evfDhY6tRWeyIu+4Hy5/B6t3f47oz/w6tSg/777PNtWoD1EpNJFz1B72Yferd8Abc8AbcAACj1gJRTHARkwxYs/keTERdEwNWIiIioka8Xi9sNhvq6upQV1dX/3WtDUAqgMSteIsqd+CZhX+N3P/k1+cBAGP7n4HLTrkTALBm9w+QIWN0n1NadDyCCGT3tjR5XKFQYODAgRg4cCA8Hg+2bduGrKyslr1IIiKiLqBv377IycnBgAED4rY+VChEpOYYUFXiTLit5t6D7e5qfPLr83B4amHWp2Js/zNw1jGXNnuMplQtNDqePiEioiOPzWbDypUrsXbtWgQCAQwbNgzjx4+P+lyZ1cuM6gPOuBc6Ldu6AADwr4W3RT1+6cl3YNyAs1BStQv7K7YBAB5877KoZR7809tIM2UnPMaMfFOrXxcRUUcQ5PYeKEZERETUhcmyDI/HEx2eNrr1ev+Y86ZQKGCxWGCxWODd3AMBe8e3CBQE4Pjz+2LkaQUdvm8iIqKu4Kd3dmDL8rIOn4UqiECfYzJx5jVDO3S/REREyVZZWYkXXngBKpUKo0ePxpgxY2A2m5sst+2XMix5c3snHCFgTNVg9qMndMq+iYiaw0swiYiI6IgiyzKcTmfCADUQ+GOAjEqlgtVqhcViQV5eHoYOHRq5b7VaYTQaI20K135ThF8/3QN08OVpsgz0HpXRsTslIiLqQvoem4nNSw80v2A7kyWg37HsDkFEREceq9WK888/H3369IFGo4m7XK/hGRAVO5pt1d/eBAHoPyZxdSsRUWdiwEpERETdiiRJsNvtUaFp+Ovwn1AoFFleq9VGwtLevXtHhadWqxU6nS5qzlsig47vgZWf7+3QD5aCCBQMToM5Tddh+yQiIupqcvpbYcnUwVbh6dD96kwq9Bye1qH7JCIi6ggqlQqDBw9udjmtUYV+x2Vh56pDHdpJQpaBIRNyOmx/REStxYCViIiIupRgMBgJShuHp3V1dbDb7Wg44UCv10fC0uzs7KgA1WKxQKvVttux6Yxq9D8uCzs68IOlLAHDT8nrkH0RERF1VYIgYMSp+Vj63s4O3Gf9e7CoEDtsn0RERF3RsJPzsGNFeYftTxAFFA5J5YXGRNSlMWAlIiI6CtTU1MBsNkOprH/rLyoqwh133IHi4mIYjUY8+OCDOOGEjplr4vf747buraurg9PpjFreZDJFwtL8/Pyo6lOLxQKVStUhxx027tw+2LOuEgFfqPmF20gQgcKh6cgfnJr0fREREXV1gyfkYMuyA6g56E76hU6CABhTtRjB+edERETI6mnGwPHZ2LGyHLKU/P2JInDChf2SvyMiojYQ5IYlIERERNQtlZaWory8HEOGDIFOV3+F56pVqzB37lz4fD4oFApccMEFmDdvHoLBIGbPno1jjjkG559/PqqqqnDuuediy5YtsFgsbToOWZbh9XrjVp/W1dXB4/mjtZ8oijCbzZGwtHF4arFYoFAo2nRMybBjxUF89/q2pO9HrVXgTw+Og8ESfx4OERHR0aSq1IkPHl3VISd3z7v9GOT0tSZ/R0RERN2Azx3A2w+shNfhR7IThRMv7IcRk/KTuxMiojZiwEpERNTN3XjjjVi8eDH27duHNWvWYNSoUQCA8ePH4/7778fpp58On88Ho9GI8vJyZGZmQqVSobq6GmazGQAwduxYXHbZZbjhhhsSBpqyLMPtdkeFp41vfT5fZHmFQtGkZW/DW5PJBFHsfm33ZFnGNy9vwe61FUASf5M6+/ph6D0qI3k7ICIi6obWf1eMnz/andR9HHt2IcZN75PUfRAREXU3JdtrsPCZ9Um70EkQgLyBKZh680gIopCcnRARtRO2CCYiIurmLr/8cjz33HM49thjUVtbC1mWIQgCfvvtNwD1Iee+fftw0kknIRSqb2ublpaGhQsX4pJLLoHD4cDBgwexYcMGuFyuSOgK1AeJGzZswObNmyMBajAYjDyvVqsjYWlBQUFU9anVaoXBYIAgHHkfigRBwGlXDobfE0Txtpp2DVllyBAg4ORLBjBcJSIiimHkaQXwOANY+3VRUrY/ZEIOxk7rnZRtExERdWf5A1Nx+lVD8O0rW9q9ilUQgKxeZpz95+EMV4moW2DASkRE1M2NGTMGgiBAp9OhpKQkEmh+//33mDdvHq6++mrU1NTgzjvvjFSLPvvss/jss8/w73//G3l5eRg+fDgMBgPcbndUwCpJEkKhEFQqFfr27RsVnlqtVmi12iMyQG0JhVLEOTcOx/evb8Wu1RXtsk1BFABZhsOyA9qcwnbZJhER0ZFo3PTeUGsVWPHZXggi2lxJI9S/BeOYMwsw7tw+R+3vN0RERM3pNzoLSrUCi1/aDCkkt9tc9PwhqTjrumFQqbvemCAioljYIpiIiKibkyQJoijioosuwrBhw3DfffcBAF5//XVs2rQJ9913H6xWK8455xwMHToU8+fPBwDs2bMHNpsNxxxzDO655x4cOnQIL7/8cme+lG5JlmXs+u0QfnpnBwJ+qU0fLjMLTTh19kB8/cMClJSU4Oqrr0ZGBqtYiYiI4jm4x4ZvXt4EZ62/TdvRmVQ4/eohyB+Y2k5HRkREdGSzV3nw7WtbUL7H3qbtiAoBEy/uj8En5vACJyLqVrrf0DMiIqKjmCTFL88oLCxEUVERAoEAAOCXX35BamoqrFYrAGDy5MnYu3cvPB4PZFlGnz59cMwxx8DpdGLHjh0YMWJEs/ugpgRBQP8x2fjTg+Mw6IQeUChb/uuV8PuixhQNJszsh/PvHI20HBMuuOACWCwWvPPOO3C5XEk6ciIiou5NlmRU7LfD7QgAbTkfKwBeVwCH9tohhfh7EBERUUvUlLlgO+Rp23swACkko3yPDX5PsPmFiYi6EFawEhERdRGyLMPj8cBms6Guri4y87Th/XPOOQdDhgyJtPoNrycIAt544w18/vnn+OSTTwAAf/3rX7F27Vr88MMPCAaDmDdvHurq6vDyyy+jtLQU//znP/HTTz/B6/VixowZeOihhyLVsHT4fO4Atq8ox+7Vh1BV4kQwEPtErc6kQo++Vgw+IQcFg1ObzJix2Wx46aWXkJKSgtmzZ0Op5GQHIiKisGAghMUvbcH+jVXtut2c/lZMvnE41Fq+7xIREcUiyzJWLdyH1V/urw9X2yFdEATAkKLBebcdA3O6ru0bJCLqAAxYiYiIOogsy3C5XFHhaeNbv/+P9nZKpTIy8zQ893TAgAHIyMiI2Tbnueeew9///ndceeWVKCwsxKxZs3DHHXdg6dKl0Gg0GDBgAJ588knk5+fD4/Fg48aNUKlU6NmzJ1JT2Q4vGSRJRt0hN2wVbgQDEgRBgFqnQHqeCXqzutn1Dxw4gNdffx0DBw7EjBkz2C6JiIgIQCgo4Yt/b8CBHbVo7zMaggBkFpox/dZRUGk4A46IiKixXz/djbWLi9t9u4IoQGtU4YK/HcuQlYi6BQasRERE7USSJDgcjqjQtHEVaigUiiyv0WgiwWn4tuHXer2+RYFaMBjExRdfjG3btqF3797IzMzE8ccfj6uvvhoulwuSJMFkMiXzpVMSbd26FR9++CEmTpyIU045pbMPh4iIqNN99/pW7FhZ3i4VM7EIAlA4NA3n3DicFzcRERE1sOnHUix9b2fSti+IgClFi5n3jWE3CSLq8hiwEhERtVAoFIpZdRq+tdvtUfNL9Xp9kwC1YZCq1Wo78dVQd7Js2TIsWbIEl1xyCfr27dvZh0NERNRp9q6vxFcvbOqQfZ16+SAMOr5Hh+yLiIioq6urcOO9h1YiFExunCAIwJAJuTjpTwOSuh8iorbiZSBERES/CwQCCatPHQ5H1PJGozESlubl5TWpQlWrm28BS9QSJ554InQ6HXr16hWZuUtERHS08boC+OGt7e027605y97fifxBqTCmaJK/MyIioi5MlmR8//pWNLimPHn7koHNSw+gzzEZyBvIcUZE1HWxgpWIiI4aXq83bnhaV1cHt9sdWVYQBJjN5pjVp+GZqEolr1OijtVcuBoMBvn3koiIjlgrF+zFmq/2t/vc1XgEUcCQCTk4aRYraIiI6Oi2b0Mlvny+YzpIAPVVrGl5Rsy8Z0yH7ZOIqLV4Bo6IiI4IsizD7XbHbeFbV1cHn88XWV6hUESC0qysLPTv3z+q+tRsNkMUxU58RURNJQpXKysrcfPNN+PZZ59FRkZGBx4VERFR8oWCEjb/dKDDwlWgvlpn+68HMf68PpwDR0RER7WNP5RCEAG5AypYgfoq1qoSJyqK7MgsNHfMTomIWomfEIiIqFuQZRlOpzOq+rTxbSAQiCyvUqkiYWleXh6GDh0aVYVqNBrZZpWOCOGq1oyMDAwaNAiXX345vvrqq84+LCIiona1d30lvK5A3OcXr3sHG/Ytx6G6YqgUGvTOHozpY69DljU/skwg6Mcnvz6PNXt+QDAUwKD84zDzxLkw6+O3Hwz6JexcWY6hJ+W16+shIiLqLmyVbpRur437fEveg99d+hR2HFgLm6saGpUOvbKGYPrYa5GdUhB3u4IoYNOPpZg0e3C7vh4iovbCFsFERNQlSJIEu90edwaqzWZDKBSKLK/VamO27g1Xoep0OgaodNSw2WywWCwAgD//+c8IBAJ45ZVXOvmoiIiI2s93r23Fzt/K41bOPLdoHo7tezIKMwYiJIewcNUrKKvZh3svehUalQ4A8N6yp7GleCUuPflv0KkN+GD5MxAFEbed+0z8HQtA4ZA0TJkzIgmvioiIqOvb+EMJln2wK+7885a8By/f+gWyrQVIMWXC7bVj0Zo3caB6Dx6c9RZEURF331qDElf9vwk8v0NEXRIrWImIqEMEg8EmM08bVp/a7XY0vOZHr9dHwtLs7OwmQapWq+3EV0PU+Xw+HzQaDQDgxRdfRFFREf7973/j6quvxuuvv965B0dERNTOyvfZErYlvGny41H3Lz35b7jrzfNRUrkLfXOGw+Nz4tftX+GKSXdjQO6oyDIPf3Al9h3ail5ZcapjZODQfnt7vQwiIqJup7LIAUEQEK9Oq7n3YAA4cfCUyPNppmxMPe5KPPbRdah2HEKGJSfuvr2uIFx1fhhTNO3wSoiI2hcDViIiahd+vz9u6966ujo4nc6o5U0mUyRALSgoiKo+tVgsUKlUnfRKiLq+rVu3oqSkBGeeeSYA4I477kCfPn0wc+ZMbNu2DaNHj0YoFMK2bdswdOjQTj5aIiKitgn4QrBVelq1jtfvAgDotSYAQHHVLoSkIAbkHhtZJjulACnGzMQBKwCvMwBXnQ8GK0/uEhHR0ad8nx2y1PImmI3fgxvzBTxYsWMx0kw9kGLMaHZ7FUV2GFOaX46IqKMxYCUiombJsgyv1xuzdW/4vsfzx0kvURRhNpthtVqRlpaG3r17R4WnFosFCkX8FjBElFh1dTXmzJmDH374AXl59TPhZs+ejX79+uH888/HRRddhCVLluC2227D448/jrPOOquTj5iIiOjwOWu9cdsSxiLJEj765Tn0zh6KnNReAAC7uwZKUQW9xhi1rFmXAru7ptltOmq8DFiJiOio5Kz1tnjZWO/BYUu3fI7PVrwIf9CLLGs+5kyeD6WimYvrhfr3YCKirogBKxERQZZluN3umK17w4/5/f7I8gqFIhKW9ujRAwMHDowKUE0mE0RR7MRXRHRkmzBhAv7617/isssuwyuvvIKDBw/itddew2uvvYaTTz4ZADBu3Dg888wzmDt3Lnr37o3+/ft37kETEREdplAwQW/gGD5Y/gwO1uzHrdP/1X7HEGjdMRARER0pQsGWX+WU6D34uL6TMDDvWNhdNfhu4wd49buHcNv0Z6BSquNuTxBa/3sAEVFHYcBKRHQUkCQJTqezSWjaMEgNBoOR5dVqdSQsLSgowPDhw6NmoBoMBgiC0ImviIj+/Oc/4+DBg7jnnnvw7bff4pZbbsHJJ58MWZYRCoWg0+kwceJETJ8+Hc8++yyeffbZzj5kIiKiw9KaC/c+WP4MNhetwC3T/hnVdtCsT0VQCsDtc0ZVsdo9tTDrU5s/BgV/9yUioiNPIBCA2+2Gy+WC2+2O+jp8K8vpAJp/L473Hhym0xih0xiRaclDz6xB+Nvr52LD/uUY3ffU+BuVAYWCF/ATUdfEgJWI6AgQCoVgt9vjzkC12WyQpD+u+NPpdJGwtG/fvlHhqdVqhVarZYBK1A08+OCDCAQCcDqdSElJQTAYhCiKUCrrf8XzeDwIhUKRNsJERETdkc7UTPtA1Hdk+fDnZ7Fh33L8ZdpTSDf3iHq+IL0fFKISOw6sxajeEwEAh+pKUOusSDh/NUxrbP4YiIiIOpMsy/D7/U0C0obhaePHA4FAk+2oVCoYDAbo9XoYDAaIakDyJd5vovfgmOv8/r9gyJ94ORnQGhhhEFHXxJ9ORETdQCAQaDLztOF9h8MBWf6jZYvBYIiEpTk5OVEBqsVigUbD+VFERwqVShWpUD3hhBMQCoWQmpqKmpoaGAwGrFixAq+99lpnHyYREdFh05nU0JlU8DiangQO+2D5M1i9+3tcd+bfoVXpI3NVtWoD1EoNdBojxg88G5/8+jwMGhO0agM+/PlZ9Moa3GzAqlCJsGTq2/U1ERERNUeWZXg8nphBabyvQ6FQk+1otdpIWKrX65GVlRUVoOr1+qivVaroi4q+tG3E/o1VkON0Cm7uPbjKXoY1e37EoLzRMGotqHNV4Zv170KlUGNIwdhmvw/pBabWf/OIiDqAIMvxfjQSEVFH8fl8catP6+rq4HK5IssKggCTyRQ187Rh9anFYolUrxHR0aGsrAyTJ0/GqaeeimuvvRZFRUUoKipCdnY2hgwZgj59+nT2IRIREbXJouc2oGhzddyTu3P+Oynm45eefAfGDTgLABAI+vHJr89jzZ4fEAwFMChvNGZO+EuzLYKze5tx/t9Gt+n4iYiIQqFQ3Da8sapMPR4PGp+6FwShSSDa+H7DW51OB4VC0abjXv3lPqz6Yh/kOKNQm3sPrnNV4Z2fnkRJ1U64fU6YdCno22M4zj72MmRZ8xPuW6EUcd0zJ0EU2WWNiLoeBqxEREkWvuIwXvVpXV0dvF5vZHlRFKOqTRuHp2azuc2/HBPRkWf9+vW45ppr8MILL2D06OiTwJIkRc2v27dvH+rq6jBq1KiOPkwiIqLDsu7bYvzyyW6gg89gCCJwzBmFGHcuL1YiIqJogUCgxdWlLpcLPl/TPrsKhSJmFWmswFSv10On03X4SKeyXXX49Mm1HbpPABAEIKd/Cs69lZ9biahrYokTEVEbybIMl8sVFZ42vvX7/5gpoVQqI2Fpbm4uBg8eHNXC12g0RgUhREQtMXLkSNx111249NJLsWrVKpjN5shzjX+mrFq1Ch6PhwErERF1GwPHZWPFp3sgdfA14rIEDD4xp0P3SUREHU+WZfh8vhZXl7rd7pjzS9VqdVQomp6enrDKVK1Wd3hg2lo9+lpgydDBVunp0P3KMjDspNwO3ScRUWswYCUiaoYkSXA4HFGhaeMAteGMC41GEwlLe/bsGVV9arVaodfru/wvz0TUPZ1//vnIzc2NCleB+pMFDX/uFBYW4rvvvkMwGGRLcSIi6hZ0JjX6js7ErtUVkKUOClkFoGBwKszpuo7ZHxERtRtJkuDxeFoUlIZvJalpD1ydThcVjmZnZ8etLjUYDEfk5ytBEDDslDws/2BXh+5XZ1Kh54j0Dt0nEVFrHHk/8YmIWikUCsWdfWqz2WC326N+ydbr9ZGwtH///lHhqdVqhVar7cRXQ0RHu3HjxkXdD4VCCAQCUCqVkQ/7hYWFCIVCOHDgAAoLCzvjMImIiFpt1BmF2PXboY7boQyMPCPxbDgiIuoYoVAobuvdWK153W53k22E55c2DEcbVpjGCk3ZYazeoPE9sObL/fC4Ah3Wrv/Ys3pCoeD3n4i6LgasRHTECwQCMatPw/cdDkfU8kajMRKW5uXlNZmBqlarO+mVEBG1niRJeOmll5CTk4MZM2ZAEARkZWVBo9Fg//79DFiJiKjbSM8z4thzemL1ov1J35cgAP3GpSO3X0qT5xrONt+1axfee+896HQ63H777Uk/LiKiI4Xf729RUBr+Otb8UqVSGRWIWiwW9OjRo0lQGr7VarXsKHaY1DolTr18EBb9Z2PS9yWIAjILTBh2Sl7S90VE1BYMWImo2/N6vXFb99bV1UVdtSgIAsxmM6xWK1JSUtCrV6+oANVsNh+R7VyI6OilUqkwadIkfPjhh0hNTcUpp5wCURRRWFiIoqKizj48IiKiVhl9dk/sXVuJ2kMuyE07ObYLQQQMVg1OvnhIzMolt9uNnTt3Yv78+bBYLPj0008xatQoXHHFFUhPZytDIjr6yLIMr9fb4upSl8uFYDDYZDtqtbpJdWlBQUGTNrzhW5VKxcC0A/Ucno7+Y7Oxa1U5kjkSXRCASVcMgijyvy0RdW1MEajLk2UZciAA2R+AqFYB/OXpqCLLMtxud9wWvnV1dVFXMSoUikhgmpWVFWnhG64+NZvNbO9CREedwYMHY9KkSfj++++RlpaG4cOHo7CwED/88ANCoRAUCkXcdUMhCaGABIVChKgU+B5MRESdSqEUMfmm4fjoidXwugLtHrIKIqDSKDF1zkioNE3fH7dt24b58+cjLy8PF154IVJTU1FaWopbb70V6enpWL9+PX799VdMmTIF+fltay8shSQEAxJEUYBCKULgiWYi6iDh+aWNg9J4M0wTzS9tGI4mqi7V6/W84L0bOPlPA2A75EZFsT0pFzoJAnDmtUORkm1o/40TEbUzQZaTeb0JUevJwSCcy5bBvXIVPJs2wrt1G2SPJ/K8aLFAN2wYtMOGwjhhAnSjRvFkbzcmyzKcTmfc6lObzYZAIBBZXqVSRcLSxq17rVYrjEYj/z4Q0VFNlmWsX78earUaAwcOjISnsixjwYIF2LRpEy6//HIoFAq8/PLLuOqqqyIngGVZxqF9dhRtrkZFkR0V++3wuv64slypFpGeb0JWTzNy+1tRODQNImfiEBFRJ6gtd+Gzf66DxxGALLXPaQ1BBNRaJabfMgoZBaYmz7vdbtx666346KOPUF1dDQC4+OKL0bNnTzz++OP4z3/+g9deew2jR4/GypUrMWXKFDz00EMt3n/dITf2rq9ERZEd5XvtcNX9cSGpKApIzTEgq5cZ2b0t6D0qA2otgwgiaplgMBi3ojTWY54G5+HCRFFsUkUaLyg1GAzQ6XS8wP0I5XMHsPDZDajYb2+3SlZBqP+/M64egr7HZrbPRomIkowBK3UZwdpa1L3/PmrffgfBykpAqQRitAsBUP+uK4pAKAR13z5IvfQyWM6dDlGr7diDpmZJkgS73R53BqrNZkMoFIosr9VqI2FprABVp9MxQCUiSsDj8eD9999HUVERTCYTRo8ejWOPPRYGgwGhUAhvvfUWDh06hKuuugovvfQSTjzxRIwfdzx2rCjHxh9KUVPmgiAKkGUZiPNboqgQIIVk6EwqDDs5D0Mn5kJn4nxqIiLqWM5aL757fSsO7Khrl+1l9TTj9KsHw5Khj7uMz+fD3LlzsXz5cgwZMgQejwfPPPMMevXqhYceeghKpRJ33303PB4PzjvvPMybNw8nn3xy3O3Jsoz9G6uw8YdSlG6vRfijTrwzNaIoQJJkKNUiBh2fg+Gn5MGaFf94iejII8syAoFAi6tLXS4X/H5/k+0olcqY4Wis0NRgMECj0fB8DEUE/CEs/3AXti4rgyDEf99qCUEA9BYNzrh6MHJizD4nIuqqGLBSl2D/6isc/L/7IblcQIyWIgn9/i6uKihA7vwnoBs5MinHSLEFg8FIUBqrCtVut6PhjxmDwdAkQG14q2VITkTULsrLy7Fq1Sps2rQJsixj6NChGDNmDFJSUvDyyy9HZlLLbi0UZfmwVXgAAXFD1XgEAVBpFTjpTwPQb3QWT7oQEVGHkmUZW5eXYfmHuxAMSIf1PiaIAsaf1wfDT81POO9NkqRINdaPP/6ICy64ACqVCitWrEBRURG+/fZbfPTRR3j99dcxduxYpKWl4dVXX8X06dMhy3KT90hHjRdL3tiG0h21EES0utWiIAKAgDFTemLUmYVQsKsEUbcUnl/akrml4a9jzS/VaDQtri7V6/VQq3mBJLVdybYafP/GNrjqfK0OWsPvfUMn5mL8jD7szEBE3Q4DVupUIacLB+++G45vvkGbL3cSRUCWkXbNNci45S8QEsyTo5bz+/1xq0/r6urgdDqjljeZTFFVp42rUFUqVSe9EiKio5Pb7ca6devw22+/wWazIS8vD4MGDcKypcugdxZCqMqAKArtMj+n18h0nDZ7MNQ6fjAmIqKO5XUFsO2Xg9j0QwkcNb5Iq8HG7YMFEYBc/9FTb1Fj2Ml5GHxCDvTmlgUN4ZD1r3/9KyoqKjBjxgwsWbIEX3zxBZ5++mkUFxdj3rx5mDx5MgwGA1555ZWYLTJ3rCzHj29vRygot0uL47Q8I866biismaxmJepskiTFbcMbr8o01unZWO1441WX6vX6yGgQoo4WDISwZ00FNv5QiooiB4A/uh411PC9WaVRYNAJPTB0Yi7nrRJRt8WAlTpNyGZD0ZVXwbd9e+urVpthPuds5MyfD0HJE7yJhK+SjBee1tXVRc3dEEURZrM5bvWpxWLhL/RERF2UJEnYuXMnVq1ahX1798HqGAyFKxUC2q/iVBCBtBwjpt8yClojL6ghIqKOJ0syyvfVzxGvKLajqtiJgC8EGfUnc9PzTMgoMCGz0IQefa0JK1YTefPNN5GSkoKpU6di4sSJmDRpEu6//34AwMKFC/HTTz9h/vz5McPV9d8V4+ePdrfpdTYmiAI0OiXOvW0U0nKN7bptoqNdMBhscXWpy+WC1+ttsg1RFGNWkcarMuX8UuquqsucKN9jQ2WxAxVFDvjcAUghGQqViJQsPTJ7mpFRYEJu/xSoNDyHSETdGwNW6hSS242i2bPh3boNaDB/s90IAszTpyHnsceO6laFsizD7XbHbN0bfqzhHA6FQhEzPA1/bTKZ+As+EVE3J8syvnxxHfavqwXaMVwNE0QgLdeI8/56DFs8ERHRES1czfrwww9DlmXcd999AIB7770XJSUleOONN6KWl2UZW5aV4ad3diTleAQR0OhUOP/OY1nJShSHLMvw+/2tqi6NNb9UpVLFDUdjPc75pUREREceBqzUKQ7e/wDqPvyw3StXG8t+8EGkzLwoqfvoTJIkwel0xg1QbTZb1FwOtVodt3Wv1WqFwWDgL/xEREe4rT+X4Yf/bU/qPgQBGHh8D5x62aCk7oeIiKgr2LRpE+bMmYO0tDSMHj0ab7/9NubNm4dLLrkkcoGqLMso2VWFhf/c1Oo5sa0hiALScgy44K7RnMlKRwVZluHxeFoUlIZvQzEu9NdqtS2uLjUYDBx/RERERAxYqeO5fv0VxVde1SH7ErRa9Fn0BVS5uXGXcTgc+PLLL+HxeHDFFVd0yHG1VCgUgt1ujxue2mw2SA1Cap1OF7N1bzhI1Wq1DFCJiI5ijhov3nlgBYL+5F7gFDb15hEoGJLWIfsiIiLqbM899xyqq6tx4okn4qSTTooanxIKSnhl3hIEnAKS0UGisbHTemP0OT2Tvh+i9hYKhRKGo7EC1ManNgVBgE6na3F1KeeXEhER0eFgwEodSvb7sfuMMxGsqEh69SoAQKGA4fjjUfDSi02PRZaxceNGfP3111AoFJg+fTr69euX/GNqIBAINJl52jBAdTgcUR8UDAZDk6rThrcajaZDj5+IiLqXRc9tQNGWGshS8n/9EwRAZ1bj8oePh0LFChoiIjp6SZKEZR9vxabvD7Xr7PNEBFHAn+4fC2sWWwVT5woEAi0KSsNfx5pfqlAoWhSUhm91Oh0vLiciIqKk42As6lCO775DsLy843YYCsG1bBl8e/dB07tX5GG73Y4vvvgCu3btwrBhw3DWWWdBr2//D54+ny9u9WldXR1cLldkWUEQYDKZYLVakZKSgp49ezZp46tU8p8sEREdnroKN/Zvqu6w/cky4Lb5sXttBQaMze6w/RIREXU1UkjGlqXlENCxFxxt+qkUEy7q36H7pCObLMvw+Xwtqi4N3wYCgSbbUalUUaFoamoq8vLy4rbmVavVDEyJiIioy2FaQx2q5q23AVHsmOrVMIUCde+/h6y77oIsy1i/fj0WL14MlUqFiy++GAMGDDiszYbnfDSuPm14v+GVl6IoRgLTjIwM9O3bNyo8NZvNbElDRERJs2XpAQgiIHfgW7AgABt/KGXASkRER7V9G6ogBzo2XJUlGdt+Pohx0/tApeHnTIotfF6jcSgab4ZpovmlDQPRrKysuNWler2e80uJiIjoiMCAlTqMv7gYnrVrEy6z2u3GqzXV2OL1oTIUxDM5uTjNZIpaZo/Ph6cqK/Gbx42QLKOPRoOnc3KRE+8X9FAIdR99DM3112PRV19h9+7dGDFiBM4880zodLq4xyLLMlwuV8zWveHHGl6JqVQqI2Fpbm4uBg8eHBWgGo1GiCJbJBIRUceTJRlbfz6YMFzdXbYR3214H8VVu2B3V+PaMx7EiF4nRp73BTz4fOVL2Lj/Z7i8dqSZsnHSsBmYMHhq/P3KQMV+O2rLXUjJNrTnSyIiIuo2ti4vgyDUvy/GsnjdO9iwbzkO1RVDpdCgd/ZgTB97HbKs+ZFllm/9Aqt3L0Fp1S54A27Mv+Jz6DXGhPsN+ELYu76SFzq1UiAQwA8//IC0tDSMGjUKoihi/vz5WL58OQ4ePIjTTjsNt99+O9LSut6c+fD80kQVpQ2/9ng8MeeXNq4iTU1NjRmUGgwG6HQ6XixORERERyUGrNRhPOvXN7uMW5IwQKPFDIsVc8sONHm+2O/HpcVFON9ixU3p6TCKInb7fdA00ypGcrnw9vz58GVmYtasWejfvz8kSYoZmjZ8rOGVmRqNJhKW9uzZs8ksVL1ez5Y1RETUJdVVuOH3BBMu4wt6kJvWB+MHno2Xvrm/yfMf//I8dpatw+Wn3oU0Uza2lazGB8v/BYs+DcN7Hp9w24f22RmwEhHRUUmWZJTvtcUNV4H6i5wmDpmGwoyBCMkhLFz1Cv696G+496JXoVHVXxQcCPowOP84DM4/DgtWvdyifYsKAeV7bQxYW0iWZQiCgG+++QZTp07F1VdfjZdeeglvvvkmtm/fjmuvvRbDhw/HtddeixdffBF33XVX0o8pEAjErS51uVxNqk99Pl+TbSgUiqhw1Gw2Izs7O+4MU61Wy3MbRERERC3AgJU6jHfLFkCpBILxT/BONBox0Rj/Ktx/VVViotGI2zMzI48VqNUt2n8PjwdyYSF++eUXfPXVV7DZbFFXaur1+khY2r9//6jw1Gq1QqvVtmg/REREXU1lsaPZZYYUjMWQgrFxn993aAvG9j8D/XNGAgBOHDwFP2/7AkUV2xMGrKJCwP9n777j2yjM/4F/7rS3vEecxNkmOyEkJIEQMkgghBnWt8yyW6DsMtrSMlpKyygUGmiBFkp/ZTWMhJ1AICSQ5ezpDDtOHMdTe9/9/jASki3ZsmPJ6/N+vfKSJZ3uTo4tWfe553mOVThQMrWg3ftNRETU09lqPAj6W+/P//MFj8dcv3zmvbj/tQtxqGYvhhaOBQCcPvZCAMCeI5uS3rYUklF90N6+He7DBEFAQ0MDVq5ciVNPPRW5Pxx3WLlyJYLBIBYubOraYbVa4fF42r3+8PzS1ipKmweowTjHT9RqdUwomp2d3aLiNPprzi8lIiIiSg0GrJQ23p07Ww1X2yLJMlY6Xbg2MxPXHzqEnT4v+qlUuD4zq0Ub4RaPFQSoKg+juqEBGRkZKCoqiglQLRYL1EkGtURERD1N3WEnRIUAKdRK+UwbBuWNwtbyNZhaMh8WfTb2HtmEY7ZKXDj1Z60+TgrJSQW8REREvVHdYWe7H+P1uwAAem3rn3OTUX/YGanMpMTC36Onn34agwcPxvDhw7FixQrYbDbce++9ePLJJzFx4kTU1dVhzJgxuPbaa+Oux+VyYf369QlnmEpSy7Bdp9PFBKIFBQUJq0v1ej2USh7KIyIiIuoO+FcZpU3IdnxnztaFQnDLEv5RX4fbsnNwZ04OVrlc+MWRw/hn/wE4Sa9v9fGi14OGhgYUFBRgxIgRKCoq4odMIiLqE3yeENDxbBUAcNEpt+D/ff0UfvXvSyGKCogQcdlpd0Yqa1rdvjvQ5jJERES9ka+NFv3NSbKEd1Y/j8H5o1GYOei4tx8KypAkGQoFP/u2RhAEbNiwAQ6HA1dccQVWr14NAJHAU6vV4uqrr8b8+fOxePFi3HXXXXjrrbcgimLMeoLBINavXx9TRRquMI03w1Sv17dYBxERERH1DAxYKW3kqHmmHXr8D0eGZxlNuCozEwBwglaLTR4P3mxsaDNgVYoigsEgNm7ciPXr10OhUMBkMiEjIwMGgwFKpRIqlSruv9bui76fgS0REXVHsnSc6SqAldvew8Hqnbhx3iPINOWhrGor3lr1LCz6LJQUnZjy7RMREfVE7X0PfGvVs6iqP4g7zv1L5+6DotNW1yPIsoxAIJBwdml+fj5GjRoVE25+9tlnqK6uhiRJWLVqFUpLS/HCCy+gtrYWBw4cwLPPPgsAuOSSS/DHP/4Ra9aswfTp02O2azabcdddd6X1uRIRERFR12DASmkj6o5vhqlVoYQSwBBNbCvfwRo1Nrpbn38iiCJyioowZcoUBAIB1NfXo7a2Fo2NjWhsbIRarYZOp4NKpYIkSQgEApF/oXYEw9FBbHsD22RDXJVKxTNciYioXZQqETiOc4D8QR8+XPsyrj/jdxg98GQAQL+sIaisK8PyzW+3GbDanTZ88MEHsFgssFgsMJvNkUuVStXxHSMiIuomZFmG0+mE3W6HzWaDzWaD3W7Hsd1eAMm1+n1r1bPYVv4dbj/naWQYczpt3xTKnv/5UZZleL3euIFpvNmlbrc77vxSjUYDvV7f4nN1IBBATU0N1q9fj7lz50KhUKCurg5Hjx6F1WrFhg0bYpbds2cPhg0b1mL9POmaiIiIqO9gwEppoxkyFN4dO4EOVrKqBQGjtToc8Ptjbj/o96OwjYOzgiSheOo0ZM6aFXN7MBjEnj17sHXrVuzduxeyLOOWW25BRkZGZBlJkhAMBmNC1+h/rd3X/P7wh7xEyyVLoVC0O5RNZvnmyygUfew0ZyKiXsqap4d0HFWkISmIkBRscdBQFETIaDlLLIYgQ2WUcPToUezZswculyvmbr1eHxO4Ng9hTSYTTywiIqIuFQ73wqFpdIAavm6322PmayqVSlgsFhiV2WgrYJVlGW9/+xw2H1iFX5zzFLLNBZ2276YsbbcM/SRJajUcjRegJppfGt1612q1tmjDG/11ovmlKpUKTz31FJ566ikAgNPpxOzZs3HDDTegqKgI+/fvx2mnnQaVSgW73Y677roLubm5Kf0eEREREVH3xoCV0kY7ahRs77/f6jIuSUJFVIB6OBDATq8XFoUChSoVfpqZiTuPHMYknR6T9XqscrnwldOJf/Yf0PrGZRna0aNa3KxUKjFy5EiMHDkSHlNb/sgAAQAASURBVI8Hhw8fhtlsjllGFEWo1Wqo1eoWj+9Msiy3Gr4mG+IGAgH4fD44nc6EyydLFMWUh7jhILc7fugnIuotcgaY2pzB6gt4UGM7HLle5ziKytoy6DUmZJryMLRgHN777iWolBpkGvNQVrUZa/d8jgum3tzqegUIOGnGGIybfRaAppObog9GRx+kLi8vh81mg8/n+/HxggCTydQihI0OY/V6Pd9HiIiowwKBQNz3pejL6M9RoijCZDJF3oeKiopanCSk0+kgCAKCgRBe+sVKyK2cj/TWqmexvmw5bpj3CLQqPezuegCAVm2AWqkBANjd9bC761H7w3v1kfr90Kr0yDDmwqA1x12vIAL5gy2d9F1qXTAYTNiON16Q6vG07EIlimKLWaU5OTktZpeGL3U6XaefhCVJEsQfxgstWLAAgUAAKpUKf/zjH1FaWorMzEzk5uYiPz+/U7dLRERERD2PIMsyh2JRWrhLS1F+2f+1usxatwtXHzrU4vbzzGb8vqAQAPCurRF/r6tDdTCIYrUat2RlY7apjZZLgoARG9ZDbGNOa18gyzJCodBxh7htLR8IBNCel5f2BLIdqd4N38YD8ETUFwX9Ibx0e+sHd/cc2YRnP2w5M2zK8DNwxem/hN1dj/e//wd2Va6H2+dApikP005YgFljFrX52nr+XRNROMya9P76fL42D3RHt/BXKBQtDmw3v67VHt+oAiIi6plCoRAcDker1afNwz6j0djqiT0Gg6Fdwd7/e/h71B9xJbz/lhdnx7398pn34OQR8wEAy9b/Cx9veK3VZZoTBGDqBUMxYW4bJyQ3I8sy/H5/qxWlzQNUf7NOU0DTCc3NQ9FEXxsMBmg0Gn5eIyIiIqIegwErpY0cDGLv6bMQqqlJ74YVChimT8eAl15M73apRZDb2SFu+P6Ozsk93mrcRPcrlUq2sySibmfZC5tRvq2u1ZA1FXQmFa5+fDpERee9LsqyDLfbHTd4DV86HI6YE33UanWrAazFYknYNpCIiLonWZbhcrkSnoxjt9vhcDhiHqPVattsTd/Z7wfrPzqItR/uR1ccfbni0akwZWnh9XqTri51uVxxP2NpNJq4gWm86lKDwcA560RERETUqzFgpbSqXbwYNc8+B8SZnZJK/V96EcYZM9K6TUofSZI6HOK29Zjo+zoyJzcVLZWj/zHIJaJkVeyow4fPbk7rNgUBmLRgECafPSit2wWa3hscDkfCaiWbzQa32x3zGL1eH7daifNgiYjSLzz3tLXXcYfDERMEhueetlZ9murRL/G4bD786/7VkI9jHnr7yYDJBU/eHrjd7hbdhQRBgE6na7WitPltCoUijftPRERERNS9MWCltArW1mLvzNOBdgRVx0UQoMzPx9DlX0DgAVE6Tq3Nye1IYNvabckSRTFlLZWbB7ls10XUs8mSjH//Zg0cdd60VdAIooCrfj8NBqsmPRtsp+h5sIkqn+LNg22tCpbzYImIkhMIBNp8DY5uOysIQkxgGu81ODz3tDv69B/bsG/jsbR2ksg/OYDsQdq41aVarZYnDRERERERHQcGrJR2tYsXo+aZv6Rte/1fXAzjaaelbXtExyvRnNxUtFtO9i1AEISk2yN3NMRVKpWck0uUYhXb6/Dhc+mrYp28cBBOWpD+6tXOFF09leiy+TzYtqqnNJruETjv2rULn376KS677DLk5uZ29e4Q0XEKBAKorq6OhI9dKTz3tLXq0+ZzTw0GQ6ut3I1GY48IBMPzS5u34W2odmLXh37IIQBI7d+7gihgwMhMLPj5WP5tTURERESUIgxYKe3kYBAHFl0E3969QDtmZ7abKMJyzjkofPwPqdsGUQ8my3JMe+VUhbiBQABSO9qCH09Y256WyzzYdPzKyspw+eWX48wzz8QDDzwAlUqFP//5z9iyZQsEQcD8+fNx0UUXca5lN7Pi9Z3YtboqpVWsgghk5Btw8YMnQdGJs1e7o+h5sK3N/4v+k1uj0bQawJrN5pT/3tTV1eG8887D2rVr8dFHH2H27Nl4//338cgjj0CtViMjIwO/+tWvMHXq1JTuBxG1X1VVFV577TWce+65KCkpQVlZGa655hq43W5IkoSpU6fij3/8I0wmU0q2Hz33NFGA6nQ6W7zuNa82bV6N2l3/XpBlGR6PJ2ZeabwZptFfx5tfqtVqoff2g1hVmPJ9VmkU+MnvTu62HSSIiIiIiHqD7vkJhno1QalEvz//CQcuuhiyz5eaeawKBVQFBch74P7OXzdRLyEIAhQKBRQKBbRabUq3FS/I7Ui75WAwCJfLlXD5eAezEgkHre1tn9zeubk9odKio5566ikcPHgQQFMw/vDDD+PIkSOYPXs2RFHEiy++iMzMTMybN69rd5RinLJoGA7vaYSjzpOSNoWCACiUIs64dlSvD1eBptdSg8EAg8GAwsL4B83D82DjhRFVVVXYtWtXwnmwicKI45kHW15ejqeffhqTJk1Cfn4++vXrh507d+L+++/Hq6++isGDB+Ptt9/GI488gg8++KDbhh5EfdVTTz2FJ598Erm5uSgpKcF9992HK6+8Etdffz0AwGq1YtGiRZg1a1a71y3LMnw+X6snjdjt9hZzT8OvT9nZ2Rg8eHCLk0a6S+U+0FRdmygodblcMWFq+Hq8+aXN55NmZmbGnWFqMBig0+mgUCggyzI+emELyrfVpfREp9OvKGG4SkRERESUYjxaQl1CM3QoBvz9JVRcex3kQKBzQ1aFAsqsLAx87V9QdHFrLCJqIooiNBpNyg+uSZIUE8p2NMQNBALweDyw2+0Jl0+WQqHo0Azc9j5GoVCk8Dv7I0mSIIoibrzxRsyaNQuNjY2RgH758uWYN28errrqKgDAY489FglgqftQ65Q4744JePeJDXDb/ZClzjvCKwiAqBBx9i3jkNXP2Gnr7elEUYwEDYmEZxHGqwY7cOAAbDZbi1mE4XmwidppGgyGFtupqqrC4sWL0b9/f0yfPh2//vWvYTAYUFNTg8zMTBiNRuTk5KB///7Yvn172l5bqHN5XQHUlDtQW+mEz900EkCpVsCcrUPuQBOsuXoIIjs59ESbN2+G3W7HnDlzIjOiKyoqUFdXB6fTiZqamsjJE/GEQiE0Nja2Wn0ab+5p+PWlX79+Laruu3ruaSAQaLOiNPr+6NnaYQqFIiYUNZvNyM/Pj7kt+uuOPmdBEDDv+tH48LnNqCprTEnIOuPS4Rg2Ka/zV0xERERERDEYsFKX0U+ahIH/+icqbrgRksvVOe2CBQHqAQMw4JWXoSooOP71EVGPIooi1Go11Gp1Srcjy3IkaO1IiBt9m8/ng9PpTLh8R+fkdkY1bl5eHlQqVcx2RFHE22+/DUmSsHDhQnz88ccQBAGBQADPPfcc7rnnHnz77bfw+XyYOXMmFi5cmIr/AjpOpkwtFv1yEj74Sykaqt1AJxzgFUQBKo0CZ98yDgVDEgeJFJ9KpUJWVhaysrISLuP1ehNWlB0+fDimqiwrKwu33HJLi3W8+OKLyMrKwl133YVly5ahoKAAGRkZ6N+/P+bMmYPTTjsNarUaY8aMwcsvvwxBECDLMtuq9wBeZwA7V1dh+zeHYatpmm0pCIgEqbKMyAkVSrWIweNzMGZmEfIGmfn/2wOEfw9/+9vf4sEHH8Trr7+OiooK+Hw+vPvuu/jZz36GZ599Fg6HAxdffHGL92+gKVzduHEjPvroo8ht4bmnZrMZgwYNalE5n+65p+EK2kTVpeHANPp6vBPf1Gp1TCCanZ0NnU4Xt7pUr9dDrVan7fdAqVZg4a3j8Onft+Hg1rpOWWf493zmT0Zg5PTUtyAmIiIiIiIGrNTFdOPHY8jHH+Hob38Lx+dfNB0F6shpvKIIyDIyf3oNcm69FWKK250SUd8WHWamkizLCIVC7Z6Hm+i+8EHIeI+JNyf31ltvRWZmZsxtDQ0NWLx4MV5++WXo9Xr4/f5IELtx40YUFxdj8uTJqK6uxrp161pUiUiShJqaGjQ2NrY5T5cH/FPLmKHBxQ+ehHVLD2DjZxVNb8EdaSghAJCB4jFZmPmTEujNqT3BoS/TarXQarXIy4tfmRSeixiuvm+uoqICy5YtQ21tLQ4ePIhNmzYhEAhg//79WLp0KWpra7Fq1SoYDAbceeedOHz4MADwd7Gb83mCWLOkDDu/rYIkyTEnTMgyIIda/m0d9EvYu/4Y9qytRlY/A2ZcOhyFwzLSuNfUXoIg4L333sOYMWMwadIkrFq1ClVVVdBoNCgrK8OAAQPw4osvorCwEDfffDMee+wxPPPMM7BarZF1iKKI4cOHIzs7O23zniVJgsfjSSooDV/G+5tEp9PFVJE2ry5tXmXa3VubK9UKnPWzsdix6ghWvb0XoaB8XB0lMgsNmHvNSHaPICIiIiJKo+79qYP6BGVWFoqeew72Tz5FzV//Cn9ZGaBQJFfR+sNy+kmTkHvnHdCNH5/y/SUiShdBEKBUKqFUKlM+JzdekBuvnemaNWuwd+9ezJo1CwaDAYcOHcKKFSvgcDjwyCOP4JtvvsHw4cMBAPPmzcOnn36KG264Iab6ZfPmzVizZk2b+5Rs6+SOtGCOvq83z8lti1KlwNTzh2Lw+Fysea8Mh3c3QhCFpA7yhpfLyNPjpLMHYeiJuQziupggCDAajTAa4x9gHzBgAJYuXYqdO3eirq4OpaWlaGhowIoVK/DMM8/gr3/9K0pKSgAAJSUlWL9+PS688MIW61u7di0MBkOXVbjRj8q312HFv3bC4/C3+xzF8O95/REXljxZirGnF+Hk84ZApWFb6K7g9XpjWvYWFRUhNzc38rslyzKWLVsGvV6PnTt34ptvvsGGDRug1Wqxfv16DBkyJDIHev78+fjnP/+JmpqamIBVEIQ225W3JRQKJWy9G681b/P50uH9aB6OZmdnt2jDGx2a9sbXGEEQMOrUfhgwKgtrluzDvg3HIMtyUr/L4fOSdSYVxs8dgHGz+/eJuedERERERN0JA1bqNszz58E07wx4Sjeh4c3/wr16DYI1NfEXFgSo+hfBdPrpsF5yKTSDB6V3Z4mIehmFQgGFQtHmnNyzzjoLZWVlcDgcEEURF154IU4//XQsWrQIv/jFL+D1eiPLer3eFoGbIAiYNWsWpk+f3q5K3EQVuYkeEwwG2/Xckwlk2wpq2wp5u/Msy7xBZpx3x0Q0Vrux7evDOLilNtJiNB69WY2ikgyMmtEPBUMsDFZ7kLy8vEgF7Ouvv47LLrsMt9xyCz7//HPs27cvslxpaSlOPPHEFv+3wWAQy5cvb3VGY/PL7jCjsbeRZRnrlh3EuqUHOtwA5sd1NV1u/aoSFTvrcd7tE2CwpnZmel/T2ozl8PXmv1Pz589HTk5O5DaXywVBELBy5Urs27cPsixDpVJh4sSJMBqNkUDVYrFg06ZN0Gq1GDZsWJv75vf7kwpKw1/Hm1+qVCpjAlGLxYKCgoKE7Xi1Wi1fD6KYMrU449pRcF80DDtXH8He9cfQcMTVVJEeh1qnRP5gM0ad0g/FY7MgMlglIiIiIuoSgpzscDeiLhCsr4d3+w6EGuohBwIQ1Gqo8vOhOWEkFEZDV+8eEVGfN23aNNx222249NJL8cILL+Ddd99FUVERZFlGbW0tXnrpJRQVFaV9v6Ln5B5PiJvMY5IlimKHw9q2AtzoZRQKRaccuPZ7g6g95ISj3otQUIJCKUJnVCFngAk6E9sA92ThWY6vv/46Bg4ciOnTp6O8vBzXXXcdGhsboVQqUVxcjMcffxyDBw+O+3ifzxcTFDW/jJ4HCzQFMNGBa7wwtq0TPOhH3723Dxs+Ke/09QqiAKNVgwt/eSIMFv5/JEOSJDgcjoS/CzabrUUVZziETPS7YDKZ2qzYrKiowKJFi/D222+joKAATz75JF577TXodDoMHDgQjzzyCEaPHh33sa+88grsdjtcLlfcE5LUanXC1rvxqkxVKhUD004WCkqoP+JCY7UbwUAIgihArVUiu78RpkwG1ERERERE3QEDViIiIuqwqqqqSKvQQCCAb775BnV1dXC73Zg2bVpS1TM9WXhObnuD3PaGuIFAAMn+yRaeEdze1skdWZ4HeHsfh8OBw4cPIyMjI+Gs12SE58FGh0zNq/YcDkfMY7RabatVsCaTqdvPVUyHrV9V4uv/7knZ+gVRQEaeHhc9MAlKVfetvE8HWZbhdrvb/DmOfn3WaDSt/hwf79zTUCgEhUKB+vp6fPTRRzjjjDOQm5uLUCgEQRCSaqW7YsUKAEjYjpe/Z0RERERERG1jwEpERETUAzQPcjs7xA3fH0pmBvoPUh3ick5u7xYKheBwOFoEV9GXHk9sq2qDwRATVDUPrnriPNhQKISjR4+isLCwzZMWGqvd+O8j3yMUTPFHOAGYeMZATD1/SJuLOhwOBINBZGRkpHafUqCtSmybzRbzmqhQKBJWnYYvW5uZHgwGE7bebX6bwWDANddck45vAxEREREREXUAA1YiIiIiipAkqcMhbnseczxzcjs7xA3/62nBXF8QCARarR602WwxrbpFUYTJZGo1BOtu82APHTqEV155BcOHD8eCBQtgNpvjLidLMt798wYcO2iHLKVhxwRg0b2TkDcowf7IMtatW4fPP/8cubm5uP7669OwU8kLBoOthvd2uz1mnqggCDCZTK1Wn+r1+sjPjizLkfmliYLS5rdHz1kNUyqVcatIzWYzpk6dmrbvFxEREREREbUPA1YiIiIiSjtZljsc4rZ1X/PbkxU9J/d4ZuK2db8oit0q4OvJZFmG1+ttNYC12+2QpB8TSaVS2WoVrMVigVqdvjnDe/bsQV1dHVavXo1AIIC5c+di4sSJLX5G9pfW4OMXt6ZtvwQRyB9swQV3n9jivtraWrz//vuorKwEAOTm5uKmm25K28+1JElwOp2thqculyvmMeG5p4n+z41GI/x+f8KK0niBabyKf41GExOUxmvDG31/On/WiIiIiIiIqPMwYCUiIiKiXivRnNzjabec6Lb2zsltK5Bt7+3Nl+Gc3CayLMPpdCZsAWuz2eB0OmMeo9VqWw3jzGYzFIrOmU/673//G/v27cPIkSMBADt27EBxcTEWLlyIzMzMyHLvPb0RR/Y2pqd6Ncplv5mCzEIDgKZg89tvv8VXX30FWZYhiiJmzJiBadOmddrczvDc09ZC8+ZzT9VqdYvQ3GQyQavVRn4PEoWn0dfj/Q43D0kTfR2+7KyfCyIiIiIiIureGLASERERER0nWZZj2iu3N8Rtz9zc6GrMtqhUKuh0OmRmZiIjIyMSQJlMJphMJhiNRmi12phQSJZlyLIMQRAgCELk68bGRng8nrghb08PcsPzYFuriGw+D9ZoNMZtIxtdEZnM90WSJJSWluKrr76Cx+PB8OHDceTIEbhcLsyaNQtTpkyBvcaLNx76LuE6Pi39DzYfWIXqxgqoFBoMzh+Jc6fcgDxr/xbLyrKMv318P3YcWofrz/gdxg06JeF6BVHA6Bn9MOPS4Th69Cj+97//oaamBgAwbNgwnHnmme2evRqee5oo8Lbb7TEtxBUKReRnVq/XQ6fTQaVSRX5mo1v1RgeoXq+3xbZFUYxbRZqoylSr1bJ1OBEREREREcXFgJWIiIiIqAcJhUIdmn/bWoirUCig0WhiwiaTyQSDwQCbzYbdu3dj9+7dCfcpXDHbntbJHWm13JVhl9/vj1v9Gl1d2XwebHQFbLwwVqvVRkJYv9+PNWvW4Ntvv4UoisjNzcWhQ4dQVFSEEdnTsPmTKiDBJ7fnl92HE4fOxMCcEoTkED5c+zKO1B/Ary5+BRqVLmbZFVvewa7KDdhxaG2bASsAGCxq9JvjwerVqwE0Bctnn302RowY0WLZ8NzT1qpPo+eeAoiEphqNBkqlMvJ/HK4893q9cLvdceeXqlSqhK13432t0Wh6/MkARERERERE1D0wYCUiIiIiohYkSUq6qrYjlbjR9ycr3pzczg5xOzonNzwPNl4AGx00Rlcgq1SqFsGrRqPBgQMHsHfvXhgMhqZK4sNF0HhyEgaszTk8jbj/tQtx+8KnMbRwbOT2ytoyLP7kQdx7wd/wwOsXJRWwAkBd3hpAEcKkSZNwwgknwO12t3h+NpsNbrc75nHh76dCoYAgCJGfKb/fH7cSW6vVJl1dqtfroVKpkvuGEBEREREREXWyzhmUQ0REREREvYooilCr1VCr1SndjizLMSHs8YS44Tmb8ZaPVwGZSPM5uR0JcPV6PSwWS8wySqUSfr8fHo8HbrcbTqczElLW1NSgrKwsZh6sy+UCAGT4jEmHqwDg9Tc9Tq81RW7zB7z45/LHcPEpt8Gsz0z00LhUARP8YgPWrVuHdevWRb5HoihG2mPH+x6q1eqk5paG/3F+KREREREREfUUDFiJiIiIiKjLRIeZqSTLcqTtbLKVta3d5vF4Eoa87WkSFB3KarVaGAyGmDa5DocDYkiT9PokWcI7q5/H4PzRKMwcFLn93TUvYFD+KIwtnp78Nw2ADBlCqKm1brjCNDy/t7XQVKfTsR0vERERERER9VoMWImIiIiIqNcTBCEyK1an07X9gOMQDnI7EuL6fD7U19ejrq6uqZpVBgxIfvbsW6ueRVX9Qdxx7l8it205uBp7Dm/CfYte7NDzEeSmSlVZllFYWIjhw4cjMzMzboVvV87JJSIiIiIiIkoXzmAlIiIiIiLqQrIso6KiAlu2bMH27dvh8/mQlZUFAKirq0NW1SkQ0HY16FurnsWWg6tx+zlPI9tcELn9nW+fx8ptS2IqSiVZgiCIGJI/Bref81TifYMMl3kfvIaqpJ6LQqFIqoVyvPvampkbvQzbCRMREREREVFXYsBKRERERESUZrIso66uDqtXr8auXbvg8XigVCqhUChatBnOPHoyRDlxC2VZlvH2t89h84FV+MU5TyHXUhRzv91dD6fXFnPb79++Doum/RyjB06NCWPjsVt3wq+rhVqthiAI8Pl8Mffn5ORg0KBByM3NbbV6N5n5uskSRTGpULY9c3PjLaNQKNjqmIiIiIiIiFpgi2AiIiIiIqJO5vf7YbPZ0NDQgOrqatTW1qKhoQEOhwMejyfurNZgMIhgMAhRFGEymZCZmYnMzEw0lGrgOCIl3NZbq57F+rLluGHeI9Cq9LC76wEAWrUBaqUGZn0mzPrMFo/LMOa2Ga4CwDkXn4GQ0gObzRZ5TseOHYPL5YIsy6ipqUFNTQ0AwGQywWw2w2KxwGw2IyMjI3LdYrHAYDAkDCzbOyc33jLR191ud9zl2zMnN9xaOpUhbvg6g1wiIiIiIqKegwErERERERFRO4RCIdjt9pgAtb6+HjabDU6nEz6fD6FQKO5jFQoFdDpdJHh0Op2orq5GKBTCmDFjcMoppyA3NzfmMd9J+7DxaAVkKX4o+M2ODwAAf/nwzpjbL595D04eMf+4nqtSLWLk+KEQxJbhnyzLKCsrw9q1a+H1ejFhwgTYbLbI96a6uho2mw3BYDDyGFEUYwJXs9nc4rpWq+02c3KTqcb1er0J70v0cxBPOHQdO3YshgwZApPJBK/XC4/HA6/XG7OdUCjUrgCXc3KJiIiIiIg6F1sEExERERER/UCWZTidzki1Zl1dXUz1abgqMhG1Wg29Xh+p3szOzkZeXh6ysrJgNpuhVP54juuRI0fw1ltvYfTo0ZgyZQpMJlPcdVZsr8OHz23u9OfaFkEEikoycc5t4zu8DlmW4fF4YoLX8Nfh63a7PaaiVK1Wx1TBRl+Gv1apErdM7k4kSUoqyA3f379/fxQWFkKSJIiiCFmWI9+b6GBUkiS43e5IyB/+vkZ/nz0eT9x9ip6TezyVuG3dzyCXiIiIiIh6MwasRERERETUJ8iyDK/XGxNG1dXVoa6uLqb6NNFHJEEQoNVqYTAYYLFYkJmZiby8PGRnZ0eCv1SESpIk47UHvoWr0d/p627LmTeNweDxOSndhiRJcDqdCQNYm80Gl8sV8xidTtdqFazJZIJCoUjpfncn4Z/Z6DbD4ZbLfr8/8s/r9cLlcqGhoQF+v79dlbodnZPbVijbWlCbTLtlURTZXpmIiIiIiNKOASsREREREfUKfr8/JpQLB6gNDQ2w2+1wu92QpMSzTEVRhF6vh8lkilSfZmdnIyMjAxaLBUajscuCnA2fHMT37+9HOj+96c1qXPWHaRAVXV+JGAwGW1S9Nq+K9fl8keUFQYDRaEwYwLY1D5biaz4nN5lAtj1zc6P/tWdObrLtkTsS4obv55xcIiIiIiKKxoCViIiIiIi6vfDc0+YBan19PRobG+F0OtusrlMqlTHVpzk5OZHw1Gq1QqfTddsAxeP049+/XgO/J/mZnsfrlIuHYdys/mnb3vHy+XytVsHa7faYebAKhSImfI3Xjlij0XTbn4neTJblSHvlVIa4gUCg1ZMumuto1W172y3zZ46IiIiIqPtjwEpERERE1IcFg0EIghBpp9rQ0IBHH30Ue/fuRSgUwh/+8AeMHTs2pfsQPfc0ujKxsbExUn3afJ6kIAgtKtw0Gg2MRiMyMjKQlZWFzMzMSHhqtVqh0WhS+jxSbc+6o/j85R0p344gCsgdaMIF95wIUew9QU/0PNh4VbDhQLatebDNw9hUz4O9++67sXr1auTl5eFvf/sb8vPzATT97rpcLlgslpRuv7fraJDbnhA3EAggFEr+5IhEc3I7e2Yu5+Sm3ldffYX77rsPa9euxeLFi3HDDTcAABobG/GnP/0Ju3fvhiiK+MlPfoKFCxdG/k8+//xzHDx4EGq1GrNmzUL//j3nZBciIiKivkLZ1TtARERERESpc/ToUVRVVWH48OEwGAwAgF27duGWW26BzWaD3+/HVVddhTvvvBMA8Pvf/x6yLOOOO+5AIBDABRdcgPXr18NqtXZo+9FzT5tXEzY2NqKxsREulyumiixcvdU8QA3P3czMzERmZiasVmskQLVYLCkPurrasEl5KFt/DAe31kJOvuiu3QQBmHP1yF4VrgJNP1d6vR56vR4FBQVxlwnPg43381pdXY09e/a0mAer1+tbrYI1mUwdDrJkWcbcuXMxcuRI3HHHHZETDbxeL5599lm88cYbEEURZrMZzzzzDCZMmBC5f8OGDcjNzUVRURF0Ol2Htt8XiKIIjUaT8hMwJElqdyibaHmPx9PqY5IVb05uZ4e4fX1ObmFhIZYsWYJFixbB5/NBkiSIoohbb70V+fn5uOqqq+ByufCnP/0JGRkZmDFjBl588UWsWLECmZmZsNlsWLNmDX77299GTq4gIiIiou6BFaxERERE1CpJCkEQ+u7B0Z7s3nvvxQcffIA9e/Zg5cqVOPXUUwEA8+bNw+WXX46zzz4bKpUKZrMZO3fuxIgRI6DX67Ft2zYMHjwYADBjxgxcdNFFuPnmm6FUtjw/M3ruabwAtXlbVqCpOivcAjRMEAQYDAZkZGRE/kVXn5rN5kiVbV/mcwfwvz9vRMNRN2QpBR/lBODMG8Zg8ISczl93LxGeB5uoCra1ebCJZsK2NQ928+bN+OlPf4rPPvsMWVlZ+Oabb7Bw4ULU1dVBoVDg5ZdfxquvvopVq1ahrq4Ojz/+ODZs2ACfzweFQoGXXnoJJSUl6fj2UCdr73uwLMsxwWx7Q9z2PKajc3JTEeKqVCooFIpu97dKOFCdPXs2/u///g/XXHMNRFFE//798fDDD+Oaa64BAGRnZ+PFF1/EhRdeiIEDB+Lpp5/GBRdcAACYMmUK7rrrLlx88cVd+VSIiPoc+YfPKgI7PhBRAqxgJSIiIqKIYwf340DpelTvL0NV2W64GuojB1C1RiPyBg9D/pDh6D9yDAaMHssPm93cJZdcgieeeAJTp05FQ0ND5EDvN998gxtvvBEZGRmora3FSSedFPl/zs7OxrfffhsJWKurq/H999/jiiuuiKlilSQJX375JVatWhWzzfAB7lAoFHPwPTzvMiMjI6byNPz18VT59SUavQrn3TEB7z1dioajrk6rZA1nEnOvHcVwtQ1KpTJSRZ2Iz+eLe9KB3W5HVVUVbDZbTMtYlUqF+++/v0U4JMsyBEHAzp07YTKZoNfrATRVHo4ePRoHDx7EkCFD4Pf7UVNTAwD46KOP8N5772Hv3r0AgH//+9+45ZZb8MUXX0ReA6h7stfWoGzdd6jevxdVe3ejsfooZKnp50Sl0SBn4GDkDx2OwuEnYMiJk6FUq1usIzrMTCVZlhEKhTo8F7f5bc2rcsP3+f3+pINcAEkFsscT4obvb2+Q63a7odVqI79/b7zxBh544AH85z//gdPpxM0334zTTjsNQNPMcXXU/61er8eGDRuwcOFCVqMTEaWIz+3C3u9X4+i+Pajauxt1hw8hFAgAABRKFTL7FaFg6AjkDRmGYZOnQmcyd/EeE1F3wICViIiIqI8LBYPYveYblH78IY7u29MUmsqA3Cy58TqdKN+yCYe2bcH3S96EOTsX4+efjTGnnwGt0dhFe0+tCbcLNRqNOHToUOTA7tKlS/Hoo4/i9ttvR3V1NX75y18iOzsbAPDwww/jo48+wptvvgmLxYLi4mKYzWbY7faYgFWW5UjYAzQd1A4Hps1b91qt1jYr9Ch5OpMaF9xzIla+sQt71x8DBADHUcwqCIDOrMbca0aiqCRxaEjJ02g0yM3NRW5ubtz7ZVmG2+2OBLBer7fV34+DBw8iPz8/EpoNGzYMEyZMwKRJkwAAM2fOxPvvvx9ZdsCAAZHH6nQ6hEIhHD16lC1GuyFZllG+dRNKP/kQ+zeuAwAIghgJVsMCPh+O7NmJo/v2YONH70OjN2DM7HkYf8YCWHLz0r7fgiBAqVTG7WzQ2UKhUIdD3Oa3O53OhMu3Z05udAirVCoxdepUTJgwIWGnBb/fH/Oe+fHHH+PUU0/FSSedhF27dqG0tDRS+X777bfjzTffxKFDh6DX61FeXo4xY8a0K2gmIqLk1JQfQOmnS7Hj6xUIBQIQFQpIzd4PQsEAasoPoK6yAluWf4Llr/wNJdNmYML8hcgfMqyL9pyIugMGrERERER92LGD+/HxX59E7aHyH+deSq2VxMmQfjjoa689hq/feBVr338H8268DUNPOjkNe0wdUVRUhMOHD0eq4RobGzFy5Ei88sor6N+/P84//3w8+uijeOaZZ3D11VdjwoQJ2LdvH+bOnYu//OUv2LVrV4tgRhRFjBo1CsXFxbBardBqtQxQ00ijU+KM60Zj6KQafPn6LnhdgXavQxAFyJKME6YXYPqFw6DW8eNhuoRbYhsMhoTzYIEfK1j3798f8zv4u9/9DhkZGWhoaIDD4cDll1+ONWvWoKSkBCeffDJKS0vx7rvv4uSTT8bbb7+Nmpoa2Gw25OfnR9ZJXc/ZUI/PX3oO+zeu++HkpqYATZYTB33hg74+twsblr2HjR9/gFMvvRITF5wLUeydbdQVCgUUCkWXzMlNNsTNzMxs9ffK7/dHqlKPHDmCpUuX4uOPP0ZRUREAYNy4cVi3bh369euHu+++G//4xz+wbt06jB07FiUlJSgqKmoR3tbX12P58uWdUqnLFvxE1NcEfF58++a/sWHZexBEReTEpubharTwfVIwiJ2rVmLH1yswbu6ZmHH5T6HWssMAUV/ET9BEREREfZAsy/h+yVtY/fYbMbd1YEXwOh14/8+PomT6aTjjhluh0mo7cU8pnkAg0KL96MiRI5GTkxP3AO+AAQOwf/9+BAIBqNVqfPXVV8jIyEBxcTEA4JxzzsGyZctgt9thNpsxbtw4jBs3DgCwZ88eDBo0CGq1GqFQKHIQVhCEyCxJ6jqDx+egqCQDe9ZWY/OKQ2g86gaEpqrUeO2Dw6GqUiWiZGoBRp/WD1n9WIHeXYWrzu12O6ZNmwalUglZlvHtt9/iscceAwCYTCbk5eWhrKwMoVAIc+fORWNjIxYvXowPPvgALpcLU6dOjVQaRr9GrFq1CiqVKjIL1mKxQK/XM4BNgz3frcKni59FwOcF0NbJTfHJkgRZkrDy369g95pVWHjHfTDnxK+apraJogi1Wh3Tnrcz1hmWl9dUaWwymVBWVhYzh9xms0Eb9ffTddddh+uuuw4A8PTTT+Pee+9tETAHg0F4vV44HI6EwW979rOtQLYzZuZ2xzm5RNT3VO8vw4dP/wH2mmMA0KJrRDLCj9nyxSfYt2Edzr79l+g34oRO3U8i6v4YsBIRERH1MbIk4fO/P4+tKz7tpBU2BbO713yDxuqjWPTgw9DoDZ2z7j4oFArB4XC0mN0YfenxeGIeo1arkZGRgaysrJgqlPBBzBNOOAEbN26MHDTW6/X4+uuvI8tVVlZGZqRWV1fjH//4B7777jscO3YMJ598Mn7zm99AlmVWuHRTaq0So2f0w6hTC3HsoANH99twrMKOYwcd8LkDkGVAqRJhzdMjr9iMnIEm9C/JZMVqD7B48WL8/e9/R2lpKcrKylBaWoo//elPyM/Px+7du3HGGWdApVJh1apVuOOOOyK/oxdddBEuuugiAMAFF1yA/v37o7CwsMX6t2zZgvr6+pjWqAqFIiZwbX5psVhSXknY22367CMsf/mFTl1n9YEy/OdXd+Hih/6AzMKiTl03ddx9992HN998E+Xl5Tj33HNhtVqxadMm/Pa3v8WVV16J/Px8eL1enHrqqZg6dSoA4J133sG+fftgNBqxdetWnH766ZH5rNFyc3NxxRVXJNx29JzcZCtxW7vf7XYnXP545uR2dojb0Tm5RNQ3HNqxFf/7w0MIBYOd0npdlmW4Gurx1sP347y7f4VBEyZ1wl4SUU8hyBziQERERNRnyLKM5a8sxubPlqVk/YIoIn/ocFz0q0eh0rCStTlZluFyuVpUn9rt9sh1p9MZ82FfpVJBo9FEKtdCoRB8Pl9MZYooipgzZw6mTJkSUy0T9o9//AO/+tWvcPPNN6OoqAjnn38+7rzzTqxfvx6iKKKoqAh/+ctfMGzYMLhcLqxYsQI+nw9DhgzB8OHDYTAwMCfqCoFAAOXl5Thy5Aj27t2L3bt349FHH8XBgwfx85//HLW1tfD5fDj33HNx7733IiMjA8uWLUN9fT2GDx+OzZs3Y/HixXjrrbcwdOjQuNsIz4ON97oUvnQ4HDGvSxqNptUA1mw2p2U2Z0+07asv8OnfnknJugVRhM5kxk8ee4qVrN2Ix+OBz+eDy+WC2+3GsGHD4PV6sW7dOtjtdni9XsyYMQM5OTkAgE8//RSffvopHA4HiouLcd9993X7E5ziBbntDXGTWb6jc3JTEeKGb4/3dxcRdU9Ve3fjrd/dj1CwfSeGJEUQIIoiFj34CPqPGtu56yaibosBKxEREVEfsuObL/HxX59M6TYEQcDYuWdhzrU3p3Q73Y0sy/D5fAmrTsMhavNKMZ1OB7VaDUEQIMsy/H4/PB5PzHJKpRJWqxVWqzUSYERfN5lMcSs1QqEQLr30Umzbtg0DBw5EdnY2pkyZgltvvRU2mw0ulwv5+fk8OEjUgzkcDqjV6khV6UcffYR///vfOHz4MAoKCvD4449H2oF3lCRJcDgcCV/bbDYb3G53zGP0en1M4No8gDWZTH3utaem/ABev+8XHWoHnCxBFJE7aAj+79E/99qZrNR3SZKUdCDb0RA3fJkshUKR0hA3/K+vvV4SdTaf24VX77gJbrstZe/DgiBAozfgmmdehN5sSck2iKh7YcBKRERE1Ec4G+rx6h03we9xt71wJ7jo17/HgNGtn727Z88ebNiwAeeff37M7LHuKBAItAgUmocMfr8/srwgCNDr9ZHqUwCR6lO32x0ze02j0SQMT61WK2ciElG3F36NTFSdb7PZWrxGmkymVqtge8Jr37fffguXy4WZM2e2OrszFAzi3/ffjrrKipQGrGEzLv8pTlp4Qcq3Q9QbybLc4VbKbd3X/PZkiaKYdHvkjoa44SC3u7/uEnXEJ397Bju+XpHy92BBFDFs8lQsvOP+lG6HiLoH9uwhIiIi6iNWvPI3BHzetGxLEER88sJTuPbZv0OhVLW43+1245NPPsHWrVsxbNiwVg9Kp0N0dVaiCq3m1Vk6nQ56vR4qlQpqtRpZWVkIBALwer2RNr8ulwsulytSyZWVlRU3QO3u4TIRUVtUKhWysrKQlZWVcBmv15swgD1y5EiLKn+lUhkTvjYPYLvDPFir1YqVK1dix44dWLhwIYYMGRJ3uQ3L3kNtxcG07deq//cvDJs8Dda8/LRtk6i3EAQBarU65X+ftjYnt71Vt36/Hy6XK+Fjkq2vEQQh6fbIHQ1ylUol5+RSWlVs24ztX32Rlm3JkoQ9332LsvXfY+ikKWnZJhF1HVawEhEREfUBjdVH8fJt16V9uwt+cS9Kps2IXJdlGdu3b8fHH38MSZIwf/58jB07NqUHWMJBZ2tVVc3nnmo0GhgMBmi12hbVpx6PBy6XK2Yb4Sqs6NA0+rKrA2Qiop6g+et1vK4B8V6v41XBRl+meh5sQ0MDPvzwQxw4cADjx4/HGWecAZ1OF7k/FAzixZuvgsduS+l+RBNEERPPOhczr7g2bdskou5JluWY9sqpnJcrtaM68HjC2va0XGaQ2zsFg0H87W9/w9ChQzFjxgwYDIaEy777+9+gfOumtHSQAJregwuGjsBlj/wpLdsjoq7DgJWIiIioD/j6jVexfumStH2oBH74YDlsBC57uOmDpcPhwLJly7B7926MHDkSZ555JoxG43FvJ15FVPPL5nNPzWZzZPapQqGAJEkIBoOR6lOPx/Pj8xAEmM3mhDNQ03HwnoiImoRCITidznZ1HDAYDK1WwRqNxuOebyjLMkpLS/HZZ59BpVLhrLPOwgknnAAA2PPdKnz49OPHtf6OUOt0uOmlf0Ol7toqXyLqO0KhUNwAtjND3EAgEPO3fVvCFbNttUc+3rm5nJObfmvWrMHKlSsBANOnT8fJJ58MlSq2e1JXnWgMAFf+6a/IGVDcJdsmovRgwEpERETUy8mShOev+z/4XM6EyyzfWYatlUdR43BCqVCgOCsDC8aWINccG4AerG3Ax9t2o6KuEaIgoNBqxg0zJkOlVCRc9zXPvIiDVdX47LPPoFQqsWDBgshB57Z0dKaf0WiETqeLBJ+SJMHv98Ptdrd4jEKhaLX61Gw284AJEVEP0trM7PD15u8d0eFrvJmwOp0uqSoou92OZcuWYc+ePZGTiT75yx9RsW1zwpOcknkPtnu8WLplF/ZW18IbCCLXZMDskUMxtqig1f0567Z7cML005L8zhER9QzhkyNTGeKG709WvDm5nR3ick5uS263GytXrsT69ethNBpx+umnY+zYsZHPb9++9Qa+X/Jmwvfg1WXlWLOvHPWuphNs8y1GzBk5DCcU5AIAvttXgY0Vh3G4wQ5fMIhHzjsDOnXLETjNiaIC4+efjdOvur6TnikRdUcMWImIiIh6uYaqw3jl9htbXebvX6/F+P4F6J9phSTL+GjrLhy1OXHP/BnQ/BBSHqxtwD++WYtZJUMwsjAPoiDgiM2O0YV5UCoSB6ym8VNQ5Zcwbtw4zJs3L9I2MXruaaJ2kM2rkMKzTPV6PTQaTeSDc/TsU7vdHnMwRKVSxQ1Pw18bjUYepCAi6kNkWYbP52u1Cra1ebCJWhGH58FGt8OXJQnqbd8jFBXoNpfMe/BLK7+HJxDA+RNGw6BRo7TiMD7dvge3zzkF/TIscdcrKhQYO+dMzP7pTZ343SMi6jtkWY4ErW0FsomWae1x0fd1dE5uKkJclUoFhULRoz4j1dfXY/ny5dixYwfy8vIwZ84cDB06FG89/AAObd+S8HHbj1RDFARkGw0AZKw/WImvdu/HHXNPRb7FhK/3HEDwh78HPtq6O+mAFQDyBg/F5X94phOeHRF1V+xlRkRERNTLVe8va3OZ62dMjrl+6Unj8NsPvkBlgw1DcrIAAB9s2oFThhZj1glDI8s1r3BtToYA+5FKnDhvIdRqNZYtWxY5gO1wOFrM0QtXEGVlZSEvLw+CIMRUn9rtdhw7dizmoLdWq42EpXl5eTHhqdVqTbrqiIiI+gZBEKDVaqHVapGXlxd3mfA82HhVsLW1tdi3bx8cDkfMY7RabUzgOnHiROzbsQ2OVsJVILn34IN1Dbhw4mgMyLICAOaMHIav9xxAZYMtYcAqhUI4WrY7mW8JERHFER1mppIsywnbK3ckrPV4PAkf05E5uakKccP3dcZntczMTFx00UWorKzE559/jjfeeAODBg1CQ9meVh83qjD274Azx5Rg9b4KlNc1IN9iwozhgwAAZcfq2r1PNRUHIYVCEFs5GZmIejYGrERERES9XE35AYgKBaR2zCryBoIAAL1aDQBweH2oqG/ExIGFeG75t6hzupFrNuLM0SMwKCezlTXJkBw2lJaWRuaVWq1W5OXlQaFQRM4K9/l8kWrW/fv3xwSv4dl5VqsVhYWFLapQwxVDREREnUUQBBiNRhiNRvTr1y/uMqFQCA6HI+4c8MOHDze1Iq4+DF07t938PRgAirMysOlQFU4oyIVWrcLmQ1UIhKRIAJtITcXBdm6diIjSTRCEyKxYrVab0m21FeS2J+R1Op0JH9PeObnJhLJtBbXhr8844wwcPnwYa1Z+haDPm/R+SJKMzZVV8AdDGJiV0ZFvb+z6gkE0VB1GVtGA414XEXVPDFiJiIiIejmf29Wu5SVZxvubdqA4OwMFFhMAoN7V1Kr3s+17cfa4E9DPasb6g4exeOX3uHveDOSYDHHXJQBAKAilUolgMIhjx47h4MGDMcuYTKZIWDpgwIAW7XxTfcY4ERFRRygUisj7V7RgMIi9e/diy5Yt2Hf0ULvWGe89GACumDoRr6/ZiN+8/zlEQYBaqcDV009EdoL337BQIIBQMAiFkod/iIio6b1LoVCk/CTVeHNyOzov1+PxRMbAxFs2EdHrhj6Jfa1qtOO5FasRDEmR99f8qPfg4+F1te+zOBH1LPwLm4iIiKiXa08bKABYsnEbjtoc+PmsqZHbwhWlJw8egMmD+gMA+mVYUHasFusOHMJZY0sSrk8UBIgqFZxOJyRJQlZWFoYPH46xY8ciJycHCrZMIiKiHk6WZVRWVmLz5s3Yvn07vF4vCgsLMeqEkSg7fCDp9cR7DwaAT7bthicQxI2nTYFBo8a2w0fx+pqN+PnpU1FgNbe6TkkKQcHDP0RElEaiKEKtVkMd1Y0hFaLn5Ib/+f1+HDx4EJtWr4Jnf9vryDEZcefcU+ENBLGlsgr/XbsZN888uVNCVrkdlbxE1PPwL2wiIiKiXk6pVuOHWtI2/W/jNuw4cgw/O30qrPofmxqafmhVlWeJnbmaazaiwe1pdZ25+fm48u674ff7sXPnTmzZsgVr1qzBunXrUFJSgrFjx2LIkCEQRbF9T4yIiKiL1dfXY8uWLdiyZQsaGhpgNpsxadKkyElEO775EmVfLEtqXYneg2udLnxbVo67582IHOwttJpxoKYe35aVY9GkMa2uV6lkJwgiIuqdoufkBoNBbN26FWvWrEFNTQ3ykgxIlQox0hGiKNOCQ/WNWLX3YJvvr0mtO8UBMxF1LQasRERERL2cNa8QktT6mbOyLGNJ6XZsO3wUN8+ciixjbDOlTIMOZp0GNfbYFkc1DhdK8nMSrlcQxcjMGbVajXHjxmHcuHGw2+3YunUrNm/ejP/85z8wGAy49NJLUVRU1MFnSURElD6yLOPNN9/E7t27oVarMXLkSCxcuBDFxcUQhB9ParLmFSS1rtbegwPBpvdwodm5UoIgQIaM1phzciHwBCYiIurFPB4P1q9fj7Vr18LpdGL48OFYsGABCvPz8dz3X0FuZ0cnCUCwnY9JxFpQ2CnrIaLuiQErERERUS8SCoVgt9vR2NgIm82GxsZGHD1cBcitH4D938ZtKK04gmumT4JGqYDd4wUA6FQqqJQKCIKAmSOG4LPte1BgNf8wg7USxxxOXDltYuIVyzLyBg9tcbPZbMb06dMxbdo0HD16FLt374ZOp4uzAiIiou5HEAQMHDgQo0aNQklJScJ54TnFg5qC0Fbeh9t6D841G5Ft1OOd9duwcNwJ0GtU2Ha4Gnura/HTU09KvI+iiIJhiVv4ExER9WQNDQ347rvvUFpaCkmSMG7cOEydOhXZ2dmRZTILi1BXWZFwHR9t2YURBTnI0OvgCwRRWnEE+4/V4foZkwEAdo8XDq8Pdc6mE42rbA5olApk6HXQa1qvTjVl50BrMLa6DBH1bAxYiYiIiHqQQCAQCU7jXdrt9pjljUYjzEYDmloEJz64u2Zf04fOv331Xcztl5w0Fif9MHN1xvBBCIZC+GDTDrj9ARRaTbhxxhRkGw0J1ysnCFjDBEFAQUEBCgrarvAhIiLqTqZOndrmMiq1BhmFRag/fCjhMm29BytEEdeeOhkfbdmFV1atgy8YQrZRj0snj8MJBbmJNy6j1fdgIiKinmrHjh145513oNVqMXXqVJx00kkwGluGmQXDStBQdRhSglmoTp8P//1+M+xeH7QqJQotJlw/YzKG/9Clac2+Cny+Y29k+Re+XAMg9nNyPIIoomDoiON5ikTUAwhya6dREhEREVFa+Xy+mNA0/HX4usv1Y4teQRBgMplgtVphtVphsVhaXCqVTefTvfuHh1C+pbTd7ZGOl85kxo2L/wUF578REVEftfrt/+C7//037e/BAHDtX/4Oaz5PYiIiot6lvr4ehw4dwgknnAB1K3NO95euw5LHf5fGPfvRgl/ci5JpM7pk20SUHqxgJSIiIkoTWZbh8XhahKfRl16vN7K8KIqRsDQnJwfDhg2LXLdarTCZTFAoFElte8L8s3Fw04ZUPbW4BFHEuDPOYrhKRER92tjZ8/Ddu/8vrdsURBEDRo9juEpERL1SZmYmMjMz21yueNxEmLKy4airTcNe/UhrMmHY5LY7XRBRz8aAlYiIiKiTyLIMp9OZsPq0sbERgUAgsrxSqYyEpf369cPIkSNjqlFNJhMEQeiUfSseNxGm7Bw462pbnQPXqWQZY2bNS8+2iIiIuiljZhaGTp6GsnVr0lbFKksSJsw/Oy3bIiIi6q5EUYEJ8xfim//8M22fgwVRxPi5PNGYqC9gwEpERESUJEmS4HA4Elaf2mw2hKJmu2g0mkhYOmjQoJjqU4vFAr1e32kBaltEUYHZP70J7z3xSFq2B0HA5PMugjk7Jz3bIyIi6sZm/N/V2L9xLUJpCFgFUUT/UWMweOLklG+LiIiouxs/bwE2f/4R7LU1KT/RSRAE6C1WTFp4YUq3Q0TdA2ewEhERUbdWX18Ps9kcmSVaXl6Oe+65BxUVFTAajfjd736H6dOnd8q2gsEg7HZ73PC0sbERdrs95qxXvV4fCUubh6dWqxVarbZT9qszffTXP2PXt1+n9IOlIIqw5hfgyif+CqWKZ+0SEREBwMaPP8SX/3wx5dtRajS45qm/wZydm/JtERER9QSHd+3Afx+6Ny3buvDBR1A8dkJatkVEXYsVrERERNSlKisrcfToUYwaNQo6nQ4AsHbtWtx2223w+XxQKBRYtGgR7rvvPgSDQTzwwAOYMmUKnnjiCdTW1uK8887D9u3bYbFY2txWIBBotfrU4XDELG8ymSJhaVFRUUx4arFYoFarU/I9SaVZV9+Eyp3b4ayvS03IKggQFQosuPUehqtERERRJsxbgP0b16Ji2+aUnug097qfM1wlIiKK0q9kJKacfwm+X/JmSrczYf5ChqtEfQgrWImIiKjL/OxnP8Onn36KAwcOYMOGDZgwoemDyNSpU/HQQw9h7ty58Pl8MBqNOHr0KHJzc6FSqVBXVwez2QwAmDJlCq644grcfPPNUCgUMetftWoVjhw5EglR3W535D5BEGA2m2OqTqOrUKOrZnsb27Gj+M+v7obHYe/UA7wyAIVCgfN/+RCKx03stPUSERH1FgGvF2898iCq9+9NScg64/Kf4qSFF3T6eomIiHo6WZbx+UvPYeuKz1Ky/hHTZuCsW++CKCraXpiIeoXeedSQiIiIeoQrr7wSzz//PE488UQ0NDRAlmUIgoB169YBaArrDhw4gNNOOy0y2zQrKwsffvghfvKTn8DhcKCqqgqbN2+Gy+WKhK5h9fX18Pl8yMvLw4gRI2ICVJPJBFEU0/6cuwNLbj7+79En8fYjD8JeU43OON9OEEVAECAPH4vsIcM7YS+JiIh6H5VWi4t+/Sje//NjqNi6qVPWKYgiIMuYdc1NGD9vQaesk4iIqLcRBAFzr78Fap0eG5a9B0EQjv+zsCAAsoyxs+dj9nU3M1wl6mNYwUpERERdRpIkiKKI6dOn44YbbsBVV10FAFi5ciXuu+8+VFRUoL6+Hr/85S9x8803Iy8vD2+//Tbee+897N+/H0VFRfB4PBg6dCjuu+8+5OfnR9YdDmspsYDXi2/+379Q+smHEAQRstzxSpqBYydg2k9+iv/+bwlMJhOuvvpqqNgimIiIKC5ZklD66VKsfP0VSKHgca3Lml+ABbfdi/whwzpp74iIiHq3/RvX4eMXnoK32Zig9tLo9Djjptsw/ORTOmnPiKgn6ZtlG0RERJR2rZ3T1a9fP1RUVESuHzhwANOmTcP27dvh8Xiwdu1aPPnkkwCAiy66CA8//DCef/55vP322xg3bhycTmdMuAqA4WoSVFotZl1zIy5+6A/IH9p0UFZI8oxb4YfqX3NOLubdfDsufOBhFBYPwmWXXYaamhosWbKkUypjiYiIeiNJCsHjsEOSQse5JgEBnw8+l6tT9ouIiKi3k2UZHocdoUCgqQK1owQBwWAQHoeDn32J+ii2CCYiIqJOEQwGI7NOm182Njbiuuuug8lkivvYgQMHory8HIFAACqVCqtXr8bAgQNhtVoBAAsWLMCXX34Jj8cDrVaLIUOGAACcTid2796N0047DcCPFbHUPv1HjsH/PfokasoPYPPnH6Fs/fdwNdT/uMAPbY/CNHoD+o8ag3FnLMDA0eMiYSsAFBQU4IILLsCbb76JFStWYPbs2el8KkRERN2ex+nAu7//Dar3l8W8v3aMDHdjA9557FeYdvFPcPIFl/IkMyIiogSkUAifLv4Ldny94vhXJssIBfz44h/Po3xLKc667R4o2cWJqE9hwEpERERJ8fv9LULT6CDV6XTGLG82myMzTwcMGBB3neEDgKNHj8b7778faSlrMpnwxRdf4MEHH0QwGMSBAwdgtVqh0+lQWVmJp59+GitXroTX68UFF1yAW2+9leFqJ8gZOAhzrvs55lz3c7jtNhzbXwZ7XS1CwQAUSiV0JjPyBg2FKTun1YO3JSUlmDt3Lj7//HNkZmZiwoQJaXwWRERE3ZfH6cCbD/0S9UcqOyFcbRKumln91hsI+v049bKrOmW9REREvYkUCmHpM3/E3nVrOn3dZevW4L0nHsH5v/w1FEqGrER9BWewEhEREWRZhtfrjRughq97PJ7I8qIowmw2w2q1wmq1wmKxRMJUq9UKs9kMhSK5VrMA8Pzzz+ORRx7BNddcg4EDB+Kyyy7DPffcg6+//hoajQYjRozAk08+if79+8Pj8WDLli1QqVQoLi5GZmZmKr4ldJxkWcbSpUuxadMmXHHFFSguLu7qXSIiIupSUiiE/z50L47u2wtZ6vjc87bM+ulNmDDv7JStn4iIqCda/spibPp0aeo2IAgYeerpOPPnd6ZuG0TUrTBgJSIi6gNkWYbL5UoYnjY2NsLv90eWVyqVkcC0+aXVaoXRaOyUatFgMIhLL70UO3fuxODBg5Gbm4tp06bh2muvhcvlgiRJCdsKU/cXCoXwn//8B0eOHMHNN98Ms9nc1btERETUZb5f8hZW/fe1lG9HVCpx9Z+fR0ZBv5Rvi4iIqCc4uKUU7z7267Rs65y7HsCwydPSsi0i6loMWImIiHoBSZLgdDrjtu4NXwaDwcjyarU6YXhqsVhgMBg4v4s6hdfrxYYNGzBtWtMHTP5cERFRX1RbcRCv3/cLSKFQyrcliCLyhwzDpQ8/AVFMvqMIERFRb+Rzu/HqHTfBbWtAyqMQQYDWYMRPn3kROhNPMCbq7TiDlYiIqAcIhUKw2+0Jq0/tdjukqFZzOp0uEpYOHTo0Jjy1Wq3QarUMuigttFotpk+f3uZywWAQSiX/NCUiot7p6//8K/UHdX8gSxKq9u7G3u9XY8TUU9OyTSIiou5q48fvpydcBQBZhs/twtr338Fpl/809dsjoi7Fo1hERETdQCAQiFt1Gr602+0xyxuNxkhYWlhY2CJAVavVXfRMiNqvpqYGt956K5577jnk5OR09e4QERF1KtuxahwoXZfWbQqiiNJPljJgJSKiPk0KhbDp02VpO8kJaDrRacsXn2DaxT+BSq1J23aJKP0YsBIREaWBz+eLCU2bB6gulyuyrCAIMJlMsFqtyMjIQHFxcYt2vqz0o95AlmUIgoCcnByccMIJuPLKK/Hxxx939W4RERF1qi3LP4EgipCjuo1EW76zDFsrj6LG4YRSoUBxVgYWjC1BrtkYWabW6cLSzTtxoLYBwZCEEfk5OH/iKJi08Q/cypKEw7u2o66yAllFA1LyvIiIiLq7fRu+h9vWmPD+1WXlWLOvHPUuDwAg32LEnJHDcEJBLtw+Pz7dvgd7qmvR4PbAqFFjdGE+5o0eDp1a1ep2/R439qxZhVGnze7Mp0NE3QxnsBIRER0nWZbh8XjiBqjh616vN7K8KIotZp9Gz0A1mUxQKDgvi/oGm80Gi8UCALjpppsQCATw8ssvd/FeERERdZ6Xf3EDGo8eSXj/379ei/H9C9A/0wpJlvHR1l04anPinvkzoFEq4QsG8dSn36DAasK8UcMBAJ9s2wO714tbZ0+HmGDsgyCKmH7JFZhy3kUpeV5ERETd3ScvPI0d33yZ8CSn7UeqIQoCso0GADLWH6zEV7v34465p0IG8Nm2PZg0qAh5ZiMaXB68u2EbCqwmXDXtxFa3Kwgihpw0Befe9WDnPyki6jZY/kJERNQGWZbhdDoThqeNjY0IBAKR5ZVKZSQs7devH0aOHBnTwtdkMnH+KfVpPp8PGk1Txc1LL72E8vJy/PWvf8W1116Lf/7zn127c0RERJ3I7/W0Gq4CwPUzJsdcv/SkcfjtB1+gssGGITlZOFjbgHq3G3eccQq0qqaKmUsnj8Nv3vsMZcfqMDwvO/6KZaB6/95OeR5EREQ90ZE9uxKGqwAwqjAv5vqZY0qwel8FyusaMGXwAFw1/ccgNdtowJljRuA/329CSJKgEMWE65XlpnnoRNS7MWAlIqI+T5IkOByOuK17w5ehUCiyvEajiYSlgwYNiqk+tVgs0Ov1DFCJEtixYwcOHTqEefPmAQDuueceDBkyBJdccgl27tyJSZMmIRQKYefOnRg9enQX7y0REdHxOXZwf7sf4w0EAQB6tRoAEJQkCBCgjDqQq1KIEAQBB2rqEwasPLhLRER9WcDrRUMbJzlFkyQZmyur4A+GMDArI+4y3kAAWpWy1XA1zNVQD4/DDp3JnPQ+EFHPwoCViIh6vWAwCLvdnrD61G63I7pjvl6vj4Slw4cPjwlPrVYrtFptFz4bop6trq4Ot9xyC7788ksUFRUBAK666ioMGzYMF154IS6++GKsWLECd955Jx5//HHMnz+/i/eYiIio4+zHqtu1vCTLeH/TDhRnZ6DAYgIADMy0Qq1UYNmWXThzTAlkyPhoyy5IsgyH19fq+pz1dZAlCUISB4KJiIh6E3tdDZDEdMSqRjueW7EawZAEtVKBq6efiPwf3oOjuXx+fL6jDCcP7p/0PjRWVzFgJerFGLASEVGPFwgEWq0+dTgcMcubTKZIWFpUVNRiFqr6h2oBIup8p556Ku666y5cccUVePnll1FVVYVXX30Vr776KmbOnAkAOPnkk/Hss8/itttuw+DBgzF8+PCu3WkiIqIOCgb87Vp+ycZtOGpz4OezpkZuM2o1uGLqRPxvwzas2nsQgiBg/IBC9MswI5mmKcFgACq1pr27TkRE1KOFokY5tSbHZMSdc0+FNxDElsoq/HftZtw88+SYkNUbCOAf36xDntmIM0Yl//k05E9uH4ioZ2LASkRE3Z7X640JTZsHqG63O7KsIAgwm82wWq3IysrC4MGDYwJUs9kMpZJvf0Rd6aabbkJVVRUefPBBfP7557j99tsxc+ZMyLKMUCgEnU6HGTNm4Nxzz8Vzzz2H5557rqt3mYiIqENEUZH0sv/buA07jhzDz06fCqteF3PfiPwc3L/gdLh8foiCAJ1ahd998AUyDfo216tQ8G9fIiLqfWRZhs/ng9vthsvlirl0u91oOFKZ1HqUChHZJgMAoCjTgkP1jVi19yAWTRoDoKl1/9+/XgvtD9WtybQHDhOVyf8dQEQ9D//KJiKiLiXLMtxud8LwtLGxET7fj63PFApFJCzNz89HSUlJzAxUk8kEkS3QiLq93/3udwgEAnA6ncjIyEAwGIQoipETIDweD0KhUKSNMBERUU+kMRrbXEaWZSwp3Y5th4/i5plTkWVMHJoaNE2dVvZW18Lp9WFUYV6r61aq1RAVPLhLRETdnyRJ8Hg8LYLSeF+HLyVJarEerVYLg8EArZhEm4d4+4Gm+edAU+Xq379eC4Uo4ppTToKqne+pGkPbfwcQUc/FgJWIiFJKlmU4HI4WAWp0iBqIatuiUqkiYWn//v0xevTomBmoRqMRQjK90Iio21OpVJEK1enTpyMUCiEzMxP19fUwGAz47rvv8Oqrr3b1bhIREXVYXvGQNpf538ZtKK04gmumT4JGqYDd4wUA6FQqqH6ofFl74BDyzEYYNGqU1zXg/dIdOHX4IOSaWz9wm5vE9omIiFIhFArFDUWjA9Po6x6PB3KzmamCIECv18NgMEQus7KyYq5HX+r1+shJ97Is4/n138Dncibcx4+27MKIghxk6HXwBYIorTiC/cfqcP2MyfAGAnhp5VoEQiFcNX08vIEAvD8cvzJqNBDbCHAVKjUyCgqP87tIRN0ZA1YiIjouoVAIDocjYfWp3W5HKBSKLK/VaiNh6ZAhQ2KqTy0WC3Q6HQNUoj7kuuuuw5IlSzBkyBBcf/31KC8vR3l5OfLz8/HYY49hyBAeGCYiop7LlJ0DjV4PX9RIi+bW7KsAAPztq+9ibr/kpLE4aVB/AECNw4WPt+6G2+9Hhl6P2ScMxYzhg1rdtqhQIH8o55gTEVHn8Pv9CYPSeF9HdyMLUygUMaGo2WxGfn5+3KDUYDBAq9V2+BiRIAjIHzIM5Vs3Ac2C2zCnz4f/fr8Zdq8PWpUShRYTrp8xGcPzc1B2rA4V9Y0AgMc/+irmcQ8sOL3NNv25xYPaNSqAiHoeQW5+WggREVGUYDDYIjSNrkZ1OBwxZxgaDIZIaNo8PLVardBoNF34bIioO9q0aROuu+46LF68GJMmTYq5T5KkmLbfGzZsQP/+/ZGbm5vu3SQiIuqQJU88jAOl6yHHaWOYagvvvB/Dp0xP+3aJiKh7k2UZXq83YevdeF8Hg8EW61Gr1XHD0XjVpQaDASqVKq0n1X/3vzex+u030v4eLIgiJp19Pmb85Jq0bpeI0osVrEREfZzf709YfWqz2eB0xrZSMZvNkbB0wIABMeGpxWKBSqXqomdCRD3V+PHjcf/99+Pyyy/H2rVrYTabI/dFh6uyLOPLL7/EhAkTMHv27K7YVSIionYbO3s+9m9Ym/btao0mDDlxctq3S0RE6ReeX5psdWmi+aU6nS4mFC0oKEhYXarX66FUdu94YdRps7H6rX+nfbuyJGH06WekfbtElF7d+xWQiIiOS/iMxOZVp9EzUD0eT2R5URRhNpthtVqRk5ODoUOHxlShms1mKBRsb0JEne/CCy9Ev379YsJVoOl1LHyGsyAIGDhwICoqKrpiF4mIiDpk0IQTYczMgrO+Lm3bFEQR4+aeCYWSJz8SEfVEwWAwYTga77boYzthoii2CESzs7MTVpfqdLqYE1x7A1NWNoZMmoJ9G9ZBlkJtP6ATCKKIopFjkFnYLy3bI6Kuw4CViKgHk2UZLperRXgafen3+yPLK5XKSGBaUFCAE044ISZANRqNve6PaSLqOU4++eSY65Ikwev1Qq//cbbNgAED8PnnnyMQCLBinoiIegRRVGDyeRdhxSuL07K9puEdAsadcVZatkdERK2TZRmBQKBFQBodlDa/PfpYTphSqYypIrVarSgsLIwbmOr1+uOaX9qbnHTOIpSt+67tBTuJLEmYcu5FadseEXUdBqxERN2YJElwOBwJq09tNlvMDAy1Wh0JSwcOHIixY8fGzEA1GAz845qIegyHw4HFixfjjDPOwIQJEwAAxcXFCIVCqKysxKBBg7p4D4mIiJIzfu5Z2LnqKxwt25PyOXACgOmXXQW9JaPFfdGzzffu3Yv//ve/0Ol0uPvuu1O6T0REvUm4W1h72vHGm1+q0WhiQtGcnJy4bXjDl2q1uguebc9XOLwEE888B6WffAhZllO6LUEUMeq02Rg4dnxKt0NE3QMDViKiLhQKhWC32+OGp42NjbDb7TEzMXQ6XSQsHTp0aEx4arVaeXYiEfUqZrMZI0eOxNKlS5GRkYHi4mLk5uZCp9OhvLycASsREfUYgijizJ/fiX/d9XOEZBlI0QFeQRRRVDIKUxaeH/dzgdvtxp49e/DEE0/AYrFgyZIlmDBhAq6++mpkZ2enZJ+IiLo7SZIStuFNVGUaL6gLB6PhUNRqtSasLu0J80t7k1MuuxJl67+Do642ZSc6CaIIvdmCmVdel5L1E1H3w1dxIqIUCgQCLVr2RgeoDocjZnmj0RgJSwsLC1sEqDxbkYj6EkEQcNZZZ6GxsRFvvvkmrrvuOmRlZWHAgAEoLy/v6t0jIiJql4z8Qiz4xT344Kk/pGT9gijCnJ2DBb+4N264unPnTjzxxBMoKirCRRddhMzMTFRWVuKOO+5AdnY2Nm3ahDVr1uDss89G//79U7KPRETpEAwG29WO1+v1tlhHeH5pOBQ1Go3Izc1NWF3aG+eX9iYqjRbn//Ih/L9f34OAz9vpIasgCFCoVDjv3t9Aozd06rqJqPsS5FTXxRP1IaGQhEM76nF0nw3Hyu2oqXAi4AtClgCFSoQlR4e8QWbkDjSjeGw29GaGZT2dz+dLOPvUZrPB5XJFlhUEAWazORKWxrvk2YtE1JdJkoQtW7agsLAQubm5kdu9Xi9efvllSJKEa6+9Fps3b8aKFSvwy1/+MvK6KcsyjuzZhcodW3F0/14cLdsDj8MBWQpBVChhzMxEwbAS5A8eioHjJiKrHw8cExFR19j57Up8/NcnAVnutFaFTeFqLi5+6PcwZ+e2uN/tduOOO+7AO++8g7q6OgDApZdeiuLiYjz++ON44YUX8Oqrr2LSpEn4/vvvcfbZZ+Phhx9Oevt1hw+hfPNGHN1fhqq9u+Csr4cUCkIQFdCZTMgfOhz5g4ehaOQYFA4vYdcdIkqaLMvw+/1xW+8mascbb36pSqWKW0XaPCgNX2o0Gr5W9ULV+8vw9iMPwu/1dFrIKogilGo1Lrz/YfQrGdkp6ySinoEBK1EncNl82P7NEWxbWQmPIwBBFCBL8X+1RFGAJMkQRAFDJuZgzMwiFA61pneHKSmyLMPj8bSoOo1u4xt9lqMoignDU6vVCpPJBIVC0YXPiIioezt06BDeeustOJ1OFBcXY/LkyRgxYgREUURDQwP+8Y9/ICcnB3PmzMHLL7+Mq6++GgV5udjx9Zco/fgD1B+phCCKgAzIcssPy4IoNh3IlmUUjRyNCfMXYuhJJ0MU+dpMRETpVb5lEz7665/hcdg75QBv8bgTcebP74DeYk24jM/nw2233YZVq1Zh1KhR8Hg8ePbZZzFo0CA8/PDDUCqVeOCBB+DxeHD++efjvvvuw8yZMxOuT5JCKFv3HUo/+RCVO7YBggBBEOI+H0EQAQGQJQmZhUWYcOY5GDnjdKi1uuN+7kTUs4SPtSRqx+vxeFrcHgqFWqxHo9HEbb2baIapSqXqgmdL3VH9kUosfeYJ1JTvP/6VCQIyC4tw9u2/RM6A4uNfHxH1KAxYiY6DLMnY/s1hrHqnDFJQavcYnXAQO2RiDk67bAR0Jla0ppMsy3A6nQnD08bGRgQCgcjySqWyRcve6EuTycSzG4mIjlMoFMKOHTuwdu1aVFZWwmKxYNKkSZg4cSJqa2vx2muvYdSoUdi9ezdGFRXg8DfL4WqsByAASP6NWBBFyJKE3EFDcNYtdyOriBWtRESUXl6XE1+99g9s/+oLCKICstQyQGiNIAhQajSY/dObMXLGrFY/i0iSFGld+dVXX2HRokVQqVT47rvvUF5ejs8//xzvvPMO/vnPf2LKlCnIysrCK6+8gnPPPReyLLdYd11lBT7665M4dmBf5D21HXsOQIbBmon5P7sdxeMmtut5E1H3EgqF4laRJqo49Xg8Lar3BUGATqeLCUSbX28envIEdjoeUiiEdR+8i9VvvwFZltt9slPTib0yplxwCU6+4BIolAzwifoiBqxEHeSy+fDZP7bjyN7G416XIAJqrRKzrx6JQWOzj3/nCEDTQQS73Z5wBqrNZos5C1Kj0SSsPrVYLNDr9QxQiYjS6MiRI1i7di22bdsGQRAwZswYZGRkYMUXX8DcUA2purKpUuY4/pwVRBGCIODUy67CiWefz9d5IiJKu+r9Zdj02TLs/OYrhIIBiAoFpDjVWtFVoMbMbEyYfzZGnz4XerMlqe2EQ9a77roLx44dwwUXXIAVK1Zg6dKleOaZZ1BRUYH77rsPCxYsgMFgwMsvv9xinqAsy9iwdAm++X//6tAB6djn0/QePmbWPMy65kYo1TzhmKg7CAQCCatL480wTTS/tLXq0ua3abVazi+lLmGvOYbNX3yMzZ9/DJ/L2fQeLEloWUUjQFSIkEIhqHU6jJk9H+PmnomM/MIu2W8i6h4YsBJ1gL3WgyVPboTL5k/YCrjdfjiee/rlJRg5nW/OyQgGg7Db7QmrT+12e8xBd71eHwlLm4enVqsVWq22C58NEREl4nK5sHHjRqxbtw4OWyOMh/dDdjSis6PQ8fPOxqxrbmTISkREXcLrdOLApvWo3l+Go/v2oP5wJYKBphE0Gp0eeYOHIm/wMBQMG4H+o8Z0uMX9a6+9hoyMDCxcuBAzZszA7Nmz8dBDDwEAPvzwQ6xcuRJPPPFEy3BVkrDiny9h06dLj/u5RhMEAf1OGIXzf/kQWwYTdTJZluHz+ZIKSsOX0Z28wlQqVdxwNNEMU7Vazb+pqUcJBgIo37IRR8v24Oi+vThWfgBBnw+ADKVag5wBg5A/dBjyBg9F8fgToVJrunqXiagbYMBK1E6uRh/e+eP6zg1Xm5n705EYPjk/JevuSfx+f6vVpw6HI2Z5k8mUsPrUYrFAzTOiiYh6NJ/Hg//89peoP3gA7WkH3B4nLjgXp11xHQ8IERFRrxauZn300UchyzJ+/etfAwB+9atf4dChQ/jXv/4Vs7wsy1j5+j+wYdn7KdkfQRRRVDIKF9z/O1ayErVCkqTI/NJEoWnzADXe/FKtVpt0daler+f8UiIiojiUXb0DRD2JLMn45O/bUhquAsDyf+5EdpEJmYWGlG2jO/B6vTGhafMA1e12R5YVBAFmsxlWqxVZWVkYPHhwTJBqNpuhVPIljYioN1vz9htoKE9duAoAG5a9j/yhI1AybUbKtkFERNTVwtWp5557Lm655RaUlpZi0qRJWLJkCe67776Yma2SJGHdJ0tTFq4CTdWxlTu3YdWbr2PmFdembDtE3U14fmlbQWn460TzS5sHollZWQmrS3U6HeeXEhERdQJWsBK1w5YvD+GbN/emfDuCCGT3M2LRfZMgKhLPoKivr8dHH32Efv364fTTT0/5frWHLMtwu91xA9TwdZ/PF1leoVC0qD6NrkI1mUycx0FE1Icd3rUD/33o3tRvSGhqw3jN04thsGakfntERETdwPPPP4+6ujqccsopOO2002LCF2dDPV685adAMJiWfbn04T+h34gT0rItos7m9/sThqPxbos+LhKmUCjiVpEmqjLV6XTsvkJERNQFGLASJclR78Ubv/kOoaCUtm1OXzQU4+cMaHG7LMv4/vvvsXz5chiNRixatAj9+vVL236F98HhcCQMT202W8zcDpVK1aJlb/R1o9HIDwRERBSXFArhldtvhL32GGQp9e/Dgihi2JTpWHj7L1O+LSIiou5MkiT85+EHcXTn1k6ffR6PIIowZ+fip8+8CJEVdtTFwvNLmwekrc0wDcY5EUGtVicMR+PdzvmlREREPQP7aRIladvXhyGl4aButNLPKjD29KKYKta6ujq8//77OHToECZPnozZs2enZLZoKBSCw+GI27o3fBn9/dBqtZGwdMiQIS0CVJ5RSUREHbVvw/ewHTuatu3JkoQ9362CveYamHNy07ZdIiKi7kSWZdRXHUF1msJVoOk92HbsKPZtXIthJ01N01aprwjPL022Ha/b7Y57HEin08WEowUFBa3OMOU4IyIiot6J7/BESQgFJGz/+jDk9OarcNv9OLi1DoPH50CSJHz//fdYsWIFTCYTrrrqKhQXF3d43cFgMGH1aWNjIxwOR8xcD4PBEAlL8/PzY8JTq9UKjUbTCc+YiIiopdJPlkIQxbRUr4YJgoAtyz/BKZdembZtEhERdSeCIGDn18vT/x4siij95EMGrNSmYDCYsA1vvCpTj8fTYh3h+aXR4Wh2dnbC1rx6vZ7ji4iIiAgAA1aipBzYUgufO/G8mU9L/4PNB1ahurECKoUGg/NH4twpNyDP2j+yzDMf3Imyqs0xj5t+wtm4bMYdCdcriMD2rw/DXCTg/fffR2VlJaZMmYJZs2a1WbXq9/tbrT51Op0xy5vN5khYOmDAgBazUFUqVavbIyIiSgXbsWoc2r6l1WWW7yzD1sqjqHE4oVQoUJyVgQVjS5BrNgIA6l1u/H7Zl3Efe8XUiRjXv6DF7bIkYfPnH2P6JVewAwMREfVJsiRhyxeftBquri4rx5p95ah3NQVX+RYj5owchhMKmjpABEIhfLhpJzYdOoKgJGFEXg4uOHE0TNrEJ+jKkoRD27bAdqwalty8zn1SvVwgEMCXX36JrKwsTJgwAaIo4oknnsCqVatQVVWFOXPm4O6770ZWVlZX72oLsiwjEAgkXV3qcrng9/tbrEepVMYEohaLBQUFBS2qS8OXWq2Wf+sRERFRhzBgJUrC0X02iAoBUij+yOKyI1swY9Q5GJhTgpAcwodrX8Zfl92LX138CjQqXWS5aSULcPZJV0euq5StV33KElC5tx6L/7YUFqsF11xzDQYMGABZluHxeGJC0+YBavSZmaIowmw2w2q1IicnB0OHDo0JUM1mMxScb0NERN3QkT0721xmf009pg8diP6ZVkiyjI+27sJLX6/FPfNnQKNUwqrT4TcLZ8c85rv9h7By9z6U5OckXK/X6UBjdRUy8guP+3kQERH1NI3VVfA6Ha0uY9FrcdbYEmQbDQBkrD9YiX9+ux53zD0V+RYTPti0AzurjuGKqROhU6mwpHQb/vXtBtwye1qb2z+ydxcD1iTJsgxBEPDZZ59h4cKFuPbaa/H3v/8dr732Gnbt2oXrr78eY8eOxfXXX4+XXnoJ999/f1r2yev1JgxH480wTTS/NDoUzcnJSVhdajAYoFKpGJgSERFRWjBgJUpC9UFbwnAVAH6+4PGY65fPvBf3v3YhDtXsxdDCsZHb1UoNzPrMdm1bCgAF2QORW2TFqlWrIiFq9JmaSqUyEpYWFhZi5MiRMTNQjUYjW9gQEVGPVL2/DKJCASkUSrjM9TMmx1y/9KRx+O0HX6CywYYhOVkQRQFmnTZmmW2Hj2Jc/wJoVK3/OVy9v4wBKxER9UnV+8vaXGZUYWwAeuaYEqzeV4HyugZYdFqsPXAI/zdlAoblZQMALjlpHJ74ZCXK6xowMCsj4XpFhQLV+8twwvTTju9J9BGCIKChoQErV67EqaeeitzcpgrilStXIhgMYuHChQAAq9Uat01uMiRJSjooDV9Gjx0K0+l0MYGoxWJJWF2q1+s5v5SIiIi6Lf6VQpSE2kpn2wtF8fpdAAC91hRz+/qy5VhX9gXMukyMHjgVZ068HGqVNt4qYtQddsIPJ6xWKwYOHIixY8fGzEA1GAw8Q5OIiHql6gNlrYar8XgDTdUP+gTt9CvrbTjSaMcFE0e1uh5RoUDNwf0omTajXdsnIiLqDY6VH2jzJKdokiRjc2UV/MEQBmZloLLBhpAkY/gP4SoA5JqNsOp1KK9tPWCVQiEcSyLgpR+rV59++mkMHjwYw4cPx4oVK2Cz2XDvvffiySefxMSJE1FXV4cxY8bg2muvjbuO2tpa7Nu3L2Fr3njBrCiKMVWk4QrTeEGpwWCATqfjyd9ERETUazBgJWqDJMkI+hPPnGmxvCzhndXPY3D+aBRmDorcPmnoLGSa8mDRZ+FI/X68//3fcazxEK6f97u21xkQoFQqMHjwYIwaNQpGo7FDz4WIiKin8Thab03YnCTLeH/TDhRnZ6DAYoq7zPcHKpBrNqI4u+2uEl5X+06yIiIi6i18zuTeA6sa7XhuxWoEQxLUSgWunn4i8i0mHGm0QyGK0KlVMcubtGrYvb421+tx2Du0332NIAjYsGEDHA4HrrjiCqxevRoAoNfrUVBQAK1Wi6uvvhrz58/H4sWLcdddd+Gtt96KCTplWUZVVRWWL18eE45mZGSgX79+catLDQYDNBoNT/YmIiKiPosBK1Eb5FZaA8fz1qpnUVV/EHec+5eY208ZeXbk635Zg2HWZ+G5pXejxnYEOZbErQdlyNBqdKirq8Inn3yCTz75JPJBJysrCxqNBiqVKvJPqVTGXI/3L7yMUqnkhyEiIurW5HZWry7ZuA1HbQ78fNbUuPcHgiGUVhzBnJHDklqfFEr+JCsiIqLeRJJCSObTcI7JiDvnngpvIIgtlVX479rNuHnmyZ2y/b5KlmV4PJ4WVaQulwvDhg1DXl5eTED62Wefobq6GpIkYdWqVSgtLcULL7yA2tpaHDhwAM8++ywA4JJLLsEf//hHrFmzBtOnT488XhRFjB49GmPHjm2xL0REREQUHwNWojaIyuQDyLdWPYtt5d/h9nOeRoYxp9Vli3NLAAA19sOtBqwCBPQrKoC2IBNerxf19fVobGxEZWUlKisrIwErAAQCAQQCAUhS8geDkwllm9/fnhA3/I9BLhERdYRSrUl62f9t3IYdR47hZ6dPhVWvi7vMlsoqBEIhTBrYr831SZKEQ5WV+PLLL2GxWGA2m2GxWGCxWKBO0H6YiIioJ/L5fLDb7bDZbJHLQ5WHISfx2VKpEJFtMgAAijItOFTfiFV7D2Jc/wKEJAkefyCmitXh9cOsbfv9XalK/m+A7i4UCsHj8bSYUZpohmmi+aV6vR5WqzUyYxVoOg5QU1OD9evXY+7cuVAoFKirq8PRo0dhtVqxYcOGmGX37NmDYcNanmjG1r1ERERE7cOAlagNgiDAlKmFo96bcBlZlvH2t89h84FV+MU5TyHbXNDmeivr9gEALPq22xOeMmsyCoZaY25rbGzE1q1bsXXrVtTU1CAzMxN33nknBEFAKBRCMBiMBK7hf/Fua2sZl8uVcNlQO6qKFApFuwLZjgS/KpWKHwqJiHqZzH5FqKk40OoBXlmWsaR0O7YdPoqbZ05FllGfcNnvDxzCyMI8GJM4sAtZhk8QUVpaCkezVsVarTYSuEYHr9G3KRSKpJ8nERFRqgSDQTgcDthstpgANfrS6439vGsymaARRCBOyNcWCUBQklCUYYFCFLD3WC3GFjV9Rj5md6LR7cHA7MTzVwFAEEVk9itq97bTJRAIJAxK433d/PsLNAWa0TNKjUYjcnNz47bj1ev1CeeXqlQqPPXUU3jqqacAAE6nE7Nnz8YNN9yAoqIi7N+/H6eddhpUKhXsdjvuuuuumICWiIiIiDqGAStREvIGmeFs8Cb8bPnWqmexvmw5bpj3CLQqPezuegCAVm2AWqlBje0I1pctx6gBU2DQmnG4bj/+t+YFDC0Yi35ZQ1rfuABk9285Q85qteLUU0/FKaecgurqajQ2NkaqRBUKBRQKBTSa1J7xK0lSi0C2IyFuMBiE1+uFw+FIuHyyRFHs1GrcRPeLosiqXCKiNMgbNAS7V3/d6jL/27gNpRVHcM30SdAoFbB7mg5i6lQqqJQ/hpy1DhcO1NTj2lNPSnr75/7f5Sg6YTRCoVDk4HT4gHT468OHD2PHjh3weDwxjzUajS1C2Ogw1mAw8MQgIiI6LpIkweVytRqeOpvNUtXpdJH3pAEDBrQ4SchkMkGhUKByxza8+bv7Wt3+R1t2YURBDjL0OvgCQZRWHMH+Y3W4fsZk6NQqTB7UHx9s2gm9WgWtUoUlpdswMMuKgVmtB6yQZeQNHnq8356kyLIMn8/XIhRtLTQNBAIt1qNSqWJC0czMTBQVFUUC0uahaWfPL5UkCaIoIhgMYsGCBQgEAlCpVPjjH/+I0tJSZGZmIjc3F/n5+Z22TSIiIqK+jAErURJyB5qxb+OxhPd/s+MDAMBfPrwz5vbLZ96Dk0fMh1KhxO7DG/Hl1nfhD3qRYcjF+EGnYt7Ey9vctiVHB5UmcQWMIAjIz8/vkg9JoihCrVanvE2iLMsxoWxbIW5r1bt+vz9uVW74/nhtmOIRBCHlIa5KpYJCoWCQS0R9Wt6QYW2+Nq/ZVwEA+NtX38XcfslJY3HSoP6R62sPHIJFr8Xw/Nbb+EfLHdR0IpRCoYDVaoXVak24rN/vh91ubxHA2mw27Nu3DzabLeaArCiKMJlMMQe2m1fD6nQ6vg8QEfVR4Tmczd9Xoq87HI6YETEqlSryHpKXl4dhw4a1eJ9J9vNb7qDBbS7j9Pnw3+83w+71QatSotBiwvUzJkfea88ZPxICduJfqzciGJIwIj8bF0wcndRz72jAGv6+JVtd6na743Zn0mq1MYFoXl5e3KA0fBke3dNVwidtWa1W/OY3v4ncbrVacfrpp3fVbhERERH1WoKcbJpA1Ic1VrvxxkPftb1gJxMEYOK8gTj5vDaqXKlTyLKMUCjU4RC3rcdFh7zteelN1Vzc5vfxAD4RdUehYACLb7wSXqej7YU7kSCKKBo5Bhf/+rFOW6csy/B6vXGrYKMrjZofKI+ufo3XjpjzYImIeia/39/qe4LNZovp5iOKYsLOCOFLrVbbqX/Xv/XIA6jcsS2pWaydSWs04aYXX4NCqUIoFEpYXRpvhqnH42nxeUsQBOh0uritdxN9zVb/RERERNQaVrASJcGap0fRiAwc3tsAOY2fK2UAo2b0S98G+zhBEKBUKqFUpv6lMdGc3PaGtYFAAE6nM+Fj2jMnN9nQtq2gtq2Ql+0wiag9FEoVxs09E2vffyetB3dlScLE+Qs7dZ3hg7s6nS5h5wlZluF0OuMebK+pqUFZWVmLVo9arTZhG+JwKMuDxERE6RUKheK2642+bD6X02g0Rl6/c3NzW7yeG43GtJ8UOWH+QhzatiWt24QgQM4pxAt/WwyXywWfz9diEYVCEROIhit2E1WXsiMEEREREXU2BqxESRpzehEqdzekbXuCCAwcnQVTpjZt26T06co5ue2ZmRt9v9vtbrUFc7IUCsVxhbXJtlxmmEDUe4ydMx/fv/d2GrcowJCRgcEnJj+rtdO2LAgwmUwwmUzo1y/+SVbR82CbH7A/dOgQ7HZ73HmwrVXBdsVBeyKinip8Mkxr1afx5p6GX3P79++P0aNHx7weh+eedjdDJk6GwZoBV2Mjmk4BTgNZRv6YCTDn5CasOFWr1XzfIiIiIqIuxYCVKEmDxmajcJgVVfsa01LFKggCpl3QsZkzRGFdNSe3oyFuIBCAz+eLqcpt/i9Zoih2OMhtz9xczsklSj1zdi4mnX0+1i9dAqRluoWMWVffAFHsfge6gfbNg4138L+srAx2u73FPNjo8DVeNWxnt50kIgoLBAKorq6OvA51peh27omqT+O1cw+/Zubk5GDo0KEtXkt7Sjt3SZLg8Xhi2u8OOHU2dn74Tnp2QBBw0sILMOMnl6dne0REREREHcQZrETtYK/14D+/+x6hQOoT1mkXDMWEMwakfDtEPUn0nNzjCXHbWj4QCCQ9J1cQhHaHsh2Zm8s5uZ2nrKwMl19+Oc4880w88MADUKlU+POf/4wtW7ZAEATMnz8fF110UVrahVPygn4//nXPz2E7Vp3SVsGCKGLY5KlYeMf9KdtGd9DRAKG1ADadAcKuXbvw6aef4rLLLkNubm5atklEx6+qqgqvvfYazj33XJSUlKCsrAzXXHMN3G43JEnC1KlT8cc//hEmkyll+xB9Akqi17/edAJKKBSKmVMab3Zp8zmmzQmCAP2R/RAa6pDKKlZBFGHJzcNVf3oeyh4SSBMRERFR38Ujh0TtYM7WYcalw/Hl67tStg1BBPIHWzBuTv+UbYOop4qek6vT6VK6reZB7vGEuF6vN+HyxzMnt7ND3PC/7nqAsLM89dRTOHjwIICmwOjhhx/GkSNHMHv2bIiiiBdffBGZmZmYN29e1+4oxVCq1Tjr1rvx34d+CVmSkYoDvIIoQm+2YPa1P+v0dXc3ycyDlSQJLpcrbhVsonmw0S0w44UQndECs66uDtdffz3Wrl2L0aNHY/bs2Xj//ffxyCOPQK1WIyMjA7/61a8wderU49oOEXW+p556Ck8++SRyc3NRUlKC++67D1deeSWuv/56AIDVasWiRYswa9asDq0/PPc00czT1uaems3mSOVpd26h7vf74walzUPS8PVE80ujW+9aLBYUFBS0aMMbvtRqtfA47HjtnlvgtttSc6KTIEAQRZx1690MV4mIiIioR2DAStROI6cXwm334/v393f6ugURyCo0YsHPx0EUu8+HeKK+KDwnV6tN7RxkSZI6HOImmpMb776Ozsnt7JbK0f9EUUzhdzaWJEkQRRE33ngjZs2ahcbGxsj/7fLlyzFv3jxcddVVAIDHHnssEsBS91IwdATOvetBvPenR5o6BXdiIxZBFKHRG3DxQ3+A3mzptPX2ZKIoRubBJtI8zIiufj106BC2bduWMMxINBO2tTCjvLwcTz/9NCZNmoT8/Hz069cPO3fuxP33349XX30VgwcPxttvv41HHnkEH3zwASvReyC/14NjB/ahrvIQAt6mWcIqrQ5ZRf2RO2gI1NrUnmBFqbN582bY7XbMmTMnEvpVVFSgrq4OTqcTNTU1kd/teMJzTxPNPI0391Sr1UZeX/r3749Ro0a1eP3pyrmn4W4CrVWUNg9Q4/1Np1arYwLR7OxsDBgwoEVQGr7syAl1erMFFz/0B/y/X98Dn9vVuSGrIEAQBJx714MoGDqi89ZLRERERJRCPOJA1AGTziyGUiXi23fKIIjotJmseYMsOPuWcdDo+KtJ1FeIogiNRgONRpPS7ciy3OEQt/l9Xq8XDocj4fLJip6Te7zVuM3vz8zMbLGtt99+G5IkYeHChfj4448hCAICgQCee+453HPPPfj222/h8/kwc+ZMLFy4sLP/C6iTDJ54Ei745UN4/8nHEAoGO+UAryCKMFgzcNGvf4/Mwn6dsJd9h0KhQEZGBjIyMhIu4/f7E7bhrK6uhs1miwkMxo0bh/POO6/FeqqqqrB48WL0798f06dPx69//WsYDAbU1NQgMzMTRqMROTk56N+/P7Zv396loQm1j9vWiK1ffo7tX32BhqrDkduFH07Eif49zyjoh1Ez52DMrDN4MkQPIcsyBEHAb3/7Wzz44IN4/fXXUVFRAZ/Ph3fffRc/+9nP8Oyzz8LhcODiiy+GSqWKu5733nsPW7ZsiVyPblsennvaVW3Lw8LzS5OtLg23Rm5Op9PFhKLR1aXxqkzTdTJJZmERLnvkz3j7kQfgamzotPdghVKJc+96EMXjT+yEvSQiIiIiSg+mOEQdNH7OAOQVm/HFqzvgqPd2uIhGEAEBAiafMwgT5g6AqEhfRRcR9R2CIECtVqf8QGOiObkdabfs9/vhcrkSLp9oTq5arcb998fOz2xoaMDixYvx8ssvQ6/Xw+/3Iy8vDyqVChs3bkRxcTEmT56M6upqrFu3Lm47PaAp4AkGg3FDXoVC0a1aCPZmxeNPxNVPvoCPn38ah3dt7/B6BEGALMsYddpszLzyOmj0hk7cSwpTq9XIyclBTk5O3PtlWYbH44kEr3q9PlJ1Hu3FF19EVlYW7rrrLixbtgwFBQXIyMhA//79MWfOHJx22mlQq9UYM2YMXn755cj/L38vuy9XYwO+fuNV7Pp2JWRJavG6Hi+8aag6jG//+xpWv/VvlEw/DTN+cg0M1sQBP3U9QRDw3nvvYcyYMZg0aRJWrVqFqqoqaDQalJWVYcCAAXjxxRdRWFiIm2++GY899hieeeYZWK3WyDokScKkSZMwcuTISHiq0+lS/vsdDAaTmlsa/trj8bRYhyiKLQLR7OzshNWlOp0urV0+2iuzsB+ufvIFfPXaP7Dty88jr7UdVTj8BJz58ztgyY1fuUxERERE1F0xYCU6DgVDrbj0oSlYv+wgtn5ViYAvBAhIaixcuPK1aEQGpl80DFmFxpTvLxFRqqVrTq4syzHtlaP/xZtru2bNGuzduxezZs2CwWDAoUOHsGLFCjgcDjzyyCP45ptvMHz4cADAvHnz8Omnn+KGG25ocYDz448/xqFDhxLu1/G2VE62UpeBEWDJzcclD/0BW5Z/gjXv/heuhnoIophUNY0gKiBLIWT1H4gZP7kGg1gx06UEQYiED4lag1ZUVGDZsmWora3FwYMHsWnTJgQCAezfvx9Lly5FbW0tVq1aBYPBgDvvvBOHDx+OrDvM5/Nhz549kQq3zpgHSx0jyzJ2rf4aX/z9eQR83nZXwcmyDDkUws5VX6Fs3XeYc/3PUTJtBl8bu0goFILD4YhUpg8fPjymM4csy1i2bBn0ej127tyJb775Bhs2bIBWq8X69esxZMgQFBYWAgDmz5+Pf/7zn6ipqYkJWEVRRP/+/Y9rP2VZjswvTTY09fv9LdajVCpjqkitVisKCwvjBqZ6vR5arbbX/Wxq9AbMu+kXGH7yKfj6jVdRW3Ew8t7alvB7tSEjE1MvvBRjZ8+PVKsTEREREfUkDFiJjpNKrcDU84dg0lnF2Lu+Gtu/PozaQ05IUlPKKggAhNg2wgarBsNOysOoUwthzdV3zY4TEfVggiC0a07uWWedhbKyMjgcDoiiiAsvvBCnn346Fi1ahF/84hcxMyK9Xm/CA6GLFi2C1+vtULvlYDAIl8uVcPl4wXAi4aC1I/Nv2/OY7lxBAzQdpB039yyMmT0PB0rXY9Ony1C5cxuCPxwQFwSh6Y1YliPVNVqDEYMnnoTx885G/tDhve6gd281YMAALF26FDt37kRdXR1KS0vR0NCAFStW4JlnnsFf//pXlJSUAABKSkqwfv16XHjhhTAafzyB7dixY/jf//4Xs16TyRQJXJtfWiwWGAwG/ox0MikUwmcvPovtK5dHfj87SpYk+L0efPTsn1C+pRRn3HArRIbmnUqWZbhcrpiZp80vHQ5HzGOuvfZaFBUVRa67XC4IgoCVK1di3759kGUZKpUKEydOhNFojASqFosFmzZtglarxbBhw5LaN6/Xm3R1qcvlivteq9FoYkLRnJycuG14w5fpbjvcnQ0afyKKx03E0bI92PTpUuzbuA4+V9Mc3HjvwUq1GkUnjMb4eQswaMIkiCJ/X4mIiIio5xLk4+nlQkRxhYIS6o+4UFvpgM8dhCwBSrUIa64eOQNM0BrjzxUiIqL0mDZtGm677TZceumleOGFF/Duu++iqKgIsiyjtrYWL730UszB4XSQJCluKNveELe15cPLJEuhUKQ8xA23V+4ssiSh4egRVO8vg8duQygYhEKlhik7G3mDhsKUlc3ArBc477zzMGfOHNxyyy1YsGABTjnllEhr8LPPPhsnnngi7r33XhgMsW2fw/NgEwVFzefBKhQKmEymmJmOzS97Y3VaqkhSCMv+8ifs+W5VStY//ORTsOAX9zC0SVI4oEz0u2Cz2eBwOGJCSaVSmfB3Ifx70lYAWVFRgUWLFuHtt99GQUEBnnzySbz22mvQ6XQYOHAgHnnkEYwePbrF4+x2O5YsWRITmsY7nNE8GE0UlIb/pWt+aV8gyzIcdbWoPlAGR20tQgE/FEoldGYL8gYPRUZ+IatViYiIiKjXYMBKREREfU5VVRUMBgPMZjMCgQC++eYb1NXVwe12Y9q0aUlVzvRUsizHBLHtDXHb85hk/8wUBKFdgWxbAW6iZTgnt+cLz1R9/fXXMXDgQEyfPh3l5eW47rrr0NjYCKVSieLiYjz++OMYPHhwh9bv8XhahEx2uz0mfIr+2Var1a2GTWazGSoVT64DgOWvLsamT5amdBvj55+N2dfclNJt9BSBQKDFz3Hzy+gWuIIgxPwMN/85tlgsxzX3NBQKQaFQoL6+Hh999BHOOOMM5ObmIhQKQRCENrsm+P1+fPjhh3ED1PDX3X1+KRERERER9R4MWImIiIio08myjFAo1OEQt63Hhe/z+/1JB7lAyzm5HQ1x25qlyyA3/RwOBw4fPoyMjAzk5eWlbDuSJMHpdLYaXLlcrpjH6HS6mKCqeXDVU+fB+nw++P1+mEymNpc9uKUU7z726zTsFbDowUcxcOz4NpdzOBxQq9Ux80J7ivDc00QnAthsNng8npjHGAyGVn8OjUZjwnAyPL80Uevd6NuGDBmC008/na+DRERERETUqzFgJSIiIqIeLRQKdTjEbU/A25E5ucfTTjmZkJeVWt1TMBhsEXY1v+7z+SLLC4IAo9HYahVsd5wHu3r1aqxYsQKnnnoqTjnllIQhsc/txqt33Ai3rbFdJ0R0hCAI0FszcM1Ti6HR6+MuEwqFsGrVKqxcuRInnngiFixYkNJ9aq/ouaeJ2vc6nc6Y76VGo2m1lbXZbI5phRuu1k4UlMa7Pd5roFarbVFFOmDAAIwfPz4d3yoiIiIiIqIuw2EjRERERNSjKRQKKBSKlFehxZuT29GZuW63u9UWzMlSKBRJhbLtvb35/T2xurIrKZVKZGZmIjMzM+EyPp8vYQB79OhR2O32FvNg22rfqtFo0hbCyrIMq9WKSZMmYeXKldi5cyfOOeccFBYWtlh2w7IlcNtsKQ9Xw/vlbmzEhmXvYdpF/9fi/iNHjuC9995DTU0NALSo8kzH/vl8vjbbUDefexr+P87OzsbgwYNb/P8rlcq44eiBAwda3Bb+1/z/QxAE6HS6mFmlmZmZrc4w5WsDERERERH1VaxgJSIiIiLqRprPyW1PiBtvmdYekyxRFDvcOrk9j+Gc3B/Jsgy3252wgtFms8HhcLSYB5uogrGz58H6/X48/fTTAIBx48bhwIEDqKmpwbRp03DaaadFthMKBvHizVfBY7d1ynaTpTNbcOPf/gXFD1WbgUAAX375JdasWQNBEKBUKjFnzhxMmjSpUyvBo+eeJgpQ4809bf5/pdfrodFooFAoEAqFEoak4eter7fFvigUilbnlTa/TavVsiqeiIiIiIgoSQxYiYiIiIj6oOg5ucdTjZvM8sl+5AgHX+HANSsrCxkZGTEzIo1GIwwGA3Q6XUz1nCzLkGUZgiBEQtrwdsNBZG+bkxueB5toFqzdbm8xD1av17daBWsymZIO2ZxOJ1auXIkNGzbAZDKhqKgIu3fvhtVqxTnnnIMBAwZg95pVWPrM4wnXsbqsHGv2laPe1VRJmm8xYs7IYTihIBcA8M76rdhbXQub1wuNUonirAwsGFuCXLOxzf07+/b7MGLqKSgvL8eSJUtgszWFvKNHj8a8efNgNLa9jmiSJMHhcMQNT8OXbrc75jEGgwEmkwkmkwk6nQ4ajQZKpTLysxsMBuHxeFq04413AoRKpUoYjsYLT9Vqda/4OSciIiIiIuqOGLASEREREVFKNQ9yO6sSN9zSNBwomUwmmM1mWK1WaLVaHDt2DKWlpThw4ECLfWrP/NuOVO52lzm54XmwrVVUNp8HG/4+JpoJq9frY4K72tpaLF++HLt27UJ2dnbktpNOOgmhPVux9/tvIUtS3P3bfqQaoiAg22gAIGP9wUp8tXs/7ph7KvItJny3rwI5ZgMy9Dq4/QF8tn0PjjTa8cBZsyCKicNDQRQx7ORTIA8qQWlpKQAgIyMD55xzDoqLi1ssH64Ybi2sbl4xHA48tVptTHAvSRJCoRB8Pl9kzmmi+aXR4Wi86tLo+zur+piIiIiIiIiOHwNWIiIiIiLqFSRJSmklbniZ45mT29khbvjf8QS5iWaCRl9GB4TR82Cjq2H9fj+2bNmC6upqZGdno7GxEdrdmwBf++ac/vq9z3D22BJMGTygxX1HGu146rNvcN9ZM38IZROTNVq4hoyBQqHAKaecghEjRkQqfqMD5sbGRtjtdkhRIbAgCNBoNJHvrSzLkZ8vv98fd35paxWlzUPT5hXYRERERERE1LMou3oHiIiIiIiIOoMoitBoNNBoNCndjizLHQ5xm9/u9XrhcDgSPiZZ4Tm5xzMTV6lUwmQyITMzs8XtwWAQLpcLTqczJnytr6/HgQMHWlR31tbWAqEQZJ8HyTaplSQZmyur4A+GMDAro8X9vmAQ6w5UItOgg1Wna3uFPi8UaPr/WrlyJVauXBm5KzzvV5KkmGA1+vupVqtbhKSJqky1Wi3b8RIREREREfUhDFiJiIiIiIjaQRAEqNVqqNXqlG5HluVIxWxHQtzo+/x+P1wuV8LHtGdObvOw1mAwwGKxRCo9ZVluqoqtOpxUuFrVaMdzK1YjGJKgVipw9fQTkW8xRe7/tuwglm3ZBX8whByTATecNgVKRdsVuwIA2euGpNVDqVRGWvKazeY2q0w5v5SIiIiIiIhawxbBREREREREfVh0+9uOhLjh+30+X6Tdrsfjgeh2Qn9wZ5vbD4YkNLo98AaC2FJZhe8PHMLNM0+OhKwefwBOnx92rxcrd++HzePFLbOmQZVEi133/2fvvuOcLuz/gb8+n+xcLsntwQHHwbFkyF4CyhCLIooiDtxapVVbRy0d3w5rW6ttHa2KVtQ6WjdgRZYgArLx2BuO4xYHt5Jc9vj8/uCXmNwludzIzdfz8eCRS/LJ5/PJcZdcPq/P+/3uMwg+jQ5ZWVkYPHgw+vXrB41GE1LJyyCViIiIiIiImooBKxERERERETWLJEk4e/Ys9u3bh8OHD8PpdCIlJQWSJKG2tBjawsNNXudrG7cjRZeAG0cPbXCfx+vD/y1fi5vGDMWIXj0aXZetz2D4NNFntcrl8kZn3LbG3NyWzMklIiIiIiKijoUtgomIiIiIiKhJqqqqsG3bNhw+fBh2ux0KhQIymQyiKKKqqgoAIMRQYRqOD4AnzFzUiyQAEjzeSPfXW1omg1KphFwuh8vlgsfjCdynVCqRlZWF3r17Q6lURqzatdvtMJvNcZmT25KZuZHuF0WRVblERERERERxxoCViIiIiIiIAnw+H+rq6lBbW4vz58/jwoULqK6uhslkgtVqhdPphNfrDXmMP2wUBCEwk9VoNKLkzBH4gkLN+r7cfxQDstKQpNXA6fag4GwZTp+vwv1TxqKqzoa9xWUYkJGGBJUSJrsdG46egkImw8Cs9Eafh0ypxPU33wKz2QKTyQSz2YzKykqYTCZ4PB64XC4UFRWhqKgoMJvVYDBAr9cjLS0tcN1gMECn04WtQI11Tm60NsvxnJMbrxDXH6gzyCUiIiIiou6KASsREREREVE3IUkSbDYbzGZzIECtrKxEbW0tLBYLbDZbxKpMQRCgUqlgNBqh1Wpht9tRXV0NSZIwZMgQTJ48GWlpaSGP+eDgLpQejdwmuM7pxAc79sHscEKtkCPbkIj7p4xF/8w0mOwOFF6oxubjhbC73dCpVMhLS8ZD0yYiUa1q9Llm5uVj6NBh4bdbV4fdu3dj//79SEpKQq9evQIhbGFhIUwmE1wuV8hzT0xMDASuwWGs/zIxMTFugWMsc3Ibm5UbfJ/dbo+4vC9i9XBDwYGrUqnEJZdcguzsbCiVSjidzsA//7Z8Pl+TQ165XM4gl4iIiIiIOhzOYCUiIiIiIuoinE5nICisqalBZWUlqqqqAtWnDocjYiWkTCaDWq2GTqeD0WhESkoKMjIykJqaiqSkJKjV6kDQtXPnTnzzzTcYPXo0xo4di4SE8HNOt3zwDnau+ARSE0K71iCIIsbOvRGX3XxHsx4vSVLI99JkMgW+9l83m80hlbxyuTxs8BocyqpUjQfD7c3r9cYc1Ab/GzZsWGD+riAI8Pl8EAQhpPLXH/CbTCbU1NSEfH/9l1artcE+xTr/trGgtrFKXc7JJSIiIiKiWDFgJSIiIiIi6gQ8Hk9IwOcPUGtqagLVp/Vb9wZTKBTQarXQ6/VISkpCWloa0tPTYTQaYTQaoVQqm7Q//iAtmtpz5Vj6k/ubtN7Wcu+L/4IxMytu65ckCVarNWIAazKZUFdXFxJoq1SqkMC1fgCr1+shl3ePRlPB35fgnyN/22W32x2ogLXb7YHKa4vFEjbojdaCOVYymaxFYW2s7ZZlzZxPTEREREREHUf3+ORGRERERETUgfnnngZX8lVXVwdmn9bV1YW0rA1HrVYHwtLk5GSkp6cjKSkJRqMRBoOh1YO7WNq2GjOz0HvYCJw9uK/NqlgFUUSvIZfGNVwFLj5/nU4HnU6H7OzssMt4vV5YLJYGVZpmsxmlpaU4fPgw7HZ7yGP8M2zDBbDR5sF2NpF+foJnyGq12hZvJziwjbWdcqRlnE4n6urqIi4fK1EUmzX/trHl6y/DOblERERERPHDgJWIiIiIiCiOJEmC3W4PqXL0V6BWV1fDYrHAbrdHbN0LXAyd/NWnRqMRaWlpSE5ODgSqiYmJHbYqbuzcG1G0v6DNtif5fBg794Y22140Mpks8H8UidvtblAF6788ffo0zGZzSLguiiISExOjtiPWaDQM1v6/4MA2niRJgtfrbXKQG6kS1z8POdy/WBuRCYIQ9xCXc3KJiIiIqLtii2AiIiIiIuqUPB4PBEEIBIs1NTV4+umnceLECXi9Xvz5z3/GsGHD4r4fTqezQYWiP0Ctra2F1WqN2roXuBia6XQ6GAwGJCcnIyUlJRDMGY1G6HS6Th1grH71BRzetCHuVayCKOKSqdMx68GfxHU7bSl4Hmy4maX+S1/Q91Yul4cNX4Mv22Ie7BNPPIGtW7ciIyMDr776KjIzMwFc/N21Wq0wGAxx34euqH6Q29wQt7HHNPa6FawpLZWbE+JyTm7b2rhxIxYvXoydO3diyZIl+OEPfwgAqK2txXPPPYdjx45BFEXcdtttmDNnTuD/Zd26dThz5gyUSiWmTZuGnj17tufTICIiIoorVrASEREREVGHdO7cOZSXl6N///5ISEgAABw9ehQPPfQQTCYTXC4X7rzzTjz22GMAgD/96U+QJAmPPvoo3G435s2bh927d0etHmyMx+OBxWJpEG75A1SLxdKgda8gCA0qzORyeWD2aXDlqb99r1ar7dQBamOuuPN+nNm7BzaTCZIUn5BVEEVo9QZcfsd9cVl/exEEAWq1Gmq1GhkZGWGX8c+Drf8zajabUVlZiVOnTsFisYQ8Rq1WR62CTUxMbFFbaUmSMHPmTAwePBiPPvpooBWyw+HASy+9hPfffx+iKEKv1+OFF17AiBEjAvfv2bMH6enpyMnJgUajafY+dFUymQwymQxqtTqu2/H5fM0OcevfFq4i139/c+fktiTEbez+7h7kZmdnY9myZbjxxhvhdDrh8/kgiiIefvhhZGZm4s4774TVasVzzz2HpKQkTJkyBa+99ho2bNiA5ORkmEwmbNu2Db/73e8CJ1YQERERdTWsYCUiIiIiog7nySefxOeff47jx4/jm2++weTJkwEAs2bNwsKFC3HNNddAoVBAr9fjyJEjGDBgALRaLQ4ePIi8vDwAwJQpUzB//nwsWrQobFDkn3taP5Aym82ora2FyWSCzWYLeYz/oLuvXiWmSqUKVJ/WD0+NRmPcg5DOoPzkMXz0+1/A24QWp7ESBAEyhQILfvsMMvv1b9V1dxX+ebDRqmAjzYONNBM2lnmw+/btwz333IO1a9ciJSUFmzdvxpw5c1BVVQWZTIalS5firbfewpYtW1BVVYVnnnkGe/bsgdPphEwmw+uvv46BAwfG81tD7UySpGbPxW3q7bHyz8mNpaq2uSGuP8jtiCfX+APV6dOn49Zbb8Xdd98NURTRs2dPPPXUU7j77rsBAKmpqXjttddwww03oHfv3nj++ecxb948AMC4cePw+OOP46abbmrPp0JEREQUN6xgJSIiIqIuoby8HGfOnEFZWRlKS0ths9kCBwgNBgNycnKQlZWFvn37Iikpqb13lxqxYMECPPvss5gwYQJqamoC/5ebN2/GAw88gKSkJFRWVmLMmDGBsC41NRXffvttIGCtqKjAjh07cPvttzeoYv3ggw9w4sSJkKBUFEWIohiYpRjMHzQlJycHQlN/gGowGKBUKuP7DekCsvoNwA2/eAqfPvPbiyFrK7ULFkQRMoUCN/zi9wxXo4h1Hmy4Kliz2YxTp07BZDKFhFSiKKJ///5YsGBBg3VJkgRBEHDkyBEkJiZCq9UGHjNkyBCcOXMGffv2hcvlwoULFwAAX375JZYvX44TJ04AAN577z089NBD+OqrrwKvAdQx1dTU4NSpUygvL0dJSUmgbbUoitBqtejRoweys7ORm5uLrKyskMcKggClUhn319FIc3KbMjfXf5/L5YLVao24fFPm5MYSyjb19vrLNHdOrs1mg1qtDvzuvf/++/jlL3+J//znP6irq8OiRYswdepUABdP4gj+P9RqtdizZw/mzJnDSnQiojiy2Ww4efJk4HNwZWUlvF4vBEGASqVCdnY2srOzkZOTg9zcXP49RdSKGLASERERUafldrtx8OBB7NixA+fOnQscPKx/YNPhcODChQvYs2cPAKBfv34YO3Ys+vXrxw+YHZS/XahOp0NxcXHg/+mLL77A008/jZ/+9KeoqKjAz3/+c6SmpgIAnnrqKXz55Zf48MMPYTAYkJubC71eD7PZ3CBUkslkIeGqXq+H0WhEUlJSIED1X+r1+ha1SqXv5Qweglueeg7/e/7PqK04B7S0klUQYMzIxDU/XYz03LzW2cluTKFQIDU1NfA7VZ8kSXA4HCEBbGPV2WfOnEFmZiYUCgUAID8/HyNGjMDo0aMBAJdffjlWrFgRWLZXr16Bx2o0Gni9Xpw7d45tRjsgn8+HkydPYufOnTh58iSAiwF6/Qp/h8OBmpoaHDx4EJIkISsrC2PHjsWQIUMCPxdtQRCEQNgYz8BPkqSQ9spNDXHr32+32yM+pv73OppIoexVV12F7OzssI9xuVyBkyMAYNWqVZg8eTLGjBmDo0ePoqCgAE6nEwDw05/+FB9++CGKi4uh1WpRVFSEoUOHtnrHAiIiuqi0tBS7du3CgQMH4PV6w74HO51OWCwWHDt2DJIkQa/XY+zYsRgxYkRgBAsRNR+PEhARERFRp1RUVITPPvsMJpMpYrAaLPjD5qlTp3Dy5En06tUL1113HZKTk+O+v9Q8OTk5KC0tDVTD1dbWYvDgwXjzzTfRs2dPXH/99Xj66afxwgsv4K677sKIESNw6tQpzJw5Ey+++CKOHj3aIJiRJAkTJ07E2LFjYTQakZiYyKC9DaXn5uHO517G1k/+g12ff3pxZm0Tq1mF/19pPPbaGzDhxlshZwVxmxAEARqNBhqNJuI8WD//7+zp06dDfgd///vfIykpKTDDeOHChdi2bRsGDhyI8ePHo6CgAJ9++inGjx+Pjz/+GBcuXIDJZEJmZmZgndT+qqursWzZMhQXF4f8n0QK/ILfn8+dO4cVK1Zg48aNmDdvHnr37h33/W1LgiC02Zxcr9fb5LbJ9ZeJVjnscrkC95eVleGLL77AqlWrkJOTAwAYPnw4du3ahR49euCJJ57AG2+8gV27dmHYsGEYOHAgcnJyIJPJQtbp8/lQWFiIo0ePNrkSl3NyiYgAu92O1atXY9++fSGhaizvwWazGevXr8emTZswe/ZsDB8+nH9bEbUAA1YiIiIi6lQ8Hg/WrVuHHTt2xBSshuNfvqSkBK+88gpmzZqF0aNH88NlG/D5fLBarSHtR8eMGROxQrRXr144ffo03G43lEolNm7ciKSkJOTm5gIArr32WqxcuRJmsxl6vR7Dhw/H8OHDAQDHjx9Hnz59oFQq4fV6Awd5BUFAjx492uT5UnhypRJTbr0Ll0ydjn1rv8TBr9fC7XRClMngq9ee2c9/n0KlwpArrsTwK2cjpUfPNt5zipU//DCbzZg4cSLkcjkkScK3336LP/7xjwCAxMREZGRk4OTJk/B6vZg5cyZqa2uxZMkSfP7557BarZgwYULg9cH/Gu3xeLBr166QmbA6nY6v4W1AkiTs2rULa9euDRzIbe57sNlsxltvvYVx48Zh5syZ7BTQDP4gV6VStep6g8NL/8kUiYmJOHnyZMgB/PpV7Pfddx/uu+8+AMDzzz+PJ598ssG+SZIEq9WKkpKSsIFvU/axKYFsc0Lcjjwnl4i6p1OnTuGzzz6DzWYDEDlUjUaSJLhcLixfvhyHDh3Cddddx2pWombiX69ERERE1Gm43W7897//RWFhIYCmH9Stz+fzwefzYeXKlaipqcHMmTN5EK0FJEmC3W4PO7/Rf91isYQcCJDJZOjfvz9SUlJC1uX/fxg0aBC+++67QAWNVqvFpk2bAsuVlJRAJpNBr9ejoqICb7zxBrZv347z589j/Pjx+M1vfgNJkhpU0FDHkNKjJ6bd/QAuu+UOnN6zE+dOnUD5yWOoLC6Cx+UCcDGMTe3ZG1n9BiCzbz7yRo2FUs15fh3dkiVL8K9//QsFBQU4efIkCgoK8NxzzyEzMxPHjh3DlVdeCYVCgS1btuDRRx8N/I7Onz8f8+fPBwDMmzcPPXv2bNC+1Gw24+uvv24wDzYxMTEQuOr1+pAAVq/XQ6PR8DW+BSRJwrp167B169ZWWx8A7Ny5E5WVlbj55pvbtGUwRbZ48WJ8+OGHKCoqwty5c2E0GrF371787ne/wx133IHMzEw4HA5MnjwZEyZMAAB88sknOHXqFHQ6HQ4cOIArrrgiMJ81mEwmw7BhwzBs2LAG90mS1KDytintlINvC56TG+5frOrPyY1HiKtQKCCTyfj6RERR7d+/H8uWLQPQ8s/BfidPnsQbb7yBu+66CwaDoVXWSdSdCBKHIRARERFRJ+DxePDf//4Xp0+fjts8r8mTJ2P69OlxWXdX4HK5AqFppMvgg5aCIECtVgcqQHw+H1wuFxwOR8h6b7/9dvTp0yfsgcU33ngDv/71r7Fo0SLk5OTg+uuvx2OPPYbdu3dDFEXk5OTgxRdfRH5+PqxWKzZs2ACn04m+ffuif//+PBubqJ243W4UFRWhrKwMJ06cwLFjx/D000/jzJkz+PGPf4zKyko4nU7MnTsXTz75JJKSkrBy5UpUV1ejf//+2LdvH5YsWYKPPvoI/fr1a7B+/zzY4Neg+q9HZrM55IQOhUIRCF3rX/q/jtYutbtbv349Nm/eHJd1C4KAvn374uabb2Ylawdht9vhdDphtVphs9mQn58Ph8OBXbt2wWw2w+FwYMqUKUhLSwMArFmzBmvWrIHFYkFubi4WL17cYU9ukiQJXq+3xSFuY49xuVxN+ps13iGu/z4GuUSdz+HDh/HRRx/FZd2CIMBoNOLee++FTqeLyzaIuioGrERERETUKXz11VfYsmVL3Ldz0003YfDgwXHfTkfj9XobVJvWv14/GNVoNFAqlYEDqF6vF06ns8Fy/gDDaDSGvQxXseT1enHzzTfj4MGD6N27N1JTUzFu3Dg8/PDDMJlMsFqtyMzM5Aw2ok7MYrFAqVQGWoh++eWXeO+991BaWoqsrCw888wzgXbgzSFJEurq6sKGsP7rdXV1IY9Rq9VRq2D1en2HDY3iKZ4Hdv0EQcCkSZMwY8aMuG6HqC35g9zmhLhNud0bob1+OLGGto0FtY2FvPwbjah1VFZW4tVXX23S73lTCYKA3Nxc3HHHHTwJg6gJGLASERERUYdXWlqKf/3rX22yLY1Gg4cffhharTbiMpIk4cCBA6ioqMDMmTPbZL9aojkhg0qlglqthlKphCAIgVk9drsdrv/fuhW42JbTHz6EC1C7axhBRJ1Dc04u0el0EQPYzjQPdt26dcjIyMDQoUOj7q/VasU///lP2O32Ntmv+++/n3OyiZrI5/M1O8RtSpVuU+bkymSyFoW1sYS4/vbKRF2Vz+fD0qVLUV5e3qx5q001Z84cjBo1Ku7bIeoq2HeFiIiIiDo0n8+Hzz77LBDyxZvD4cCqVatwww03hL3fZDLhiy++wMmTJzF69Oi4709jgttkRmrbW79NplwuR0JCAlQqFWQyGRITE6HVauF0OmGz2eB2u+F0OuF0OiGXyyOGp0ajETqdjhUKRNRpyWQyJCUlISkpKeIy0dqjnzx5EiaTKSR0EEUxJHwN145YrVa3ewjrcrmwbNkyHDx4EFdffXXE2WurV69uEDLHiyAI+Oyzz/DjH/+Y7y1ETSCKIpRKZdzbnIebk9vcmbkOhwN1dXUtnpMrimKzg9xYQ1zOyaX2smvXLpSWlrbZ9lavXo38/Hzo9fo22yZRZ8YKViIiIiLq0I4ePYoPPvigzbf76KOPhhxsliQJe/bswbp166BSqXD11VdjwIABcd8Pl8sVcb5guLmnoigiISEBWq02MPtUkiS43W7Y7XbU1dWFtJdSKpWBsDRckJqQkMCDSUREUUiSBLvdHrUK1mKxNDoPtn4Y2xbzYI8dO4aVK1fC6XRi5syZGDVqVMhrvslkwvPPPx/3/ajvlltuaZP3WCLqmOrPyY01wA23TGOPifXQuCAIzZqB25QQl3Nyu4fz589j+fLlGDNmDIYPHx7xhCKfz4e///3vDToNxZMgCJg8eTKmTZvWZtsk6swYsBIRERFRh/bOO++gsLCwTapX/ep/sKyqqsL//vc/FBUVYeTIkZg5cybUanWLt1O/NWW4y/otGXU6XaD6VC6XB9bjrz61WCwh3yuNRhOx+rSjVFEREXV1Pp8PVqs16sky9Q+gajSaqFWwiYmJrdIa0+FwYO3atSgoKEDv3r1x7bXXIjk5GQCwYcMGbN68uc3fg/v06YM77rijzbZJRN1X/SC3qa2WYw19WzInt6UhbqRl+BmgfbhcLnz++ec4dOgQ0tPTMXPmTPTt27fB/0d7nWis1Wrx2GOPBT5rElFkDFiJiIiIqMOqra3FCy+8EHWZXbt2Yffu3aitrQUApKenY8qUKcjPzwcAvP322ygqKgp5zKhRo3DNNddEXa9Wq8Xjjz+OHTt24Ouvv4ZOp8O1116LPn36xLTv/rmn0Sqa6h9MV6vV0Ov10Gg0UCqVIdWnDocDFoulwWN0Ol0gLK0fnhqNxjapgCIiopbzeDywWCxh52X7LyPNg400E7Yp82BPnz6N//3vf6irq8MVV1yBcePG4W9/+xtsNlvEx0R7D66trcWLL74Y9nE33ngjLrnkkqj789Of/hRGozGmfSci6uh8Pl+zQ9ymzNBt7pzceIW4/o461FBJSQnWrVuHs2fPIi8vDzNmzEBWVlbg/vfffx8nT56M+SSnLVu2YP369Rg3bhyuuuoqABf/tlizZg0OHToEj8eDfv36Yfbs2dDpdFHXtWDBAgwaNKj5T46om2DASkREREQd1oEDB/Dpp59GXebYsWMQRTFQbbN3715s3boVDzzwANLT0/H2228jJSUFV1xxReAxCoUCKpWq0e1nZGTg/PnzGDduHKZNmxYIK4PnnkYKUMPNPTUYDNDpdFCr1YH2X16vFy6XC1arFRaLBVarNfAYQRACB8sjtfDlmcVERN2Hfx5spCrYSPNgIwWw9TsZuFwubNiwATt27EB6ejoqKiqi7k+09+DU1NQG4eyePXuwdetWPP74442eAHTjjTdiyJAhzfk2ERF1W/6TM5sT4jY14I1V8JzceIW4/iC3s1XlSpKE48eP46uvvkJlZSWGDRuGadOmQa/X489//jNcLldM6yktLcUnn3wClUqF3NzcQMD6xRdf4MSJE7juuuugUqmwatUqCIKAe+65J+K6RFHEuHHjMGvWrFZ5jkRdGY/GEBEREVGHVV5eDlEUQ4LK+urPaJs+fTp2796NkpISpKenA7gYqDZ2lm44FosFl112GWQyGVatWhUSoAYfVPAHof5qIYPBAJlM1qD61Gw2o6qqKvA4URQDYWlmZiYGDhwYEqC2VvtHIiLqGpRKJdLS0pCWlhb2fv882EhVsGfPnoXZbA6phlEoFA3aEF922WXYs2dPo/vT2Htw/ffeo0ePYvDgwY2Gq6IooqysjAErEVETCYIApVIZ9y42kebkNqfdsv9k00jLN2VObiyBbFNbMNf/J5PJWi3IFQQBAwYMQH5+Pr777jts3LgRhw4dwvDhw2MOV10uFz777DPMmTMHmzZtCtzucDhQUFCAG264IdCFae7cuXj55ZdRUlKCnJycsOvz+XwoLS1t+ZMj6gYYsBIRERFRh1VWVhY1XK3P5/Ph8OHDcLvd6NmzZ+D2AwcOYP/+/dDpdOjfvz+mTp0KhULR6PpsNhu2bNmChISEwEHnnj17Ii8vr0H1qdlsxrlz50KCV/9Ba6PRiJ49ezaYgdqU1o1ERESNEQQBWq0WWq02pM1gMJ/PF7aFvclkQkVFBY4fPw6r1drkuauR3oP9ysrKcO7cOcyePTumdZWVlTVp+0RE1HYEQYBcLodcLodGo4nbdiRJCmmv3Jz5t8HXHQ5HxGWb8rkzlkA2WlAb7r7c3Fzceeed2Lt3L3bs2BHzvnz55ZfIz89HXl5eSMBaXl4On8+HvLy8wG2pqakwGAwoLi6OGLACwLlz52LePlF3xoCViIiIiDqsaHPfglVUVGDp0qXweDxQKpVYsGBBoLpn6NChMBgMSExMREVFBb766itUVVVhwYIFMa1br9dDrVbDbrejoqICXq83cJ9KpQqEpX369GkwA1Wr1TJAJSKiDsXfNliv1zc4uOrxeHD8+HHs3bsXJ06ciClkjfYeHKygoACpqalhw9dwYv0bgIiIui5BECCTySCTyaBWq+O6rXBBbnPn5Vqt1oiPCf48GUmsJzkdPHgQ5eXluP/++xvcV1dXF/b7lpCQgLq6uqjrdblc8Pl8nJ9L1AgGrERERETUYcV6FnFqaioefPBBOBwOHD58GMuXL8ddd92FtLQ0jBo1KrBcRkYGEhMT8c4776C6ujowMy4SURRht9thNpshk8mQnZ2N/v37o1+/fjAajXH/kE9ERBRvkiShuLgY+/btw+HDh+FwOJCdnY0ePXrE1Eki2nuwn9vtxoEDBzBlypSY96splUREREQtJYoiVCoVVCpVXLfj8/lCgtngr10uF86cOYOCggJYrdao6zGZTFi9ejVuv/12yOWtH/MwYCVqHANWIiIiIuqwYv2gKJPJAmFpdnY2ysrKsH37dsyZM6fBsj169ACARgNWURQxatQoXH311aisrMS+ffuwf/9+rF+/Ht999x2GDRuGYcOGNRrSEhERdUTV1dXYv38/9u/fj5qaGhgMBowePRrDhw9HamoqVq5cGVOb3ljeg/2tg4cPHx7z/sXjYDEREVF7E0WxwZxct9uNffv2Ydu2bYHPqY0FrOXl5bBarXjttdcCt0mShKKiIuzcuRMLFy6E1+uFw+EIOTHYarU2mJEejkwma8azI+pe+NcqEREREXVYKSkpqKioaPIcOEmSIrZe8s+TSUxMbHQdSUlJAC5W50yfPh3Tpk1DUVFR4MPvN998g969e2PBggVxnT1ERETUWux2Oz788EMUFRVBqVRi8ODBuPbaa9G7d++QtvZJSUlNfv8Fwr8HFxQUYMCAAUhISIhpHYIgIDU1tcnbJiIi6kysVit27dqFXbt2wW63Y9CgQbj++uvh8Xjw9ttvR31snz59sGjRopDbVqxYgdTUVEyaNAl6vR6iKOL06dMYPHgwAKCyshImk6nRdv0Gg4GjbohiwICViIiIiDoESZJgs9lQW1sLk8mE2tpamM3mRg/ufvXVV8jPz4fBYIDT6cSBAwdw5swZLFy4ENXV1Thw4ADy8/Oh1WpRUVGBNWvWoHfv3sjIyGh0f7Kzs0NuEwQBubm5yM3NxezZs3Hs2DEUFRWxdRIREXUaoigiLS0No0ePxoABA6BQKMIul5WV1aL3YL/q6moUFRXhtttua9J+ZmVlNWl5IiKizqKqqgrbtm3Dvn37IAgCLr30UowfPz7QEcLpdDa6DpVKhfT09JDbFAoFNBpN4PYRI0Zg7dq10Gg0UKlUWLVqFXJychrMYA8mCELU+4noewxYiYiIiKhNSJIEi8USCE+Dg1T/pcfjCSyvUCig1WobXa/VasWyZctQV1cHlUqFjIwMLFy4EH379oXJZEJhYSF27NgBl8sFg8GAQYMGxTwDLjMzM+J9CoUCQ4YMwZAhQ2JaFxERUUegUqlw9dVXN7pcLAFntPdgv4KCAuj1+pDbGhPuJCciIqKuYPPmzdiwYQMSEhIwefJkjB49usHnXpVKhaSkJNTU1LRoW1dddRXWrFmDjz76CF6vF3379m21vwGICBCk5vR7ISIiIiKqx+v1wmw2NwhQg0NUn88XWF6tVsNoNMJoNMJgMMBgMIRc12g08Hg8+Nvf/gaHw9Gmz0UQBPTq1Qt33313m26XiIioI3nrrbdw9uzZZrUKbgm1Wo3HH388YnUtERFRZ3Xy5ElYLBYMHTo06rzxdevWYevWrW3+HgwAP/7xj5GWltbm2yXqbFjBSkREREQx8Xg8EcPT2tpaWCyWkA9/CQkJgbA0KyurQYCqUqka3aZCocCoUaPa/IOlJEkYN25cm22PiIioIxo3bhyKioradJuCIGDUqFEMV4mIqEvq169fTMuNHj0a3377bZz3JpT/RGOGq0SxYcBKRERERAAuznmp37I3OEC1Wq0hy+v1+kBo2qtXrwbVqK11YLQ9PlgmJCRgwIABbbpNIiKijmbAgAFISEho8DdAPEmShNGjR7fZ9oiIiDqipKQk9OvXD6dOnWqzk415ojFR0zBgJSIiIuoGJEmCw+GIOPvUZDLBbrcHlhdFMRCUpqWloV+/foHw1Gg0Qq/XQyaTtcm+JyUlYdy4cdi5c2ebfbCcNWtWmz0/IiKijkomk2HWrFn47LPP2mR7giBg3LhxSEpKapPtERERdWQzZ87E6dOn2+RzsCiK6NGjBwYOHBj3bRF1FQxYiYiIiOKguroaer0+MFOlqKgIP/vZz3D27FnodDr8/ve/x6RJk1pte5IkwWq1Nqg6DW7j63K5AsvL5fJAWJqdnY3BgweHtPDV6XQQRbHV9q+lpk+fjqNHj8JsNsf1w6UgCOjfvz+GDh0at20QERF1JkOHDsXBgwdx4sSJuL8HGwwGTJs2LW7bICIi6kwyMjJw+eWXY8OGDXHfliAIuO666zrUcQCijk6Q2mNKMhEREVEnV1JSgnPnzuGSSy6BRqMBAOzcuROPPPIInE4nZDIZbrzxRixevBgejwd33nknRo4ciRtuuAGVlZW47rrrcOjQIRgMhpi25/P5YLFYGoSnwSGqx+MJLK9UKkNa9gZfGo1GaLVaCIIQl+9NvJw9exZvv/02fD5fXNYvCAI0Gg0WLVqExMTEuGyDiIioM7JYLHj11Vdht9vjFrKKooi77roLvXr1isv6iYiIOiOv14s333wTZWVlcT3R6eqrr8aYMWPitn6irogBKxEREVET/ehHP8KaNWtQWFiIPXv2YMSIEQCACRMm4Le//S1mzpwJp9MJnU6Hc+fOIT09HQqFAlVVVdDr9QCAcePG4fbbb8eiRYsatKL1er3YvHlzSIhqNptDgkWNRtNg5mnwdbVa3ekC1FgcPnwYH3/8cVw+WKpUKtxzzz3IyMho9XUTERF1dhUVFXjzzTfhcrla/X1YEATMnz8fgwcPbtX1EhERdQU2mw1vvvkmqqqq4vJZeMqUKewgQdQMbBFMRERE1ER33HEHXn75ZYwaNQo1NTWQJAmCIGDXrl0ALs4rKywsxNSpU+H1egEAKSkp+N///ofbbrsNFosF5eXl2LdvH6xWayB09ZPJZDhw4AC0Wi0MBgOys7MbVKMqlco2f94dweDBg7FgwYJAyNoa1ayCIECSJGRnZyMtLa0V9pKIiKjrycjIwD333IN33nkHNputVQ7wiqIYCFc5842IiCg8rVaLe+65B++++y7Ky8tbZZ3+z8HTpk3D5MmTW2WdRN0NK1iJiIiImsjn80EURUyaNAk//OEPceeddwIAvvnmGyxevBhnz55FdXU1fv7zn2PRokXIyMjAxx9/jOXLl+P06dPIycmB3W5Hv379sHjxYmRmZrbzM+p8Kisr8dlnn6GsrKzF6xoyZAgGDBiAZcuWYfz48bjyyitbYQ+JiIi6JpvNhpUrV+LQoUMtXld2djbmzZuH1NTUVtgzIiKirs3j8WDTpk3YtGlTi9el0+kwb9485OXltcKeEXVPrGAlIiIiaqYePXrg7NmzgeuFhYWYOHEiVq1aBaPRiNmzZ8Nms+HZZ5/F/PnzMXLkSJhMJowcORK/+tWvUFFRwXC1mVJTU3Hfffdh+/bt2Lx5M+x2e+AM3MaIogifz4fk5GTMnDkTgwYNAnDxgPHq1auRkpKCUaNGxfspEBERdUoymQxarbZV1qXRaKBQKFplXURERF2dKIrQaDSBz7QtoVKpoFarW2nPiLonBqxERETU7UmShLq6upCZp/6v3W437rrrrrCP6927N4qKiuB2u6FQKLB161b07t0bRqMRAHD11Vfj66+/ht1uh1qtRt++fQEAdXV1OHbsGKZOnQrg+4pYahpRFDFx4kSMHTsWR48exc6dO1FSUhL4oBn8PfXfplAo0K9fP4wdOxa5ubkhc2rHjh2LqqoqrFy5EklJSTyTl4iIqJ6amhr8+9//hslkapX1FRYW4uWXX8Ytt9yCPn36tMo6iYiIuiKn04kPPvgAhYWFrbK+6upq/Otf/8Ls2bMxZsyYVlknUXfDgJWIiIi6PJ/PB7PZ3CA89V83mUyBWanAxTM5/TNPk5OTGwSg/lBuyJAhWLFiRaDyIjExEV999RV+9atfwePxoLCwEEajERqNBiUlJXj++efxzTffwOFwYN68eXj44YcZrrYCuVyOIUOGYMiQIfB4PLhw4QLKyspgs9ng9Xohl8uh1+uRnZ2N5OTkiN9vQRBw1VVXoaamBh999BHuvfdezmQlIiL6/6qrq7F06VLY7fZWmb8KXPwbze12491338Vtt90WOBmNiIiIvud0OvHOO++0yogcP/97+cqVK+HxeDBhwoRWWzdRd8EZrERERNTpeTwemM3mkPA0+NJsNoccCNRqtYEA1WAwwGAwhFyPtU3Oyy+/jD/84Q+4++670bt3b9xyyy342c9+hk2bNkGlUmHAgAH429/+hp49e8Jut2P//v1QKBTIzc1FcnJyvL4d1EJOpxNvvvkmXC4X7rvvPiQkJLT3LhEREbUrm82GJUuWwGKxtFq4GkwQBMhkMtx7773Iyspq9fUTERF1Vj6fD++++y7OnDkTl/dgv3nz5mHYsGFxWz9RV8SAlYiIiDo8l8sVsfq0trYWdXV1IcsnJiZGDE8NBgOUSmWL9sfj8eDmm2/GkSNHkJeXh/T0dEycOBH33nsvrFYrfD4fEhMTW7QNal+1tbV44403kJycjDvvvBMymay9d4mIiKjdfPrppzh48GBcD+wKgoCUlBQ8+OCDkMvZcI2IiAgAtm/fjtWrV8d9OwqFAg899BAMBkPct0XUVTBgJSIionbncDgiVp+aTCbYbLbAsoIghASn4S4ZhlFrKCkpQVlZGcaOHdveu0JERNRujh49ig8++KDNtjdlyhRMmzatzbZHRETUUVVVVeGVV14JGWkUL4IgoE+fPrj99tsDY5GIKDqeEkhERERxJUkSbDZbSGhaP0B1Op2B5WUyWSAszczMxMCBA0MC1MTERM4spTaRk5ODHj16NLqcx+NhpQ0REXVJPp8PX375ZZtuc/PmzRg9ejT0en2bbpeIiKijWbduXVy7RwSTJAmnT5/GiRMn0L9//zbZJlFnxyNBRERE1CKSJMFisYQNUP3XPR5PYHmlUhkIS3v16hUSnhqNRiQkJPBsSeowGvtZvHDhAh5++GH84x//QFpaWhvtFRERUds4ceIEzGZzm293z549uOKKK9p8u0RERB2FyWTCsWPH2ixgBS5+/t2xYwcDVqIYMWAlIiKiqLxeL8xmc8Tw1GQywefzBZZXq9WBsLRv374N2vdqNBoGqNTpSZIEQRCQlpaGQYMG4Y477sCqVavae7eIiIha1c6dOyEIQsSDu7t27cLu3btRW1sLAEhPT8eUKVOQn58PAKirq8O6detw6tQpuFwupKSkYPLkyRg8eHDEbUqShF27dmHKlCkc+0BERN3Wd99916Tlt2zZgvXr12PcuHG46qqrAFw8YenAgQMoLy+Hy+XCz3/+c6jV6ojrkCQJp06dQnV1NZKTk1u0/0TdAQNWIiKibs7j8URs3VtbWwuLxRJyUC0hISEQlmZlZYVUnxoMBqhUqnZ8NkRtQxAEmEwmGAwG/Pa3v8WDDz6Ie++9F0uXLm3vXSMiImoVTqcTp0+fjlo5o9frMWPGjMBB2L179+KDDz7AAw88gPT0dCxbtgwOhwO33HILtFotDhw4gE8++QT3338/srKyIq7XZrOhpKQEvXv3bvXnRURE1BkcPHgw5urV0tJS7NmzBxkZGSG3u91u9OvXD/369cP69etjWpcgCDh69CgmTpzY5H0m6m4YsBIREXVxTqczYvVpbW0trFZrYFlBEJCYmBgIS/0tfP3XDQYDFApFOz4bovbldDoDJxG8/vrrKCoqwj//+U/ce++9ePvtt9t354iIiFrRuXPnGj2wO2DAgJDr06dPx+7du1FSUoL09HQUFxfj6quvDsw0nzJlCrZv347y8vKoAasgCCgrK2PASkRE3ZLL5UJ1dXXMy3722WeYM2cONm3aFHLf+PHjAQBnzpxp0vbLy8ubtDxRd8WAlYiIqBOTJAkOhyNi9anJZILdbg8sL4piIChNS0tDv379Qlr46vV6tmIjiuDw4cMoLi7GrFmzAAA/+9nP0LdvXyxYsABHjhzB6NGj4fV6ceTIEQwZMqSd95aIiKhlysvLo7YHrs/n8+Hw4cNwu93o2bMnAKBnz544dOgQ+vfvD7VajUOHDsHj8SA3Nzem7RMREXVHsZzk5Pfll18iPz8feXl5DQLW5pAkCSUlJS1eD1F3wICViIioA5MkCVarNSQ0rV+F6nK5AsvL5fJAWJqdnY3BgweHBKg6nQ6iKLbjMyLqvKqqqvDQQw/h66+/Rk5ODgDgzjvvRH5+Pm644QbcdNNN2LBhAx577DE888wzgbk3REREnVF1dXVMAWtFRQWWLl0Kj8cDpVKJBQsWIC0tDQAwf/58fPLJJ3j22WchiiIUCgUWLFjQ6Fw3SZJw4cKFVnsuREREnUms1asHDx5EeXk57r///lbdfm1tLSRJgiAIrbpeoq6GASsREVE78vl8sFgsEatPTSYTPB5PYHmlUhlo2du7d28MHz48ZAaqVqvlH8BEcTJ58mQ8/vjjuP3227F06VKUl5fjrbfewltvvYXLL78cwMUWTC+99BIeeeQR5OXloX///u2700RERM3kdrtjWi41NRUPPvggHA4HDh8+jOXLl+Ouu+5CWloaNmzYAIfDgdtvvx1arRZHjx7Fxx9/jLvvvrvBnLjmbp+IiKirCT4OFInJZMLq1atx++23Qy5v3ZhHkiR4vd5WXy9RV8PfECIiojjyer0NZp4GXzebzfD5fIHlNRpNICzNz88PCU8NBgPUajUDVKJ29OCDD6K8vBy/+tWvsG7dOvz0pz/F5ZdfHvgAqtFoMGXKFMydOxf/+Mc/8I9//KO9d5mIiKhZYv2bUyaTBSpSs7OzUVZWhu3bt2PSpEnYtWsXFi1ahPT0dABAZmYmzp49i127duGaa66Jul52XSEioq7M5/PBbrfDarXCZrPBZrMFvi4sLGz08eXl5bBarXjttdcCt0mShKKiIuzcuRO//vWvW/ReyvdhosYxYCUiImoBt9sdMTytra2FxWIJWV6n0wXC0h49egQCVP+lUqlsp2dCRLH6/e9/D7fbjbq6OiQlJcHj8UAUxcDZvXa7HV6vN9BGmIiIqDPSaDTNepz/pCN/BWr9oFYUxZjmyjV3+0RERO3B4/E0CEqDw9P6t9vt9gbrEEURWq02pnCzT58+WLRoUchtK1asQGpqKiZNmtSigFQulzNgJYoBA1YiIqIoHA5H2Na9/gDVZrMFlhUEAXq9HkajEUlJScjNzQ2pPjUYDGyvQtRFKBSKQIXqpEmT4PV6kZycjOrqaiQkJGD79u1466232ns3iYiImi0jIyOk00o4X331VaDritPpxIEDB3DmzBksXLgQqampSE5OxhdffIErr7wSGo0GR48exalTp3DrrbdGXa8oisjKymrNp0NERBQzSZLgdrvDVpeGu81ms8HpdDZYj1wuh1arRUJCArRaLYxGI7Kzs0NuC/7a37Wsqqqq0W5IKpUq0CHCT6FQQKPRBG6vq6tDXV1dYKZrRUUFVCoVDAZD1BOZMjMzm/otI+qWeJSXiIi6LUmSYLfbQ6pP6186HI7A8jKZLBCUpqeno3///iHVp3q9nmf4EXUj9913H5YtW4a+ffvi/vvvR1FREYqKipCZmYk//vGP6Nu3b3vvIhERUbNlZ2c3uozVasWyZctQV1cHlUqFjIwMLFy4MPAeeOutt2L9+vX473//C5fLheTkZFx33XXIz8+Pul6fzxfT9omIiGIhSRIcDkfYoDRSlWm4OagqlSokEE1LSwu5Xv9SoVA0a8xTUlISFApFi+eR7969G998803g+ttvvw0AmDt3Li699NKwjxFFET169GjRdom6C0GKpS8LERFRJyRJEurq6hpUnQa38Q3+Y1WhUDRo2Rs8A1Wn03H+KRGF2Lt3L+677z4sWbIEo0ePDrnP5/MFTrqQJAnbtm3DmDFjoFAo2mNXiYiImsTn8+HZZ58NOeGwLT3yyCOB2a5ERETBfD5f2CrSaBWn4WIQjUbTIBSN9nVbdiV75513UFhYGFNb/dZ24403YsiQIW2+XaLOhhWsRETUafl8PpjN5gbhaXCI6vV6A8ur1epAYNqnT58GAapGo2GASkRNcumll+IXv/gFFi5ciJ07d0Kv1wfuC65ot1gsWLduHdLS0hqt2iEiIuoIRFHEyJEjsW3btjY9uCsIAnr27MlwlYioG/HPL421ujTa/FJ/IKrT6ZCWlhaxulSj0XToLmQjR47E6dOn23y7KpUKAwYMaPPtEnVGDFiJiKjD8ng8IdWm9S/NZnPIwR7/PAuj0YjMzMyQ8NRgMECtVrfjsyGiruqGG25Ajx49QsLV+hITE5GQkICioiIGrERE1GmMHj0aW7dubdNtSpKEcePGtek2iYio9UiSBJfLFVNQ6r90uVwN1qNQKEKqSP3zSyNVnKpUqi510vzAgQOh1Wphs9nabJuCIGDUqFHsukQUIwasRETUblwuV8TWvbW1tairqwtZPjExMRCW5uTkhISnBoMBSqWynZ4JEXV348ePD7nu8/ngcrkCJ3YIgoDc3FwUFRW1x+4RERE1S3JyMgYOHIjjx4/D5/O1yTZVKhUGDhzYJtsiIqLGSZIEu90eMRwN93VwNzE/lUoVEo6mp6c3aMMbfNndQz65XI4JEyZg/fr1bbZNURQxZsyYNtseUWfHgJWIiOLG4XCEbd3rvww+C08QhEBQmpKSgry8vAYBqkwma8dnQ0QUu7Nnz+Ljjz/GXXfdhbS0NABA7969sXr1arhcLp4QQkREncbs2bNx+vTpsNVF8XDjjTeGbdkYPNv8xIkT+OCDD6DRaPDEE0+0yX4REXUVXq8Xdrs95na84eaXCoIQMr9Uq9UiKSkpYjterVbLYzrNMHHiRBw4cAAXLlxok3b906dPR1JSUty3Q9RVMGAlIqJmkSQJNpstaoDqdDoDy8tkskBYmpmZiYEDB4bMQE1MTOzQsy+IiJoiKysLOp0O//nPf3DfffchISEBvXv3hs/nQ0lJCfLy8tp7F4mIiGKi1+sxe/ZsLF++PK7bEQQBY8aMQb9+/cK2eLTZbDh+/DieffZZGAwGLFu2DCNGjMBdd92F1NTUuO4bEVFH5na7I1aUhrvN4XA0WIcoiiGhqE6nQ3p6eoM2vP5LtVrNYzhtQCaTYd68eXjttdfiuh1BEJCdnd2gMxMRRceAlYiIwpIkCRaLJSQ0rd/G1+PxBJZXKpWBsLRXr14h4anRaERCQkKXmoVBRBSNSqXCLbfcgjfeeAMffvgh7rjjDqSlpUGr1eLMmTMMWImIqFMZPnw4SkpKsHv37risXxAE5OTkYObMmWE/Mxw5cgTPPvsscnJyMH/+fCQnJ6OkpASPPvooUlNTsXfvXmzbtg3XXHMNevbsGZd9JCJqC5Ikwel0Rg1K69/udrsbrEehUISEo8nJycjJyYlYXdrV5pd2JZmZmZgzZw4+//zzuKxfEAQkJCRg/vz5DM2JmkiQ2qK2nIg6PK/HjbMH9+PcqeOoOH0SF4oK4XY4AEGAUq1GWm4eMvPykdm3P3peMhQi23p0el6vF2azOWJ4ajKZQuYsqdXqkJa99QNUtVrNP8aJqNvyeDw4ceIE8vLyoFKpAreXlJTg3//+NwYOHIh58+bho48+gs1mw9133x1YRpIklJSUoLi4GOXl5SgrK4PD4YDP54NCoUBqaip69OiB7OzsBusnIiJqKz6fD//73/9QUFDQqusVBAE9evTAwoULA7PLg9lsNjz66KP45JNPUFVVBQC4+eabkZubi2eeeQavvPIK3nrrLYwePRo7duzANddcg6eeeirm7V+4cAFnzpxBeXk5SktLA7MD5XI5DAYDcnJykJWVhby8PCQmJrba8yai7sE/vzSWuaX+r8PNL1Wr1Q1C0UjVpVqtttvPL+2Kdu7ciS+//LJV1+kPV++++26kpKS06rqJugMGrETdnLnyAg6sX429a7+Eo84CQRQBSQozW0EEBEDy+aA1GHHprKsxdNos6JKS22nPqTFut7tBYBp8abFYQv6fExISGsw8Db7OA/pERJHt3LkTq1evhkKhwPDhwzF27NhAu8JDhw7hk08+wdSpU6FWq/HVV1/h5z//ObxeL/bt24cdO3aguro6cJJKuD/PRVEMBK4jRozA6NGjkZ6e3qbPkYiISJIkbNq0CRs3bgxcb6mhQ4dizpw5UeeTO51OPPLII9iyZQsuueQS2O12vPTSS+jTpw+eeuopyOVy/PKXv4Tdbsf111+PxYsX4/LLL4+4Po/Hg6NHj2LHjh0oLi4G8P17bX3+2wVBwKBBgzB27Fj07t2bJ5cSdVNerzemdrz+63a7Pez80nAhabigNCEhARqNhvNLCcDFz5aff/45XC5Xq7wH5+Tk4MYbb4TRaGz5zhF1QwxYibopn9eLXZ9/iq0fvw9JkiCF+SAZjSAIEGQyTLn1Loz4wRyIIv/Qa2tOpzNi9WltbS2sVmtgWUEQkJiYGDE8NRgMPLuRiKiFzGYzdu/ejT179sBms6Fv374YO3Ys8vPzsWXLFmzYsAHTpk3D+vXrMXXqVOzYsSPs/KPGCIIASZIwevRozJw5kyfAEBFRmysvL8dnn32GCxcuBN6Xmkqr1eLaa6/FwIEDoy7n8/kCLQs3btyIG2+8EQqFAtu3b0dRURHWrVuHTz75BG+//TbGjRuHlJQUvPnmm5g7dy4kSWoQhJaUlOCzzz4LnNzUlH33h615eXmYO3cuDAZDk583EXUsbre7QUAarR2v0+lssA6ZTBax9W64rzUaDU/SoGazWCz4/PPPceLEiYgnB0UjCAJEUcSMGTMwbtw4tgUmagEGrETdUFVpMVa++CwuFBW2yvqy8gdg9sM/gzEjs1XWRxfPBHc4HCHhaf1Lu90eWF4UxZDgtH6AqtfrebYjEVEb8Xg8OHToEHbu3ImysjIkJSVh9OjRKC8vx6FDhy6e2NQKf4L7T5654YYb0Lt371bYcyIioth5vV4cPHgQO3bsQFlZWdRODMD34aTRaMTYsWMxYsQIaDSamLblD1kff/xxnD9/HvPmzcOGDRvwxRdf4IUXXsDZs2exePFiXH311UhISMDSpUsbHDD2er3YsGEDvv3222aHwn6CIEAul+Pqq6/GpZde2uz1EFHr8s8vbay6NPjrcPNLlUplzNWlWq0WSqWSgSm1KUmScOrUKezcuRPHjx+/WAgjCBHDVv97sFqtxqhRozBmzBhWrRK1AgasRN1M+clj+OTp/4Pb6Why1WokgihClaDDTb/5E9J65bbKOrs6SZJgtVpDQtP6AarL5QosL5fLI1afGo1G6HQ6nnFGRNQBlZSUYOfOnTh06BBEUYTH42mVcNXP/0F6/vz5GDRoUKutl4iIqCnKy8tx8uRJlJWVobS0NGQciUajQXZ2Nnr06IHc3Fzk5uY2+7PLO++8g6SkJMyZMwdTpkzB9OnT8dvf/hYA8L///Q/ffPMNnn322Qbrd7vd+Pjjj3H8+PGWPdEwLr/8ckydOpXhClEc+Hw+2O32sEGpv/1u/dvDBUxqtTrm6tKEhATI5fJ2eLZEzVNbW4ujR4+ivLwcJSUlqKmpCfweKJVKZGZmokePHsjJycGAAQP4803UihiwEnUj58+cxge/fRIel6vVwlU/QRSh0mhxy9N/Q3J2j1Zdd2fk8/lgsVjCBqj+fx6PJ7C8UqlsEJoGB6larZYf2ImIOrHz58/jrbfeCuk+0JoEQcAtt9yC/v37x2X9RERETeWfW9ran2P81axPP/00JEnC//3f/wEAfv3rX6O4uBj//ve/Q5b3er348MMPceLEiVY9ySnY9OnTMXny5Lism6gr8Xq9jVaU1g9Q6/PPL60/ozRSdalWq+UJ6dTtxOs9mIhCMWAl6iZcdhveemwRrLU1rR6u+gmiCEN6Bu587mXIlcq4bKOj8Hq9DWaeBl83m80hZ01qNJoGM0+Dr6vVav7RQ0TURUmShHfffReFhYVxO7ALXOx28OMf/xhJSUlx2wYREVFHceDAATz00ENISUnB6NGj8f7772Px4sW47bbbAmGKz+fDihUrsG/fvrjvz2233Yb8/Py4b4eoo5AkCW63O2J1abgZppHml0arLq1/G4+fEBFRR8GAlaibWPevl3Fg/RpIUnzC1QBBwJg58zDltrujLnbu3DmsW7cO48eP75AfQt1ud8TWvbW1tbBYLCHL63S6iNWnBoMByi4eOBMRUWTfffcdPv/887hvRxRF9OzZE3feeSfP0iciom7j5ZdfRlVVFS677DJMnToVMpkMwMXwp7i4GG+++Wbc98FfUffQQw/FPFeWqKORJAkOhyOmoNR/GdyZy0+pVIYNRyPNMFUoFAxMiYioU2LDbaJuoPjwAez/alXbbEySsOt/n6H/+MuQ2bdhcOr1erFp0yZs2bIFqampSEtLa5v9qsfhcDQITYMDVZvNFlhWEATo9XoYjUYkJSUhNze3QTUq5xcQEVE4FosFq1a1zXuwz+dDUVERCgoKMGrUqDbZJhERUXv78Y9/HPZ2n8+HDz74oE32QZIk2Gw2rFu3Dtdee22bbJOoMT6fL2o4Gi5ADTe/NLj9rlarRVZWVtSKUx4fISKi7oLveETdwI5lH0EQxbi1Bq5PEETs+t+nmPPTxSG3l5eXY/ny5aisrMRll12GKVOmBM4ubk2SJMFut0esPjWZTHA4HIHlZTJZIChNT09H//79Q6pQ9Xo9K4GIiKhZdu/eHfbM/njatGkTRowYwfcuIiLqtnw+H/bu3Rty4my8SZKEgoICXHHFFUhMTGyz7VL34fF4mtSON9z8UlEUQwLRhIQEpKWlRawu1Wg0/JuSiIgoAgasRF1c7blyFO0vaNNtSj4vTuzYCmttDRKMSfB4PIGq1fT0dNx///3IzMxs/volCXV1dQ2qToMDVLfbHVheoVAEwtKcnBwMGTIkJEDV6XRsR0NERK3O6/Vi165dcZ27Go7JZMLp06fRr1+/Nt0uERFRRyGKIg4fPgxBENr8ffi7777D1KlT23Sb1PlIkgSXyxW1orR+gOpyuRqsRy6Xh1SRGo1GZGdnR5xhyvmlRERErYcBK1EXd+DrtVGrV7eeLMK2U0Wotl48szHToMOMwfkYlJUespwkSXhj8y4cO3cBd00ahSE9GglIJeDgxq/Qc+wkLF++HFVVVZg6dSouu+yyRqtWfT4fzGZzxPDUZDLB6/UGller1YGwNC8vr8EMVI1Gww8QRETU5o4fPx61cmbXrl3YvXs3amtrAQDp6emYMmVKyGzy4uJibNiwAaWlpRAEAZmZmVi4cCEUCkXE9QqCgN27dzNgJSKibstkMuHUqVNRl2nsfbi6uhrr1q3D2bNn4fF40K9fP/zgBz+ATqeLuE5JkrBr1y5MmTKFn0GbyO124+uvv0ZKSkqgE8ezzz6LLVu2oLy8HDNmzMATTzyBlJSU9t7VsPzzS2OtLrVarSHHNfxUKlVIKJqWlobc3NyIM0yVSmU7PFsiIiICGLASdXnFhw5EbQ1s0Koxe9hApOoSAEjYfaYEb3+7G4/OnIxMw/dtjTYfL0RTPh5KkLBvyzdYs/8IMjMz8cMf/hAZGRkALra18QelwQGq/7rZbA45y9h/FqbRaERmZmZIeGowGKBWq5v6bSEiIoq7oqIiiKIYdpYVAOj1esyYMQPJyckAgL179+KDDz7AAw88gPT0dBQXF+P999/HZZddhh/84AcQRREVFRWNHrCVJAlFRUWQJIkHd4mIqFs6e/Zso8tEex82Go147733kJGRgTvuuAMA8PXXX+O///0v7rvvvqjvr3V1dTCZTDAaja3yXLo6/98ra9euxZw5c3DvvffiX//6F9555x0cPXoU999/P4YNG4b7778fr7/+On7xi1+0yX7555c2Nrc0+Otw1dL1g1Gj0RixupTzS4mIiDoXvmsTdWE+nxcXzpyOuswl2Rkh138wdCC2njqLoqqaQMBaWmPCN8cL8ZMZk/DU/9bHtnFJgrmsBP1GTkRqaiq2bNkSCFPr6upCFk1MTAyEpT179mwQoEar0iEiIuqoSktLI4arADBgwICQ69OnT8fu3btRUlKC9PR0rFmzBmPHjsVll10WWCY1NTWmbdvtdpjNZhgMhubtPBERUSdWXl4e9SQnIPr7sMViQW1tLR544AGoVCoAwHXXXYe//OUvKCwsRF5eXqPbZ8AaG0EQUFNTg2+++QaTJ09GevrFblrffPMNPB4P5syZAwAwGo1hZ4rGyu12R2y9G67K1OFwNFiHf36pPxTV6XRIT09vEJT6v+b8UiIioq6NAStRF1Z7rhwed8MZHZH4fBL2lZTD5fGid0oSAMDl8eL9HXtx/chLoNc0rVJU8Hpw8vAhXEhLh8FgQEpKSqCFrz88NRgMjbYMJiIi6mwkScK5c+diXt7n8+Hw4cNwu93o2bMnrFYrSktLMXToUCxduhQ1NTVITU3FtGnT0KtXr5jWWV5ezoCViIi6pcZOcqqv/vtwdXU1AIR8VpXL5RAEAWfPno0asIqiiPLycgwaNKj5T6Cb8FevPv/888jLy0P//v2xYcMGmEwmPPnkk/jb3/6GkSNHoqqqCkOHDsW9994bdj1lZWWoqKiI2o7X7XY3eJxCoQgJRJOSktCjR48G1aX+S5VKxe4gREREFMCAlagLs1ssMS1XXmvGPzZshcfrg1Iuw12TRgWqVz/fexi5KUmNz1yNQCEK6NWrF4YOHYq8vDyevUlERN2Cz+cLeyCvvoqKCixduhQejwdKpRILFixAWloaSkpKAFys3pg5cyYyMzOxb98+vPPOO1i0aFFM88daUuVBRETUmUWbgR4s0vuwf7blV199henTp0OSJHz11VeQJAmWGD5n8z04NoIgYM+ePbBYLLj99tuxdetWABfb6mZlZUGtVuOuu+7CVVddhSVLluDxxx/HRx99FHJcQZIk7N27F7t27YJKpQoJRTMyMiJWlyYkJLBbFhEREbUIA1aiLkzyemNaLi1Rh8dmTobD7cH+knJ8sHMfFl0+HlV1Npw8X4lHZ05u9j6oVSocOXIE+/fvh0wmQ3JyMtLT02E0GqFQKBr9J5fLQ67LZDKeMUpERB1erFUzqampePDBB+FwOHD48GEsX74cd911V2CG16hRozBixAgAQFZWFgoLC1FQUIAZM2a02j4QERF1NS19H05LS8P8+fOxcuVK7NixA4IgYOjQocjKyorp86g3xs/iXZXX6w1bRXrppZcGWi77rV27FhUVFfD5fNiyZQsKCgrwyiuvoLKyEoWFhXjppZcAAAsWLMBf/vIXbNu2DZMmTQpZx/Tp0zFr1ix2xyIiIqI2xYCVqAuTxXg2plwmIjUxAQCQk2xAcXUttpw4A4VMRFWdDf+3fG3I8v/eugd9UpPxoysmNLru7JwcQK2F1WpFbW0tqqqqcOHCBYiiCLn84kuQ2+0OHEiORVMC2frXG1s++HYGuURE1FyxHuDzn3wEANnZ2SgrK8P27dsDc1fT0tJClk9LS4PZbI5p3ceOHYMkSdDr9YG2/GxtR0REXY3P54PFYoHZbIbJZILJZIq5gjXS+/CcOXPQt29fPPLII7DZbBBFEWq1Gn/9619xySWXNLpe/2fdrsLtdoedVxrua6vVCqfT2WAdoigiLy8v5G8bt9uNCxcuYPfu3Zg5cyZkMhmqqqpw7tw5GI1G7NmzJ2TZ48ePIz8/P2S9giA0CG2JiIiI2kLX+ouPiEIY0jOa9TgfAI/PhysvycfYvNA5b39bswnXDh+MwdkxrFsQMG/BLVCov5/d6vP5cObMGRw4cACHDx+Gy+XCqFGj8IMf/AAejwdutzviv2j3B99XV1cX8TFNOZM4WvjaGiGu/z62TSYi6npEUYROp0NdXV2THidJErxeL4xGIxITE1FZWRlyf1VVFfr16xfTusrKynDy5MmQk5iUSmUgcA0OXoNvY7s8IiLqKCRJgs1mg8lkCgSo9S8tFkuD97qmnMBbf3v1PzNqtVoAQGFhIaxWKwYMGNDoOoxGY7O23xYkSYLT6WwQitYPTIOvR5pfGtxuNyUlBT179gw7uzQhIQFKpbLBSV4KhQJ///vf8fe//x0AUFdXh+nTp+OHP/whcnJycPr0aUydOhUKhQJmsxmPP/440tPT2+T7RERERNQYBqxEXZjWYITWYITNVBtxmS/3H8WArDQkaTVwuj0oOFuG0+ercP+UsdBr1NBr1A0ek5SgQYpO2+j2kzKzQ8JV4PuzVvPy8jB79mwcP34cKpUKMpkMMpks7mee+ny+mIPaxu73f9AM9xiPxxPzPslksphC2caC2sZCXrZLIiJqWzk5OYEq0nC++uor5Ofnw2AwwOl04sCBAzhz5gwWLlwIQRAwceJEbNy4EZmZmcjMzMTevXtRWVmJ+fPnx7T9hx9+GAqFAnV1dSEHov1fV1RU4Pjx47BarSGP02q1DULY4DA2MTGRJwcREVGrcDqdYd+jgkPU4M9WMpks8J6UnJyM3NzcBicMqdVqbN68GRs2bIgatEZ7HwaAgoKCwDzWkpISrF69GuPHj0dqamrU5yRJErKzs1vnGxQDn88Hu90ec3WpzWYL20JZrVaHzCrNyMgIG5T672/NE7J8Ph9EUYTH48HVV18Nt9sNhUKBv/zlLygoKAiMGsrMzGy1bRIRERG1FANWoi4uK38ATu3ZCUT4YFnndOKDHftgdjihVsiRbUjE/VPGon9mWtjlYyWIIrLyo5/Zq1AoYmqv1JpEUYRSqYRSqYzrdiRJihjWNhbi1l/G4XCEVOXW/xcrURRjbo/c3BCXc3KJiL6XnZ2NY8eORbzfarVi2bJlqKurg0qlQkZGBhYuXIi+ffsCAMaPHw+Px4M1a9bAbrcjIyMDt99+e6CVYTTJycmBk5b0ej30en3EZT0eT8jB7OAD3UVFRTCZTCGt/gRBgE6nCzmYXf/gdkJCAt8LiIi6Of/7S7QAtf77S2JiYuA9JTMzs8FJPlqtNqb3l+zs7EarWBt7H66qqsL69etht9thNBoxefJkjB8/PqbnnpWVFdNy4fjnl8ZaXRquHbIgCIEg1B+KpqSkhASkwaGpRqNp1xNy/SduGY1G/OY3vwncbjQaccUVV7TXbhERERFFJUjN7ZtCRJ3C/vVrsO71f7TLtq/56WIMmHBZu2y7u/C3sGppNW4sy8f6diEIQrOrbpvSbplzcomoozt37hyWLFnS5tsVBAETJkzAlVde2WrrbKzCyGQyhbRUDK4wChfAGgwGqNUNu2QQEVHn4PP5Ah0SIrXvbc8OCS6XC3/961/hcrlaZX2xEgQBPXv2xD333BOyL5GC0nBfh5tfKpPJwlaRRqou1Wg0/KxEREREFGcMWIm6OLfDgVcfWAi3w9Gm29XoDXjg1X9DJmehfFcgSRJ8Pl/cQ1y32x22XVUkzZmB25yZuTw4QUTN9cYbb6C0tLTZs+Ca65FHHomp0rW1+GfkRQtgw83Ii3SQ3R/Kch4sEVHbq/+aHq4KNdprekeZ8b169Wrs3LmzSZ8vWkNmZiZEUQyEpuHGxyiVyojhaLivw80vJSIiIqL2xeSDqItTqNUYOm0WClb/D1IbfbAURBHDZ85muNqFCIIQmJMb74qj+kFuU0Pc4NusVmvEx7R0Tm5rh7gKhYIzDYm6oLFjx+Kzzz5rs+0JgoC8vLw2DVf9201ISEBCQkLEtojRqp3Ky8tx7NixsNVO0Q7Ycx4sEVHTOZ3OsG3hY5l7mpSUhN69ezd4PVapVB0uABw9ejS2b9/eptsURRFGozHi7FL/pZyflYmIiIg6Pf5FR9QNjJ17Iw5t/ApOuy3iLNbWIggCNIl6jLp6bly3Q12XKIpQqVSB2YHxIklSs+fi1r/N4XDAYrFEXD5W9efkxiPE9Qe5He0AGFFXdckll2Dbtm04d+5cm1Wxzpw5s02201SiKAaC0p49e4ZdJtq8vjNnzsBsNked1xeuGjbWeX1ERM3hdrtRUVHR6LzrthJprnbw9UhztfV6PTIzMzv1XG2PxxPScrdPnz4oLCxss+1fe+21uPTSS9tse0RERETUftgimKibOPrtN1j50nNtsq15i3+HPiNGt8m2iDo6SZICFbPNCXGbcntz5uTGK8RVKBSQyWSd5mBcZ3Hy5EksXLgQP/jBD/DLX/4SCoUCf/3rX7F//34IgoCrrroK8+fPZ1VEB3P+/HksWbKkTVoUXn755bj88svjvp325J8HG6nqKto82EjVsG05D/bo0aNYs2YNbrnlFqSnp7fZdomoZcrLy/HOO+9g7ty5GDhwIE6ePIm7774bNpsNPp8PEyZMwF/+8hckJibGbR+COwFEClDrdwLQaDRh2/X6LxMTEyGTyeK2zy3hPyGy/uzS4Lml9W+vP3O1rQ55CYKAfv364dZbb+Xfv0RERETdBI++EXUTAyZOwYld23Fi+5b4fcgUBAyddiXDVaIgwWGmRqOJ23YkSYLX621WS+Vw99nt9oiPaeqc3MYC2WhBbawhb3c5kPX3v/8dZ86cAXDxe/vUU0+hrKwM06dPhyiKeO2115CcnIxZs2a1745SiPT0dMyYMQNr166N2zYEQUBmZiYmT54ct210FCqVCunp6RHDSf/swHABRHV1NQoLCxvMDlSpVFGrYPV6faucuFBVVYX7778fO3fuxJAhQzB9+nSsWLECf/jDH6BUKpGUlIRf//rXmDBhQou3RUSt6+9//zv+9re/IT09HQMHDsTixYtxxx134P777wcAGI1G3HjjjZg2bVqz1i9JEux2e9jXLv+lxWIJ+TtMqVQGXqsyMjLQv3//Bq9dHWmWtSRJcDgcIQFpuNA0+OtwYz1UKlXIjNK0tLSo80xLSkrw7rvvxu1zsCAIUKlUmDNnTrf5m5SIiIiIGLASdRuCIOAHP3oUNlMNSo8chiS1chWNICBvxGhMv2dR666XiGIiCALkcjnkcnncK7EaC3KbEvLW1dVFfExwBVpj/EFrc6pum/KY9pj16PP5IIoiHnjgAUybNg21tbWB/+P169dj1qxZuPPOOwEAf/zjHwMBLHUsEyZMgNlsjsssOEEQkJSUhIULF3bYKqS2FDwPNjs7O+wyPp8PFoslbAVYeXk5jh49CpvNFvIY/zzYSFWwjc2DLSoqwvPPP4/Ro0cjMzMTPXr0wJEjR/CLX/wCb731FvLy8vDxxx/jD3/4Az7//HNWondCHo8HFRUVqK6uhtvthiiKUKvVyMzMhMFgYPDSie3btw9msxkzZswItNc9e/YsqqqqUFdXhwsXLgR+tyMJnnsa6TI4TBRFMfD6Ejz3NPi1p73nnvp8vohBqdVqhd1ub3B7uJBTo9GEhKNGozFsUOr/uqmvj3l5ebjuuuuwbNmy1nrqAf6TKe+8884O0SKaiIiIiNoOP7UTdSNypRLzfvF7fP63P+HM3j2tuu7+4yZi9sNPQMaDgURdnkwmg0wmi/ucXJ/P1+S2yZGW8VdARFouVjKZLK4hrlKpbPB9FUURH3/8MXw+H+bMmYNVq1ZBEAS43W784x//wM9+9jN8++23cDqduPzyyzFnzpzW/q+gViAIAmbNmgW5XI4tW7a06nrT0tJwxx13ICEhodXW29X5gwuDwRBxHqzb7Q5puxl8WVhYCJPJFNKKUhAEzJkzB8OGDWsQdJeXl2PJkiXo2bMnJk2ahP/7v/9DQkICLly4gOTkZOh0OqSlpaFnz544dOgQg/JOxGKx4LvvvsOhQ4dQWVkZscuDWq1Gr169MHLkSPTv379dTtihppMkCYIg4He/+x1+9atf4d1338XZs2fhdDrx6aef4kc/+hFeeuklWCwW3HTTTRGrRZcsWYKKioqQ24LnR2dkZDRo49sec089Hk+jFaXB9zscjgbrEEWxQTVpWlpag+pS/6VGo2mT34fhw4dDFEUsW7YMkiS1SjWrIAhQq9W44447kJWV1Qp7SURERESdCZMQom5GoVTh+p//BgWrvsDm/7wNn88LqZkz4QRRhEwuxxV3/hBDp8/iWflE1KpEUYRSqYRSqYzrdvxzclsa4rrdbjidzkBVbrh/jenTpw/uuOOOkNtqamqwZMkSLF26FFqtFi6XCxkZGVAoFPjuu++Qm5uLsWPHoqKiArt27QpU1tRXUVHRIOjlnNy2JQgCZsyYgZycHHz++eew2+3NPsArCAIkScKECRNwxRVXdKgWkF2FQqFASkoKUlJSIi7jcDhCqmBzcnLCBgWvvfYaUlJS8Pjjj2PlypXIyspCUlISevbsiRkzZmDq1KlQKpUYOnQoli5dGvj/5e9nx1VdXY3169fj8OHDABqf8+hwOHDixAkcP34cOp0OkyZNwtixYxmmd3CCIGD58uUYOnQoRo8ejS1btqC8vBwqlQonT55Er1698NprryE7OxuLFi3CH//4R7zwwgswGo0h65k4cSIEQQiEp20x91SSJLhcrojVpeFmmNafXwpc7BISHIomJSWhR48eYatLExIS2r2qNpqhQ4ciLS0Nn332Gc6fP9/i9fXv3x9z5syBTqdrhb0jIiIios6GAStRNySKMoy6ei7yRo7G+jeXoGh/AQRRjDlo9S+bN2IMpt39APRp4WegERF1BsFzcuPJPyc3Wkgbrip427ZtOHHiBKZNm4aEhAQUFxdjw4YNsFgs+MMf/oDNmzejf//+AIBZs2ZhzZo1+OEPf9gg5Hn99dfDVlbFq51y/ds76sHW9jBw4ED06tUL69atw759+5pUSSOKInw+HzIzMzF79uyI1ZfUNtRqNdRqdcR5sMDFNqIrV65EZWUlzpw5g71798LtduP06dP44osvUFlZiS1btiAhIQGPPfYYSktLASDwOyNJEmpra1FbW9uq82CpeXw+H3bv3o21a9fC5/M16SQJ/7J1dXVYs2YN9u/fj3nz5iEtLS1eu0uN8M89NZvNqKurQ79+/Rrcv3LlSmi1Whw5cgSbN2/Gnj17oFarsXv3bvTt2zfQivyqq67C22+/jQsXLjQIWIcNG9Zq+xprdanNZgs7bkGlUoUEounp6WGDUv9lVzuBJzMzEw888AC2bNmCb7/9Fi6XK3BSS2P8y+n1esycORNDhgzh3zdERERE3Rg/mRN1Y0lZPXDjr/6AmvJS7Fu3Coe+WQ9HnQXAxRA1+MCeP3zV6g0YcsVMDJvxAxjSM9pt34mIOpvgObkajSbmx82ePRsnT56ExWKBKIq44YYbcMUVV+DGG2/ET37yk5D2fA6HI+yBPkmScM8998RciRtuTm64+5szJ7exULa5Ia7/vs7SdlOr1WLu3LmYMWMGCgoKsHv3btTW1gK4+LMS/P/oD8aVSiUGDx6MMWPGoEePHu2x29QMvXr1whdffIEjR46gqqoKBQUFqKmpwYYNG/DCCy/gn//8JwYOHAjgYvi+e/du3HDDDYGKKJ/PhyNHjmDdunWBdSYkJAQq4epfGgwG6HS6TvO70Jm4XC588MEHOH36dKus79y5c3j11Vdx3XXXtUoARw25XK6QFt/B85b914NHBfz6178OqSy1Wq0QBAHffPMNTp06BUmSoFAoMHLkSOh0ukCgajAYsHfvXqjVauTn58e0b16vN+yM0kjVpeHmlwqCAI1GExKKJiUlNQhKg79m1fTFkQ9Tp07FhAkTcOjQIezcuRPnzp0LfH+DXz/978GiKKJv374YO3Ys+vbty9dYIiIiIoIgtcbgCSLqEiRJgqWqEhWFJ1FVfBZu58UD9QqVGqm9eiOjTz/okiO3ySMiovibOHEiHnnkEdx888145ZVX8OmnnyInJweSJKGyshKvv/46cnJy2mRffD5fs9spN/a44PuaOie3pdW4sYS88ThAbbPZUFZWhoqKCjgcDkiSBLlcjpSUFGRnZyMpKYkHdLuA6667DjNmzMBDDz2Eq6++Gpdddhl+8YtfAACuueYajBo1Ck8++WTITF2v14va2tqoQVH9ebCJiYkNZjoGX2q1WlZeNYHT6cS7776L0tLSVpndWN+1116LkSNHtvp6uzKv1xt2RnLwZf0ZoTqdLuT3IvjEBL1eD51OF/X34uzZs7jxxhvx8ccfIysrC3/729/wzjvvQKPRoHfv3vjDH/6AIUOGhDzG5/Ph7Nmz2L59e0hgGml+abhwNFJ1qVqt5vtCK3G5XDh37hzKy8thtVrh9Xohl8thMBiQnZ2NtLQ0htNEREREFIIBKxEREVEnUl5eHqhec7vd2Lx5M6qqqmCz2TBx4sSYK2c6k0hzcpsb2Ea7LVaiKMbcHrk5IW5wkMsQrGvwz1R999130bt3b0yaNAlFRUW47777UFtbC7lcjtzcXDzzzDPIy8tr8rqdTmfUANZsNodUncvl8gbhUv3r4dqWd0c+nw/vvfceCgsL4xKu+t18882BaubuTpIk1NXVRf2ZrqurC3mMRqOJWtndkrmnXq8XMpkM1dXV+PLLL3HllVciPT0dXq8XgiBEDTklSUJxcTE2b94ccW6p/7aOPL+UiIiIiIhCMWAlIiIiIkLkObmxBLixtFsO/hfrn+DBM4KbWnUba4jLObntz2KxoLS0FElJScjIiM8IBkmSYLVaG4RVwZd1dXUhP5sqlSpqANuZ58E6nU7IZLKY9n/79u1YvXp13PdJrVbjoYceCrSHjsZut0OtVnfK31tJkuBwOCL+HPpD1OC54QqFIuLPof9SqVRG3Wa4drz1vx47dizy8/NZFUpERERERI1iwEpERERE1IYkSQq0V25qiBtrgOv/FxxQNKY5M3CbEuL6/3XGQKi78Hq9sFgsUedV2u32kMckJCRErBj0t1ztiGHVxx9/jNLSUsyZMwd9+/aNuFxVVRVeeeWVJs2cbi5BEDBw4EAsWLAg4jIulwtff/01tm/fjvnz52Pw4MFx36+mcrlcUYN8s9kc0jFAFMWQ4DTcz1L9MNnr9TYISKPNMLXb7WHnl9avJh0xYgTy8vI65M8sERERERF1LJ3zdGMiIiIiok5KEATIZDLIZDKo1eq4bitckNvcENdqtUZ8TFPCp3Bzcls7xFUoFAxImkEmk8FoNMJoNEZcxu12RwzPTp06BbPZHDIPVhTFwDzYSNWHGo2mTYN3j8eDwYMHw2az4b333sOll16KK6+8EhqNpsGya9eubdKJCi0hSRKOHDmCwsJC9OnTp8H9hYWFWLFiBcxmMwCgurq6TfYrmD+Ejxae1g/h/XNP9Xo9+vXr1+D/PyEhAV6vt0FAWlVVheLi4rBBqtPpbLBvMpksJCzV6/XIzMxs0IbX/3Vb/9wREREREVHXwgpWIiIiIiJqEZ/PFxLMNjXEbcoM3VjVn5Pb0pbKke4XRZEhTRB/+9dwwVtwKBccWsrl8rCVi8FhbLT2r01VUlKCpUuXIjMzE3369MF3330HhUKB2bNnY9CgQYHlamtr8cILL7TadmMhiiIGDBgQUsXqcDiwdu1aFBQUQBAEqNVqzJo1C8OGDWvVnz3/3NNoFcz1556q1eoG/2d6vR4ajSbw++FwOBptzRvud1upVDaYVarRaBrMLvVfKpVK/i4SEREREVGbYcBKRERERESdgiRJ8Hg8zZqH29TbmzMn1/9Pp9MhNTUVBoMBiYmJ0Ol0SEhIQEJCAtRqdcjcz+DtBIdD/tudTifkcjlkMlmXCY/882CjVUFaLJaQx6jV6ohtiP2XMpks5n04e/Ys1q1bh5KSEuTm5kKSJBQVFWHw4MH4wQ9+AJ1Oh/Xr12PLli0x/yxs2bIF69evx7hx43DVVVfBbrfj66+/xunTp2EymaDVajFw4EBcccUVUavXBUHAo48+Cr1ej+PHj2P58uVwOByQJAljxozBtGnTmlz9Xj/4jvR9jxR8JyQkQKVSQalUBmY2S5IEp9MZtj1vuKpfjUbToIo0XFDq/7qzzvclIiIiIqLugQErERERERFRkGhzclujShf4PmwKbp/rb88riiLKysqwefNmlJeXB/arNVoqx3J/Rwhyg1vRRqqoDNeKNloVbEJCQkjraH9L3q+++go1NTXo3bs3zp8/DwCYNWsWNm7ciJqampj2t7S0FJ988glUKhVyc3Nx1VVX4fz589i4cSOGDx+OtLQ0mEwmfPHFF8jIyMBNN90UdX0zZ85EaWkpjhw5AgDIyMjA3LlzkZWVFXZ5t9sd9XtlMplCqkQFQQgEmiqVCnK5PPC98f/sOxyOQIVpff75peHC0Ui3s203ERERERF1JQxYiYiIiIiI2onX621ytW1zWi03ZU5urKFtU2+vf39LAzeXyxWxFbH/MjhUDJ4HG9zONjExESUlJfjuu+/gcrmQkpISCFpj3Y/XXnsNV199NTZt2oTMzExcddVVYZc9dOgQli1bhl/+8pcRn78gCIEKUYVCgRkzZiA/P79BYOq/XltbC4fDEbIOpVIJpVIZqHz2V3+7XK6w7XjlcnlMQan/Uq1Wd4ggnoiIiIiIqL2w5w4REREREVE7kclkkMlkUKlUcd1O/Tm5zQ1xPR4P7HY7zGZzxOVjJZPJYgplY5mZm5SUhPT09JDbZDIZvF5vxLmixcXFDdriiqKICxcuBELJWHz55ZfIz89HXl4eNm3aFHVZp9MJlUoVNVyWJAmSJAXaAK9atQqrVq0K2Uf/471eb8T9VCgUEdvx1g9NFQoFA1MiIiIiIqImYMBKRERERETUxYmiGKhqjCd/pWRLQ1y32w2n04m6urqwy7tcrpj3SRTFsKGswWBASkpKIFj0er3wer2w2+2orKyMKWA9ePAgysvLcf/99ze6rM1mw6ZNmzBy5MiY9tvpdAa+VqlU0Gg00Ol0SExMhEajiVhdqtVqOb+UiIiIiIgozvipi4iIiIiIiFqFIAiBADOeJEmC1+uNKcCNpZ2yP8y1Wq1wuVwxhasmkwmrV6/G7bff3mig6XQ68Z///AdpaWm4/PLLY36OCoUCgwYNwvDhw5GVldWh5uQSERERERF1Z5zBSkRERERERN2OJEkoKirCvn37cOTIETidTqSkpMDn86G6urrRxx89ehQffvhhSNjp/3gtCAJ+/etfQxRFOJ1OvPfee1AoFLj11ltjri6NFqLGOue2qXNx6/9jkEtERERERBQeA1YiIiIiIiLqNqqqqrBr1y4cPHgQVqsVSqUSMpkMTqczMI81lo/JTqcTJpMp5LYVK1YgNTUVkyZNQnp6eiBclclkuO2225pU2atQKKBWq+Hz+WCz2ULuMxgMyMrKQmpqaqOVvOFaMMcqeE5uvEJchUIRdSYtERERERFRR8QWwURERERERNQlSJIUCD6rqqpQUVGByspK1NbWoq6uDna7HW63O+Qx/nmugiBArVYjMTERKpUKxcXFUbelUqmQnp4ecptCoYBGowmEq++++y7cbjcWLFgAp9MZmKuq1WqjhoppaWkYOXIkTCYTzGYzamtrUV1dHXi8yWSCyWSCXC5HSkoKDAYD9Ho9kpOTYTAYAtf1ej1kMlmD71G0tspNabnscDhgsVgiPiZW/jm58Qxx/UEuq3KJiIiIiKg1MGAlIiIiIiKiTsHtdsNsNsNkMqGyshIXLlxAdXU1TCYTbDZbSBVqff7w02AwwOPxwGQyQRAEXHLJJZgyZQpSU1MDy3q9XvzpT3+C1+tt9r6Wl5ejtLQUAPCPf/wj5L6f/OQnMBqNYR8niiLy8/MxYcKEBvd5vV4UFhZiz549OHXqFPLy8qDT6WA2m1FcXAyTyQSHwxHyGJ1OFwhcw12mpKTEJXQMnpPbkhDX7XbD5XLBZrNFXDbWxlzBM4KDQ1m1Wo3+/fsjNTUVgiDA5XLB5XLB4/HA4/HA5/MFwttYQl7OySUiIiIi6vrYIpiIiIiIiIjandfrhcViCQlQKysrUVNTE6g+jdbeVq1WQ6vVBio509PTkZ6ejuTkZCQmJgYqRj/55BOcOXMGY8eOxZgxY6DRaMKu74033kBpaWnM4V1ruummmzB48OCoy0iSFDbEc7lcgcpXf6Wr2WwOuR78fRRFMSR09X8dHMKq1eoOGxhKkgSfz9fsEBcAxo0bB4PBAEmSAt/X+hXGNpsNZrMZNTU1Id9f/2VdXV3Iz0oslbVNvT3c/R31/4WIiIiIqKtjwEpERERERERxJUkSrFZrIIyqra1FVVUVqqqqYDabYbVaA+1vwxFFMdC+12AwIDU1Fenp6UhJSYHRaERCQkLMQZO/KrV+69z6CgoKsGLFitifZCtRq9V44oknIJfHp+GUJEmw2+1RA1iLxRJSCaxQKKIGsHq9HkqlMi7729EEH0IJ/pnzt152uVxwOp1wOByw2Wyw2+2oq6tDbW0tnE5no8Gvv2o2Vv6K2WiBbGu0W+acXCIiIiKiUAxYiYiIiIiIqEUcDkdINZ8/QK2trYXFYoHNZotaCSqTyZCQkAC9Xo+kpKSQ8NRoNLZLBaXb7cZf//rXqMFvaxMEAZMmTcKMGTPabJvh+Hw+1NXVNajSDA5hrVZryGM0Gk3ENsQGgwGJiYmNhtp0kSRJMVfiRro/1jm7sYo0J7e1Z+ZyTi4RERERdRYMWImIiIiIiCgi/9zT4HCttrY2MPvUarU2WnGnVCqh0+lgNBqRkpKClJQUJCUlwWg0wmAwQKVStdGzaZr169djy5YtbdYmWCaT4eGHH444n7Uj8Xg8sFgsIVWw9S/rz4NNTEyMGsI2pRKZWs5fddvcELcpAW9L5uS2doirUCggk8n4s0ZERERELcKAlYiIiIiIqA15PB4IghCo5qupqcHTTz+NEydOwOv14s9//jOGDRvWJvvi8/kCIVn9ALWmpgYWiyWmCk5/9aLRaERqampIeGowGKBQKNrg2bQ+t9uNV155BbW1tW0Ssl555ZWYOHFi3LfTVpxOZ8QqWP9lpHmwkVoSt0U18xNPPIGtW7ciIyMDr776KjIzMwFc/N21Wq0wGAxx3X5XE2lOblNm5oa7P9xtwa2tGxNrINvcENd/H4NcIiIioq6JASsREREREVErOnfuHMrLy9G/f38kJCQAAI4ePYqHHnoIJpMJLpcLd955Jx577DEAwM9+9jN4vV7MmTMHbrcbP/rRj7B79+4WVzFKkgSbzdYgPDWbzaipqYHJZGrQutcfBNS/LSEhAQaDIaTy1B+g6vX6Lt36tbi4GEuXLo3rNgRBQI8ePXDPPfd0q1mX/nmw4X5Gg4PY4J9HpVIZtQpWr9e3KNCXJAlr165FaWkpHn30Uezduxd9+vSBw+HASy+9hPfffz8QBL/wwgsYMWIEgIttsvfs2YP09HTk5ORAo9G0+PtDTef1epvVNrkpIa7b7Q7Mco5FrFW3jQW1jYW83em1I5qNGzdi8eLF2LlzJ5YsWYIf/vCHAIDa2lo899xzOHbsGERRxG233YY5c+YEvm/r1q3DmTNnoFQqMW3aNPTs2bM9nwYRERF1AgxYiYiIiIiIWsmTTz6Jzz//HMePH8c333yDyZMnAwBmzZqFhQsX4pprroFCoYBer8eRI0cwYMAAaLVaHDx4EHl5eQCAKVOmYP78+Vi0aBHkcnnEbTmdzojtWf2zT4NDAEEQIAgCJEkKCaz8YZHRaERycnJIeGo0GqHT6br9gftt27ZhzZo1cVm3P8C+7777OkVr4LbmnwcbrQo23DzYaFWwscyD3bdvH+655x6sXbsWKSkp2Lx5M+bMmYOqqirIZDIsXboUb731FrZs2YKqqio888wz2LNnD5xOJ2QyGV5//XUMHDgwnt8aakc+n69JgWxzQlz/fbGSyWQtCmtjrdTt6CfUHD9+HImJibjxxhtx880348c//jFEUcTtt9+OzMxMTJkyBVarFf/85z/xpz/9CVOmTMFrr72GDRs2IDk5GSaTCXq9Hr/73e8C1etERERE4UT+tE5ERERERHEnSRLq6o7AZCqAxXIQZssBeDxmSJIPoqhGQkJf6BOHQq8fCqNxPGSyjjmrki5asGABnn32WUyYMAE1NTXw+XwQRRGbN2/GAw88gKSkJFRWVmLMmDGBkDM1NRXffvttIGCtqKjAjh07cPvttzcI3Hw+H1577TXU1tbC5XKF3OefKej1ekMCVIVCAYPB0KDy1P+1VqtlC8tGTJgwAW63Gxs2bGjV9frD1bvuuovhagT+EwD0en3EZTweT4M5wf7rRUVFMJlMIa2uBUGATqfDhAkTMH78+JCff0mSIAgCjhw5gsTERGi12sB+DBkyBGfOnEHfvn3hcrlw4cIFAMCXX36J5cuX48SJEwCA9957Dw899BC++uqrwGsAdVx2ezFqa3fCbDkIs3k/XK4qSJIHoqiEWp0DvX4Y9IlDkJQ0DgpFEoCLPw9KpRJKpTKu++afk9uSENd/3el0oq6uLuLjYiWKYrNbJzflMc2dk9uvXz+Iogi1Wh34/QUuVrY+9dRTmDNnDgDgoYceCvwO/+lPf8Lzzz+PefPmAQDGjRuHTZs24aabbmry9omIKHZVLg+21tZhv8WGvWYbzjpccEkSFIKAdKUcl+q1GJaoxQSjDj3V8X3PJWoOBqxERERERO3A67XhXMX/UFz8b1itxwAIEAQZJCm0WsVuL0Jl5dcAvJDLE5GdfTNyetwKjaZXu+w3RedvF6rT6VBcXBwIVr744gs8/fTT+OlPf4qKigr8/Oc/R2pqKgDgqaeewpdffokPP/wQBoMBubm50Ov1MJvNDUI3URRht9tDwlWVSoWkpCQkJSUFgtPgAFWtVrfNk+/ipkyZAp1Ohy+//LJBiN1cWVlZuOmmmxiutpBcLkdycjKSk5MjLhM8D9YfwKampsLn84WtyDtz5gwyMzMD7Ybz8/MxYsQIjB49GgBw+eWXY8WKFYFle/X6/jVZo9HA6/Xi3LlzrIDroCTJi8rKr1Fc8g5qar4FAAiCPMx78FnU1u6AJHkgCHJkZFyLnJyFMOiHt8l+CoIQCBzjSZIkeL3eVqvEtdlsYe93uVwxv3YKgtBoIDtv3ryI3xubzQa1Wh14H37//ffxy1/+Ev/5z39QV1eHRYsWYerUqQAutpYODsu1Wi327NmDOXPmsN03EVErkyQJ35lteKu0EsvP18AjAXIB8EpA8DvEWYcLey12eKRKCACmJiXinpxUTE/RQ8aTQ6mDYMBKRERERNTGLlz4CkeO/gJudzUA/4dDqcGB3Yt8ga88HgvOnn0TZ8++gV697kVen0chkzE864hycnJQWloaqIarra3F4MGD8eabb6Jnz564/vrr8fTTT+OFF17AXXfdhREjRuDUqVOYOXMmXnzxRRw9ejRiMHPVVVdBoVAEgtR4V1DR90aOHIk+ffpg2bJlOHv2bKDlclP4WzVPnz4dEyZMYHVjG1GpVEhLS0NaWlrU5fy/s6dPnw75Hfz973+PpKQk1NTUwGKxYOHChdi2bRsGDhyI8ePHo6CgAJ9++inGjx+Pjz/+GBcuXIDJZEJmZmZgndQxWCyHcejwY7BaTwD4PlwP/x78/XuzJHlQUbEC5859htTU6Rg48E9QKVPbZqfjzB9myuXyuAeK/iC3OSFu/dujtSt2uVwhFayrVq3C5MmTMWbMGBw9ehQFBQWByvaf/vSn+PDDD1FcXAytVouioiIMHTo07Ov7/v37UVVV1azqXb7eE1F3V+F044ljxVhXZYbs/4eqAOCJ8Oe05/+/DksANtdasLHGgsEJarw8uDcG6XgCDLU/BqxERERERG3E47Hg6LHfoKLicwQHq01zcabm2bNv4sKFtRhyyYvQ64e15m5SFP65p2azGU6nE5dccknY5Xr16oXTp0/D7XZDqVRi48aNSEpKQm5uLgDg2muvxcqVK2E2m6HX6zF8+HAMH36xIur48ePo06cPlEolvF5vgwPIgwcPjutzpOiSkpJw11134ejRo9i5cyfOnDkTCM8iha2iKMLn80GpVGLkyJEYO3Zs1GpLaj/+AMRsNmPixImQy+WQJAnffvst/vjHPwIAEhMTkZGRgZMnT8Lr9WLmzJmora3FkiVL8Pnnn8NqtWLChAmBGcrBPx8mkwnFxcWBmbCJiYkMXdqIJHlReOYVFBa+hO/fg73RHhJ2HQBQVbkR27bNwKCBf0RGxtWtu6NdnEwma5M5ri6XK3ACUllZGb744gusWrUKOTk5AIDhw4dj165d6NGjB5544gm88cYb2LVrF4YNG4aBAwciJycn7H6WlJTg2LFjLZ6TGy2Qbaxyt7Fl+JpCRB3Rsooa/OxYMey+iycQe5v4Mdi//DGbAzN2H8PPcjPxSO8MiDyJjdoRA1YiIiIiojbgclXiu4LbYbWe+v+3tLS9qA92ewl277kJw4YtQWrK5S1cH/nnOPoD1HCXwXMclUplg4DVH6QMGjQI3333XeDgrlarxaZNmwLLlZSUQCaTQa/Xo6KiAm+88Qa2b9+O8+fPY/z48fjNb34DSZLa5CA0NZ0oihg8eDAGDx6MCxcu4OjRoygrK0NJSQksFkvIchkZGcjJyUFOTg4GDRrEiuMObsmSJfjXv/6FgoICnDx5EgUFBXjuueeQmZmJY8eO4corr4RCocCWLVvw6KOPBn5H58+fj/nz5wMA5s2bh549eyI7Oztk3T6fD0VFRVi+fHngNv88WH/gqtfrG1wmJCSwAraFfD4XDh16DOcvrGqV9Unwwuutw8FDj8DhKEXv3j9slfVSywWHixkZGQAunhRx8uRJ+HzfdwUxmUwhLfTvu+8+3HfffQCA559/Hk8++SRUqoZz72fPno3Zs2cHroebk9vcmbkOhwMWiyXiY5ryPWjtmbiRgly+NhFRLF4qqsCfTpdDQMs/BfuD1r8UnsMxqwMvDeoNhcjXImofgtQag2OIiIiIiCgit9uEPd8tgM12OlD90nouzm69dPibSE6e1Mrr7jp8Ph/q6upCwtL6AarVag15jFKphEqlChysdbvdcDqd8Hq//z9cvHhx2AOwb7zxBn79619j0aJFyMnJwfXXX4/HHnsMu3fvhiiKyMnJwYsvvoj8/HxYrVZs2LABTqcTffv2Rf/+/ZGQkBDfbwjFjdfrhcfjgSiKkMvlPPjcybjdbhQVFaGsrAwnTpzAsWPH8PTTT+PMmTP48Y9/jMrKSjidTsydOxdPPvkkkpKSsHLlSlRXV6N///7Yt28flixZgo8++gj9+vULu43gSvhwr0UmkynkdcZ/Mka4ANb/NWctRyZJXhw8+BOcv7AaLT+sG15+v1+hV6974rJuaprFixfjww8/RFFREbKysmA0GrF37178/e9/x6pVq5CZmQmHw4HExET885//hMFgwCeffIJTp05Bp9PhwIED8Hq9eP311zvU63f9ObnNDXFjeUxT5uTGEshGC2pjCXn5XkrUuf2jqAJ/PF0el3ULAK5PN+Kfg3uzkpXaBQNWIiIiIqI4kiQJ+/f/EJVV36CprQhjJ0Am02D8uDVQq7MbX7yLkSQJdrs9YlBhNpthNptDDhj658z5D9r5fD643W7Y7faQChe1Wg2DwRCYdxp8aTQaodFoQg76eb1e3HzzzTh48CB69+6N1NRUjBs3Dg8//DBMJhOsVisyMzPZvo+oE7NYLIETMADgyy+/xHvvvYfS0lJkZWXhmWeeCbQDbw5JkmCz2cKGsP7rFosl5DVNqVSGBK71A1i9Xg+FQtHSp94pFRb+E6cLn4/7dkZc+g5PdOog7HY7nE4nrFYrbDYb8vPz4XA4sGvXLpjNZjgcDkyZMiUwk3nNmjVYs2YNLBYLcnNzsXjx4m7bQUKSpMDfRE0JccMt09hjgv/eakxLwtqmVOoyyCVqXRuqzLh1/+m4b+dXeVl4uHdG3LdDVB8DViIiIiKiOCo/txyHDz8e9+0IggxJxgm49NK3ox4ckiQp0Lp26NChcd+v1uB0OiOGDP7rwTPQRFGEVquFSqUKHCD1eDxwOByw2Wwh69ZqtYGw1B9GBF9nVRgRdUQ+nw8WiyXqa2O417tIAWxnmgfrdrvx9ddf49JLL0V6enrUZS11R7Fr17Vx6B5RnwiVKg3jx62FXK6L87aIuob6QW48QlyPx9OkObn+sLWp7ZObOje3M7zWErWU2ePFZTuOoNLlQeynUzSPXADWjxmIAQn87EZtiwErEREREVGcuFyV2LptOrxeK+LVlrC+wYOeRVbWDWHvq6ysxOeff47i4mJceeWVmDBhQpvsUzT+uafRQoLguacAkJCQALVaHThA5T9AZ7PZYLfbQ5ZNTEyMWH1qMBi6bUUXEXWLvBm2AAEAAElEQVR9brc75PW0/qXJZILL5QosLwgCEhMTo7Yj1mq17V7h5XK58MYbb6CqqgpTpkzBZZddFrbaUJJ82LlrDqzWE20QsAKAiB49bsXAAb9vg20RUawkSWpRiNvY44Lvi5VMJot7iKtQKLptJTZ1DE8cPYv/lFfHPVwFABmAS3QarBndv93/TqHuhQErEREREVGcnC78BwoLXwLa5GPlRWp1T0yc8HWDtrVbt27FN998A4PBgGuvvRa9e/eO+76Em3ta/7L+3FONRtOg+tTr9cLpdKKuri4kbBVFEXq9PmL1qcFg4IElIqIoHA5Hox0C6s+DDRe+Bl+2ReW/x+PBpk2bsGXLFqSlpWHu3LnIzg5tkV9ZtRH79t0b930JJghyXDbpWyiVqW26XSJqf5IkBSpmmxPiNuX25s7JjUeI6w9yGWp1D0ePHsX+/fsxefJkZGVlRVyuwunGyK2H4jYgJ5KPh/fF5OTENt4qdWcMWImIiIiI4sDn8+DbbyfB5a5s820Hz4E7d+4cVqxYgYqKCkyYMAGXX355q1RtBs89jTYjMHi+lkKhQGJiIjQaTYPqU7vdjrq6upBqKplMFjE8NRqNnaadJRFRZxU8DzbSyTL158GqVKqoVbB6vR5yubxV9i/ae9zeffehqmoT4jf/PBwRffMeR27ug224TSLqTiLNyW1u1W2025ozJzdeIa7/dga57auiogKffPIJKisrMWzYMFxxxRUwGo0Nlvv7mXP4a+G5NjzNGJAJwJUpBrw1tE8bbpW6OwasRERERERxcKFyPfbv/2HMy//3v7VY+kY15s3T40c/Dq18kSQJv/zFOezaZcfvf5+BSZclRFyPIMiQmjoTgwe9iE2bNuHbb79Fampq2OqeaILnnka6rD/3VK/XIyEhASqVKnDw3F99arVaG1RCKZXKiK17jUYjEhISeBCFiKiD88+DjRbCRpoHG2kmbFNOoAnXpSEjU4Vvv70Msbbnj/QefPiQA2++WY2jR50QRaBvXxWe+UsmVKrI+6ZSZWLSxC18/yKiTs/r9TY5qG3OzNzgzweNCRe+xnpbrPfL5XKexBmFz+fDd999h40bN8LhcGDcuHGYPHlyoIOFJEkYvvUQzrtim39s/c+bqHvjH9DOuxWJD/0MAOApLUbdkufhOlgAuN1QjpmIxId/DllyStR1iQD2TrwE6SqOgaG20TqnDBIRERERUYjamh0QBDkkqfEPlkePOrDyCzPy8pRh7//0UxNiPU4rSV5UVW3Da68tQXV1Tdj5dB6Pp9GD4Q6HI2S9Op0OBoMBGo0G6enpyMrKalB9ajabUVtbG3iMRqMJhKU9evRoEKSq1WoegCYi6uREUQyEo5H458GG63pQWFgYcR5spAA2eB6sTCbD5MmTMWjQIHz++ed4++23MXacCKUytnA10nvw4UMOLP5FOW65JQkPPZwKmQw4dcrV6PuW03kOTuc5qNWRWycSEXUGMpkMMpkMKpUqrtvx+XxNbpsc6X673Q6z2Rxx2VjJZLKYq2qbE+L67++M40xEUcTo0aMxbNgwbN26FVu3bkVBQQEmT56MMWPGoNTtjTlcdR89BNsXn0Kelx+4TbLbUfvkjyDv2x9Jf3sdAGB96xXU/uonSH75HQhRwm8fgN1mK2anGVvyFIlixoCViIiIiCgOTOb9MYWrdrsPf/7TBTz6WCref7+2wf0nTzrxyccmvPJqD9w0/2xM2/b5TFAorJg+fToAYN26dSEHtMPNPfVXDKWnpwcqXb1eL1wuV6A9ZFlZWUgbyISEhEBY2qtXrwZVqPE+GENERJ2DQqFASkoKUlLCV55IkgSn0xmx7XxZWVmDLghyuTwkfNXr9Rg2bBgyMjJQeeFfyMoSIYjRmxNGew9+5dUqXH+9AbfcYgzc1rNn+BOh6rNYDjBgJSKKkSiKUCqVUCpje41tLv+c3JaGuG63G06nE3V1dREfEytRFFsU1sZaqRuPOblKpRKXX345Ro0ahY0bN2LdunXYuXMn5JddEdPjfXYbTH/6JfSP/x+s770RuN11cC+8FWVIfv2/EBN0AAD9z5/ChblT4SrYCdWo8RHXKReAfRY7A1ZqMwxYiYiIiIjioK7uUEzLvfRiJcaN12DUKG2Dg7sOhw9/+uN5PPxIKpKTm/anu9N5AuvWOaBQKAIHnlNTU5GdnQ1RFCFJEtxuNxwOBywWC2pra1FRURF4vL96yB+Y5ubmhgSoer2+VWa5EhERCYIAtVoNtVqNjIyMsMtIkgSr1Rq280JVVRVOnz4Ni8UCABgy9AIgND75LdJ7cE2NF0ePODF9ug6PPFyKsjIPevVS4O57kjF0qLqR5yKD2XIIaWlXxv4NICKiuBMEIRA8xpMkSfB6vS0Ocf232Wy2iI+Ldfqj/7k3p3VyLI+ZPn06Ro8ejY0bN+Kdg0ch9uwHnxC9zbLlxT9DNW4yVKPGhwSscLsACBAU3wfuglIFCCLcB/ZGDVi9ErDPbIt4P1FrY8BKRERERNTKfD43vN7GP9h9vaEOJ0468corPcLe/+orVbjkEjUmTYo8czUStdqLjIwMaDQaOBwOlJWVhbT99bd0NBqNSEtLQ79+/UKqT/V6fadsWUVERF2TIAjQ6XTQ6XTo0aPh+6bH48GRI0dQUFAApcLeaGv9aO/B5eUXq4/e+XcNHngwBX37KrFunQVP/qwM/3qjJ3Jyoh2cF+B21zbhmRERUVciCALkcjnkcjk0Gk1ctxUc5DYW4jY2F9fhcERcvilzcp39L4UkAYjyPuzYsBqeE0eR/Op7De5TDB4KQaNB3esvQnffQ4AEWP71IuDzwlddGXXbEoBKd+ytoIlaigErEREREVEri6U18PnzHrz8chWefTYTSmXDs3u3brVi7147lryW06x98PncOH/+PCRJgkajQU5ODvr374+MjAwYjUbodDqIUebXEBERdXSSJKG4uBj79u3DoUOH4HQ60aNHDyToNJAkU8THNfYe7C8IuuYaPa66KhEAkJ+vQsF3DqxebcF99yU3sl+xt4ckIiJqLv+cXLU6eneFlvL5fI2GuE6nEyUlJdjijH6Srvf8OVhefg7GZ1+9WJlaj2hMhuE3z8Lywp9gW/ZfQBChnnYV5PmD0OjZUwDcvtiqeolaAwNWIiIiIqJWJoqNzw86cdyJ2lovHnywNHCbzwcc2O/A8uVmzLlWj7IyD+Zeeybkcb//fQWGDFXj73/Pjrr+OdfOQ0b6XJw4cQL79+/H8ePHcerUKfTt2xfDhg3DwIEDGbASEVGnVFVVhf3792P//v2ora2FwWDA2LFjMWzYMKSmpmL7js9gtZ6L+PjG3oPf/ndPAEDv3qGVqr16K3D+fOMnUcXydwAREVFnIYoiVCoVVKqGgajL5UJBQQG2b9+O2tpaaEdeBlEUEanm1X38CHw11ah+4Nbvb/R54d7/HWzLP0T6mh1QjZkA1fv/g89UA8jkEHWJuHDDDMiyZjW6ryqxdWfNEkXDgJWIiIiIqJUJggxKZSpcrsgtjEaM1OBfb4RWpz733AX06qnAgpuNMBhEXHONPuT+++8rwaJFKRg/QdvoPmjUPSCTyTBw4EAMHDgQdrsdhw4dwv79+/HZZ59BqVRi1KhRmDlzJoQYzgQmIiJqb5WVlVixYgVKSkqgUqkwePBgDBs2DL179w55L9NqesFqPQEg/BzWxt6Ds7LkSEmRobgktBK1pMSNsWOivwdLkg9qdfjW/0RERF2FxWLBzp07sXv3bjidTgwZMgQ33XQTPnaJ2H26POLjlCPHImXpxyG3mZ79LeQ9+yDhlrsgBI2pEQ1JAADXdzvhq62GauLUqPskA5Cr4UlO1HYYsBIRERERtQK3243a2lqYTCbU1tbC6ewBoAqCEL5FkVYrok+f0A9/arUAvf7725PDdCBMT5cjKyva7DcAEJCYODjkFo1Gg9GjR2P06NGorq7G/v37UVdXF+vTIyIianculwtGoxHjxo3DgAEDoFCEfz/U64fhQuWGiOuJ5T34pgVG/Pvf1eibp0TffiqsXWtB8Vk3fvvbxEb20gd94tAmPS8iIqLO4vz589i2bRsOHDgAmUyGkSNHYvz48TAYDACA4dWWiNWrACBqEyD26Rdym6DWQNQbIP//t9tXrYCsdx+IhiS4D++H5eXnoL3xNsh75UbdNwnAcH1CC54dUdMwYCUiIiIiioHD4QiEp/4gNfi6zWYLLCsIAvr1UyM9o332VaPOgVwe+QBwcnIyLr/88rbbISIiolaQnZ2NG264odHlEhOHAFEP7zbuhhsMcLkkvPpqFSwWH/LylPjLs1nIzm7sJCcgMfGSFm2biIioI1qxYgX27t2LxMREXHHFFRg1alSD+a9DEzUt3o6n+Azq3vgHfBYTZJnZSLjtXmhvXNjo43wAhrfC9oliJUiSxKm/RERERNStSZIEm80WCEzrX16sSHUGlpfJZDAYDDAYDDAajYFL/9d6vR511sPYtWtumz8XQZAhJ+dO9M//VZtvm4iIqCPweKzYvGUcfD57G29ZhF4/HGNGf9LG2yUiIoq/rVu3IiEhAUOGDIEsqJVvfVftPob9FnuERv3xo5OJ2D9pCLQysY23TN0VK1iJiIiIqMuTJAl1dXUh1af1L93u7+esKRSKQFiak5ODIUOGhASpOp2u0bml+sQhSEwcCovlECLNgIsHSfIip8etbbY9IiKijkYuT0B29o0oLf0PJKlllaxN40PPnne24faIiIjazsSJE2Na7t6cNDx85Gyc9yaUTABuy05huEptigErEREREXV6Pp8PZrO5QdWpv42vyWSC1/v9AVa1Wh0IS/Py8hpUoWo0mkYD1Fj0zLkDh4/8rMXriZ0MSUljodX2acNtEhERdTw9evw/9u47vo3C/B/45+60t+Rty3b2IjuBDFaBUGbYe7asAqUtu0Ch37LaQssulFnWD2gplL1pQiCBkAXZIdvxjreGte9+f7gSli15SvL6vF8vv2RLpxvBWNJ97nme81FR8XJGt6lS2ZCbc0xGt0lERDTYLM6x4Xc7KuAKZ+5C44gCXFyYnbHtEQEMWImIiIhoCAiHw51mnravPnW5XGg/+cJgMMTC0vz8/LgA1Wq1dpoTky55eYtRtu8ZeL270N9ZcD2jYNzYmzOwHSIiosHNZByPgvzTUV3zFjLVSWLc2JsgipqMbIuIiGiw0kkibhtTiFu2V2RkeyKAcwscGGPQZmR7RFGcwUpEREREcRobG2GxWKBStV2LV1ZWhptuugn79u2DyWTCnXfeiYMPPjil2wwGg0mrT5ubm+HxeOKWN5vNcTNPO85AVavVKd2//nC7t2LV6pOQ/pO7AkaVXomxY29M83aIiIiGhlDIhW9WLkIo1Aggfae/BEGCzTYPs2a+lJIOGEREREOdrCg47budWN3iTeulxiKAXI0KX82bDLMq+VxYonRgwEpEREQ0wlRUVKCmpgYHHHAA9Ho9AGDVqlX49a9/jUAgAEmScMYZZ+CWW25BOBzGxRdfjNmzZ+P0009HfX09TjnlFGzevBlWq7VH21MUBX6/P2l42tzcDJ/PF1teFEVYLJak4anVaoUkDa0PTnv3PoFdux9I2/oFQYLBMBYHHfg2RJFX7RIREUU1NCzD9+svRfoCVhGSZMT8eR9CpytM0zaIiIiGnjJfAEet/gGtETltlxsLAF6fMRaHOsxp2gJRcgxYiYiIiEaQq6++Gp988gn27NmDtWvXYtasWQCABQsW4P/+7/9w9NFHIxAIwGQyoaamBrm5uVCr1WhoaIDFYgEAzJs3DxdeeCGuuuqquKBTURR4PB5s3LixUzVqMBiMLSdJUqeWve0DVLPZDFEUM/sPk2aKomDbD3egquq1NKxbhF5fgLlz3oBWm5vy9RMREQ11lVX/wrZtt6VhzSJEUYPZs1+F1TIjDesnIiIa2la3eHHm9zsRlJW0hKwPTyrGOQVZaVgzUfc4g5WIiIhoBLnooovw+OOPY86cOWhqaoKiKBAEAatXrwbQFn7u2bMHhx9+OCKRtkY+WVlZeO+993D++efD7Xajuroa69evh9frjYWuACAIAoLBIJYtWxYLS0tKSjB9+vS4INVoNI649nmCIGDSxLsgiVqUV7yAtutsU3GdowCfzwST8TaGq0REREkUFZ4NQZCwdeutaHsN7n+zQkGQIIoGzJr1IsNVIiKiJA60GvHGzHE4Z/0u+GQZkRR8DJbQ9mn60cklOCPf0f8VEvURK1iJiIiIRhBZliGKIg4++GBcccUVuPjiiwEAy5Ytwy233IJ9+/ahsbERv/3tb3HVVVchLy8P//73v/H2229j9+7dcDqd8Pl8GDduHG655Rbk5+fHrT/61nKkBai9UVv7Abb9cDvCYS/6foJXBCDD6bwQe/fMwrffrse5556L8ePHp3BPiYiIhpcW13ps3nw9fL69/V6Xw34IJk/+M3S6gv7vGBER0TBX4Q/ium378FWTp9/rGmfQ4m+TSzHTYkjBnhH13fDqvUZEREREPVJUVIR9+/bFft6zZw8WLlyIzZs3w+fzYdWqVXjggbaZoWeeeSbuuusuPP744/j3v/+NGTNmwOPxdApXgbZgleFq1/LyTsCC+Z8hL/d4tL0d7/lbckFoa8lsMIzG7FmvYOKEP+Dooxdj/PjxeOONN1BbW5uenSYiIhoGDPoSmE1TUrAmAVbrbGg0bElIRETUE7kaFeZajOjX2YL/XdA91aRHqV6Tkv0i6g+2CCYiIiIa4gKBQNzM0+it3W7HokWLEj6ntLQUZWVlCIVCUKvV+Prrr1FaWgqbzQYAOOGEE7B06VL4fD7odDqMHTsWAODxePDDDz/g8MMPB/BjRSz1jkaTjalTH8Y4/29RVfUvVFa+hmCoHkA0RBUQbSOsKOH/3a9GTs5P4XReCJt1bizIFkURp59+Op5//nm89tpruOyyy2AymQbmwIiIiAYpl2sDvl9/CUIhVwrWpmDP3sdQV/8ZZs58AVpNdgrWSURENDzVBkI4Z/0ubPP6+zco53+fgd/b34yvmjx4bcYYTDezipUGDgNWIiIiokFMURT4fL5YaBoNUNv/7Pf7Y8uLohibdZqb23kmZzSUmzp1Kt555x2o1WoAgNlsxueff47f/e53CIfD2LNnD2w2G/R6PSoqKvDQQw9h2bJl8Pv9OO200/CrX/2K4WoK6HQFGDPmWowe/RsEAjVwuzfB7dmGSNgNRYlAlHQw6EfDbJkKo2EsRFGdcD0ajQbnnnsunnnmGfzzn//ExRdfHPtvS0RENNI1t6zFd99dDFkOAJBTtFYFXu92rFlzBubOeZ2z0ImIiBKoDgSxeO0OVAdC/QtX24kAaA6Fccq6nXhj1ljMthhTtGai3uEMViIiIqIBpCgKvF5vXHja8TYYDMaWV6lUsNlssRC1463JZOpR6Pn444/j7rvvxs9//nOUlpbi3HPPxU033YQvv/wSWq0WEydOxAMPPIDi4mL4fD5s2LABarUao0aNgsPhSOc/CfVDVVUVXnjhBYwfPx5nnHEG2zUTEdGI5/XuxOo1pyIS8SN14eqPBEGCXj8aB879D1QqnuAlIiKKcocjOGbNdpT5A4ikIYUSARgkEZ/MnYCxBl3qN0DUDQasRERERGkkyzLcbndcaNoxQI1EIrHltVptp9C0/fcGg6FfoVk4HMY555yDrVu3YsyYMcjNzcXChQtx6aWXwuv1QpZlmM3mVBw6DZCtW7fi9ddfxyGHHIKjjjpqoHeHiIhowMhyGKvXnAqP5we01buki4iiovMwaeKdadwGERHR0HLjtn14tboxDZc3/UgSgOkmA96fMx4SLzCmDGPASkRERNQPkUgkYdVp+1a+7d9uGQyGpNWnNpsNOh2vuqT+++abb2C1WjF58mRWsRIR0Yi1d+/fsWv3XzO2vVmz/h8c9gUZ2x4REdFgtazRjbPX78rY9n4/thBXl7BdP2UWA1YiIiKiLoRCoYTVp9Gf3W533PImkymu6rRjFapGoxmgI6GRJPoWv7twNRwOQ6VSZWKXiIiIMioQqMOKrw+BooQztEURBn0p5s//jBc3ERHRiCYrChas3IpyfzCt1avtaQQB6xYegGwNP99S5vC3jYiIiEY0v9+ftHVvc3MzWltbY8sKggCLxQKbzQa73Y7Ro0fHBagWi4VhFQ0KPTmxW1dXh1/96ld47LHHkJOTk4G9IiIiypyq6tehKJk6rQsAMlp9e9DUvJJVrERENKJ92eRGmT+Y0W2GFQX/rG7ANaV5Gd0ujWw8A0hERETDlqIoaG1tTVp92tzcjEAgEFtekqRYYJqXl4cJEybEVZ9aLBaIojiAR0TUf4qiQBAE5OTkYPLkybjooovw0UcfDfRuERERpYwsh1FR8TLQw7qZ115rxnPPNuK00yy4+pfZqKkJ4YLzyxMue8fvc3H44aYka5JQUfEyA1YiIhrR/lFRDwnJp597XngS3peeirtPKh6F7BffAgAowQDcf38Q/qWfAMEgNAcugPk3t0FyZCXdpgzgH5X1uKokl7NYKWPYIpiIiIiGLEVR4PF4klaftrS0IBQKxZZXq9VJW/fabDaYTCa2dKMRoaWlBVarFQBw5ZVXIhQK4bnnnhvgvSIiIkqN5uY1WLvu7B4tu22bH/fcvR8Gg4iZM3W4+pfZiEQUtLTEnxb+4H03Xn+9Ga//uxR6ffIL7gRBwuGHbYQkaft1DERERENRa0TGuC83dHmJk+eFJ+H/8nPY//pk7D5BkiBa7QAA10P3IvDtclhvvhOCyQT3o38GBBGOx17odvsfzhmP2RZjP4+CqGdYwUpERESDlizLcLlcCWegNjc3w+VyIRL58eSXTqeLhaVjxozpFKDq9XoGqDRiBQIBaLVtJ3uffvpplJWV4W9/+xsuvfRSvPDCCwO7c0RERCnkcm8EIADouqbA55Pxpz/W4brrs/HKK82x+yVJgMMRf8ps+QovDj/c1GW4CgCKEoHX+wMslul93HsiIqKha7PH16P+EYIkQXJkd7pf9rjh++htWH/3R2hmHwQAsNx8Jxp+dhqCWzZAMyX566sAYL3bx4CVMoYBKxEREQ2YcDjcqWVv++pTl8uF9s02jEZjLCzNz8+PC0+tVit0Ot0AHg3R4LVlyxaUl5fjmGOOAQDcdNNNGDt2LM4++2xs3boVc+fORSQSwdatWzF16tQB3lsiIqL+cbs3QRBEKEqy5oRtHn2kHvPm6zFnjiEuYO1o+/YAdu0M4te/7nwiuDMBLvcmBqxERDQirXe39uASJyBcuQ91Zx4NQaOFesp0mC77FaS8AoS3bwXCYWjmzI8tqyoZDTE3H6HNXQeskgBscLem5kCIeoABKxEREaVNMBhMWH0a/dnj8cQtbzabY1WnJSUlndr4qtXqAToSoqGtoaEB11xzDZYuXQqn0wkAuPjiizF+/HicfvrpOOuss7BkyRJcf/31+POf/4xjjz12gPeYiIio7zye7d2Gq0uXeLBjZwBPPFHU7fo++siNkhI1Djig+4v5BEFCa+vuHu8rERHRcLKrNQBJAMJdJKzqyVNhvfkuSMWlkBvr4X3xKTT+5hJk/eMNRJoaALUaoskc9xzRngW5qaHLbYcV4AevPxWHQdQjDFiJiIioTxRFgd/vT1p92tzcDJ/PF1teFEVYLBbYbDZkZWVh7NixcQGqxWKBJEkDeEREw9ehhx6KG264ARdeeCGee+45VFdX4/nnn8fzzz+Pn/zkJwCA+fPn49FHH8Wvf/1rjBkzBhMmTBjYnSYiIuojOeLr8vH9+8N4/PEG3H9/PjSarlv+BgIylvzXgwsusPV4+5Futk9ERDRc+SJyt9Wr2nmH/PjD2AlQT56G+nOPR+CLTwFt/zqTtUZ60qCYKDUYsBIREVFCiqKgtbU1aXja3NyMYDAYW16SpFilaUFBASZNmhRXfWo2myGKXZ/AIqL0ufLKK1FdXY3f/e53+Oyzz3DttdfiJz/5CRRFQSQSgV6vx2GHHYaTTz4Zjz32GB577LGB3mUiIqK+Ebp+z7ljewDNzRFceWVl7D5ZBjZu8OPtt1346OPRkCQBAPDll14EAjKO/qk52eo6b17gRYNERDS8hcNhtLa2wuv1xt3WtAIKtIAg9HhdoskMyVmCcGU5tHPmA6EQZI87ropVbmqAaM/qdl18BaZMYsBKREQ0QsmyDI/HkzRAbWlpQTgcji2v0WhiYWlJSQmmT58eNwPVaDRC6MUbaCLKvDvvvBOhUAgejwd2ux3hcBiiKEKlavtY4PP5EIlEYm2EiYiIhiKVytLl47Nm6/HMs/GvdX/5Sx1KitU4+xxbLFwF2toDL1hghM3W81O2KsnYux0mIiIaQIqiIBgMorW1NWFomuj79hfcR6lUKnjHTweyiwD0/PyQ7GtFpKoC0tEnQDVhMqBSIbjuW+gOWwQACO/bC3l/DdQHdD/f3KxixEqZw4CViIhomIpEInC5XEnD05aWFsjyj61T9Hp9LCwdN25cXHhqs9mg0+kYoBINA2q1OlahevDBByMSicDhcKCxsRFGoxErV67E888/P9C7SURE1Gdm8wFwuzdCUcIJHzcYRIwerYm7T6cTYLHE319ZGcLGDX7c+8f8Hm9bUcIwmSb1bceJiIhSIDrSqWNQ2j4k7Xh/JNJ5drlWq4XRaITBYIDBYEBOTk7s5463BoMBGo0G/6xuwOpt5V3un/vvD0K78DBIeYWI1O+H98UnAVGE7shjIZrM0B93CtxPPADRbIVgNML96H1QT5kOzZSuA1aVAEwz6/v1b0fUGwxYiYiIhqhQKBQLShNVobrdbijKj5MvjEZjLCwtLCyMC1CtViu0Wu0AHg0RZdJll12Gt956C2PHjsXll1+OsrIylJWVIT8/H/feey/Gjh070LtIRETUZxbzVFQmCVd74+OP3MjOkTB3bu9O1prNU/u9bSIioihZlpNWlCarMm1/PigqGoRGQ9FoN7KOQWn0e0nqfTXoDLOh22Ui9bVouedWyK4WiFY71NNmwvG3lyDaHAAA8y9vBEQRzX+4EUooCO3chTBfe2u36w0rwPQebJ8oVQQl0f9pRERENOACgUCnmaftA1Wv1xtbVhAEmM3muJmn7atPrVZrrAUoEREAfP/997jsssvw5JNPYu7cuXGPybIcm5ksyzK+//57zJ49eyB2k4iIqNc83h349ttjB2TbkmTC4Yd9B6GbObBERDRyhUKhpEGp1+uFz+eL+9nv93dahyiKCcPRRNWlRqMROp0u9hkvncKygglfbURru45pmbRi3iSMNegGZNs08vBMKxER0QBQFAU+ny9peNrc3Bz3BloUxVhgmpOTE2vhGw1PLRZLn64sJKKRa+bMmbj11ltxwQUXYNWqVbBYfpxX1/6D9/bt2/H+++9jypQp0On4QZWIiAY/k3E8zKYD4PZsBZC5E7wCJBQWnslwlYhoBInOL+3J3NLobSgU6rQetVodF5Q6HA44nc6k1aVarXZQjnFSiQLOLnDgpap6RDJY2icCmGkxMFyljGLASkRElAaKosDr9SZs3Ru9r/0bapVKFQtLi4qKMGXKlLgA1WQyZeRKQyIaWU4//XQUFRXFhasd5ebmQlEU7Nu3DxMmTMjg3hEREfWds/gibN3624xuU0EERYXnZXSbRESUWtEL4pNVlyaaYZpofqlOp4sLRPPy8hIGpdFbtVo9AEebHhcXZeH5yvqMblMGcJkzJ6PbJGLASkRE1AeyLMPtdicNUFtaWuLeYGu12lhYOmrUqLjw1GazwWAwDMorD4lo+Js/f37cz4qiIBKJxNqK2+12mM1mlJWVMWAlIqIhIy/3ROzceR9CoWZkoopVlgUYDHNgMIxO+7aIiKjnIpFIl3NLE7Xn7ThVURCETi14HQ5HwqA0+jWSu4xNMupxqN2Er5s9GaliFQFka1Q4Icea/o0RtcOAlYiIKIFIJJIwNG3fyrf9G26DwRALSydMmBAXntpsNrbVJKIhY82aNVi/fj0uvvhiqNVqCIKA0tJSlJWVDfSuERER9Zgk6TB58p+xYcMVGdmeKKoxa+ZfE1402X62+Y4dO/DPf/4Ter0eN954Y0b2jYhoOAmFQklb7yZqzZtofqkkSXGhqMViQX5+ftJ2vHq9nhfF99JfJhbj8FXbEFHSn7DKAB6ZVAItO79RhjFgJSKiESkUCnVq2ds+QHW73XHLm0ymWFjqdDrjAlSr1QqNRjNAR0JElFpFRUX47LPP8Pbbb+OMM86IBaybN29GIBCAVqsd6F0kIiLqkZzso5CfdzJqat8H0Ll9YypNnHgH9HpnwsdaW1uxfft23H///bBarXjrrbcwa9Ys/OxnP0N2dnZa94uIaDBTFAWBQCBpO16fz9fp/kTzSzUaTVwgmpWVheLi4k7VpdFbjUbDwDTNRum1uGNsIW7fUZnW7UgAzsp34Iis5GNviNKFASsREQ1Lfr8/aXja3NyM1tbW2LKCIMBiscBms8HhcGDMmDFx1acWiyXWKpOIaLgrLCzEaaedhn/9619YsmQJjjrqKIwaNQqKoqC8vBzjxo0b6F0kIiLqsYkT74TbsxWtrbugKOkIWQXk5S1GUeG5CU/Wb926Fffffz+cTifOPPNMOBwOVFRU4LrrrkN2dja+//57fPPNNzjxxBNRXFychv0jIsocWZY7zS9N9n30VpY7t3HX6XRxoWhX1aVGo5HnbAapS4qysarZi/fqmpGOOlYJwCSTDnePL0rD2om6x788RDTkhcNhlJeXo6qqClVVVaivr0c4HI7NRygsLERBQQGKi4vhcDgGencpBRRFQWtra6cAtf3PgUAgtrwkSbHANC8vL9bCN1p9arFYYi27iIhGmmAwiNraWjidztiJ4UmTJmHRokX4/PPPkZWVhRkzZsBoNKKsrCwuYFUUGW73JrhcG+Byb4LHsw2RsAcQBKhUZphMk2A2T4XVMgMm0xReJU5ERBmnUpkxe9bLWLvufLS27kFqK1kF5OQcgymT70/4Gtfa2oqHH34Y7777LhoaGgAA55xzDqZNm4ZFixbhiSeewPPPP4+5c+fimWeewYknnoi77rqrx1v3enejxbUObvcmuN1bEAo1Q1EikCQDTMbxMJunwmyZBqtlJkRRnbKjJqKRIxKJdNuOt+PPHUXPz7UPRLOzsxMGpdH7eI5meBAFAX+bUoLgZhmf1LtSGrJKAMYbdfjXjHEwqUbuvFsaWILScWIzEdEQ0dTUhLVr12LNmjXw+/2xD7Qd/6yJohi7Gq60tBTz5s3DxIkTR/Sw+cFOURR4PJ6k1actLS1xLWHUanWnlr3tA1STycST+kRESfzrX//Ctm3bkJOTg4MOOgjTp0+HRqOBoih47733sH79elx44YVYvXo13G43LrnkEoRCLaiufhPlFS/C768AIEAQJChKOG7dgqD6X7WQAoNhLIqdFyM//2SoVKYBOVYiIhq5QqFmbNr0GzQ2LU/B2kQAMoqLL8H4cbdAEJJ/tgwEAvj1r3+N5cuX44ADDoDP58Ojjz6K0aNH46677oJKpcJtt90Gn8+HU089Fbfccgt+8pOfJF2fLAewf//HKK94ES7XegDR19twhyUlAAoAGWp1FpzOC1BUeDa02rz+HjwRDWHBYLBHc0uj37e/eD1KpVJ1CkeTBaVGoxE6nY7nZEa4sKzg/3ZW4rnK+v+9gvadgLZXtyMdZvx9SimsatYQ0sBhwEpEQ04oFMKSJUvwzTffQBCEToFqV6LL22w2nHrqqSgtLU3jnlIysizD5XIlnYHqcrkQifx4ZblOp0santpsNuj1er5ZJyLqI0VRsHfvXqxatQo//PADNBoNZs2ahQMPPBBWqxWvvPIKampqcOCBB2L58q9w0UWjsHvPfZDl6MmWnr4Ot/2dliQjJk74A/LzT+HfbiIiyihFUVBd/Qa2b78TETmA3p/ibXvd0ukKMWXyX2G3H9Tl0rIsx6qwvvjiC5xxxhlQq9VYuXIlysrK8Nlnn+GNN97ACy+8gHnz5iErKwv/+Mc/cPLJJ0NRlE6vkw0NX2LL1t8iGNwP9PoUtQhAwOhRv8SoUVdBFDW9eC4RDUaKosDv93dZXdrx+3C448UYbfNLk4WjicJTtVrN9/HUJ8ub3Pj11n2oDrQVTfQ2mJIA6CQRfxzvxFn5dv4e0oBjwEpEQ0p5eTn+85//oLm5uVfBakfRoHX+/Pk46qijoFazXVIqhcPhhFWn0VuXyxX3389oNHYKUNsHqVqtdgCPhoho5GhubsaaNWuwbt06+Hw+jB8/HjNnzsR///tfCEITCgs/gtW2v59babvmOCvrCEye/GdoNdmp2HUiIqIeCwRqUVHxMioqX0U43JKkAvRH0cf1+lIUOy9CYeFZkCRDj7YVDVlvuOEG7N+/H6eddhqWLFmC999/Hw8//DD27duHW265BSeccAKMRiOee+65Tq0xw2Evtu+4B9XVr6P3wWqno4HROA4HHPAwzKZJ/VgPEaVadH5px6C0q3a8ieaX6vX6uHA0UXVp+8c5v5QyyRuO4JXqBjxXUY8yfxAqAQh3cYo3+rhdJeFnRdn4WVE28rQ8j0uDAwNWIhoytm3bhtdffx2KovQrXG1PEASUlJTgvPPOY4jXC8FgMGH1afRnj8cTt7zZbI6rOu1YhcqAm4hocAmFQti0aRNWrVqFmpoa5OVFMGr0m5CkAEQxVR8fJOi0eZg9+1Xo9cUpWicREVHPyXIAdXWfoal5FVwt38Pj/SEuaJUkA8zmabBYpiMr63DYbfP7XC3z0ksvwW63Y/HixTjssMNw1FFH4f/+7/8AAO+99x6WLVuG+++/v1O4Ggo14bvvLobbsxX9C1bbkyCKasyc8Rzs9vkpWicRdRQOh5NWlCa6z+fzdVqHKIq9aser1+s5v5SGBEVRsLzJgyWNLnznasVGjw/eyI+vc2pBwGSTDrMtRiy0mXBstgUa/m7TIMOAlYiGhB07duDVV19NWbDaXjRkveCCCxj04ccWM4la90Zv27/pF0URFoslafWpxWLhvFsioiFKURTs2vU19uy9EoLggyCk9nVYECRoNNmYO+dN6HQFKV03ERFRb8lyGJFIKxQlCFHUQpJMKW0/GK1mveeee6AoCu644w4AwO23347y8nK8+OKLsWUVRUE47Ma6786Dx7MdQCTJWvtKhCCoMHvWy7DZ5qZ43UTDj6IosfmlPaku9Xq9CAaDndajUqkShqPJqky1Wi3boNKIICsKvBEZflmGRhBglCSoRP7u0+DGgJWIBr3GxkY88cQTCedEpIogCJg1axZOOumktG1jsFAUBV6vN2n1aXNzc9yHAJVKFRecdqw+NZvNvDqSiGiYikT8WPntsfD7q5D6E7ttBEgwmibiwLlvQRTZnoyIiIa/jRs34pprrkFWVhbmzp2LV155BbfccgvOP//82GcrWZaxZu2lcLtXIF2vwYAISTJiwfzPoNXmpGkbRINT9OLynswtjd5GIp3/X9Rqtd0Gpe2/12g4/5iIaLhgwEpEg5osy3j++edRWVmZcK5Eql1wwQUYN25cl8uUlZVhxYoVOPHEE2GxWNK+T70lyzI8Hk/S6tOWlpa4sFqj0SQNT202G4xGI6+WJCIaoXbs+CP2lf8DQPo/MowdcwNGjbo67dshIiIaLB5//HE0NDTgkEMOweGHHx7r/CPLMvbufQN79t6a9n0QICEr+yeYPu0pfu6jIU2W5aTVpcmqTBOdFu+qHW+i8JQdu4iIRi4GrEQ0qK1atQoffvhhRrYlCAKMRiN+9atfJZzHGgwG8fnnn2P16tUoKSnB+eefPyBXHkYiEbhcrqThaUtLS1wYrdfrE7bujX6v0+n4QZqIiDppafkOa9aeiUyEq0Bbu+CDDvoAJuP4jGyPiIhosAoGG7Hsy0MhCH5k6qPaAQc8jPy8xZnZGFEPhMPhHgelXq8Xfr+/0zpEUexxUGowGDi/lIiIeoU9uIho0IpEIvjyyy8ztj1FUeDxeLBhwwYceOCBcY/t2bMH7777LrxeL4499lgcdNBBaQslQ6FQp5a97QNUt9sdd5WlyWSKhaWFhYWdZqEmCouJiIi6s3fvEwBEpK8tYWf7yp7FlCn3ZWx7REREg40sy/h+/aMZDVcBAXv2PIa83BN58S2lRXR+abLWu4la8yaaX6pWq+NCUYfDAafTmTQ05fxSIiJKJwasRDRobd++HR6PJ+Pb/fbbbzF37lwIgoBAIIDPP/8ca9asQWlpKS688EI4HI5+rT8QCMSFph1noHq93tiygiDAbDbDZrPBbrdj1KhRnapQVSr+KSciotTy+SpR37AUmapeBQBFiaCm9h2MH38r1GpbxrZLREQ0uMgIBD7OYLgKAApaW3ehuWUN7LYDu1+cRjxFUeDz+ZK24/X5fJ3uTzS/VKfTxQWieXl5CYPS6K1arR6AoyUiIkqMZ+WJaNBavXo1BEFIOBMjkeXLl+O///0v5s2bh2OPPRYA8N5772HPnj1wu93QaDQoLi7GokWLkJ2dnXQ99fX1KC8vRzgcxrvvvovW1lYcd9xxOPDAA7u98jH6ISNZ9Wlzc3Nc2xpRFGOBaU5ODsaPHx9XfWqxWDjPg4iIMq6q+nUAAnoasL72WjOee7YRp51mwdW/bHuNvf76KmxYH9+q7cQTzbj2upyk61GUMKpr3kJJ8c/7uutERERDWkPjMgSDdT1ePtFrcGNjGE8/1Yi1a33w+WQ4nWqcd74Nhx1mSroeQZBQWfkKA9Y+CIVCWLp0KbKysjBr1iyIooj7778fy5cvR3V1NRYtWoQbb7wRWVlZA72rSUUikYRVpMkqTn0+X6dzNYIgQK/Xx4WiDoejy3mmPN9BRERDGQNWIhqUZFnGvn37ehyuVlZWYu3atcjLy4u7v7CwENOnT4fVaoXP58MXX3yBl19+Gb/5zW+SztUQBAGffPIJqqqqMGrUKFx88cWw2+0A2gJUr9ebNDxtbm5GKBSKrUulUsWqTYuKijBlypS46lOTycT5HkRENOg0NX0DQO52OQDYts2PD953YcyYznPJjz/BjJ/9zB77Wavt7jVPQHPTtwxYiYhoxGpu+haCoIKihLtdNtlr8H1/roPHI+Pue/JgsUhYssSDe+7ej8efUGP8+MQjZBQl8r/Xf+opRVEgCAI+/fRTLF68GJdeeimeeeYZvPTSS9i2bRsuv/xyTJ8+HZdffjmefvpp3HrrrRnbt1AolLS6NNEM00TzSyVJigtELRYL8vPzk7bj1ev1bMdLREQjCgNWIhqU6uvrEQ53/4ESAILBIP7zn/9g8eLFnWa2zpkzJ/a9zWbDkUceiSeffBLNzc1JW/0qioKqqirMmDEDdrsdX331VVyQ2r6tjVarjYWlo0aNigtPbTYbDAYDP2AQEdGQoigy3O7NPVrW55Pxpz/W4brrs/HKK82dHtdpBTgcvfnIIaPFtb4XyxMREQ0vLa71PQpXu3oN3rzZj99cm41Jk3QAgAsusOPNN1qwY3sgacAKAMFgPYLBemg0yTs+0Y8EQUBTUxOWLVuGQw89FLm5uQCAZcuWIRwOY/HixQDazkX4fL4+b0dRFAQCgR4FpdHb9hd+R2k0mrhwNDq/tGNQGv1eo9HwfAYREVEXGLAS0aBUU1PT42U//PBDjB8/HmPGjOkUsLYXDAbx3XffxQLQriiKgvXr18NgMMTC0gkTJnQKUHU6XY/3k4iIaCjw+cogy52rGBJ59JF6zJuvx5w5hoQB63//68Hnn3vgcEiYv8CICy6wQafruoo1GNyPYLARGk3/Zp4TERENNYqi9Pgip65egw84QIcvlnoxb54BJpOIZV94EQopmDFT3+163e7NyMo6vC+7P6JEq1cfeughjBkzBhMmTMCSJUvQ0tKCm2++GQ888ABmz56NhoYGTJs2DZdeemnC9VRUVMDlcnXbmleWO3cW0el0ceFoV9WlnF9KRESUegxYiWhQ8nq9PZq/umnTJlRXV+Pyyy9Puszq1avx2WefIRQKISsrCxdeeGGP5nxkZWVh+vTpmDZtWqxFMBER0XAXDDb0aLmlSzzYsTOAJ54oSvj4kUeakJenQlaWCnt2B/DMM42oKA/iD3fmd7vuUKiJASsREY04ihKCLHdf6djda/Adv8/F3Xfvx2mnlkGSAK1OwB/uzENRUfcBWzDY2Ov9HokEQcDatWvhdrtx4YUX4uuvvwYAGAwGFBQUQKfT4Wc/+xmOPfZYPPnkk7jhhhvw+uuvdxoR9OGHH6K6uhqCIHQKRLOysjoFpe3b8XJ+KRER0cBiwEpEg1KiqzM7amlpwccff4wLL7wQKlXyP2fTpk3DmDFj4PF48PXXX+ONN97AJZdc0uVzACAcDuOLL77A0qVLYTKZkJeXh4KCgtiVnx2/VCpVwvtFUWRbHSIiGjJ60pZw//4wHn+8Afffnw+NJnFF6oknWmLfjxmjgSNLhZturEZVVQiFhV2f4JWVzm3tiIiIhrtUvQY//3wTvB4Z9/+lAFariBUrWnH3Xfvx0MOFCWemx+8DX4ODwWBcFWkwGMQBBxzQablPP/0UtbW1kGUZy5cvx3fffYcnnngC9fX12LNnDx599FEAwNlnn4377rsP33zzDQ4++OC4dZx99tnQaDTQ6XQ8b0BERDTEMGAlokGpJ1diVldXw+v14qmnnordpygKysrKsGrVKtx+++0QRRE6nQ46nQ5ZWVlwOp247777sHXrVkybNi3pugVBQHZ2NiwWC9xuN1pbW7Fr1y7s2rWrR5W1HdfV00A2WUjbk8clSeIHMiIi6jdR7PrEKwDs2B5Ac3MEV15ZGbtPloGNG/x4+20XPvp4NCQp/jVp0qS2mW+Vld0HrJs3bYPNBlitVlitVuj1er7GERHRsBOdrdnS0vK/r6Zun9Pda/ALLxbjnbddePY5J0aNantNHztWi40b/Xj3nRZce11Ol+sXevA+YCiJ/ht3nFHa1QzTcDg+6JYkqVPAGgqFUFdXhzVr1uDoo4+GJEloaGhATU0NbDYb1q5dG7fs9u3bMX78+E771934IiIiIhq8GLAS0aBktVq7DTFHjx6Nq666Ku6+d955B9nZ2Tj44IM7td4B2j5cKYqCSCTS5bodDgcuuOCCuPu8Xi82b96MjRs3oqKiAiqVCsceeywmTJiAUCgU9xUOhzvd19UyPp8v6XN6Us0ble4QN/o4T3ITEQ1fWm1Bt8vMmq3HM8864+77y1/qUFKsxtnn2DqFqwCwa1cQAJDl6PoiKkUBliz5DqHQ+th9KpUKVqsVFosl6a1Wq+3J4REREWVMKBSCy+VCS0tL7Lb99y6XC8FgMLa8IAiYN18HlSr5LPTuXoP9fuV/64p/nigCcg+uE9ZpC3t+gANAlmX4fL6EQWmy7xN9ptbr9XEtdwsKChLOLY1+35FarcaDDz6IBx98EADg8Xhw1FFH4YorroDT6cTu3btx+OGHQ61Ww+Vy4YYbbkBubm7a/32IiIgocxiwEtGgVFDQ/cldrVbb6QOKWq2GXq9Hbm4umpqasGnTJowdOxZGoxEulwvLly+HWq1OeOVolCiKcDqdne43Go046KCDcNBBB6GpqQlbtmxBXl4ezGZz7w+wFyKRSMLwtbchbigUgtfrTbpsd6Fze+1D2K4C2WSP9TTkTRSSExFRemm1+VCprAiHW5IuYzCIGD06vsJFpxNgsbTdX1UVwpL/enDQPAMsFhG7dwfx9ycaMH26DmPGdh2EGgyluPXWP8Dr9SY8IV1fX49du3bB7XZ32L4uaQBrtVphNpu7HQ9ARETUU7Isw+12JwxNo7etra1xzzEajbHXpzFjxsReo6KvVyaTCRs27EVD45cAEqeh3b0Gh8MKiopUePihevziSgcsFgkrlnuxbq0P99zb3Rx0AWbzlH78q/ReOBxOWEWarMrU5+s8o1YUxU6BaHZ2dsLZpUajEXq9PmWfNWVZhiiKCIfDOOGEExAKhaBWq3Hffffhu+++g8PhQG5uLvLzu59BT0REREMLzzAQ0aBktVqh0+ng9ye/crc7KpUK+/btw7fffgufzweTyYTS0lJccsklMBqNSZ8ny3K3Aa/dbu80OyVdJEmCJElpr8yRZblPQW7Hx8PhMHw+H1wuV9Lle0qSpD5X3fbmOT1pSU1ENFIIggCLZToaG5cj2cnd7qhUAtat8+HNN1vg9yvIzZVw6KFGnH+BvZttS7BaZkEQBJhMJphMJhQVFSVcNhKJwO12J6wIqqysxJYtWzqdhI2e2I6ezG4fwFosFphMJl7cQ0REUBQFXq+302tM+589Hk9c1yWtVht7PSkqKsLkyZM7veb05EIfi2U6GpuWQ1F6fgFseyqVgHv/WIBnn23A7b+rhd8vo7BQjZt/m4N58zpXYran1zmhUpn6tF2g7d8temFvT9vxtq/g/fEYVHGhqM1mQ2FhYcLA1GAwDOj80uj7BpvNht///vex+202G4444ogB2SciIiLKDEHpzSBBIqIM+s9//oNNmzb1qkVuqlxzzTXIzs7O+HZHAkVREoayvQ1xu6veDYVCPd4nURR7HeJ2t3yiZTgnl4iGivLyF7F9x93oa8DaHwdMeRD5+SenZF2hUChhFWz7n9u/XoiiCLPZ3GU7Ys6DJSIa+vx+f5evDy6XK67DjyRJnapNO96m6oLYlpbvsGbtGSlZV28IggRn0YWYMOGO2H2KosDv9ydsvZusHW+iC2q1Wm3S1ruJQlONZnjNgSUiIqLhiQErEQ1a5eXleO655zK6TUEQUFpaip/97GcZ3S6lXnTWbl9D3J4+JxgMdjsvuL10h7ick0tEqRAOu/HV8oMgy52rStJJpbLi0EO+gShmZp5q9MRxVwGsy+WKu9grOg82WRWs1WrliWEiogEUnXuabOZpS0tLp7mn0Ytrkv1tNxgMGXt/rSgKvl11Arze7cj0hU4tzTfC7TbEhaaJPutEg9HugtLoF1v0ExER0XDEdzhENGg5nU7k5uairq6uVwFWfyiKgoMOOigj26L0EgQBKpUKKpUKer0+rduKBrl9mYvb8T6Px5P0sb7Oye1PiNvdjF220iQanlQqM/LzT0N19b/73KKw9yQUFZ2bsXAVaHut0Ov10Ov1yMvLS7hMtE1kopP0dXV1SefBdhXAWiwWtqcnIuqD9nNPk10ck2juafTv7+jRozvN6B5s7eEFQUBx8cXYtu22jG1TUQT4fE54PEaYTEbk5uYmDU1TOb+UiIiIaChjBSsRDWo7d+7E//t//y8j2xJFEfn5+bjsssv4gZEGpWRzcntaedvT+/syJ7c/M3F7EvIyiCDKPJ+vEiu//Slkue/z0HtOgEplwYL5n0GjycrA9lIrOg82WaWUy+XqNA/WZDIlbTMZPeHPbgRElE6hUAi1tbWxi0EGmqIoaG1t7fJvqdvt7jT3NNHf0Pb3DZXqSUVREAwG0draCre7CXv2/gzhcDWATIzMETB3zhuwWmdmYFtEREREwwMDViIa9N555x18//33aa9iFUURV111FXJyctK6HaLBLtGc3L60T+7JfT0limKPQtne3p8oyGWgkR47d+7EBRdcgOOOOw633XYb1Go1/vrXv2LDhg0QBAHHHnsszjzzzCFzEnSkqKh8FT/8cEf3C6bA1Kl/Q17ucRnZ1kAIBoOdwoKOVVfJ5sEmm/mXyXmw27ZtwyeffIJzzz0Xubm5GdkmEaVGdXU1XnrpJZx88smYNGkSdu7ciZ///OdobW2FLMtYsGAB7rvvPpjN5rTuR09asieae9rVxSipmnuaDoqiwOfzJZ1bmuj+9sdvMtVjxswPkf4/8wJKSy7HuHG/TfeGiIiIiIYVnsEiokHvmGOOibXfS2fIevTRRzNcJUJbW7Jo6JhOHefk9jbEbb9MMBiE1+tN+pye/u1of+y9rbrtTbvlkTgn98EHH8TevXsBtM0ivuuuu1BVVYWjjjoKoijiqaeegsPhwDHHHDOwO0pxigrPRd3+T9DY9A2AdLUKFpGbe/ywDlcBQKPRIDs7G9nZ2Qkfj86DTRbAlpeXd5oHq1aruwweLBZLSubBNjQ04PLLL8eqVaswdepUHHXUUXjnnXdw9913Q6PRwG634/bbb8eCBQv6vS0iSr0HH3wQDzzwAHJzczFp0iTccsstuOiii3D55ZcDAGw2G8444wwceeSRfd5GOBxOWnUavQ0EArHl2889tVgsKCgo6HRBSSbnnvZEJBLpMhxNFKB2fA8abU3ffkap3W7v1IY3eltbOwpl+55I2zEJggS9fhRGj742bdsgIiIiGq4YsBLRoKfT6XDxxRfj2WefRSAQiDuxmCrz5s3D/PnzU75eIkouU3NyFUWBLMv9DnGjX36/P+myvfn71JcZuH2ZmTuQJyZlWYYoivjFL36BI488Es3NzdDpdACA//73vzjmmGNw8cUXAwDuvffeWABLg4cgCJg27W9Yu+48eDw/IPUhqwibbS6mTL4/xesdetrPg83Pz0+4jKIo8Hg8CcOLuro67Ny5Ex6PJ+450XmwyWbCdjcPtqysDA899BDmzp2L/Px8FBUVYevWrbj11lvx/PPPY8yYMfj3v/+Nu+++G++++y6r0IeosKxgR6sfVYEQgrIMtSgiR6PCJKMOWo7OGNLWr18Pl8uFRYsWxQLOffv2oaGhAR6PB3V1dbH/v5OJzj3tqvq049xTg8EQ+1szevToTn97zGbzgI9lCYVCPQpKo9/7/Z1b5ouiGBeKms1m5OXlxQWo7R/X6XS9Om6T6ToEApWoqX0XQGovNhYECRpNNmbNfBGSNHgrgYmIiIgGK376JaIhISsrC5deeileeOEFeL3elFayLly4EEcfffSgujqaiFJHEARIkgRJkmLhXrr0NchNNAfX6/UmXb59+7juJJqTm+oQV61WJzxZKIoi/v3vf0OWZSxevBgfffQRBEFAKBTCY489hptuugkrVqxAIBDAT37yEyxevDiV/zkoRVQqM2bPegXfr/85XK71SOUJXod9IaZPf5IndnsoWvHVVRvPSCSSsO1mtAq2paWlU0hgMplw0UUXderkUV1djSeffBLFxcU4+OCDcccdd8BoNKKurg4OhwMmkwk5OTkoLi7G5s2bOS97iKnyB/FKdQM+b3Bhq8ePYIL315IATDDocJjDjIsKszDWkN7XUUodRVEgCAL+8Ic/4He/+x1efvll7Nu3D4FAAG+++SauvvpqPProo3C73TjrrLMSdi4JBAJ44oknOnUS0mg0sbC0oKAAkyZNiquit1gsae+E0pGiKAgEAj0KSqO3icZVqNXquEDU4XDA6XQmrC41Go3QaDRp/RwpCCKmTPkLBFGL6urXU7hmETpdEWbPegU6XUEK10tEREQ0cjBgJaIhIzs7G1dddRU++OADbNmypV/rEgQBWq0WixcvxgEHHJCiPSSikU4URWi12rTPA5NlOWEo29sQN1qR63a7kz6npw499FAcfvjhcQFLU1MTnnzySTz33HMwGAwIBoPIy8uDWq3GunXrMGrUKBx00EGora3F6tWr41oHRkXb8bUPcnlBTOap1RbMmf0q9ux5DHvLngIgoO/VrG2zjseMvg4lJZdBFPmRJJUkSYLdbofdbk+6TPt5sNEANlFo+9RTTyErKws33HADPvjgAxQUFMBut6O4uBiLFi3C4YcfDo1Gg2nTpuG5556DIAixUIcGr60eH+7fU4NP6lsAAF31XogowFavH9u9fjxVXoeDbSbcMCofC+2mzOws9ZkgCHj77bcxbdo0zJ07F8uXL0d1dTW0Wi127tyJkpISPPXUUygsLMRVV12Fe++9Fw8//DBsNltsHVqtFjNnzuw0DzrdF6wBP84v7RiKJpth2nF+aZROp4sLRdtXlyaqMs10MNwTgiBh8qQ/wmadg+3b74SsBKAofX0NFgHIKCg4AxPG3waVKr1zd4mIiIiGM57NIKIhxWg04qyzzsKWLVvw0Ucfwe12x07m9UR02QMOOADHHXccjEZjmveYiCj1RFGERqNJyWzFriiKEhfMdhXi5ubmdgpVvvnmG+zYsQNHHnkkjEYjysvLsWTJErjdbtx999346quvMGHCBABt87Y/+eQTXHHFFXHVsA0NDfj73/8e+7n9nNx0VOJGvyRJYkjUgShqMXbsjcjJ+Sm2bvsdPJ4tEASpxyd5o8tarTMxaeI9MJkmpHmPKZnu5sECbS1EP/jgA9TX12Pv3r34/vvvEQqFsHv3brz//vuor6/H8uXLYTQacf3116OyshIA4v6/URQFDQ0NAJCyebDUdyFZwWP7avHA3hoAXQerHUX/L1/Z7MFp3+/EzwuzcPvYQhhVrFoeSOFwGC6XC6FQCHl5eXGPKYqCDz74AAaDAVu3bsVXX32FtWvXQqfTYc2aNRg7diwKCwsBAMceeyxeeOEF1NXVxQWsAHDEEUekZF+jF0x1VVHa/nufz5dwfmnHQNThcCStLtXr9cOmsl4QBBQWngGH42D8sP3/UF//XwASen6xU9uyOl0hJk28G1lZh6VvZ4mIiIhGCAasRDQkTZkyBZMmTcKOHTvw7bffYs+ePbEP4B3bVEZnIhoMBsydOxdz5syB1WrN+D4TEQ017cPMvjj++OOxc+dOuN1uiKKI008/HUcccQTOOOMM/OY3v4lrU+r3+xMGmhaLBeeee263IW/7+30+X8LHgsFgr1rM9ySU7Sqo7S7EjS4z1IJci2U6DjrwXbhc61FR+f9QW/s+FKWtzaIgxH+8UJS2KmhR1CI//1Q4i86H2Twl4/tMvVdSUoL3338fW7duRUNDA7777js0NTVhyZIlePjhh/G3v/0NkyZNAgBMmjQJa9aswemnnw6T6cfKRkEQsHTp0ljnEb1eH9dGtP2t1WqF2WweNmHIYLM/EMJ5G3Zjs8fXrybf0SjnxaoGfNrgwj9njMV4I9sGp4Msy7GZy4nmLrtcLni9XgBAQUEBrrjiirjne71eCIKAZcuWYdeuXVAUBWq1GrNnz4bJZIoFqlarFd9//z10Oh3Gjx/f4/0LBoNJg9JEVaaJulRIkhQXilosFuTn5yetLtXr9UPuNTPVdLoCzJj+NFpb96Ky6jVUVf0L4bAbQKLX4Aja2vqLyM7+CZzOi+CwL4QgcK4yERERUSoISioHGRIRDZBgMIiamhpUVVWhqakJ4XAYoihCp9MhPz8/1tJupH8gJyIaSAsXLsSvf/1rnHPOOXjiiSfw5ptvwul0QlEU1NfX4+mnn4bT6UzrPkQikV63U+7usUT39WZObvsgtreBbU9D3GRzclNBlkPwenfA5d6IVu8uRCKtgCBAEvUwmibAYp4Gg2EsWwEPcaeccgoWLVqEa665BieccAIOOeQQ3HrrrQCAE088EXPmzMHNN9/cqTuIy+VCY2NjwpmwyebBtm9F2j6AtVgsMJlMfD/XSzWBEBav24GqQBCRFH76lwTAJEl4e9Y4TDbpU7fiEUBRFLS2tib9/6KlpSXp3NNE/1/YbDY4HI4ut7lv3z6cccYZ+Pe//42CggI88MADeOmll6DX61FaWoq7774bU6dO7fS8jRs3YufOnZ0C1ERjBDQaTcIq0kTVpQaDIe3zS0cCRZHh85XB5doIj2cbwhEPFCUCSdTBYBgNs3kqTKZJkCReCEFERESUagxYiYiIiCgjqqurYTQaYbFYEAqF8NVXX6GhoQGtra1YuHBhrypnBrtEc3JTMTO3P3NyJUnqU/vk3oS40fbKNHxEZ6q+/PLLKC0txcEHH4yysjJcdtllaG5uhkqlwqhRo/DnP/8ZY8aM6fX6g8FgXFVeoqCp/e+5KIpJq2CjtzqdjqHN/7jDERy7Zjv2+gMpDVejJABWtYRP506EU8cW0FGBQKDL32uXyxX3ey1JUtzvcccA1Wq1QqvV9un3OhKJQJIkNDY24sMPP8RPf/pT5ObmIhKJQBCELi++iUQiWLVqFbZu3ZqworTjfSoVL6QhIiIiopGDASsRERER0RDVcU5uOkLc6FdPiaKY9hCXc3IHB7fbjcrKStjt9k7zH1NFURT4fL6kLVKjt+0/1qrV6qRtiKPf97X1+WAgyzIEQejR7/8N2/bhterGXs1b7S1JAOZZTXhz5tge7ZMsy2mrqM+E6NzTrn4n27fDFQQhVpmd7HfSaDR2+W8XDoe7nFva2tqK448/Pq5FNxERERERpRcDViIiIiIi6pKiKIhEIr0KZPsS4oZCoX7Nye1vS+Vkz2GQO7hFZ1V2VQUbnVUZpdfru6wWHKzzYBVFwSOPPILc3FyccMIJsFqtSZf9otGFc9bvzti+3T/BiYuKspM+7vP58Mknn2DTpk247rrrOrWTHgzazz1N9vuU7Hcp2e9Tx98lRVEQCoXiAtJEoWn77xPNL1WpVHHVo8cccwxycnLS/m9ERERERERtGLASEREREdGg0T7I7cu83J4+p69zcvtbjZvscZVKNaSr+ga7cDgMt9sdF5h1vO04D9ZsNidtQ2y1WrutOkwHv9+PrVu3YunSpQgEAjj66KMxZ86cTvshKwrmrdyKSn8wrdWr7elFERsOPgBmVedgeuvWrXj//ffh9/shyzIuvPDCPrWU7o/21dDJfgc6VkNrNJoufwcsFgtUKhX8fn/CoNTr9cLn83W6P9n80kStdxO15DUajVCr1bz4g4iIiIhoADFgJSIiIiKiEUeW5T6HuN09r/1jfZmTm64QN/rFIDexQCDQZRVsormZZrO5y+rFVM+D/eabb/Dpp59i6tSpAIBNmzZh1KhRWLx4MRwOR2y5/za4cP6GzFWvAoAA4N7xRbjE+WMVpcfjwQcffIBt27bFWuUef/zxmDhxYsrDwd7+92s/z7d9cGoymaDVaiFJEsLhMHw+X9Lq0miAKsudY2y9Xt+joDT6GOeXEhERERENLQxYiYiIiIiI0qSrObmpnpfbU6IoJg1lc3Jy4HA4YDab40IgrVbbaW5p+4+S7cOyZPcPdamugOzLPNhIJIK1a9di2bJlCAaDmDRpEsrLy+H1enHEEUdg/vz5EEUR56/fhS8a3UhWp+154Ul4X3oq7j6peBSyX3wLAND6/pvw//cjhHdsg9LqRc67X0I0mbvcNwHAaL0WK+ZNAgBs2LABH374Yex3c+HChTjssMOg0Wh6fLxR0bmnXQWoHdvoRiuQzWYz9Ho9dDodVCpVrF1v+7mm7UNTn8/XafuiKHYKSZN9bzQaodfreSEDEREREdEwx4CViIiIiIhoiEs0JzfVIa6iKNDr9QkrNe12O0wmEyKRCMrLy/HJJ5+gubm5x+2R+1KJG11mMM3J7c8Mz2QtaBPNg/X7/VixYgVWrlwJtVqN3NxclJWVoaioCEeecCIO3laDrj7oe154Ev4vP4f9r0/G7hMkCaLVDgDwvvEKEGwLLD3PPtajgDXq3clF2PLxBygrKwMAlJSUYPHixcjOTjyfNdG/Wcfbjv9mWq0WRqMROp0OGo0m9jsQvaAhGAzGgtNgMNhpmyqVqkdBafS+VFciExERERHR0MeAlYiIiIiIiHpEUZRYe+V0VeJGvxK1XU2mJ6Fsosd6GuJGv09FyBatxuwqUGxfjRltrZuoDbEkSdiwYQM2b94Ms7ktAN0u6fD29IVd7oPnhScRWLEUWc/8q8vlgt+vQdP1l/ciYFVw5I71mFhdBr1ej+OPPx6jR49OWn3a3NwMt9sdV/UrSRK0Wm1ctWn0dy4QCCScn6zVantcXWowGPpURUtERERERNQeh3wQERERERFRjwiCAEmSIEkSdDpdWrfVMcjtS6vl6H1erzfpc3ozJzdaMdubGbhdLZ+Tk4PCwsJOy4RCoaRVsDU1NWhpaYkLGkVRhM/nQzgcRn1xPgRFgdJNGByu3Ie6M4+GoNFCPWU6TJf9ClJeQZ//ewGAKCvYb7BgttEIURTx1ltvdQrKO1abdhQ9Lo1G06MZpnq9nvNLiYiIiIgo4/gphIiIiIiIiAYdURSh1Wqh1WrTuh1FUfoV4ra/3+fzdfmcnko0Jzf6lZWVhdzcXIiiGGsNHd2Gy+VCo87QbcCqnjwV1pvvglRcCrmxHt4Xn0Ljby5B1j/egGgw9vnfUhZFNBotcS19BUGAXq+HwWCIm+2brMqU80uJiIiIiGgoYMBKREREREREI5YgCNBoNGlvGxut2OxriNvVY62trbH2uaECCUo3nYy18w758YexE6CePA315x6PwBefQn/8qf06ztD/2vpmZ2djzpw5mDFjBvR6fb/WSURERERENNgwYCUiIiIiIiJKM0EQYlWo/Q0cFUVBWVkZ1q9fjy1btiAYDCIrK6ut5a4CAL2bFSuazJCcJQhXlvdrvwDAZDJBq9Wivr4en3zyCT799FNMnDgRM2fOxLhx42JzVYmIiIiIiIYyBqxEREREREREQ0B9fT3WrVuHjRs3wuPxQK/Xw2g0QpZlNDQ0QK1WQytHejSDtT3Z14pIVQWko0/o9z6WOOy46aabsH37dnz77bcoKyvDDz/8gG3btkGn02H69OmYMWMGCgsL+70tIiIiIiKigcKAlYiIiIiIiGgQiEQicLlccLlcaGlpQUtLS+z7xsZGNDQ0xC3v8/ng8/mg1+tRXFyM3NxcBIwObA53PcPU/fcHoV14GKS8QkTq98P74pOAKEJ35LFt+9FYD7mxAeHKfQCA8O4dEAxGSLn5EC3WpOuVoKBYDkNRFEyePBmTJ09GU1MT1q5di3Xr1sHn82HNmjVYtWoVLrjgAowdO7af/2JEREREREQDQ1AURRnonSAiIiIiIiIazhRFgcfjiQtNo99Hf/Z4PHHP0el0sFqtsFgssFgs8Pv9cLlcqKiogEqlwuzZs7FgwQJYrT+GnutcXhy/dkeX+9J8928R2rAOsqsFotUO9bSZMF1yDVRFxQAAzwtPwvvSU52eZ7n5TuiPPanLdS/augYTG6pRUFAAp9OJ4uJiFBcXw2g0Ytu2bVi7di327NmDSy+9FE6ns6f/fERERERERIMKA1YiIiIiIiKiflAUBX6/v1PVaftbl8sFWZZjz1GpVLBarXEBavufrVYrNBpN3DYeffRRRCIRzJ8/H7Nnz4ZOp+u0L/6IjPFfbURogD7qvz8mG3JtFSoqKlBeXo7m5mYAgMViQXFxMZxOZyx85TxWIiIiIiIaqhiwEhEREREREXUhGAx2Ck07BqihUCi2vCiKMJvNXQaoer0eQi/mpAKA1+uFTqfrNpj8zdYyvFHbhEgGP+2LAOZYjHhvzvi4+z0eD8rLy1FeXo6KigpUVVUhEolApVKhsLAwVuXqdDphMpkyt8NERERERET9wICViIiIiIiIRqxIJAK3291l9anP54t7jslkigWmiW5NJhNEses5qOn0nasVx63dnvHtPjmlFKfk2btcJhwOo6amJha4lpeXw+12AwDsdnssbI3OlB3If0ciIiIiIqJkGLASERERERHRsBSde5ps5mmyuafJwlOr1Qqz2QyVSjVAR9Rzx63Zjg2e1oxUsYoAcjQqrF4wBZo+BKItLS1xgWtNTQ1kWYZarYbT6YyrctXr9ak/ACIiIiIiol5iwEpERERERERDTvu5p4mqTqO3ieaedhWgtp97OpRt9fhw9JofEM7QJ/7Xpo/BEVmWlKwrFAqhqurHOa4VFRXwer0AgOzs7LjANScnp9etlomIiIiIiPqLASsRERERERENOqFQKOHM0/Y/t597KghCXGDaceap1Wrt09zToeyRvbX4057qtG5DAnBWvgMPTS5J2zYURUFTU1Nc4FpbWwtFUaDVauMCV6fTCa1Wm7Z9ISIiIiIiAhiwEhERERERUYa1n3uaLEDtOPfUaDR2WX060HNPB6OwrOCCjbvxZaMbcveL95okABMMOrw7ezzMKikNW0guEAigqqoqrrWw3+8HAOTm5sbNcnU4HCMqWCciIiIiovRjwEpEREREREQpoygKvF5vXGja8dbtdsc9R6vVxlWbdqw+tVgsQ2Lu6WDUGpFx4Ybd+KbZ0ylk1Sp+jMUOjMYujMEuZKEOGoQQggrNsGMPxmEPxmAHJqBVMMU9VwIw1qDDm7PGIkejztjxJKMoChoaGlBeXh4LXevq6gAABoMhbpZrYWHhsGkFTUREREREA4MBKxEREREREfVIdO5pVzNPXS4XIpFI7DkqlSphYNr+Z7Z0Ta+ALOOmH8rxek0TRAD5SgUW4RMcjv9ChwBkiFAASO0i2AgEAAIkyAhDwtc4BJ/hOOzGOEAQcJjdhKcPGAWbevAG3z6fD5WVlbHAtaKiAsFgEIIgID8/Pxa4FhcXw2q1ssqViIiIiIh6jAErERERERERAWibe9qxZW/H22AwGFs+Ovc0Wdtei8UCg8HA4GqQ+LRmH9Zt/T8cqHyJCMS4QLU70eW3YDqyx96Dc0qmDLn/rrIso66uLq6tcGNjIwDAZDLFtRUuKChg1TQRERERESXFgJWIiIiIiGgEiM49TTbzNNnc02ThKeeeDi319UuwZetvEQq1AIh0u3xyEkRRgwkT7kBhwVlDLmTtyOv1xsLWiooKVFZWIhwOQ5IkFBQUxFW5ms3mgd5dIiIiIiIaJBiwEhERERERDXHRuaddVZ96PB60//gXnXuaqGVv9JYVfMNDefkL2L7jbgACgNSdAiguvgTjx9025EPW9iKRCGpra+OqXFtaWgAAVqs1rso1Ly8PkiQN8B4TEREREdFAYMBKREREREQ0iCmKgkAgEBeWdqw+7Tj3VJKkLmeeWq1Wzj0dIcorXsL27Xembf0lxZdi3Lhbh1XI2pHb7Y4LXKurqxGJRKBSqVBUVBQLXJ1OJ4xG40DvLhERERERZQADViIiIiIiogHUfu5psgC149xTs9mcdOap1Wrl3FMCADQ2rsB331+U9u1MmvRHFBWenfbtDBbhcBjV1dVxrYXdbjcAwOFwwOl0xkLX3NxcttEmIiIiIhqGGLASERERERGliSzLcLvdCcPT6G1ra2vccwwGQ5fVp2azmYENdSsc9mDltz9FIFAHQE7rtkRRjwXzP4VOV5jW7QxWiqKgpaUlLnCtrq6GoijQaDQoKiqKVbg6nU7o9fqB3mUiIiIiIuonBqxERERERER9oCgKWltbk848dblccLvdneaeJqs65dxTSqVtP/welZWvId3hKgAIggSbbT5mz3op7dsaKkKhEKqqquJaC0cvpsjOzo6b5Zqdnc2KcyIiIiKiIYYBKxERERERUQJ+vz9py96u5p4mC1AtFgt0Ot0AHhGNFIFAHZavWIhMhKvtHTj3LVgs0zO6zaFCURQ0NTWhvLw8Frru378fiqJAp9PFtRUuKirijGQiIiIiokGOASsREREREY044XA4adVpNEBNNPe0q+pTzj2lwWLPnr9h955HkMmAVRAk5OediilT7svYNoe6QCCAysrKWOBaUVEBv98PQRCQm5sbC1yLi4tht9v594WIiIiIaBBhwEpERERERCkTDochCAIkSQIANDU14Z577sGOHTsQiUTwpz/9CdOnp7fCLTr3NNnM05aWlqRzTxPNPLVarZx7SkOGoshYvmIhgsG6pMu8+GIjXn6pOe6+4mI1nn+hGADw0IN1WLfOh4aGCPR6AVMO0OHyyx0oKdF0uW1BUOPQQ1ZBrbb0+zhGIkVRUF9fH1flWl9fD6Dtb1T7tsKFhYVQq9UDvMdERERERCMXA1YiIiIiIuqxmpoaVFdXY8KECTAajQCAbdu24ZprrolVfV588cW4/vrrAQA33XQTIpEIFi9ejFAohKuvvhpr1qyBzWbr0/bbzz1N1r6349xTjUYTF5h2DFAtFguDCho2Wlv34JuVi7pc5sUXG/HVl17c/5eC2H2SJMBqbbsw4v33XSgpUSM3VwW3S8ZLLzVh564A/t//K4EkdV1FOXPG88jKOqz/B0IAAJ/PF5vhWlFRgcrKSgSDQYiiiPz8/LgqV4vFwipXIiIiIqIMYcBKREREREQ9cvPNN+Pdd9/F9u3bsWzZMhx66KEAgGOOOQYXXHABTjzxRKjValgsFmzduhUTJ06EwWDApk2bMGbMGADAYYcdhjPPPBNXXXUVVCpVp20EAoGkVafREDUcDseWlySpy7a9nHtKI01N7XvYvPnaLpd58cVGfL2iFU897ezROnfvCuCKKyrx0svFKCzs6mIEEWPHXIdRo67u+Q5Tr8iyjP3798cC1/LycjQ1NQEAzGZzXJVrfn5+wr+zRERERETUf3ynTUREREREPXL22Wfj/vvvx4IFC9DU1ARZliGKIr766iv84he/gN1uR319PQ488MBYBWl2djZWrFgRC1hra2vx7bff4sILL4yrYo1EIvj666+xZMmS2H2CIMBkMsXC0oKCgk7hqdFoZMUWUTtu92YIggqKEu5yucrKEM4+qwxqjYApU3S49FIH8vI6nyLw+WR8/Ikb+QUq5OR0fwrB5d7Y532n7kUrV/Pz83HggQcCALxeb1zgumTJEoTDYUiShMLCwljg6nQ6YTabB/gIiIiIiIiGBwasRERERETUI7NmzQIAmEwmlJeXx2aSvv/++7jnnntw7bXXora2Fr/97W+RnZ0NALjrrrvw4Ycf4l//+hesVitGjRoFi8UCl8sVF7AKgoAJEybAZrPFAlSTyRSb5UpEPRMM1qO7RlWTJ+lw080aFDvVaGiM4OWXmnDdtVV49jknDIa2/6/feacFzzzdCL9fQXGxGvffXwC1uruLGWQEAslnv1J6GI1GTJo0CZMmTQLQdsFKTU1NLHDdsmULvvnmGwCA1WqNq3LNy8vj31kiIiIioj5gwEpERERERL3idDpRWVkJRVEgCAKam5sxZcoU/OMf/0BxcTFOPfVU3HPPPXj44Yfxs5/9DLNmzcKuXbtw9NFH45FHHsG2bduQn58ft05RFJGXl4e8vLwBOiqi4aGtcrXrgPWgeYbY92PGApMna3Heefuw7AsPjjveAgA46igz5swxoLExjH+/3oK776rFI48WQqMRu96+HOz3MVD/SJKEoqIiFBUVYd68eQAAl8sVN8t169atiEQiUKlUKCoqipvlajAYutkCERERERExYCUiIiIiGuECgUBszml01un48eNRWFgYq1Jtr6SkBLt370YoFIJGo8EXX3wBu92OUaNGAQBOOukkfPDBB3C5XLBYLJgxYwZmzJgBANi+fTtGjx4NjUaDSCTCyimiFBMFDYDetc02mSQ4nRpUVoXb3SfCZBLhdKoxebIOp56yF8uXt+LII01db1/izOPByGKxYMqUKZgyZQoAIBwOo7q6Oha4rl+/HitWrAAAOByOuCrXnJychK8FREREREQjGQNWIiIiIqJhLBwOw+VydQpQ2/8cCATinmM2m5GdnY2CgoK4+6OzTidPnox169ZBo9EAAAwGA7788svYchUVFZAkCRaLBbW1tXj22WexcuVK7N+/H/Pnz8fvf/97KIrCcJUoDbS6fAiCgG66BMfx+WRUV4WQtShxeKoobV+hYHcrlaDTFfV8wzRgVCpVrGIVABRFQUtLC8rLy2Oh64YNG6AoCjQaDZxOZ9wsV52OQToRERERjWwMWImIiIiIhihZluHxeGKhaaIA1ev1xj1Hr9fHZpyWlpbCYrHEfrZYLDCbzUmDz2jA6vF4sHr1atx5551wOp24+eabcf3112Pq1KkQRRFOpxOPPPIIgLZ5rdOnT8fEiRMxduxYTJgwAWq1Or3/MEQjmMU89X9tgpN76skGzF9gQF6eCg0NEbz4QhNEETjiSBOqqkL44gsP5s41wGqVUF8fxj9fa4ZGI8S1Fk5MgcU8NXUHQxkjCAJsNhtsNhumTZsGAAgGg6iqqooFrqtXr45dTJOTkxPXVjgrKyv2GkFERERENBIIitKb61qJiIiIiCgTFEWBz+eLC0073rrdbsiyHHuOWq2OC0sT3fYn3IxEIjjnnHOwadMmlJaWIjs7G/PmzcOvfvWrWJibn5/PVpJEA8jvr8KKrw/tcpl77q7Fxo1+uFwRWK0Spk7V4ZJLHSgsVKO+PowHH6jD9u1BeDwR2O0Spk3X48ILbSgu1nS7/dmzXoXdPi9Vh0ODiKIoaGxsjAWu5eXl2L9/PwBAp9PFtRUuKiqKdTkgIiIiIhqOGLASEREREQ2A9nNPk92Gwz9WoYmi2KnatOPPOp2OFUREI5yiKPhm5SL4fGUAMvtxX5KMOPSQbyFJ+oxulwaO3+9HZWVlLHCtqKhAIBCAIAjIy8uLaytst9v5GkVEREREwwYDViIiIiKiFAuHw3C73V1Wn/r9/rjnmM3mpFWnVqsVRqORJ6aJqEfKK17C9u13IZMBqyBIcDovxoTxv8vYNmnwURQFdXV1cYFrfX09AMBoNMYFroWFhWwZT0RERERDFgNWIiIiIqJeiM49TTbztKu5p4mqTq1Wa5dzT4mIeiscduOr5fMgy4GMbnfB/M9hMIzO6DZp8PP5fHGBa0VFBUKhEERRRH5+flxrYavV2q9tKYqCBx98EACwaNEizJgxIxWHQERERETUCQNWIiIiIqL/ic497Rietr9NNvc0UdVpNFDlHDoiyrQ9ex7D7j2PIDNVrCLy80/GAVP+moFt0VAnyzL2798fN8u1qakJQFs3h/aBa0FBQa8uQPL7/Xj22Wfx3HPPYf/+/di4cSMcDgcAoKmpCbIsIysrKy3HRUREREQjCwNWIiIiIhoxgsFgXFiaqPo02dzTZNWnnHtKRIORLIewevXJ8LbuhKJE0rglAWq1Awvmfw612pLG7dBw5vF44qpcq6qqEA6HIUkSCgsLY4FrcXExTCZT0vWEw2GoVCo89NBDWLduHZ555hnodDp88cUXeOmll/Dtt99Cr9fj2GOPxW233QaDwZDBoyQiIiKi4YQBKxERERENC5FIJOGs0/a3HeeemkymTtWm7X82mUwMT4loyHJ7tmH16lOgKGGkr5JVwIzpzyA7+4g0rZ9GokgkgpqamrgqV5fLBQCw2Wy45JJLYDabOz1PURQIgoBjjz0WRx99NK699lpIkoQFCxZg4cKFeOCBB1BRUYErr7wSF198Mc4880z4/X589NFH+O6777Bw4UIcfvjh0Ov1mT5kIiIiIhpiVAO9A0REREQAEJYV7Gj1oyEURlhRoBFEOHVqFOs0DLgIiqLA4/F0WX3q8XjinqPX62OBaXFxMaZOnRoXoHLuKRENd2bTJEyf9gTWb/jF/+5JErIqCvR+GdqADFFWoIhAUC3Ca5CAbl6DJ074A8NVSjlJklBUVISioqLYfS6XC+Xl5aiurk4YrgKIvWfcvXs35syZE3udP+mkk9DS0oJAIACn04nVq1fjtNNOAwD8/Oc/h0ajgdPpxIMPPoilS5fi7rvvZnt/IiIiIuoSK1iJiIhowOxuDeCV6gZ81eTGVo8foQRvSyySiBkWA36aZcVZ+XZY1bw+bLhRFAV+vz/pzNNoiNpx7mmymafRW54YJSJqU1+/BBs2Xg1AjrULVgdlFNT6kd0YhNkThipBF+GICHiMKjTa1ajM1yGgi16UIgJQMHHiXXAWnZepwyDqkW3btmHx4sVYsmQJiouLEQ6H8fe//x0PP/wwZFmGLMu45ppr8Mtf/hIGgwFGoxGbNm3C6NGjAQBTpkzBq6++ipkzZw7sgRARERHRoMYzlERERJRxK5rceLisFl81eSAB6GoynCsiY3mTB8ubPLh7VxXOyLfjulH5KNYxPBsqgsFgp6rTjrehUCi2fHTuafvq045BKueeEhH1XHb2kTjowHewecv1kPdvxqh9XuTVBSH877qmZH9NJRmwuMOwuMMYtc+Heocae0tMCOQU4oApf4XdPi9jx0DUUzt27MC4ceNi1a//+Mc/8P7772PXrl0AgNtvvx2BQAAGgwF1dXUwGAyxi7ICgQDUajXq6+sHbP+JiIiIaGhgwEpEREQZ4wlHcNeuKrxU1YBoDUxX4WpUtK41qCj4V00j/lPbhLvGFeHCwiyGbAMsOvc02czTruaeWiwWjBs3rlP1qdFohCiKA3RERETDk8kwDgcGF0FY9zUUWUZP/8q2f5XNagwhu7EJyoJzIJqmp2M3ifrsiy++wBNPPIGVK1di1qxZ8Hq9MJvNeO+99zB79uzYcqNHj8Y///lP3H777cjKysLvf/97XHXVVTjjjDOwe/du7Nq1C4FAYACPhIiIiIiGAgasRERElBFbPT6ct343aoNtlYo9CVYTiShARFFw8/YKvF/XjH9MHQ2TinM00yE69zTZzNNEc091Ol0sLC0uLsYBBxwQF6BaLBbOPSUiyjRvA/Da2RArVgNIXrHanWgoK6x8EvjhE+CCNwHHmJTsIlF/zZs3D263G6NGjcLXX3+N4uJifP/99zjiiCOwefNmlJeXo7i4GG+99RamTZsGv98PnU6Hiy66CAaDATU1Ndi9ezdOPPFEZGVlAWh7L8SL+YiIiIgoEc5gJSIiorTb4G7Fad/thC8i9zlYTUQCMMWkx5uzxsHCkLVX2s89TRagdpx7qlKpEs46bX/LuadERIOMpw54/ligcQ+gpPBVWFQBOitwySdA9vjUrZcoxRobG3HLLbdg/fr18Hg8WLBgAW699VaMHTsW1dXVKCgoiC172mmnYeLEibjllltgtVpj9weDQXi9XthsNgauRERERASAASsRERGl2e7WAI5bux3ucARy94v3mgRgtsWAN2eNg4ZtZWNCoVCXM09bWlo6zT01m82dqk3b/6zX63lSkYhoKAl4gOeOBup+SG24GiVKgCEHuOILwFLQ7eJEA62hoQFarRYmkwkAcNddd+Gjjz7C9OnToVKpsHXrVrz66qvIz8+PPUeWZWzcuBFvv/02jEYjiouL4XQ6UVxcjMLCQqhUbA5HRERENBIxYCUiIqK0iSgKTly7Axs8rYik8R2HAOC6UXm4efTIOLkbiUTgdru7rD71+XxxzzGZTEmrTjn3lIhomPrgRmDNc4CSjkuc/keUgNE/aWsXzItwaAj69ttvsWLFCqhUKlx11VVQq9WdlgkGg9i7dy/Ky8tRUVGByspKhEIhiKKIgoKCWOBaXFwMi8UyAEdBRERERJnGgJWIiIjS5u/79uPOXVUZ2ZYI4JO5EzDNbEi6THNzMz744AO0trbi8ssvz8h+9ZaiKPB6vV1Wn7rd7rjn6HS6hKFp9Huz2czqCiKikWbPV8CLJ2Zueyc/Dsy6IHPbIxpAsiyjtrY2FriWl5ejubkZAGJz6KOha35+PufPExEREQ1DDFiJiIgoLeqCIcz+egtCGXqrIQGYbtbjo7kTOz2mKApWr16N//73v9DpdDjppJMwduzYjOxXx/3w+/1JW/a2tLTA7XYjEvmxjWN07mlX1aece0pERHFkGfjbHKBpb3qrV9vTmIAbfgC0psxsj2iQ8Xg8KC8vj4WuVVVViEQiUKlUKCwsjAWuTqcz1qKYiIiIiIYuBqxERESUFo/srcV9e6rTMne1K5/MnYAZ7apYGxoa8O6772Lfvn2YM2cOjj76aGi12rRsOxQKdWrZ2/E2GAzGlhcEIS4wTVR9yrmnRETUa7uWAC+fmvntnvgQMPeSzG+XaBCKRCKorq6Oq3KNdiGx2+1xVa65ubkc1UBEREQ0xDBgJSIiopSLKApmf70ZtcFw0mU8LzwJ70tPxd0nFY9C9otvQXa1wPPC3xFcsxKR/TUQbXZoD/4JTD+/GqLJnHSdkgCcnefAg5NLIMsyvvnmGyxduhQWiwUnnXQSRo0a1fdj+t/c02QzTxPNPTUajUmrTi0WC0wmE0+mERFR6r12LrDjU0BO/Dr8hy/8uHNZMO6+iVkitl0TX1WnKAqOf7UVH++M4K2z9ThlUufZlD8SgJyJwNUrOYuVKImWlpa4wLWmpgayLEOtVsPpdMZVuer1+oHeXSIiIiLqAodxERERUcqtbvF2Ga5GSaPGwv7XJ2M/C/+bTyU31EFuqIP5yusglY6BXFsN18P3wtVQB9sf/pp0fREF+M/+Jtxo1+D9d99FTU0N5s+fjyOOOAJqdfKTwu3nniYLUD0eD9pfl6bVamNhaVFREaZMmdKpGpVzT4mIKOMCHmD7x922Bj4gR8TnF/3Y8UGV4Hqfh1cGIaCnYakC1G1r+8qd3IsdJho5ou8dp06dCqCt+0lVVVUscF23bh2++uorAEB2dnZc4JqTk8OuJkRERESDCM/6ERERUcp972qFCHTbHliQJEiO7E73q0aPg+3OB368o6gYpkuuQcuffgclEoYgJX8L45cV/OX/vYbxBi0uvfRSFBYWIhAIoLGxMWn7XpfL1WnuaTQszc7OxpgxYzpVn6arzTAREVG/1Gzo0dxVlQjkm5J3Ufi+JoIHvglizRVGFDzg6fn2q75jwErUQ2q1GqWlpSgtLQXQdtFfU1NTLHCtqKjA+vXroSgKtFptpypXvh8lIiIiGjgMWImIiCjlNnh8Pap3CVfuQ92ZR0PQaKGeMh2my34FKa8g4bKy1w3BYOwyXI0KFJbAHGnFO++8g5aWloRzT6OBaVFRUaf2vZx7SkREQ1bV94Agdhuy7miUUfiAGzoVsKBYwp+O0qHE2ha4toYUnPemD48fr+syhO1EVLVtf+Z5fd9/ohFMEAQ4HA44HA5Mnz4dABAIBFBVVRULXL/99lssW7YMAJCbmxsLXIuLi+FwOPgeloiIiChDGLASERFRym32+BDpZhn15Kmw3nwXpOJSyI318L74FBp/cwmy/vEGRIMxblm5pQnel5+B4cTTu922KMuoElWQIGH06NFxVadWq5VzT4mIaHir29ZtwDqvSMILJ+sxMVtEtVvBncsCOPR5LzZdZYJZK+C6j/1YWCzh5C5nriYgh4H9W/p5AETUnlarxejRozF69GgAbVWuDQ0NKC8vj32tW7cOAGAwGOKqXAsLC6HRaAZy94mIiIiGLQasRERElHLeSHfxKqCdd8iPP4ydAPXkaag/93gEvvgU+uNPjT0kez1ouvXXUI0aA+PFv+h+4wLgDUewp2wPtFotxo8fjzFjxjBUJSKikSHUCrSbGZ7IceN/DE6n5wHznBJKH3bj9c0h5BgFLNkbwXe/MHaxhi4EetFOmIh6TRAEZGdnIzs7G7NmzQIA+P3+uLbCy5cvRzAYhCAIyM/Pj6tytVqtrHIlIiIiSgEGrERERJRyQo8aBMcTTWZIzhKEK8tj98mtXjT/9pcQDQbY7noQgqr7ShpJlDBr5kwcVpqDDRs2YNOmTTAajZg2bRpmzJiBvLw8nlQiIqJhrPevcTadgAlZInY2yti4H9jVKMP2Z3fcMqe/7sOhJUF88bNugle+xhJlnE6nw7hx4zBu3DgAgCzLqKuriwWuu3btwurVqwEAJpMpNsO1uLgYBQUFUKl4epCIiIiot/gOioiIiFLOLPW+WlT2tSJSVQHp6BPafvZ60PzbqwG1BrZ7Hoag0fZsPYqMsNeNcePG4aCDDkJDQwPWr1+PDRs2YOXKlcjNzcX06dMxbdo0WCyWXu8nERHRoKY1tYWcXRexxvEEFexqlHHhdAFnHaDGZbPjL2ia9ncvHjpGi8UTetAyWMfXVqKBJooi8vLykJeXh7lz5wIAvF4vKioqYpWuS5cuRTgchiRJKCgoiAWuTqeT75GJiIiIeoABKxEREaXcVLMeP7T6Eeni5K777w9Cu/AwSHmFiNTvh/fFJwFRhO7IY9vC1ZuvhhLww3rrvZBbvUCrFwAgWu0QJCnpeiMQsH/tajz9cSUAwGw2IysrC5MmTYrNrFqyZAmWLl2K6667DkZjH1sgEhERDUJKzmRAjnRZx3rjp34snqBCqU1ElVvG/30RgCQKOHeqGjlGEfmmzs8psYoYbe/mAipRBeRN7df+E1F6GI1GTJw4ERMnTgQARCIR1NbWxgLXbdu2YeXKlQAAq9UaF7jm5+dD6uL9NxEREdFIxICViIiIUm6G2YB/1zR1uUykvhYt99wK2dUC0WqHetpMOP72EkSbA8Hv1yC0dSMAoOHCk+Kel/3qB5DyC7tc9+3nngVzqxsNDQ2xr6qqKjQ0NCAUCgFom1/1/PPPIysrq9OXyWRiG2EiIhoSohcPlZWVoaysDIFdP+DcbspXK1wyzn3ThwafghyDgENKJKy81IgcYz/nlcthoHBW/9ZBRBkhSRIKCwtRWFiIgw46CADgdrvjZrl+9tlniEQiUKlUKCwsjGstzIsUiYiIaKQTFEXpReMgIiIiou6tc3lx/NodA7JtsyRi+6HTEgakiqLA7f4xeK2vr0djYyMaGhrQ1NSE6NsijUaTMHjNysqCVtuzVsVERETpIMsy9u/fHwtUy8rK0NraCkEQUFBQgNHOfBy16mIISmRgdvDX3wGOMQOzbSJKqXA4jJqamljgWl5eDre7bT6z3W6PC1xzc3Mhiv28SIOIiIhoCGHASkRERCmnKAoWfLsVZb5gb0bA9ZsE4BJnNu4e7+z1cyORCJqammLBa0NDAxobG1FfXw+v1xtbzmQyJQxe7XY7W6cREVHKRSIRVFdXx8LUffv2IRAIQJIkFBUVobS0FKWlpXA6nT9eBPTm5cDm/7RVlGaKILZVr16+JHPbJKKMUhQFLpcL5eXlsdC1pqYGsixDo9GgqKgorrWwXq8f6F0mIiIiShsGrERERJQWz1bU4Y4dlRkNWAFg+bxJGGfQpXSdfr8/Fra2D147thy22+2dgtfs7Gy2HCYioh4LhUKorKyMBaoVFRUIhUJQq9UoLi6OBapFRUVQqZJM/SlfBTx3dGZ3HABOewaYflbmt0tEAyYUCqGqqiquyrW1tRUAkJ2dHQtci4uLkZ2dzffERERENGwwYCUiIqK0aAmFMfubLWiNyBkJWSUBOMRmxr9mjs3A1tooigKPxxMLW9t/tW85rFarY2Grw+GIfc+Ww0REQ1c4HMaSJUvw+eefY86cOTj99NOhUqmgKEqvAoRAIIDy8vJYoFpZWQlZlqHT6VBSUhILVPPz83veKUFRgKcOA2o3AxlpFSwCBgdw/RZAxdc1opFMURQ0NTXFVbnu378fiqJAp9PB6XTGQteioiK+FyYiIqIhiwErERERpc0/qxtw7bbyjGxLIwj4ct4kjNIPjpM07VsOd/zyeDyx5YxGY8LglS2HiYgGp2iA+swzz+CZZ57BkUceGQsPnn/++W4D1tbWVuzbty8WqNbU1EBRFBiNxliYWlpaitzc3P5VelVvAJ7+SYYCVgDn/hOYeFxmtkVEQ0ogEEBlZWUscK2oqIDf74cgCMjNzY2rcrXb7axyJSIioiGBASsRERGljaIoOG/DbnzZ6Ea6T+/eM74Ilzlz0ryV1AgEAgmD14aGBgSDQQDxLYcdDkcseM3KyoLZbOaJJyKiNItEIli6dCmee+45+P1+vPDCC7BarQCAuro6nHbaaXj66acxefJkVFVVYfbs2Vi2bBkmTpwYtx5FUeB2u/HVV19h37592L9/PwDAarXGBaoOhyP1f9uX/glYdh+Qzl4SggRMPR04/Zn0bYOIhhVFUVBfXx/XVri+vh4AYDAYYjNci4uLUVhYCLVaPcB7TERERNQZA1YiIiJKq9pACMet3Y7aYAiRNLzrEAEck23Fc1NHQRzioWO05XCi4LWpqQmyLAP4seVwoi+dLrXzZ4mIRoo9e/Zg/fr1OPLII2GxWOByuXDbbbdBpVLh5ZdfxvLlyzF58mQAbe2Bc3NzsWPHDmRlZQEATjzxRBx33HG44oorOoUBfr8fzz77bCxMLSkpgc1mS/9BhYPA/zsNKPs6PZWsogpwjAEu/RTQ21O/fiIaMXw+X6y6tby8HJWVlQgGgxBFEfn5+bHA1el0wmq18mJDIiIiGnAMWImIiCjtynwBnLxuB+qC4ZRWsgoAjnCY8fy00dCKYgrXPPhEIhE0NzcnDF/dbndsOaPRmDB4tdvtUKlUA3gERDTclLvKsalhE7Y0bMHO5p3whrwQIMCsMWO8fTymZE3BtOxpyDfmD/Suduv666/Hu+++i927d2PFihVYsGABAGD37t0YM2YMFixYgF/96lc477zzALQFAccccwxuvPFGnHTSSQCAP/zhD6ipqcEjjzwyuGYKBjxtIWvFakCRU7deUQJspcDPPwLMg/+/MRENLbIsY//+/bHAtaKiAo2NjQAAs9kcF7gWFBSMuPe59b56bKrfhM0Nm/FD4w9wBV2QFRl6lR6jraNxQNYBOCDrAIy2jmYYTURElCYMWImIiCgjKv1BXLxxDzZ5fP1elwhABnBegQN/nuCEZpiHq90JBoMJg9f6+vq4lsM2my1h+GqxWHjihYh6xB/24+O9H+PVra9ia+NWAIBKUCGshGPLCBAgCVLsvtm5s3He5PNwZMmRUIuDs83j119/jYULF+KEE07A4sWLceWVV8Y9fuWVV0KtVuPRRx+FIAgIBAK44YYbIIoiHn30UQDAO++8g3vvvRerVq2CLMsQB9NrU7AVePtKYMs7aLs8KQWnAYrnA+e8Ahiz+78uIqIe8Hq9cYFrZWUlwuEwJElCQUFBXGths9k80LubchE5ghVVK/DattewonIFFCiQBAmyIkNp93e9/etyqaUU508+H4vHLIZJYxqoXSciIhqWGLASERFRxoRlBU+U78f9e6qhAH1qGSwCcKhVeGhSMY7OtqZ6F4cVRVHg9XoThq+NjY2xlsMqlSppy2G9Xj/AR0FEg4GiKPh478e4Z+U9cAVdECDEncztiiiIkBUZOfoc3H3w3Ti46OA0723vhcNhqFQq3HbbbSgvL8eLL74IURRj97/xxht46KGH8NFHH8FisQAAPvjgA1x99dUoKysDALz99tt4/PHH8dlnnw3koXRt03+A969tq2rtS8tgUdVWuXr03cCBlwODKUQmohEnEomgtrY2bpZrS0sLgLY51+0D17y8PEiSNMB73Hfr69bjd1/9DmXuMkiChEgP/4YLaLuIUqvS4vo51+PsiWdDFPi3m4iIKBUYsBIREVHGbff68WT5frxR04SQokBAW0VqMioBCCtAjlqFnxVl4zJnNqzqkdUGLNVkWY5rOVxfX4/GxkY0NDTA5XLFljMYDAmDV4fDMeJasRGNVA2+Btz5zZ1YWr60V8FqRyJEyJBx6rhTcfOBNw/KSpolS5bghhtuwJIlS2C326EoCgRBQFVVFQ4++GB8+eWXKC4uji1/+umnw+FwQK1WY/ny5fjb3/6Gww47bACPoAc8dcC3fwdWPwf4mwFB6jpsjT6u1gOzLgTmXw04Rmdsd4mIesPlcsVVuVZXVyMSiUClUqGoqCiutbDRaBzo3e1WIBLA4989jhc2vwBBECD3s9X77NzZuPeQe+E0O1O0h0RERCMXA1YiIiIaMC2hMN6obcLKZg/WulpRFQjFPS4BGGfUYY7FgKOyLDgmywqVyFa26RYMBmNha/vgtb6+HoFAILZcspbDVquVLYeJholyVzku+eQS1Pnqelwt0x1REDHGOgbP/PQZZOu7by8ryzJ++OEHjB8/Pu0XdrS2tmLKlCl48803MWfOnLjHDjzwQFxyySXQaDRYtGgRSktL4fP58Nxzz8Hn82HRokWYNWtWWvcvpcIBYOt7wK4lQPkqoHEn0PH0gK0UcB4IjDoEmHYmoB18oTgRUVfC4TCqq6vjqlw9Hg8AwOFwxFW55uTkpL29e/TCnZ7whrz45X9/iXW16/p8cVNHkiDBqDbi2Z8+i8lZk1OyTiIiopGKASsRERENGi2hMJrCEQRlBVpRQJ5GDZ3EFlaDhaIoaG1tjYWt0VbD0RC2fcthh8PRKXjNzs5my2GiIaTaU43zPzwfjf7GlIWrUZIgodhcjJePexk2nS3pcsFgEP/5z3+wfft2/OIXv0BeXl6/tuv1erFv3z5oNBqMHj067kR6dG7q0UcfjV/+8pc45ZRTEAqFsHPnTjzyyCN4+umnUVJSgpKSEjzyyCNDK0ztiWAr4N3fFrxKasCQDegsA71XREQppSgKWlpa4gLXmpoaKIoCjUYDp9MZV+Wq0+lStu09e/bgjTfewCmnnILx48d3uawv7MMVn16BDfUb+l212pEoiNCr9HjpuJcwwT4hpesmIiIaSRiwEhEREVG/ybKMlpaWWPDa/qt9y2G9Xh8LW6MhbHZ2Nux2O9Rq9QAeARG1F4wEceZ7Z6LMVZbycDVKEiTMzp2NZ495NuE8OJfLhddeew2NjY04/fTTMWFC708Cu1wulJWVoaysDPv27UNdXR0AYPr06Tj11FPjlo2edD/yyCOxd+9eRCIRPPjggzjuuOPw+eef4+CDD8bYsWP7drBERDRoBYNBVFVVxQLX8vJy+Hw+AEBOTk5c4Jqdnd3nTi3BYBBvvvkmduzYgUWLFmHBggVJ13XLl7fgo70fpTxcjZIECXadHe+c8g4sGl5MQ0RE1BcMWImIiIgorUKhUKfQNfrl9/tjy1mt1k7Ba1ZWFiwWS9rbtRFRvEfXPYpnNz6bspaEXbl93u04e9LZcfdVVVXhtddegyRJOPfcc3tUuaooCpqammJhallZGZqamgAA2dnZKC0tRWlpKUpKSmC1Wjs9v6mpCRdeeCGsVitOOukkLFy4MG7eKhERjQyKoqCxsTFW5VpRUYHa2loAgE6niwtci4qKoNVqe7xuWZaxdOlSLF++HNOnT8eJJ57Y6SLDJfuW4DdLf5PSY0pEFEQsHrMY9xxyT9q3RURENBwxYCUiIiKiAdG+5XDHr8bGRkQibVVzkiTF2gw7HI5Y8JqVlQWDwTDAR0E0/Gxp2IJz3z8XMtJTNdORVtLinVPeQZGpqG37W7bgrbfeQl5eHs455xyYTInnfiqKgrq6urhA1e12AwDy8/PjAlWj0ZiRYyEiouEpEAigsrIyrrVwIBCAIAjIzc2Nm+Vqt9u7rXLdtGkT3nnnHeTm5uLss8+GxdJWRdoSaMGJb52IlkBLRi5yAoAnjnoChzoPzci2iIiIhhMGrEREREQ06ERbDicKX1taWmLLRVsOd/xyOBxsOUzUR79Z+hssK1+WttbAHUmChLMnno1bDroFy5cvx5IlSzB16lScdNJJcf8fy7KMmpqauEDV5/NBFEUUFhbGAtXi4uKUzswjIiLqSFEU1NfXx1oKV1RUoL6+HgBgNBrjZrkWFhYmfF9aXV2Nf/7zn5BlGWeffTacTiee3fgsHlv3WMYuchIhYnLWZPzzxH9mZHtERETDCQNWIiIiIhpSQqEQGhsbE4av0XlZQFvL4UThq9VqZcthoiRqvDU45o1jMnZiN0qv0uN6/fX4YeMPOPzww3H44YcjEomgqqoqFqju27cPwWAQKpUKTqczFqgWFRVBo9FkdH+JiIg68vl8serWaGvhUCgEURSRn58fC1yLi4thsVggCAI8Hg9ef/11VFVV4fgTjsdNO2/C/tb9Gd/3f534L0zJmpLx7RIREQ1lDFiJiIiIaNhI1nK4oaEhruVwdM5rxy+DwdBtS7e+8Pl8WL9+PSZPnpxw9iPRYPH37/+OJzc8CVlJHLDWvlWLunfq4u7T5Gsw4c8TAAC7/7QbrT+0xj1u/4kdRT8r6nrDCjC3aS4umH4BRFHEvn37UFFRgXA4DI1Gg5KSkligWlBQAJVK1feDJCIiygBZlrF///64tsLR2eBmsznWVriwsBDff/89PvrhI6zIW5F0fd29BgNA685W1L5Zi9ZdrRBEAboSHUbdOAqiJvnFhZIg4ZRxp+APC//QvwMmIiIaYfiplIiIiIiGDYPBAIPBgOLi4rj7FUVJ2HJ48+bNaG5uji2n0+mSthzuS4WcLMsQRRF//vOfcffdd+Ouu+7C7bffjttvvx3btm3D5MmTMWHCBBx88MEYM2ZMfw+fqN++rvo6abgapS3SYtRNo2I/C1L8RQn2w+3IPTU39rOo7b5iXICAWm0tli9fDr1ej9LSUhx11FEoLS1FXl4eq86JiGjIiVau5ufn48ADDwQAeDyeuCrXJUuWIBwOQxRFtOS2QFAEKELyWpiuXoNbd7Zi7wN7kXNCDgouKIAgCvCX+4Furh2MKBF8XfV1v46ViIhoJGLASkRERETDniAIsNlssNlsGDt2bNxj4XA4YcvhnTt3orX1x0o8i8WSMHy12WxJwx9RFHHXXXdh//79OOqoozBlSlvrteXLl2Pq1KnQ6XT4/PPP0dDQgKuvvpptTmlAyYqMbY3bul1OEAWobclnHIsascvHE1EEBY3aRowePRpjx45FSUkJK1WJiGjYMZlMmDRpEiZNmgSg7X3o9u3bsWXLFixrXgYFXTca7Oo1uPrVamQtykLOiTmx+7QF2h7tV7W3Gq6gCxaNpYdHQkRERPy0SkREREQjmkqlQm5uLnJzczs95vP5YoFrfX09GhsbUV5eju+//x7hcBhAW4h6xRVXIC8vL+65gUAAL7/8MrZu3YqHH34Yp59+OvLy8uDxeCBJEm688UaMGjUqE4dI1CNlrjL4I/5ulwvUBrDt2m0Q1AIMYw3IOzMPmqwfLw5oXtmM5m+aobKqYJ5pRu5JuT2qYvWqvPDJPnzxxRcIh8OQJAlFRUWxeXXFxcUwGAz9OkYiIqKBpCgKGhoasHfvXpSVlaGsrAxutxsQgIaShm6rTZO9BoddYfh2+2BbYMOue3YhuD8IbYEWeafnwTjB2KN929qwFfMK5qXgKImIiEYGBqxEREREREno9Xo4nU44nc64+xVFgcvligWvDoej03PfeOMNrF+/Hq+99hrKy8uh1+tRWFiImpoabN++Hb/4xS9w+OGH4/jjj8fMmTMzdEREydX76rtdxjDWAOdlTmgLtAg1h7D/nf3Y88c9GHfPOEh6CbYFNqiz1FDb1PCX+1Hz7xoEa4Io+VVJj/bhuNOOQ5GxCDU1NSgvL0d5eTnWr1+PFSvaZtJlZWVh+vTpOOyww/p1rERERJnidruxbdu2WKDq8XggCAIKCwsxbdo0jBo1CjkFOXjjzTe6XE9Xr8HB/UEAwP639yP/nHzoSnRoXtGMvffvxbh7xkGb330la4OvISXHS0RENFIwYCUiIiIi6iVBEGC1WmG1WhPOTm1qasJLL72EzZs3Y9y4cdi0aRPC4TACgQBGjx6Nl156CR6PB59//jmeeOIJ3HHHHZ3mxhJlWkgOdbuMebo59r2uWAfDGAN+uPEHtKxqgeNwBxw/ccQ9rrKpsPf+vQjsD0Cb2/3J3ZAcilWuFhUVYf78+VAUBc3NzSgvL8e+ffsQCnW/n0RERIPFu+++i927d6OwsBAzZsyIzRcHAL/fj0AggLKKsm7X09VrsK5QBwCwH2GH/VA7AEBfqodniwdNXzUh/8z8btffk/cBRERE9CMGrEREREREKWa32/Hss8/im2++we7du7FmzRrs3r0bd955J/70pz/hiCOOAAAsXrwYxx9/PJ5++mncfffdkGU5bp7rypUroVarkZ2djaysLBiNRghCN73jiPpII/Z+BrBklKDN18YqZzoyjG1r6RusDfYoYE20D4IgwG63w263Y/r06b3eRyIiolSJRCKxUDQQCHT5fTAYhN/vh9/vR1ZWFlwuF9asWRPryhC3XiEClPZuX9q/BpummAAgFrRGaQu1CDX0LDjVSL1/H0BERDSSMWAlIiIiIkqD6MxIANi5cyfOOeccXH/99YhEInHLtbS0wGazAUBcuAoA69evR21tLRRFAQBotVpkZWUhKysLDocjFrw6HA5otd2HV0RdyTPkdb9QBxF/BMH9QdgW2hI+7tvnAwCobepu1yVAQJY+q9f7QERE1B1FURAMBrsNRaPfJ3u84/u49iRJgk6ng1arhVarjX2flZXV6b6O32u1Wnz6/qfwhr09Pqb2r8HqbDVUNhUC1YG4ZYI1QZimm3q0vhx9To+3TURERAxYiYiIiIjSJhKJQJIkjB49GqWlpVCr1TjrrLPQ3NyMadOmQZZlGI1GnHzyyQmf/4tf/ALhcBhNTU1oaGiI+9q9eze83h9PwpnN5k7Ba1ZWFmw2GyRJytQh0xDmNDthUBnQGm5Nukz1P6thmWmBOkuNcHMYtW/XAiJgnWdFYH8ALd+0wDzDDMkowV/hR/Wr1TBMNEBXrEu6zqhiczEMakMqD4mIiIaBnlaNdvd4VxKFngaDAXa7PWko2jEgVan6d5p1SvYUrK5ZnfTxrl6DBUFA9nHZ2P/2fuhKdG0zWJc3I1AdQPE13Y+hECBgctbkfu0/ERHRSMOAlYiIiIgoTaLB5u9+97vYfc888wy2b9+OrVu3oqGhAX/4wx+QnZ2ddB0qlQo5OTnIyelcVeD3+zsFr1VVVdi4cWNsTqUoirDb7bHAtf2XyWRiy2GKEYS2k6tra9cmXSbcGEb5k+WIeCKQzBKM440Yc8cYqCwqyCEZni0eNHzaADkgQ52lhnWuFTkndV8RIwkSpuew/S8R0XDSk6rRnvwcDoeTbkOSpITBp9FoTBqEdlxWo9EMivdDU7OnYl3tOkSUxFWyXb0GA0D2MdlQQgqqX6tGxBOBrkSHUTeN6lGL/iJTEYxqY0qPh4iIaLgTlGi/MSIiIiIiGhYURYHb7e4UvjY0NKCpqSnWclij0SQMXqOt7GjkeXbjs3hs3WOQIWd82/ceci9OGntSxrdLRESddawa7WtI2pVkoWd31aLtv+9v1ehg8m31t7js08syvl1JkHDWxLNw27zbMr5tIiKioYwBKxERERHRCBKJROJaDtfX16OxsRENDQ3weDyx5UwmU8Lg1W63s+XwMNbga8BR/z4qafVMupjUJnxx9hfQSgz2iYj6o33VaHfzRoPBYNLH+1I12puAdLBUjQ4miqLg+P8cj0pPJRRk9nTt2ye/jbG2sRndJhER0VA3fC7zIiIiIiKibkmShOzs7IRtif1+fyxsjQav1dXV2LRpE4LBIIC2NrLJWg6bzWaeLB3isvRZOGbUMfhk7ycZC1klQcKZE85kuEpEI14kEuk2FO3JvNGuJApAo7NGR2LV6GAiCALOm3we/rL6LxnbpiiImJkzk+EqERFRH7CClYiIiIiIuqQoCjweTyx4bWhoiAWxjY2NsZbDarU6acthnU43wEdBPbW7eTdOf+90hOXk1UupIkCAQWXAe6e+hxxD97NaiYgGo6FQNRr94oVQg5s35MVJb5+Eel89ZCUz7fqfP+Z5zM2fm5FtERERDScMWImIiIiIqM8ikQiam5s7ha/19fVxLYeNRmPC4NXhcLDl8CD03Mbn8PC6hzOyrT8e8kcsHrs4I9sioni7du2C1+vF9OnTsWfPHnz88cexv+fZ2dk477zzMGbMmIHezbTqrmq0u5+joWlXp9c0Gk2XwWdXP0e/Z9XoyLGyeiUu//TytG9HhIhzJp2DW+fdmvZtERERDUcMWImIiIiIKC0CgUAsbG0fvDY0NMS1HLbZbAnDV4vFwkqbARKWw7jgwwuwrXFb2loFi4KIw4oOw6NHPsr/zkQZpCgKBEHA9u3b8dOf/hS5ubn4+uuv8corr+COO+7AGWecgdGjR6OkpASHHXYY7Hb7QO9yQh2rRvsakvakajTZDNGetNNl1Sj1xT0r78HrP7yetlmskiAh35iP/5z0HxjUhrRsg4iIaLjj5W9ERERERJQWWq0WBQUFKCgoiLu/fcvh9l87d+7E6tWrIcttLfHUajUcDken4DU7O5sth9NMJarw+FGP44IPL0C1tzrlIasoiJjsmIz7DruPwQNRhgmCgEgkgg8//BC5ubmYO3cuWltbYbPZ8NOf/hQPPvhg2vchWjXan3mjgUCg11Wj7WeN9mTeKKtGaaD89qDfotJTia8rv4aM1LYKlgQJFo0Fzxz9DMNVIiKifmAFKxERERERDRqyLKOpqalT+NrQ0AC32x1bzmAwJAxe7XY7T4inUF1rHS779DLsde1N2Sw4AQJm5MzAE4uegFljTsk6iah3XnvtNaxatQrHHnssHnroIbz88svYuHEjrr76ahx55JGw2Ww49NBDcdxxx3V6brRy1OVy9ToU7UnVqCiKsYCTVaM0kgUjQdy47EYsLV+asnVKggSHzoHnj30epZbSlK2XiIhoJGLASkREREREQ0IwGEwYvDY0NCAQCABoq8yyWq3Izs6OVb9mZ2ez5XA/eIIe/HXNX/HmjjchQOhzu8Locy+Zegmunnk1tJI2xXtKRD2xd+9ePPzww7jkkkug1Wpx7bXX4pVXXkEoFMJ9992HwsJC+P1+bNy4EQsWLMC1114baysMtFWfbtiw4f+zd9/hbZV3+8Dvc462JXkPeceJk3iELLKAkMEMMy2jrDLKaguFQksLbXl/pbSMUkYpLfACb9mrzLDKyICEkRACSewsO4lHvJdkydo65/eHY2HFtmwnkrzuz3X5SiwdPc8jJ7asc5/n+8WqVav6jD1Yr1HuGiUanoAcwDM7nsE/vv0HFEU57IoSPa/BJ+SegNsX3o5kfXKEV0pERDTxMGAlIiIiIqIxTVEUdHV19Ru8tre3B0sOq1Sq4G7XpKSkYPCanJwMvV4/ws9idNvdvhs3rLkB9V31RzTOtMRpeHDpg8gx50RoZUTjn6Io8Pl8YXuKDnTf3LlzMXPmTEiSFBzv3//+N15//XW8++67eOGFF/C3v/0N11xzDc4880xkZ2cHj3v11Vfxu9/9DpWVlSEBa8/P3Pb29pBgVKPRQBTFmH99iCaCfdZ9uP3z27GtdRskQRpy0CoKImRFRqI2Eb9b+Ducmn9qlFdKREQ0cfCyQCIiIiIiGtMEQYDRaITRaEReXmi5O1mWYbVa+wSv27ZtQ2dnZ/C4/koO9wSxE3031fM7nsd9m++DgCPf/VtprcTKt1fijmPvwBkFZ0RgdUSjW+9eo4P1G/V6vQPeP1iv0UN3gxoMBiQkJMBkMoXs3JdlGfv27UN5eTmOOuooiKKIqqoqrFq1CnPnzg0JWOPi4uB2uwEgJGDt/TOXiGKjIKEAz5/2PMpay/Dy7pfx/v734Zf9ECCEBK6i0H2RQ8/nM1Nn4qLpF+GE3BOgltQjtn4iIqLxiDtYiYiIiIhoQvJ6vWhvb+8Tvra2tgZLDgNAQkJCv+FrfHz8uC85/K/v/oVHtz4albFvX3g7zp92flTGJjpSPbtGBwtFB+s3OtReo4dbTvdId43KsozjjjsOTzzxBIqKinDnnXdCp9OhubkZ+/btw49+9CNccMEFhz0+EUWHy+/C7vbdKG8rR0VHBRw+B2RFhlbSIs+ch5LkEhQnF7MUMBERURRN7EuxiYiIiIhowtJoNMjIyEBGRkbI7YqiwOl0hgSu7e3t2L9/P7755hsEAt27QlQqVbDP66EfBoNhJJ5SRD1b/mzUwlUAuPOrO2HSmLBi0oqozUETkyzLh1VO93B2jfYOO3U6HeLj4wcNRXs+VCrViF2k0bMjtaurC7NmzYLX64XdbkdnZycEQUBeXh5OPPFErFjB70+i0Uiv0mNW2izMSps10kshIiKasLiDlYiIiIiIaIhkWYbNZgsGrz19XltbW0NKDuv1+gFLDqvVI1Oir7W1Fe+99x6WLVuG3NzcsMfubNuJC967ALIiR3VNOkmHt1e+jUxjZlTnobGh967RI9k56vP5BpxDFMVBg8/Bdo6y1ygRERERETFgJSIiIiIiigCfzxcMW3sHr21tbcE+hgAQHx8/YMnhaIY2brcbL774Ig4cOIDjjjsOS5YsgSRJfZ9HwIfz3jkPVZ1VwR5u0SIJEuamz8WTJz857sstj3eyLB9xOd3D2TU6nHK6I71rlIiIiIiIxg8GrERERERERFGkKApcLlcwbO390d7eHiw5LElS2JLDkQiFZFnGhg0b8OmnnyIjIwM//OEPkZwc2p/tmfJncP/m+6Egdm8V/3r8X8OWClYUBTt37kRHRweOPfbYmK1rIjh01+hwQtLh7hodbOfoYJ9z1ygREREREY0WDFiJiIiIiIhGSO+Sw4d+2Gy24HE6na7f4DU5OfmwSg7X1dXhzTffRGdnJ04++WTMnTsXgiAgIAdw6uunotHZGMmnGZYoiChJLsGLp7/Y7/0NDQ348MMPUV1djZkzZ2LlypUxW9to17Nr9Eh2jno8HsjywKWg1Wr1EZXT5a5RIiIiIiIajxiwEhERERERjUI9JYf7C19dLlfwOLPZ3Cd0TUlJGbTksNfrxUcffYRvvvkGhYWFOOuss7DFugXXrb5uwMc0vdmElrdbQm7TZGgw9Z6p8LZ4seeWPf0+LufnOYifHx/2+f7nzP9getL04OcOhwNr1qzBt99+i9TUVJxyyimYPHly2DHGCkVR4Pf7hxSKut1ueL3efu8Pt2tUEIRgwNlfD9GhlNPlrlEiIiIiIqL+MWAlIiIiIiIaY5xOZ7/Ba1tbW0jJ4cTExH7D194lh/fs2YNVq1ZBURTsK9qHL9u/HLD3atObTejc3In8W/KDtwmSAJVJBUVW4O/0hxzf8WkHWj9oxbSHpkHS9e332kMSJFxafCluPvpm+P1+fPXVV1i/fj0kScLSpUtx9NFHj5qgr/eu0cMtpzuUXaNHUk5Xp9Nx1ygREREREVEUqUZ6AURERERERDQ8BoMBBoMBOTk5IbcritJvyeEdO3bAarUGj9NqtcGwNSkpCUuXLkVZWRlea3wNAXX/4WoPQRSgTuhblri/2zu/6YR5njlsuAoAASWArS1bsXPnTnz88cewWq2YN28eli5dCr1eP8hXY2h6do0eSTldt9s95F2jvUNPs9mM1NTUIZXT5a5RIiIiIiKi0Y87WImIiIiIiCYAv98/YMlhp9MJn+DD23lvhx2j6c0mtH7QCskgQVALMEw2IP28dGiSNX2OdVW5sPePe1Hw+wIYCg2Drk8FFc6uOhuFUwpx8sknIzU1NXjfUHeNDnb/cHeNDrXHKHeNEhERERERTSwMWImIiIiIiCawjo4ObN26FWt3rcUb+jfCHmvfZofslqG1aOGz+tD8djP8HX5M+fMUSPrQXar1z9aja1cXCu8qHPJargpchWRNcp/Q1Ov1DvgYQRAGLac7lJCUu0aJiIiIiIhoqFgimIiIiIiIaIJpbW3Fzp07sWPHDjQ2NkKlUkE/SQ8MXP0WAGA6yhT8uy5HB0OBAbt/vRu2TTYkLUkK3id7ZVi/tCLtrLRhrcvhcSBNn4aUlBTodLoh7RxVq9XcNUpEREREREQxxYCViIiIiIhonFMUBS0tLdixYwd27tyJ5uZmqNVqTJ06FccddxwKCwvxbdu3eOGjF4Y1rhQnQZuhhbc5dIep7WsbFK+ChGMThjVeR3sH9jTv6R5bkqBWq0M+VCrVkG4bzv3cuUpERERERETDxYCViIiIiIhonHvhhRewd+9eaDQa5Ofno6ioCEajEQ6HA5WVldiyZQsqHBXA4K1SQwTcAXibvUg4JiHk9o7POmCabYLKPLy3nCa9CVqvFh6PB4qiwGAwID09HXq9HqIoIhAIwOfzwefzwePxwOFwBD8/9GOoRFEcUiAbLqgdSsgrSRJ32hIREREREY0TDFiJiIiIiIjGgUAgALvdDpvNBpvNhs7OzuCfra2t0Gg08Hq92LNnD/bs6d4lajQaYTKZoFarkanNBBQAYTLAhpcbYJ5lhjpZDb/Vj6a3mgARiF8QHzzG0+SBc48TeTflDWv9WkGLedPnwW63o729PeSjh8FgQHx8PMxmM5KTk2E2m4Ofx8fHw2QyQRRFKIoSEsb2fPj9/gED2f7u7/nc6XQO+BhFUYb0/ARBOOywdrAAt/cxKpWKQS4REREREVGUMWAlIiIiIiIa5RRFgcPhCIamPcFp788dDkfIY3Q6XTB8LCwshNlshk6ng9frRVdXFzo6OtDY2IiGhgYAgEajQbwlHjbYBlyHv92P2sdqEXAEIJkkxBXGoeD2gpCdqh3rO6BOVMNYahzWc5yRNgOnnXpayG1OpxObN2/Gli1bYLPZIAgCzGYzAoEA9u/fD5vNBq/3+/LEgiDAZDIFn3dP8NrzeWJiIgwGQ0QDyEOD3MMNcX0+H9xu94DHBwKBIa9pqLtqExMTkZKSAo1Gg0AggEAgAFmWoSjKkMJfBrlERERERDRRCcpQL7clIiIiIiKiiFMUBW63u8+u00P/lGU5+BiVShUSHB4aJMbHx8Pn86G+vh4NDQ3BD5utOzzVarWwWCwhH8nJyfj9ht/j/f3vI6AMPcyLBEmQcFnJZbhp7k393q8oCvbv348tW7agqKgIJSUlwfvcbnfY4LmzszMknJQkKeTrdOif8fHx0Gq1UX/OwyXL8mGHuP3dVlJSgrlz50JRFCiKEtKLVlEUOJ1O2Gw2dHR09Pn/aLPZ0NXV1W+f3HCB7HB24rJPLhERERERjWYMWImIiIiIiKLI5/P1CacODQF79wwVRTFkF+ah4Z/ZbIZerw/ZPehwOPqEqZ2dnQC6d7IeGqYmJSX1u/vwi7ovcO0n10b/i9KPN856A4WJhREft3dYOFB4bbfbQ0r9arXasAGs2WyGSjUxCkL1/rr0/j+jKAq8Xi/cbjdcLhdcLhe6urrgcDhgt9vR2dkZUlq5v9B3qA7tk3skIW64+0VR5K5cIiIiIiIaEgasREREREREh6l339OBAlSXyxXymLi4uLC7T41GY9gde3a7vU+YarfbAXSHqZmZmSFhamJi4pBDI1mRseL1FWjoaoCC2LxVFCFiZtpMPLvi2ZjM1x9Zlgf8d+z50+l0hjympx/sQLthe/rBUv8G6pMbqXLLR9onN1ohrlqthiRJDHKJiIiIiMY4BqxERERERET9UBQFXV1dg+587E2n04Xd+WgymYa881FRlH7D1J5eq3q9vk+YmpCQcMTBzQs7X8A9m+45ojGG64GlD+CkvJNiOudw+Xy+fkvl9g7TB+oHO1CYHul+sNSXoigh5ZWjFeL6fL6QMt6DGUooGy6oHWq5Zf7/IiIiIiKKDgasREREREQ0Iurq6nDXXXehtrYWOp0O999/P3JycmIyd0/f04F6ntpsNtjt9pDenSqVqk9Adujnh9u7U1EUdHZ29glTu7q6AHTvljw0TI2Pj49KeOKX/bjg3QtQaa2Mei9WSZCwKHMR/nXCv8Z8EKQoCjweT9gA9tB+sL3/Tw3USzeW/WB//etf44svvkB6ejoeffRRZGRkAADq6+uh1+uRmJgYs7WMRf0FuYMFuMMNcX0+X8j/ocH0DmKHG9gOZ6cud2sTERER0UTDgJWIiIiIiCKisbERDQ0NmDp1KuLi4iDLMh588EG8+OKLqKmpwbp161BSUgKgO4j4yU9+gkmTJuH4449HfX09HnzwQXz55ZdQq9VHvJbeuw0H2n166G7D3gFXf7tPD+17ergURYHNZusTpvaUoI2Li+sTpprN5pgGkBUdFTjvnfOiGrAKEKBX6bFq5Sqkx6VHbZ7RpPeu6IHC/UN3RWu12gHLEEeyH6yiKPjoo49QV1eHm266Cd999x0mTZoEp9OJG264Ae+//z48Hg++/fZb5ObmBh9ntVqxdetWZGZmIicnBzqd7ojXQuHJshwSwkYjxO25f6gkSTqs8snDPV6SpCh+ZceudevW4dZbb8WmTZvw2GOP4eqrr4YgCFi1ahWef/551NTU4A9/+APOOOOM4GNkWca7776L+vp6mEwmnHjiiUhPnxg/i4mIiIgi4cjfhRERERER0YT3m9/8BqtWrcKePXvw6aefYvHixRBFEUlJSfjb3/6Gyy+/HK2trcHjOzs78f7776OsrAxpaWkAgNtuuw2rVq3COeecE3aunr6nA+0SHKjvaU8gVVBQ0GeX4GB9Tw+XoiiwWq19wtSe9RmNRmRmZmLevHnBMNVkMo34bs7CxEL8bsHvcOdXd0Z1nruOu2vChKtAd5BvNBphNBqRlZXV7zHh/n/X1dVhx44dYf9/97cLdij/vwVBwCmnnIKtW7diypQpSEhICN5+xx134Kc//SkuvfTSkAC1rq4Ot99+Ow4cOACHwwGz2Yynn346uPOVokMURWg0Gmg0mqjOoyhKMGg9nBC3920ejwcOh2PA44d67b8oilEPccdin9zMzEy8+eabOPfcc+HxeIJr12g0uOSSS/Czn/0Mu3fvxhlnnAFFUSAIAu655x5s27YNaWlpOHDgAMrLy/Hb3/4W8fHxI/xsiIiIiMYGBqxERERENCJklwvunTvhLiuHe+dO+Ds6AJ8Xgk4PdWYmdCXF0JeUQDN5MgSWHhz1fvSjH+Gvf/0rFi1ahI6OjuDt5557LkwmE7KyslBfXx+8XRRFxMfHY/PmzTjttNNgtVrhdrvx9ddf44wzzuhTFvXtt99Ga2srbDYbHA5HyMn43jv8MjMzUVRUFJUdfoNRFAUdHR19wlS32w0AMJlMyMzMxIIFC0LC1NHq/Gnnw+6146EtD0V0XAHdJ/7vPPZOnJB3QkTHHg8kSUJCQkIw4OxPuB3a+/btg81mC9l92HuHdm5uLk488cQ+Y/aELjt37oTJZILBYADQ3Vc4KysLW7ZsQUJCAuLi4oKPefPNN1FWVoZNmzYBAB555BHceOONeOWVVyDLMsvGjmJyQEZbfRdaauxoqbbDYfUg4AtAUkswmNRIzTUhNdeMlGwjDIYjryoQjqIoCAQCw+6HO9B9TqdzwMccSZ/cSIe4keyTO2XKFIiiCJ1OF/zeBYDjjz8eBoMBjz32WMhFE263G8888wwef/xxLF26FAAwY8YMLFmyBKeccsoRr4eIiAamKAp81dVwlZXDXV4Ob20NFJcbUKkgxZuhm14EXUkJdCUlkIxxgw9IRCOGASsRERERxZR79x50vPQibG++BcXjAQQBEEWgd085lQrw+7v/mpGBpEsuRvw550DF/n+j1uzZswF078isra0N3m40GgEAqampqKurA9B9UsFsNuPaa68NnuBNT09HQUFB9wkHn69PwCpJEpKTkzFp0qQR7VHZQ1EUtLe39wlTPR4PAATD3kWLFgXD1J6vxVhy5YwrEa+Nx182/qU7BDnCksGSIEEjaXDXcXfhxLy+IR8NjVqtRnJyMpKTk/u9/9Aew713wQ6mqqoKGRkZwVLdgUAAKpUKVVVVSE1NDfl+O3DgAKZMmRL8XKvVoqqqCgAYro5Sjg4PyjfUofzTOrgc3SG8KAmQA99ftCKKAnZ83gAAUOsklByXidIlWYhPNfQ75pESBAEqlQoqlSrqJaYHC3KHE/L27Mjt7zGH2yd3KCHunDlzkJKS0u9YTqcz5Guo1+sBdJfy7v29KwgCfD5fSEl+p9OJnTt3MmAlIoqSgMMB29tvo+O55+E9+PsSVKru98E9F49KEjrffQ+QZUClgvm005B00YXQzZw5piorEE0UDFiJiIiIKCZ8jY1o+J//h67PPgMk6ftAVVFCw1UgGK4CgL+xEc33P4Dmh/6OlGuuQcpPr4UQ5bKIdPiys7ODQSoA+P1+qNVqZGdn48CBAwAQPDnw61//Ghs3bkRNTQ3OOuss/PrXv0ZLS0u/QWTvvnGxpigK2traQsLUxsbGYJgaHx+PzMxMHHvsscEwtfcuv7Hu3KnnYk76HPx+w+9R1loGAQIUDK2cZw9RECErMhZYFuCOY+5ARhxLyEaTIAjQ6/XQ6/VD7qnYs4N13759sFgswR2oPbvFq6qqkJWVFbIbfM6cOdi1axfWrl2L9PR0vPzyy9BqtWhvb0dSUlJUnhsdHp8ngC/f2ouydd0/h3tX5O0drgKALH//uc8dwNY1tfjuk1pMnZ+OxedPhc4Y3R2t0SRJEiRJivqFOYf2yR1OiNvfjtzenxcVFQ04r9frDdnBKssyJEnqc7tWq8W5556LZ555Bjt37oTX64XdbofX64Xf7w/5PpdlGfX19Whvbx/STl32ySUiCqXIMjqeew7NDz7UfYFxb73e9wIIfV/s96PzvffQuWoV9LNnw3LXX6CdNCn6CyaiIWPASkRERERRpSgKbG++hcY///n7N5TD2NlxcBDA70fro4+i8+OPkPXXv0IX5gQjRZ4sy7Db7bDZbMjOzh5wd1pubi7279/fZ2dMXl4eNm/eHDKeKIpYsGABFixYAK/Xi4aGhmDp0pEqLyrLcr9hqtfrBQAkJCQgMzMTxx13XDBM7X3SerwqiC/A8yuex1uVb+G5Hc9hr20vJEEadEdrzzHFycW4rPgynJJ/Cq++H6V6vt86OztxzDHHBAOWnu/jAwcOYMaMGSHfm+effz66urpwxx13YM6cOfD7/ZgzZ06fsb1eL5qbm2E2m6PW75gGVl/RgY//vQNdHR4MsdVpCOVgVd2KzU2oKW/Hsh9PR8Gs1MgucpyJVZ/cQ3m9Xmg0muAFEz0XSHg8HqjVagQCgWAA+uc//xmPPfYYNm3ahGXLliEtLQ1ZWVn9BqTbt28PlgIfjCiKQy6PPJzb+wty+XpCRKOdt7oa9b+9Fa7vvju8AQ6+b3Zt24b9Z52N1JtvRtJll7KFDtEowYCViIiIiKJGkWU03XMPOp59LkIDKvDu24+q83+E7Ef+AeOSJZEZd4JTFAVdXV0hfRx7/3lo39Prr7++T2nSnpOcRUVF2LJlSzCU6flz5syZeP/991FTU4NAIIBJkyahtrYW//jHP7Bnzx40NDTglFNOwU9/+lMoihKTAEaWZbS2tvYJU3t6VyYmJiIzMxNTp04Nhqk95RYnIkmUcM7Uc/DDwh/iu5bv8N6+97CtZRsqrBXwy6FX32slLaYnTcdRqUfhzIIzUZTMCyJGu8ceewxPPPEEvv32W1RWVuK7777D3Xffjbq6OqSmpqK6uhorV67s8715xRVX4IorrgAALFy4EIWFhX12r9bV1eHZZ58F0B2+mEymYJnvnlLfvct+6/V6BicRsvOLBqx5bicE4LDC1d4UGXA7ffjgse1Y9IPJmHNKXkTWSEeu9/dlRkZG8Pun94USBQUFIeGpRqPBDTfcAKC7PPAtt9yC2bNn9/neE0URp556Kk466aQj2onb+/PefXIP/VCG+B9VEIQhhbL93TfUEDeSfXKJaOJxfvstaq+6GrLbfeSDBQJQAgE033sv3Nu3IfPeeyGox25FCaLxQlCG+psLEREREdEwKIqCpr/8BR3PvxD5wQUBEATkPPYojMcfH/nxx5mBejH2/rx3vzhJkvoNPXr+TE5OHrAE4JNPPok//OEP+PnPf46MjAxcdtlluOaaa/Df//4XNpsNiYmJOPHEE/Hcc8+ho6MDH3zwAbRaLSZPnoxp06ZFLcCUZRktLS19wlT/wbJcSUlJyMzMDAapFosl6r0Axwuf7EOdvQ4uvwuiIMKgMiDTmAlJZJnIscTn86G6uhr19fWoqKjA7t27cdddd+Hvf/87/u///g/V1dUwGo1ISEjAF198gaSkJLzwwgsIBAIoLi7GqlWr8M033+B///d/kZWVFRxXURQEAgG0trYO+HOos7MTsiwHH6NSqfr92dP751KsdwaORbu+asDqp3dGbfyFKwsw99T8qI1PQ3frrbfilVdeQXV1NSwWCxISErB9+3b85S9/wbp167B27VosXLgQkyZNwr///W9oNBo88cQTaG9vh9FoxGeffYYZM2bg97///YiHiYFAICIh7mDHD6dP7lBC2YF65g7nMSP9tSeiyHFt347qH18Kxevt7qcaSYIA08knIeuBByCwLDvRiGLASkRERERR0f78C2j685+jN4EgQFCrMemtN6EtKIjePKOc3+/vs9v00AC1p7wt0L3jw2QyhQ0uDAbDsE/yBQIBXHDBBSgrK0NeXh5SUlKwaNEiXHfdddi+fTsSEhKQlZUVk52pgUCgT5ja1NQUDFOTk5NDwtSMjAyGqURD0NnZiQMHDqC4uBgA8Pzzz+ODDz5AbW0tiouLcddddx1W71VFUeBwOML+HHM4HCGP0el0YXfBms3mCd0LsqHSijfv33LEu1YHc+o1pZg8Jy26k9CQuFwueDwedHV1wel0orCwEHv27EFVVRV8Ph+sViu6urpwzTXXAABeeuklbN68GTabDbNmzcL1118/ws8gtmRZPuwQd7DH9b7Pf2h/xTAkSYp6iKtWq1mmnSjK/K2t2Hva6ZAdjsiHqz0EAclXXYW0X90cnfGJaEgYsBIRERFRxHmrq7HvzLO6r9iNJkmCrrgY+S+/NOjVu42NjbBarZg+fXp01xRBvfueDlS+1+l0hjzGYDCEDR1MJtO4OrEWCATQ3NzcJ0zt2ZmSkpLSJ0zVarUjvGoiGq5AINBn1+uhf7pcrpDHGI3GsBeTGI3GMbVjbPv27cjMzOxTov1QPm8AL92xEY4Od7B/alQIgFavwsV3LITexB3FRP1RFOWwQ9zhBrxDdWif3GiEuD1B7lj6GUsUCYqi4MD118Ox7tNg/9SoEQTkv/wS9DNnRnceIhoQA1YiIiIiiihFUVB90cVwbdsW/TeVB6X95jdI/skV/d7n9/vx6aef4vPPP8fkyZNx8cUXx2RNg1EUBU6nM+zuU7vdHtKLTKPRhASmhwaoZrM52PN0PPL7/X3C1ObmZgQCAQiC0G+YyjKiRBOH1+vt8/P00D97hxC9+8EOVJJ4tPSDVRQFjz/+ONra2rBs2TIsXLhwwItlNrxWgW2ra6O+exUABBGYPDsVp1w9I/qTEdGAesqxH26IO5xyy4fTJzdaIa5arYYkSaPi5zQRANjeew/1v/p1bCaTJKizslDw7jsQ+Z6HaEQwYCUiIiKiiOr68kvUXPGTmM4pmkwo3LAe4iE7E2tra7Fq1Sp0dHTg+OOPx7HHHhuzkpEejyfsSf7Ozs6QsnG9+572t9PKbDZPqDK2vd+mVFVV4aOPPkJzczNkWYYgCEhNTe0Tpo7ncJmIjpyiKHC73YP+bO7dD1atVg/6szlWF3J4vV6sXbsWX331FTIzM3HWWWchPT095BhnpxfP3Po5ZDm2p3ou/H8LkGSJi+mcRBR7iqIEyytHM8T1+XwhP4sHM5RAdrh9dPu7n0HuxNTR0YGNGzdi3rx5YatIKIqCvSefAt+BA4jJVU4HWe65GwkrV8ZsPiL6HgNWIiIiIoqo2uuvh2PtupjtXu2Ree89iD/7bADdJ6FXr16NTZs2ISsrC2effTZSU1MjNpff7+9zYv7Qk/Qejyd4vCAIMBqNYXdJxcXFTfiTNn6/H06nE+3t7WhpaUFHRwcqKyshiiIsFkswUE1PT2eYSkRRIcsyurq6wlYXGKgfbLjqApG8uOfAgQNYtWoV2trasHjxYixevDg4/jf/rcLGt/fF8rwuBFFA6ZIsHP+jqbGblIjGvUAgMOz+t8MNcX0+X7CtxFAMdfftcG8/9P7x1M5jPGhvb8ezzz4Lu92OuXPnYsmSJYiL63tR0UhcaAxRhK64CJNeey228xIRAAasRERERBRBvqZmVC5bBoS54vyR1hb8q60t5LZJGg3em1QAAKjxenFfSzO2uFzwKgqOi4vD79PSkaJSDTyxKEJXUoJJ/3kV+/btwzvvvAOHw4Hly5djwYIFwzpJIcsyHA5H2B1OXV1dIY8xGAxhdziNt76nR0KWZTidTlitVrS0tODAgQOoqamBzWZDIBBAWlpanzBVFe7fnogoxg7tB3toAGuz2eB2u0Me03ORzUCvFcPtB+v3+7F+/Xps2LABKSkpOOuss5BpycQzv/scXdbw/c+tXS14+6snUF67CT6/BynxWbhk6S3IS52GQMCPd77+P5TXbkJbZwN0mjhMz5qDsxZchYS4lAHHVGlE/OS+xVBrY1MlgogoUmRZHnYoe7jB71BJkjSkUPZId+rGqrLPeOD3+7Fx40asX78eiqLg2GOPxaJFi0Iu+jzwi1/AvmZt2AuNm3w+3N/SgvVdDrgVBblqDf5iyUCpTg8AKN69q9/H/So1FVcmDbx7dtIbr0NXXHyYz46IDhcDViIiIiKKGNs776L+llvCHvNIaws+stvxVE5u8DYVgESVCk5Zxg+q9mOaVovrU7pP5D7c2ooWvx8v5eZBDHfyWRBQcccf8e3OncjPz8eZZ56JpKSkkEN6+p6GOyk+UN/T/nYl9fzJ3ZT98/l8aG1txYEDB3DgwAE0NDSgtbUViqJAkqQ+YWpaWhrDVCIaF7xe74AX6fS83vQ+2S6KYsjrSn+vNzqdrk8I29jYiFWrVqGxsRFzShei+qPwP0OdHjvuee1aFGbOwuKSs2DUxaPFVocUcyZS4zPh8jjw5Md34Nii05GVPBlOjx2vffFPyLKM357zaNixV948G1lTEw//i0ZENI4pihISwkYrxB1On1xRFA+rfPJw++aOpz65TqcT69evx6ZNmxAXF4elS5di1qxZEAQBe+YeDdnpHPCxtkAA51Ttx3xDHC5ISECSJKHa50OOWo3cg+0GWg4J4td3OXB7YyP+O6kAOQO1JBBFpP3qV0i+Msa7Z4kIPHtBRERERBHjLi8HVCpgkCu0JUFAaj9B2rcuF+p8Pryelw/jwSuq786wYGFlBb5yOnFMP6WYghQFjV9+iaUrVyIzMxP79+/H1q1b+5zYHqjvaWJiIvLy8vqc0NZqtePmhEA0eTweNDY2or6+Hg0NDcEwFej+OqenpyM3NxcLFy4Mhqm8ap6IxiuNRoPU1NQBy9MrigKXyzXgBT81NTWw2+19+sH2F8AuW7YM+/fvx7fr9sKIaWHX9fF3LyPRmIofL/tN8LYUsyX4d73WiF+ccV/IY84/9he4783r0G5vQpIptOdrD0EAWmrsDFiJiAYgCEIwcIwmRVEQCASGFMgOJch1Op393uf1eocc5AqCEPUQN1Z9cg0GA0455RTMnz8fa9aswTvvvIOvvvoKJ5aWhg1XAeCp9jZkqNW4y/L96272IaHpoe+R1zgcmG8wDByuAoAgwFVePvwnQ0RHjAErEREREUWMa/u2QcNVoLsM8JLKSmhFATN1etyUmopMtRpeRYYAQNPrjbFWECAC2OIKH7AqAIyNTVi3bh2A0L6nZrMZGRkZfXYEse/p4XG73X3C1LaDZZ9VKhXS09ORn5+PY445BhaLBampqQxTiYh6EQQBBoMBBoMBGRkZ/R7Tux/soRcLNTc3o7KyMqQfrMEzCQpkdL9q9m971RcoypmHpz6+AxX125AQl4LFJWfh2KLTB3yMy9sFAQL0WmOYJwQ0V9sHf+JERBRVPWFmLKrCDNQnd6g7b3vf7na7Bzz+SPrkRjrE7bktMTER55xzDhYuXIiPP/4Y6595BscMsrY1DgeOi4vDL+vqsNnlRJpKhQsTEnFeQkK/x7f6/fjM4QgJZAf4h4B769Yhf42IKHIYsBIRERFRxPgbmwY95iidHn+xWDBJrUFLwI9/tbbhxzXVWDVpEmbq9NCLIu5vbcEvU1KhAHigpRkBAC3+8G+sZVFEgiLj6KOPxsyZM2GxWBjqRYDb7UZDQ0NImNre3g6g+wRGRkYGCgoKcNxxxwXDVPabJSI6cqIowmQywWQyITs7u99j/H4/Dhw4gK1bt6JqgxdA+IuGWu0NWL9jFZbPOBcnz74I1c278drnj0ASVVg47ZQ+x/v8Xry98QnMnbIcek2Yi5xkwGF1D3g/ERGNP5IkQZIkaLXaqM7TX5/c4ZRP7m9H7kA7d4fq0D65ORCgIPyr8AGfDy9brbgsMQnXJCejzO3GXc1NUAsCVsbH9zn+bZsNBlHESUbToOvxH7zYlYhiiwErEREREUWM4vMNeszxxu93wExDd+B64r69+G+nHeckJODBzCz8qakRz3d0QARwmtmMYq02zH6cbpIowKTX49Nvv8U333yDgoICHHXUUZg+fTo04UoqUZDL5eoTpnZ0dADoLk1psVgwZcqUYM/UlJQUhqlERCPA7XajvLwc27ZtQ01NDdRqNTLi5sJlDx+wKoqC3NSpOGvBVQCAnJRCNHRUYcOOd/oErIGAH0998icoUPCjxTcOuqaAb2ilIomIiIZDFEVoNJqov6c7tE/uUENcu90OYdt2KIIAIUzZZFlRUHqwehMAFOt0qPB48Iq1o9+A9Y1OG84wm6EdwvutobwPJ6LIY8BKRERERBEjHEZPIbMkIV+jQbXPCwA4Ni4OHxZMRoffD0kQYJYkLK6swArNYGMLmFZSgnnXXx886fzmm29CrVajuLgYRx11FPLz8xkIHuR0OvuEqVarFUB370CLxYKpU6cGw9Tk5GR+7YiIRlAgEEBlZSW2bduG3bt3Q5ZlFBQU4Ac/+AGmT5+OT1+oQEVTE8K1xDMbkpCRmBdyW0ZCLr7b99khc3WHqx32JvzizL+F3b3aQ1Kz5D4REY1dw+2TW1dXhy+//BI7duxAkc83SA2J7v6qk7WhIfFkjQYfO/qW2N/sdGK/14v7LZlDW3uUe/sSUf8YsBIRERFRxKgy0uGrqxvWY7pkGTVeL840m0NuTzzYN+irri60BwJYbgzT+w0AZBmq1FTodDrMnTsXc+fORUdHB7Zt24Zt27Zh69atMJlMmD17NpYuXTqheq92dXX1CVNtNhsAQKvVwmKxYPr06SFh6kT6+hARjWZ+vx+ffPIJtm/fDqfTifT0dCxfvhwzZsyAyfR92UCDWQtBFKAEBk5YCzJK0WytDbmt2XYASab04Oc94WqLrQ43nHk/jLq+u2oOJYiAMUF3GM+OiIho7FAUBXv27MGXX36J6upqJCYmYsWKFZjc2ISmjRvDPnaO3oD9Xm/IbVU+LzJVfcPRN2xWlGh1mK4b2murKjl56E+CiCKGASsRERERRYx+xlFwbd0GhOlf89fmZiwzGpGpVqHZ78cjra2QBAGnm7oD1jdsVkzWaJEoSfjO5cLdzU24NDERkzSD9PaRZehKSkJuSkxMxJIlS3D88cejrq4OW7duxZ49e7Bw4ULo9fojfr6jkcPh6BOmdnZ2AugOUzMzM1FcXBwMU5OSkhimEhGNYp2dnaiursbMmTMxc+ZMpKen93tcWq4JcphwFQCWzzgH9799Az7c8gLmTF6KquZd+Hzne7jw+JsAdIerT358B2pbK/DTFX+BosjodHb33TZoTVBJA+yQUYC0vMF7xBEREY1Ffr8f27Ztw5dffonW1lZkZ2fj/PPPx7Rp0yCKIrw1NWgaZIxLExNxcU01Hm9rxakmM7a7XfiP1Yo/ZmSEHOcIBPCh3Y5b0tKGtjhJgm7mzMN7YkR0RBiwEhEREVHE6EpKwoarANDk9+HX9fWwygEkSRLm6PV4KTcPSQd3rFZ5vXiwpQW2QABZajWuTU7BZYmJg08uCNAVFQ1wl4Ds7GxkZ2cP+zmNZna7vU+Yard3l5jS6XTIzMxEaWlpMExNTExkmEpENMYkJSXh2muvHfS41NzBA868tOm4+uQ7sGrTU/hgy3NINllwzjE/x7zCEwEAVmcrtld/AQC457VrQh57w5n3Y2rmrH7HVZShzU9ERDTWbNu2DR999BG6urowffp0nHXWWcjJyQk5Rp2TA9FggOx0DjjODL0eD2dl48GWFjza1oZstRq3pqXjTHNopYj37XYoQPAC5EEpCvSHXGhMRLEhKEq47hxEREREREPna2pG5bJlgCzHdmJRhK6kBJP+82ps540RRVH6DVMdDgcAQK/XIzMzExkZGcEwNSEhgWEqEdEEosgKnvnd5+iyegc/OMJUGhE/uW8x1Fop5nMTERFF0/r169HZ2YmFCxciOUwp3gO/+AXsa9YCgUAMV9dt0ptvDHixMRFFD3ewEhEREVHEqNPTYFy+DI6162L7xlKWkXTJxbGbL4oURUFnZ2efMLWrqwsAYDAYkJmZidmzZ8NiscBisSA+Pp5hKhHRBCeIAmYszcbGt/chlpfSC6KAomMzGa4SEdG4tHjx4iEdl3jRRbB//EmUV3MIUYSuuJjhKtEIYcBKRERERBGVdPHFcHyyOqZziiYTTKeeGtM5I0FRFNhstj5hqvNgaam4uDhkZmZi7ty5wTDVbDYzTCUion4VHZOJTav2I5bFyhRZQenxWTGbj4iIaDQyLFwIdU4OfAcOIGZXOskyEsfJhcZEYxEDViIiIiKKKMPChdDPmQPX1q0x28Wa8vOfQ9RqYzLX4VIUBVartU+Y6nK5AABGoxGZmZmYN29eMEw1mUwMU4mIaMgMZg1mLM/G1tW1QAzO7QoiMHl2GpIscdGfjIiIaBQTBAGpv7wR9b/6dWwmlCRosrNhPu202MxHRH2wBysRERERRZy3pgb7zjgTijfKfeAkCbqSYuS/9BIEafSUJlQUBR0dHX3CVLfbDQAwmUx9eqaaTKYRXjUREY0HPm8AL9+xEfZ2d3Q30AiAVq/CxX9aCL1RE8WJiIiIxgZFUXDg+l/AsW5d9C82FgTkv/Iy9EcdFd15iGhADFiJiIiIKCraX3gBTXf+OXoTCAIEtRqT3noL2oJJ0ZtnEIqioL29vU+Y6vF4AABmszkYovZ8GI3GEVsvERGNfw2VVrx5/5aoVyg89dpSTJ6dFt1JiIiIxhB/ayv2nn4GZLsdkOXoTCIISL76aqTdfFN0xieiIWHASkRERERRoSgKmu6+Gx3PPhf5wQUBEEXkPPYojIsXR378ASiKgra2tpAwtbGxMRimxsfH9wlT4+JYNpGIiGJv91cN+OTpnVEbf9EPJmPOKXlRG5+IiGiscm0vQ/WPf9xd0SnSIasgwHTyych64P5RVcWJaCJiwEpEREREUaPIMprvvRftzzzbHYpG4ldPSYIgish+5B8wLlly5OMNQJblfsNU78GyxwkJCX3CVIPBELX1EBERDdeurxqw+pmdEBCZl+DugRiuEhERDcb13XeoufIqyG53RMsFm08/DZn33ANBrY7YmER0eBiwEhEREVFUKYoC21tvo/HOO6G43Ud8Ba+msBBZf70XuqKiCK2wO0xtbW3tE6b6fD4AQGJiYp8wVa/XR2x+IiKiaKmv6MDH/94BR7vnyAYSAF2cGst/PB2TZqZGZnFERETjmLe6GvW33gbXt98e2UAHLzJO/dXNSLr0UgiiGJkFEtERYcBKRERERFEne71ouvdeWF948YjGEbRaZN59F8ynnXb4a5FltLS0hISpTU1NwTA1KSmpT5iq0+mOaN1EREQjRVEUlH1ahw2vVkCWj+AUkADMO30Sjj4tH6IoRG6BRERE45giy+h4/gU0P/hg9wXHwNDLSkgSEAhAP2c2LH/5C7STJkVvoUQ0bAxYiYiIiCiqvNXVqL32p/BWVx95fcKDZYbNZ5wBy11/gajRhD08EAj0G6b6/X4AQHJyckiYmpGRwTCViIjGDa/Lj/8+UYbaHe0RGzMtz4TTfn4U4uK1ERuTiIhovAs4utD5ziq0P/ccvPv2d9+oUnWXD+55nyxJ3X+XZUClgvmMM5B00YXQzZgBQeDFTUSjDQNWIiIiIooaT2Ulqi/5MQJ2e0T7zkAQYFi4EDmPPQpR232CNxAIoLm5uU+YGjg4b0pKSp8wVavlyWEiIhqf3F0+vP3Qt2irc0A5sur8IQRRgDFRix/+eg6MibwoiYiIaDgURcH//eUvmAwBRVoNfDU1kF1uQKWCKt4MbVER9CUl0BYVQzLGjfRyiSgMBqxEREREFBW++nrsP+98BKzWyIarPQQB/lkzUXXBBWhoakJzczMCgQAEQeg3TNUMstuViIhovPB7A3jzgW/RUtMZ0XC1hyAC5mQ9zr31aOji1JGfgIiIaJxyOBy4//77cc4556C0tHSkl0NER0A10gsgIiIiovFHkWXU3fKb6IWrAKAokL79DjCZkH766Zg1axYsFgvS09MZphIR0YS28Z39aK7uBKJ0Sb0iA51tLnz20m6cfBVPDhMREQ1VTU0NACA3N3eEV0JER0oc6QUQERER0fjT8dJLcH3zTfTC1YMEAIVfbcSKmTMxf/585OTkMFwlIqIJrXGfDd99XBO1cLWHIgMVm5ux77uW6E5EREQ0jlRVVSExMRFms3mkl0JER4gBKxERERFFlL+jA81/vS9m8ymBABruuCNm8xEREY1WiqJgzbM7IcTqbI8ArH1+FwK+KNQhJiIiGodqamqQl5c30ssgoghgwEpEREREIdxu9xE93vb661C83gitZggCATi//AqefftiNycREdEoVLfHio5GZ1T6rvZLAdwOHyq3NMdoQiIiorHL5XKhqamJASvROMEerERERESEjo4O/Pa3v8X27dvh9/tx00034aKLLhr2OEoggLbnngeU8HUJm3w+3N/SgvVdDrgVBblqDf5iyUCpTt89jqLgkbZW/MdqhV2WMVuvx/+kZyB/oPK/koSOl19Gxu9+N+w1ExERjRfb1x2AIApQ5IFfh61dLXj7qydQXrsJPr8HKfFZuGTpLchLnQYAeG/zM9iydy06HC2QRBVyU6fizHk/QX56Ub/jCQKwbe0BTFuQEZXnRERENF709F9lwEo0PjBgJSIiIpogPB4PvvrqK6xfvx4rV65EaWlp8L6HHnoI8fHxeOWVV6BWq3HKKadAp9Phhz/84aBjNjQ0BD+cmzdjblNT2MfYAgFcXFON+YY4PJ6dgyRJQrXPB7MoBY95qr0dz3d04K4MC7LVajzc1oprDtTinfxJ0Ir9FGEJBGB7402k33YbBEEY3heGiIhoHPC6/dj/XUvYa5ycHjseeOtGFGbOws9PuwdGXTxabHUwaEzBY9Lis3Hesb9AitkCn9+LNdtfwyPv/xb/74JnYdIn9BlTUYDmqk7YWpyITzVE4ZkRERGND9XV1TCbzUhISBjppRBRBDBgJSIiIhqHrFYrNm3ahEmTJqGwsBAA8Nhjj+G9997DJ598Aq1WGxKwrl69GldeeSVyc3MBAHPnzsXTTz+Nk08+GUajMXicoihwOBz46KOPUF9fj/b2dgCASqVCRkYGpvkDUAQBQpizu0+1tyFDrcZdFkvwtuxeO1MVRcGzHe24NjkZJ5i6T/jek2HB4r2VWO1w4DSzud9xZYcDvtpaaA4+ByIioomktdYxWAEJfPzdy0g0puLHy34TvC3FbAk5Zl7hCSGf/3DRz/Dlrg9Q37YP07LnDDh2c5WdASsREVEYPf1XeVEw0fjAHqxERERE48z69etxyimn4NRTT8Xjjz8O5eDZ1pNPPhkfffQR7rzzTuzevRuy3N2gTVEUzJ49G6tWrQIAeL1euFwuHDhwIFjCqIcgCNDr9ejs7MSUKVOwcuVK/OxnP8Ntt92GK6+8EpMCAQj97TDtZY3DgVKdDr+sq8NxlRX4YdV+/MdqDd5/wOdDayCARYa44G0mScJROh2+c7nCju0uLx/y14mIiGg8aa7uxGDna7dXfYHc1Gl46uM7cOsz5+Ce167F5zvfG/B4f8CHz3e+B70mDlnJkwc8TpQENNfYD3fpRERE457X60V9fX3womYiGvu4g5WIiIhonJk+fTreffddvP7661i9ejUCgQBUKhWmTp0KACguLsa7774Lp9MJo9EIQRDw05/+FPfddx+WLFkCSZJw9NFHo6ysDCpV318XVSoVrrjiin7ndu/cCQQCYdd3wOfDy1YrLktMwjXJyShzu3FXcxPUgoCV8fFoDfgBACmHzJ2sUgXv65dKBU9FJbAi7PRERETjUntDFwRBCF5Y1Z9WewPW71iF5TPOxcmzL0J182689vkjkEQVFk47JXjc9uov8e9P/gyf3wOzIQnXn/5XGPXxA44rBxS01Tki+nyIiIjGk9raWiiKwv6rROMIA1YiIiKicSYlJQWCIGDGjBn417/+hc7OTiQlJUE8uLP06KOPRnNzM9ra2oLlf0tKSvDII4+goqIC06dPh1arxXPPPYf4+IFPpvZHdjoHP0ZRUKrT46bUVABAsU6HCo8Hr1g7sHKY8x3O/EREROOR3xMIG64C3VUrclOn4qwFVwEAclIK0dBRhQ073gkJWKdmzsJt5/4vHG4bvtj5Hv7vkzvx6x88ApM+ccCxfe4wF0ERERFNcNXV1TAYDEhJSRnppRBRhLBEMBEREdE409PPZdasWbDb7WhsbAy5PScnB5IkobKyMuRxRqMRs2fPhl6vx7333ovzzz8fpoM9UIdssOZvAFJVKkzWakJum6zRoMF/cOeq1H0NYKs/9ERtm98fvO9I5iciIhqPhvIKaDYkISMxdOdMRkIuOhzNIbdp1XqkxmdhUnoxLl56C0RBwhe7Pgg/P1+CiYiIBlRdXc3+q0TjDANWIiIionFIURTExcXBbDajvLw82G+1R0lJCerr6wEAHo8HAPDBBx/gzDPPxNSpU/HJJ5/g2muvhcFgGNa8Ytzgx8/RG7Df6w25rcrnRaZKDQDIVquRIkn4ytkVvN8RCGCb241Zev0Rz09ERDQeqTUSBmvCWpBRimZrbchtzbYDSDKlh32cAhn+gC/sMRo9i6QRERH1x+/3o66ujuWBicYZBqxEREREY4iiKOjs7MTu3buxbt06vPTSS2hubu73OACYM2cODhw4ECwP7HA4sGHDBmzbtg3XXXcd4uPj8dhjjwEACgsLccstt2DDhg1YvXo1iouLBy01eCjt9CJAksIec2liIra5XHi8rRXVXi/e7bThP1YrLkxMANC90/bSxCQ83taGNQ479njcuLWxAWkqFU44WNK4X34/tFOmDGu9RERE40VSZtyg20iXzzgH+5t34sMtL6DFVoevK1bj853v4fiSswEAHp8LqzY+if1NO9Bub0JNyx48v+4+WLtaMadgyYDjipKA5My4iD4fIiKi8aKurg6BQIABK9E4w8sLiYiIiEapnjC1oaEh+FFfX4+uru6dnQaDAZmZmfD5fFAUJaTUkCAI8Hq9sNlsuOuuu/DEE0/g0ksvxeWXX44nnngCF110EZYtW4YZM2YgNTUViqJgypQpmHJIQDnc8kX6khLY//vfsMfM0OvxcFY2HmxpwaNtbchWq3FrWjrONH/ff/XKpCS4FBn/r7ERdlnGHL0e/5udA60Y/vpAXUnJsNZLREQ0XqTmmgYt05uXNh1Xn3wHVm16Ch9seQ7JJgvOOebnmFd4IgBAFCQ0WWux8aM/osvdCYPOjLzUabjprIdgScofcFw5oCA1b5htBYiIiCaI6upqaLVapKWljfRSiCiCBGW42xKIiIiIKOIURYHNZusTpjqdTgBAXFwcMjMzkZGRgczMTFgsFpjN5gED0K6uLlxwwQXwer1YtmwZZs6ciWOPPRZmszmqz6Nr0ybUXHpZVOcYiBgXh6mbv2ZPGyIimpC8Lj+euPmzoTVjjYKL/7QQCWks1U9ERHSo5557DpIk4aKLLhrppRBRBHEHKxEREVGMKYoCq9UaEqY2NDQEw1Sj0YjMzEwcffTRwTDVZDINKziMi4vDO++8E62nMCDD3LlQpaXB30/Z4qiSJMSffTbDVSIimrA0ehXyZ6SguqwNihy7lFUQgJQcE8NVIiKifgQCAdTW1mLJkoFL7RPR2MSAlYiIiCiKFEVBR0dHnzDV5XIBAEwmEywWC+bNmxcSpo5VgiQh8aKL0PLww4Asx27iQACJF14Qu/mIiIhGoaOWZqNqW2tM51QU4Khl2TGdk4iIaKxoaGiAz+dj/1WicYgBKxEREVGEKIqC9vb2PmGq2+0GAJjNZlgsFixYsCAYphqNxhFedeQlnHsOWv/1Lyheb2wmlCQY5syBtrAwNvMRERGNUtnTExGfpkdni2vQfqyRojWoMGUue8oRERH1p7q6Gmq1GhaLZaSXQkQRxoCViIiI6DAoioK2trY+YarH4wEAxMfHw2KxYNGiRcEwNS4uboRXHRuqlBSk3nwTmu+5NzYTCgIy/vj/YjMXERHRKCaIApb/eDrevP/bmM255KJpUGmkmM1HREQ0ltTU1CAnJweSxNdKovGGASsRERHRIGRZ7jdM9R7coZmQkIDMzEwce+yxwTDVYJjYfciSfvxjdH7wX7jLyoBAIKpzpf3yRmgnT47qHERERGNFZmEijlqWje3rDkR1F6sgApNmpqLw6PToTUJERDSGybKM6upqLFq0aKSXQkRRwICViIiIqBdZltHa2tonTPX5fACAxMREZGZmYvHixcEwVa/Xj/CqRx9BkpD1t/tQdd75CNjt0QlZRRGGhQuRdPnlkR+biIhoDFu4cjLqK61oq3NAiUJLdEEEjAk6LL1oWuQHJyIiGieam5vh8XiQn58/0kshoihgwEpEREQTlizLaGlpCQlSGxsbg2FqUlISMjMzMXXq1GCYqtPpRnjVY4cmJwe5T/8b1ZdeBrmrK7IhqyhCP3sWch75BwQVf6UlIiLqTa2VcNaNs/Dm/VtgbXJGNGQVRAEGswYrb54NvUkTuYGJiIjGmerqakiShKysrJFeChFFgaAo0SwYQ0RERDQ6BAKBfsNUv98PAEhOTkZmZiYyMjKCfzJMjQzPvn2ovfoa+BoaAPkIz/AKAqAoMJ10EjLv+ytE/hsRERENyN3lwwePbUd9hTViYyZnxeGM62fBmKiN2JhERETj0auvvoquri5cccUVI70UIooCBqxEREQ07gQCATQ3N/cJUwMHd1CmpKT0CVO1Wp4kjCbZ5ULT3XfD+up/jmgcQaNBxp/+hPizz4IgCBFaHRER0filyAq2rqnFF69XHnFP1rmn5mHemZMgSWJkFkdERDROKYqCmpoaBAIBFBQUjPRyiCgKWE+NiIiIxjS/398nTG1qakIgEIAgCMEwtbS0NBimajQsZxdrjrVr0fnBfwFRPKJdrIrXi47nnoO+tATaKVMiuEIiIqLxqam6E2Wf1uFIr64XBGDnlw3InJqA3OLkiKyNiIhovBIEATk5ObwwmGgc4w5WIiIiGjP8fj+ampr6hKmyLEMQBKSmpobsTE1PT2eYOsIURUHLAw+i7YknguV9j5gkQVCpkPPovxB3zDFHPh4REdE4VfF1Ez7+dzkARKQPa89L+XHnF2Lm8pwjH5CIiIiIaIxiwEpERESjks/n6xOmNjc3Q5ZliKKI1NRUWCwWWCyWYJiqVqtHetl0iOa//Q1tTz4V+YEFAZAk5D75BOIWLoz8+ERERGNcxeYmfPRkedTGP+68Qsw8gSErEREREU1MDFiJiIhoxPl8PjQ2NvYJUxVFgSiKSEtLCwapFosF6enpUKnY6WC063j1VTT+z/+L3gSiCEGjQcHbb0GTlxe9eYiIiMaYpv2deP2+zRHZtRrOaT8/CpOOSonuJEREREREoxADViIiIoopr9fbJ0xtaWmBoiiQJCkYpvYEqmlpaQxTxyDvgTrsO+MMKG53dCeSJOhnzkTe889BEMXozkVERDQG+H0BvHznJnS2uqIbsAqALk6Ni+9YCF0cq4gQERER0cTCgJWIiIiixuv1hgSpDQ0NaG1tDYap6enpfcJUSZJGetl0hBRFQc1ll8P5zTdAIBCTOdN//3sk/fiSmMxFREQ0mn355l5s+agaiMHZHkEACuel46SflER/MiIiIiKiUYQBKxEREUWEx+PpN0wFAJVK1SdMTU1NZZg6TnVt2oSaSy+L6ZxifDwK138GUaOJ6bxERESjidvhw79/uwFyILanei6+YyES0g0xnZOIiGg02b17N5xOJ2RZRlxcHPLy8qDX60d6WUQURay3R0RERMPmdrv7hKltbW0AusPUjIwMTJo0CccccwwyMzORkpLCMHUC6XjhRUCSYrZ7FQBkmw32jz5G/Bmnx2xOIiKi0WbnFw2Q5diGq4IIlH1Wh+POK4zpvERERKPFww8/jDVr1uCrr75CW1sbjj/+eMycORNXX301ioqKoCgKBEEY6WUSUYRxBysRERGF5XK5+oSp7e3tAAC1Wo2MjIyQnakpKSkQ2QtzwvK3tKBiyVJAHrjpW5PPh/tbWrC+ywG3oiBXrcFfLBko1XVf3fux3Y5XrB0od7thk2W8npePIp0u/MSiCP1RRyH/5Zci+GyIiIjGDkVR8OzvvoCjwxP2OGtXC97+6gmU126Cz+9BSnwWLll6C/JSp/U59qXPHsTnO9/FOYt+jmVHnTPgmGqthJ/cdxxUGl5QR0REE0sgEEBpaSk++eQTZGVl4X//93/xzjvvQJIkNDY24rXXXkN2dvZIL5OIooA7WImIiCjI5XKhvr4+JEzt6OgAAGg0GmRkZKCwsBCZmZmwWCxITk5mmEohujZtChuu2gIBXFxTjfmGODyenYMkSUK1zwez+P0JWZcsY47egFNNZvxPU+PQJpZluLZuhex0QjSwRCEREU08na2uQcNVp8eOB966EYWZs/Dz0+6BURePFlsdDBpTn2O37t+AquadiDckDzq3zxNAc7UdmYUJh7t8IiKiMenLL79Eeno6srKyAACnnnoqPv/8czzzzDO444478NBDD+Fvf/vbCK+SiKKBASsREdEE5XQ6+4SpVqsVQHeYarFYMG3atJAwlSVtaDDu8h2ASgX4/f3e/1R7GzLUatxlsQRvyz6kb+pZ8fEAgDqfd3iTKwrcu3bBMGfO8B5HREQ0DjRX2wc95uPvXkaiMRU/Xvab4G0pZkuf46xdLfjP5//Adafdi0c/+N2g4woC0FLDgJWIiCaepKQkJCcnY/Xq1Vi0aBFee+01uFwuAMD8+fPx8MMPj/AKiShaGLASERFNAF1dXX3CVJvNBgDQarWwWCwoKioKhqlJSUkMU+mwuLdtGzBcBYA1DgeOi4vDL+vqsNnlRJpKhQsTEnFeQsKRTy4IcJeVM2AlIqIJqaXGDlESIAcG7gS1veoLFOXMw1Mf34GK+m1IiEvB4pKzcGzR9z3MZUXGs2vuwQkzz4clKX9okwtAc03nET4DIiKisae4uBhHH300rr/+etTV1eGCCy7A7bffDgD46KOPsGDBghFeIRFFCwNWIiKiccbhcPQJUzs7u0946XQ6WCwWlJSUBMPUxMREhqkUMb6GhrD3H/D58LLVissSk3BNcjLK3G7c1dwEtSBg5cGdq4dNkuBvbjqyMYiIiMaoLpsHijxwuAoArfYGrN+xCstnnIuTZ1+E6ubdeO3zRyCJKiycdgqA7l2uoihhaekPhzy3IgP2dvcRrZ+IiGisuu2223DFFVcAAAwGA8xmMzweDwRBwA9/OPTXUyIaWxiwEhERjWF2u71PmGq3d5eH0+v1sFgsmDFjRjBMTUhIYJhKUaX4fGHvlxUFpTo9bkpNBQAU63So8HjwirXjyANWALJ3mGWFiYiIxomAT0H4eBVQFAW5qVNx1oKrAAA5KYVo6KjChh3vYOG0U1DTsgfrtr+B357z2LB/Zwz4BpudiIho/MrIyAj5XKvV4oEHHhih1RBRLDBgJSIiGgMURek3THU4HAC6r5C0WCyYOXNmMEyNj49nmEoxJ6jVYe9PVakwWRvac3WyRoOPHYP3jRsK8ZB+rkRERBOFpBIgAGFDVrMhCRmJeSG3ZSTk4rt9nwEA9jZsh8Nlxf+8cGHwflmR8cZXj2Ht9tfxp4tfHHh+NX/vJCKiicXhcEClUkGn0/W5z+l0wmAwQJZliKI4AqsjomhjwEpERDTKKIqCzs7OPmFqV1cXACAuLg4WiwWzZ88Ohqlms5lhKo0KqvR0+OrqBrx/jt6A/YfsMq3yeZGpCh/MDoksQ0pOOfJxiIiIxiCDWQNBFKCE6cFakFGKZmttyG3NtgNIMqUDAOZNPRHTskN7mf/zvd9i/tSTsHDaqQOOK4hAXLz2CFZPREQ09vzkJz9BS0sLli9fjvnz56O4uBiJiYkwGo247bbbkJCQgDvuuGOkl0lEUcKAlYiIaAQpigKbzdYnTHU6nQAAo9EIi8WCuXPnBsNUk8nEMJVGLf2MUri2bQP8/n7vvzQxERfXVOPxtlacajJju9uF/1it+GOvckrWQAANPh+aD45RdTCQTVGpkKoK8+urLENXUhy5J0NERDSGpOaaIIcJVwFg+YxzcP/bN+DDLS9gzuSlqGrehc93vocLj78JAGDUxcOoCy3ZL4kqmPVJSE/IGXhgBUjLNR/xcyAiIhpL1qxZg2uvvRbbt2/HCy+8gEAggLy8PJx44ol499138dhjj430EokoihiwEhERxYiiKLBarX3CVJfLBQAwmUywWCyYN29eSJhKNJboSkoGDFcBYIZej4ezsvFgSwsebWtDtlqNW9PScab5+5O5ax12/L6xMfj5rxrqAQA/T07G9Smp4ecvZsBKREQTU2ru4L835qVNx9Un34FVm57CB1ueQ7LJgnOO+TnmFZ54RHMrCpCax99biYho4qirq8NJJ52E22+/PVgiuLKyEuvWrcPq1atRXV2NJUuWjPAqiSiaBEVRwl/eSERERMOmKAo6Ojr6hKlutxsAYDabYbFYYLFYgmGq0Wgc4VUTHTlfYyMqly3vPtMaQzKAzqRE1N18M0pKSlBYWAhVuN2uRERE44wiK3j61s/h7PQOfnCEqdQirrjvOGh0fO0lIqKJ48CBA9DpdEhJSYGiKMFqY3v37sUFF1yAr7/+eoRXSETRxN98iYiIjpCiKGhvb+8Tpno8HgBAfHw8LBYLFi1aFAxT4+LiRnjVRNGhzsiAcckSONavBwKBmM0rAlCddTZaW1vx6quvQqPRoKioCCUlJSgoKIAkSTFbCxER0UgQRAEzlmZh0zv7Y3qdkyAKmL7IwnCViIgmnOzs7ODfBUGALMsQRRFtbW345S9/OXILI6KY4A5WIiKiYVAUBW1tbX3CVO/BHpEJCQl9dqYaDIYRXjVRbDnWb0Dt1VfHdE4xLg6FG9ZD1OvR0tKC8vJylJWVoa2tDXq9HkVFRSgtLUVeXh5EUYzp2oiIiGKly+bBM7d9DkWO7bwX3D4fyVmsxkJERBPH/v37kZqa2m81surqauTl5Y3AqogolhiwEhERDUCW5T5hamNjYzBMTUxMDAlTMzIyGKYSAVBkGVU/ugDuHTtitos19eabkXJNaKirKAqamppQVlaG8vJyWK1WGI1GFBcXo7S0FNnZ2cESTkREROPFI7/7D4T25JjMJYhA/owUnPazo2IyHxER0Wiwa9cuFBcXY9myZTjqqKNwzDHH4KijjkJ2djbi4uJgNptRX1/PVlBE4xwDViIiInSHqa2trX3CVJ/PBwBISkrqE6bq9foRXjXR6OXZtx/7zjoL8PujO5EkQTt1Kib951UIYXquKoqCuro6lJWVYceOHbDb7YiPjw+GrRaLhWErERGNeffeey/efvMd/OS4P8PbJUe9VLBGL+HiOxbBYNZEdyIiIqJR5PHHH8dLL72EX/3qV3jrrbewZcsWWK1W5ObmIiEhATU1Nfj2229HeplEFGUMWImIaMKRZRktLS19wlT/wSAoOTm5T5iq0+lGeNVEY0/b//0bzX/9a/QmEARAkjDpjdehmzp1yA9TFAU1NTXBsNXpdCIpKQklJSUoLS1FWlpa9NZMREQUJRs3bsR1112HdevWwVbnw1sPRv/E7klXFmPqvIyoz0NERDSavPDCC2hpaQnps9rY2Ig9e/bgmmuuwbJly/Doo4+O3AKJKCYGvsyfiIhGjXZ3Ozo9nZAVGRpJg/S4dKhF9Ugva0wIBAJ9wtSmpqZgmJqSkgKLxYLi4uJgmKrVakd41UTjQ9IVl8Ozfz9s//lP5AcXBEAQkP33h4YVrnY/VEBeXh7y8vKwYsUK7N+/H2VlZdi0aRPWr1+PtLS0YNialJQU+bUTERENQg7IcHR44PfJEEUBGr0KepM6bLUFRVGQnZ0No9GIdRXvYmvresxMOSVqa5x3ej7DVSIimpAuvvhiyLIMWZaDr80ZGRnIyMjA0UcfjRNOOGGEV0hEscAdrEREo1BTVxPe2fcOtjRtQVlrGTo8HSH3q0QVChMKcVTqUVieuxwLLQshCuIIrXb0CAQCaG5u7hOmBgIBCIIQDFN770zVaFjOjCialEAAjX+6E9ZXXoncoJIECAKyHrgf5pNPjtiwfr8fe/fuRXl5OXbt2gWfzweLxYLS0lKUlJQgPj4+YnMRERH1pigK6vdYsXdLMxr3d6KtzgE5EHq6RhenQlq+GZbJ8Zi20AJTUmiFlYqKClx//fV44okncNNNN+Hmm2+Gv9mI7f9tBaBAiMT7BQGAAsw7YxLmnZ7P8vpERESH+OKLLzBr1iwYDIaRXgoRRRkDViKiUeS75u/wdPnTWFuzFhC6T7QoGPjHtCRICCgBZBmzcHHRxTh/2vnQShNj96Xf7+83TO25ejA1NTUkTE1PT2eYSjRCFEWB9eWX0XTPvVD8fiAQOPzBBAHqnBxk3fdX6GfOjNwiD+Hz+bBnzx6Ul5djz549CAQCyMnJQWlpKYqLi2E0GqM2NxERTRwBv4wdG+qxdU0tbM0uCKIARQ5zmqa7gAMUBcifkQxXXB3qbZXo6urCbbfdhvPOOw9ff/01LrnkEvz5z38GAHzz6S6se24P9GrjEfVkFURArVVh6cXTUHh0+uEPRERENI7IsgxR5KYHoomIASsR0Sjg9Dnx0JaH8NKul4Kh6XAI6L5yPMeUg7sX342jUo+KxjJHjN/vR1NTU0iY2tzcHAxT09LS+oSpajVLKBONNt4DB9Dwu9/DuWlT9y7U4QStB9+wJl1xOVJvuAFiDEt5ezwe7N69G2VlZdi7dy8URUF+fj5KSkpQVFTEK5OJiOiwtNTY8fH/laOj0XmYIygABHjimvDx9ueRlJqAJ598EitXrsSWLVuwfft2ZGRk4E9/+hO2b92Bn539/7DziwYIIqDIQ5+lJ/QtmJWCJRdNh8HMixaJiIh6VFRUICMjAyaTaaSXQkQxxoCViGiE7W7fjV+s+QWaupogYxhnOvohCiIURcFPZ/4UP5v5szFZssvn8/UbpiqKAlEU+w1TVSq2FCcaS1zbt6PjxRfR+e57UHy+YHgKudfPQJWqO4BVFEjJyUi86EIknHse1OlpI7Pog1wuF3bu3ImysjJUVVVBEARMnjwZJSUlmD59Ons4ExHRoBRFwZYPq7Hx7X3dVWuO7C0ABAFQG0R8tPv/8H8v/RMmkwk/+MEPAABarRbt7e146623YDAYYGtxoXx9HcrX18Pr8h/cERu6a1YQASjdu2RVGhFFiywoWZKF5ExWbyAiIupNlmXce++9OO6447B48eKRXg4RxRgDViKiEbStZRuu/uhquANuyEd6ZuUQ5009D39Y+IdR3ZvV6/X2CVNbWlqCYWp6enpImJqWlsYwlWgcCdjtcJeVwV1eDveOHfC3t0Px+iDqdFBnZ0NXUtL9MX0ahFH4ve9wOLBjxw6Ul5ejpqYGkiShsLAQpaWlmDp1KnfSExFRH4qi4PPXKrF1dW1ExxUEwOf3ouAENc684AQAQE1NDaxWK6ZMmdKn2kLAJ6Ol1o6WGjuaa+xwtLsR8MmQ1CIMZg1Sc01IyzMhNdcMtVaK6FqJiIjGi/r6ejzxxBO44oorkJubO9LLIaIYY8BKRDRCKjoq8OP3fwxXwBXxcLXHpcWX4pZ5t4Q9RlEUbN68Gbt27cIll1wStV2vXq8XjY2NIWFqa2srFEWBJEl9wtTU1FSGqUQ0ZthsNpSXl6O8vBz19fVQq9WYNm0aSktLMXnyZP48IyIiAMDGVfuw+f2qqIytKN0B6Tm3HI3VX7yHFStWICEhISpzEREREfDll19izZo1uPXWWyFJvCCJaKJhwEpENAK8AS/Ofedc1HTWDLvf6nA9svwRLMlZ0u99Pp8P7777LrZt24ZFixbh5JNPjsicHo+n3zAVACRJQkZGRp8wlb+IEtF40d7ejvLycpSVlaG5uRlarRZFRUUoKSnBpEmT+POOiGiCOrCrHW8/9F1U5xAEAGofnvj0Nnyy5mMkJydHdT4iIqKJ7JVXXoHb7cZll1020kshohHAgJWIaAQ8vOVhPLn9SSiI7o9gESLidfF4Z+U7iNfGh9zX1taGV199FR0dHTjzzDMxY8aMw5rD7Xb3CVPb2toAACqVqk+YmpKSwnCBiCaM5ubmYNja3t4Og8GAoqIilJaWIjc3F6I4esu4ExFR5Hjdfrz4x41w2jyI9lkYRZExZWEyTr1idnQnIiIimsAURcF9992H+fPnY+nSpSO9HCIaAaxVRkQUY/tt+/HU9qeiHq4CgAwZNo8N//j2H/jDwj8Eb9+5cyfefvttGI1GXHXVVUhLSxvSeC6Xq0+Y2t7eDgBQq9XIyMjA5MmTcdxxxwXDVIYHRDSRpaWlIS0tDUuXLkVjYyPKyspQXl6Ob775BiaTCcXFxSgtLUVWVlbUSrQTEdHI2/xeVUzCVQAQBBF7N3ag5UQ7UnNM0Z+QiIhoAmppaYHL5UJeXt5IL4WIRggDViKiGHtl9yvdJ9FjVD9AVmS8WfEmbpxzI+JUcVi9ejW++OILFBUV4eyzz4ZWq+33cS6XCw0NDSFhakdHB4DuMNVisaCwsDC4MzU5OZlhKhHRAARBCO7mP/HEE3HgwIFg2Lpx40YkJCSgpKQEpaWlSE9PZ9hKRDSO+DwBlH1WF5NwtYcgCti+9gCWX1oUu0mJiIgmkOrqaoiiiOzs7JFeChGNEAasREQx5PQ58UbFGwP2XW16swktb7eE3KbJ0GDqPVMBAD6rD42vNKKrvAsBdwBaixapZ6Qifl58f8MF+WQfXtvxGsStIqqrq3HSSSdh0aJFwRP4TqezT5hqtVq759doYLFYMG3atGCYmpSUxDCViOgwCYKAnJwc5OTk4JRTTkFNTQ3KysqwZcsWfP7550hOTkZpaSlKSkqQmpo60sslIqIjVLG5CT5P/7//97B2teDtr55Aee0m+PwepMRn4ZKltyAvdRoA4Lm192Ljno9CHlOUPQ/XnX5Pv+MpsoI9mxpxzDlToItTR+aJEBERUVB1dTUyMzOhVvN1lmiiYsBKRBRD62rXweV3hT1Gm6VF/i35wc8F6ftdTAeeOADZKSP3l7lQGVWwfmVF7b9qofmjBvo8/YBjKlDw72/+jbOtZ+P888+HSqXC+vXrg2GqzWbrnlurhcViQVFRUUiYyp1URETRIYoi8vPzkZ+fjxUrVmD//v0oKyvDV199hU8//RTp6enBna2JiYkjvVwiIjoMO79oAAQMWMHG6bHjgbduRGHmLPz8tHtg1MWjxVYHgya0vG9xzjxcsvQ3wc9VUvgTugG/gn3ftqD4uMwjfQpERETUi6IoqK6uxsyZM0d6KUQ0ghiwEhHF0PbW7VAJKvgV/4DHCKIAdUL/J0tclS5YLrXAUGAAAKSdlYa2D9vgqnKFDVgBwCpZ4Ycfr7zyCgBAp9PBYrGgpKQkGKYmJiYyTCUiGiGSJGHKlCmYMmUK/H4/KisrUV5ejvXr12PNmjXIyspCSUkJSkpKYDabR3q5REQ0BLKsoKXaHrY9yMffvYxEYyp+vOz78DTFbOlznEpSw2xIGvLcoiigqaqTASsREVGEdXR0wOFwsP8q0QTHgJWIKIa2t24PG64CgKfJg12/3AVBLcAw2YD089KhSdYAAPRT9Ojc1AnTTBMkgwTbJhtkn4y46XGDzq0ICgKJASw9eilKS0u5M5WIaBRTqVSYPn06pk+fDq/Xiz179qC8vByrV6/GRx99hNzcXJSWlqK4uBhxcYO/BhAR0cjoaOxCwC+HPWZ71RcoypmHpz6+AxX125AQl4LFJWfh2KLTQ46rqN+KW585BwatEVOzZuOMeVfAqBu4VYgsK2jab4vI8yAiIqLvVVVVBVu/ENHEJSiKEuY6SiIiiqQFLyyA0+8c8H77NjtktwytRQuf1Yfmt5vh7/Bjyp+nQNJLCHQFUPtoLRxlDkACRI2InOtyYCo1DThmb4tsi5DVkQWtVouCggIUFBRg8uTJLDtJRDRGuN1u7Nq1C+Xl5di7dy8AYNKkSSgtLcX06dOh14evZkBERLFVsbkJHz1ZHvaYXz55KgBg+YxzMXvyElQ378brX/wTP1r8SyycdgoAYHPlGmhUOiSbMtDaWY93Nj0FrVqPX638B0RRGnBsQRTws38u5YWVREREEfTWW2+hubkZ11xzzUgvhYhGEHewEhHFkDvgDnu/6ajvg1Jdjg6GAgN2/3o3bJtsSFqShKY3mhBwBpD/m3xIRgn2LXbU/rMWBb8rgC5HF3ZsAQIWn7AYyxOWo7KyEvv27cP7778PRVGQlJSEgoICTJkyBfn5+dBqtRF5vkREFFk6nQ6zZs3CrFmz4HQ6sXPnTpSVlWHVqlV49913MWXKFJSUlGDatGn8WU5ENAr4PIFBj1EUBbmpU3HWgqsAADkphWjoqMKGHe8EA9ajpywPHp+VXICs5AL88aUfo6J+K6Zlzxl4bFmBHFAgqRiwEhERRUp1dTWmTZs20ssgohHGgJWIKIaGWzRAipOgzdDC2+yFp9mD9tXtmPKXKdBldYep+lw9uvZ0oW11G7Iuzxp0PFmWkZWVhaysLCxZsgRutxtVVVXYu3cv9u7di82bN0Oj0eCGG25gyUkiolHOYDBg7ty5mDt3Lux2O3bs2IGysjK8+eabUKlUmDp1KkpKSlBYWAi1uv/e3kREFGVD+PXfbEhCRmJoD7eMhFx8t++zAR+TYs6EURePls46TMPAASsw/PcgRERENDCbzQar1Yr8/PyRXgoRjTAGrEREMaSVtIPuYu0t4A7A2+xFwjEJUDwHT4wccvG5IApDOnGjKArWfrQWje83wmQywWg0Bv9MTk5Gfn4+ZFmG1+uFJA1cZoyIiEYfk8mEBQsWYMGCBbBarSgvL0d5eTn+85//QKPRYNq0aSgtLcXkyZP5M56IKIZUGnHQYwoyStFsrQ25rdl2AEmm9AEf0+FoQZe7E2ZDctixBQGQVIOvgYiIiELJsoy9e/diypQpIaX2q6urAQC5ubkjtTQiGiUYsBIRxVBBfAF2tO8Y8P6GlxtgnmWGOlkNv9WPpreaABGIXxAPySBBk65B/dP1yLggo7tE8Dd2OModyPtl3oBjBgnA6YtOh0W2wG63w+FwwGq1ora2Fna7HX6/P3jou+++C61W2yeINZlMff6u0Wgi8aUhIqIISUhIwLHHHotjjz0WbW1tKC8vR1lZGbZv3w6dToeioiKUlpYiPz8fosiT7kRE0ZRoGbwqzPIZ5+D+t2/Ah1tewJzJS1HVvAuf73wPFx5/EwDA43Ph/c3PYlbBYpgNSWi11eOtjf+LlPhMFOUcHXbs+DQD+68SEREdhra2Nrz44ou48sorkZ2dHby9uroaqampMBgMI7g6IhoNGLASEcXQjNQZ2NOxB37F3+/9/nY/ah+rRcARgGSSEFcYh4LbC6Ayd/+4zrspD03/aUL1Q9WQ3TK06VpkXZUF00xTv+P1JkDAGfPPgF6l73OfoijweDzB4NVutwc/HA4HOjs7UVdXB7vdDp/PF/JYjUYz5CCWJ3eIiGIrOTkZxx9/PI4//ng0NzejrKwMZWVl+PbbbxEXF4fi4mKUlJQgNzeXP6OJiKIgKTMOoiRADgxcciYvbTquPvkOrNr0FD7Y8hySTRacc8zPMa/wRACAIIioa9+HjXs+gsvrQLwhGdOzj8YZ8y6HWhr4YkdBFJAxyRzx50RERDQRJCUlQaVSoaampk/AOmnSpBFcGRGNFgxYiYhiqDSlFK/sfmXA+3N+nhP28doMLXJ/cXglSPLMef2GqwAgCAJ0Oh10Oh1SU1MHHENRFHi93gGDWLvdjoaGBtjtdni93pDHqtXqIQWxWq2WJ/mJiKIgLS0Ny5cvx7Jly9DQ0ICysjKUl5fj66+/hslkQklJCUpLS5GZmcmfw0REESJJIpKzjGipsYc9bkbeIszIW9TvfRqVFteffu+w51YUBal5DFiJiIgOhyRJyMrKQm3t92X8HQ4H2trasHTp0pBjd+/ejX379mHFihUxXiURjSQGrEREMbQsZxnUoho+2Tf4wREkQsTZU84+4nEEQYBWq4VWq0VKSkrYY8MFsQ6HA01NTbDb7fB4PCGPU6lUQwpidTodAwAiosMgCAIyMzORmZmJk046CbW1tcESwl999RUSExODYWtaWhp/1hIRHaFpCzIGDVijQRAETJ4z8MWTREREFF5OTg6+/fZbKIoCQRBQU1MDAMjL+75V14EDB/Daa69hxowZI7VMIhohDFiJiGIoXhuPMwrOwKq9qxBQAjGbVxAE/GDKD2I2H9BdOjg5ORnJyclhj/P5fGGD2JaWFtjtdrjd7pDHSZI0pCBWr9czHCAiGoAgCMjNzUVubi5OPfVUVFVVoaysDJs3b8aGDRuQkpKC0tJSlJaWDvrznIiI+jd9UQa+fLMSAf/AZYIjTRAFTJ6dirh4bczmJCIiGm9yc3OxYcMGdHR0ICkpCdXV1UhKSoLJ1N2qy2az4eWXX4bFYsFpp502wqslolhjwEpEFGMXTr8Qb1a+GbP5JEHCqfmnIlk/Ok+Mq9VqJCUlISkpKexxPp8vGLr2F8RWV1fDbrfD5XKFPE4UxSEFsQaDgUEsEU1ooiiioKAABQUFOP3007Fv3z6UlZXhiy++wLp165CRkYHS0lKUlJQgISFhyOP2XO1NRDRRaQ1qTFtkQfn6OgiIzc9DRVYwY1n24AcSERHRgHp6r9bW1gYD1tzc7tZdHo8HL774ItRqNX70ox9BpWLUQjTR8LueiCjGipKLcP7U8/FaxWuQFTmqcwkQoJN0uPnom6M6Tyyo1WokJiYiMTEx7HF+vz9sEFtbWwu73Q6n0xnyOFEUYTQahxTEiqIYzadKRDTiJElCYWEhCgsL4fP5UFlZibKyMqxbtw6ffPIJsrOzUVJSgpKSkuDV2wPZuHEjrr32WsyfPx/nn38+TjrppBg9CyKi0WNT9XtQ+6dBqzJEfS5BAKYuyEDmlISoz0VERDSe6fV6pKamoqamBlOnTkVTUxMWLlwIWZbx+uuvw2az4Sc/+Qni4uJGeqlENAIERVFiV6OGiIgAAE6fE2e9dRZanC2QEd2Q9a7j7sKZk8+M6hxjUSAQCBvE9nze1dUV8jhBEIYUxMbFxTGIJaJxx+v1Yvfu3SgvL0dFRQVkWUZ+fj5OPvlkZGRkDLhTtba2Fu+//z6ef/55nHnmmfjNb34T45UTEY2cjRs34rrrrsMzD7+Bdc9WRncyAdAb1bjojwuhi1NHdy4iIqIJ4J133sGBAwewfPlyvPzyy7jhhhuwceNGbNq0CRdddBGmTJky0kskohHCHaxERCPAoDbgviX34coPr4QiK1AQ+WtdBAhYMWkFzig4I+JjjweSJCE+Ph7x8fFhjwsEAujq6howiG1oaMCePXvQ1dWF3tcsCYKAuLi4IQWxkiRF++kSEUWERqPBjBkzMGPGDLhcLuzatQvl5eWIi4sLWwY4JycH1157LZYsWYIrr7wS1157LTo7O/H444/DarXikksuwcKFC2P4TIiIYkdRlO6d/8fkYvO6nbBXq6JWOl0QBJx0ZQnDVSIiogjJycnBli1bsHfvXpjNZlRWVmLjxo1YsWIFw1WiCY4BKxHRCJmdNhsPLXsIN665EbIiR3QnqwABS7KX4M/H/Zl9746QJEkwm80wm81hj5NlOWwQ29TUhMrKSjgcDhxaPGIoQazRaGQQS0Sjil6vx+zZszF79uywx23btg3/8z//gylTpkAQBDidTqjVapxxxhk477zzkJaWhmuuuQZPPvkk5s+fH6PVExENnezxwLNnD9zl5fDs2YOAwwEogKjXQ1MwCfqSEmiLiiEZ+y8PmJycDJfLhZqaGqz65gn88OjrYa2OcBUbARAAnHJVCXKmJ0V2bCIioglAdrvh2bULrvJyeCorIXd1AQoQL4oorK1Fm9eLlPx8fPDBB5g/fz7fuxARSwQTEY20jQ0bcdPam+D0OxFQAkc0lgABChT8YMoPcPui26EWeeX6aCPLMpxO56CliR0OB2Q59MSbwWDoN4A99DaVitdPEdHo8vXXX+Omm27C0qVLcdNNN+HRRx/Fp59+io8//hgA8Pjjj+OLL77AM888M8IrJSL6nmv7dnS8+CI6330Pis/X3dxUkgBF6f4QRUAOALICCAKMS5Yg8eKLEXfsMXjv/fexb98+dHV14bbbbsN5552Hr7/+Gpdccgn+9Kc7sf6VPSj7tA6KIkMQjqythCACKrWEk68qQf6MlAg9eyIiovFPURS4vv0WHS+8iM4PPwT8/u9f73vOyYgiFL8fAgBZEGCbNg1H/fY3iFu4kJsaiCY4BqxERKNAq6sVd351J9bUrIEoiJCV4V/RLgkSTBoT7jjmDizPXR6FVVIsKYoy5CA2EAgN5vV6/ZCCWLWaATwRRY/H44FWqw1+3tjYiEsuuQR/+9vfcMMNN+C2227DihUrAAC33XYbampq8MILL0CWZfawJqIR5d6zBw1/uB3ubdu6T7AGhngR5MFjPYmJuN/Zhennn49169YhLS0NTz75JFauXIktW7Zg+/btyMjIwN2/exjalknQqeJwWGdmBAAKkFuShGWXFMGYqB30IURERNTNtb0MDbffDs+uXYf1eq8pmATLn/8Mw5w50V0oEY1aDFiJiEYJRVGwumY1nip7CmWtZZAEadAdrSJEyJBhVBtx7tRzcdWMqxCvDd9TlMYXRVHgcrkGDWLtdnufIFan0w0piNVoNCP07IhoLHv11VehVqvxgx/8AACwdu1aXH755fjwww+xYsUK7N+/P3jsihUrcM455+Cqq64aqeUSEUHx+9H25JNo+ccj3TcM9UTrIQJQIEFAwo/Oh3XlStzwm9/gjTfegMlkCv5M1Gq1aG9vx6svvYadn7WgfH0dPE4/BAGDhq2CKECRFaTkGDHn5DxMOTqNO2iIiIiGSPZ60frPf6HtiSe6d6se5us9RBFQFCRdeilSf3kjRL0+sgslolGPASsR0Si0s20n3qh4A980fYN9tn39Bq1JuiTMSJmBE/NOxKn5p0Kn0o3ASmmsUBQFbrd7SEGs3+8PeaxWqx1SENt7pxoR0SuvvIJ//OMf8Pv9mDZtGurr63HqqaciNzcX//rXv7B27VoAwK5du3D55Zfj4YcfZh8jIhoxssuFA7/4Bbo2fB65QUUR6rw8XNPYgN//7W844YQTAAA1NTWwWq2YMmUKDAYDACDgk1G5pRl7tzSjaX8nnJ3ePsMJIpCQHofMwgQUHWNBer45cmslIiKaAAIOB2qvuRaub78d/IqmoRIEaIuKkPvUk1AlJkZmTCIaExiwEhGNct6AF3ute2H32uFX/NBJOuSac5GiZ38lijxFUeDxeIYUxPp8vpDHqtXqYOA6WBDLXRZEE0dVVRU+/PBDLFmyBFOnTsXq1avxwgsv4OmnnwYAXHnllfB6vXjqqaeCO+YVRYHVakVCQgJ/XhBR1MkeD2qvvgbOzZu/77cWKZKENkFAwuOPofTYY/HSSy9hxYoVSEhICPswZ6cXtmYn/D4ZgihAq1ch0WKASi1Fdn1EREQThNzVherLL4e7fEdUXu81BQXIf+F5SGZeAEU0UTBgJSIiosMy1CDW6w3dgaFWq4e0I1an0zFYIRqHurq6cP7556OxsREFBQXo7OzE3//+d0yfPj14jCzLuO+++2AwGFBSUoLS0lKkpaWN4KqJaDyr+81v0fnuu5E/2XpQAIC6sBAbzjoTDz38MNatW4fk5OSozEVERER9KYqCAz+/Do5PP43a6z0kCYa5c5H79L8hiGJ05iCiUYUBKxEREUWV1+sdUhDr8XhCHqdSqYYUxOr1egaxRGPQd999h61bt+Lcc89FXFxcyH2KomDfvn0oKyvDrl274Ha7kZaWFgxbk5KSRmjVRDTe2NeswYGfXxf1eRQAiit2agAAKWFJREFUr+t0+Ml77yIrKyvq8xEREdH3rG+9hYZbb4vJXOn/czuSLrooJnMR0chiwEpERESjgs/nG1IQ63a7Qx4nSdKQgliDwcAglmgMCgQC2Lt3bzBs9fl8sFgsKC0tRUlJCeLj40d6iUQ0RgWsVuxdcRoCVmvk+rCFI0koeOtNaAsLoz8XERERAQB8Tc3Yd9ppkJ3OmLzeC1otCt57F5rs7KjPRUQjiwErERERjSl+v39IQazL5Qp5nCiKQwpi4+LiGMQSjVI+nw8VFRUoKytDRUUF/H4/cnJyUFpaiuLiYhiNxpFeIhGNIS3//Cda//mv6JUKPJQkwXTiicj++0OxmY+IiIjQdM+9aH/uOSAQiM2EkoSEH/4Qljv/FJv5iGjEMGAlIiKicSkQCPQbxPb+0263w+l0hjxOFEXExcUNKYgV2VeFaMR4PB7s3r0b5eXlqKyshKIoyM/PR0lJCYqKimAwGEZ6iUQ0iik+HyqWLkOgrS22E4sipqxbCzX7ShMREUWd7HKh4rjFkLu6YjqvoNGgcMN6SGZzTOclothiwEpEREQTWiAQQFdX16BBbNchb8gEQegTxPYOYXvfNtqC2HXr1mHNmjW48cYbkZCQgKqqKiQkJCA5OXmkl0Z0WFwuF3bu3Iny8nLs378fgiBg8uTJKCkpwfTp06HVakd6iUQ0ynR+9BHqbrgx7DFNPh/ub2nB+i4H3IqCXLUGf7FkoFSnDx6z1+PBAy0t+NrlREBRMFmrxUOZWchUq/sfVBSRct3PkXpd9Pu+EhERTXTW199Aw+9/H/aYwV7vu2QZD7Y0Y7XDAWsggCy1GpckJuKChMSBBxUEpN92K5IuvTSST4eIRhnVSC+AiIiIaCRJkgSz2QzzIFeWyrIcNohtaGgIBrGHXr82lB2xRqMRkiRF86kCAHbu3Ilrr70WDocDF154IWw2G4477jiYzWbo9XokJibipptuwllnnRX1tRBFil6vx5w5czBnzhw4HA7s2LED5eXleOuttyBJEgoLC1FaWoqpU6dCPVDoQUQTSteGzwGVCvD7+73fFgjg4ppqzDfE4fHsHCRJEqp9PpjF71+ra7xeXFJTjXPiE3BdSgqMoohKrwfacK0GZBmOz9YzYCUiIooBx4YNgCgO2A5gKK/3f21uwldOJ+61WJClVuPzLifubGpEmkqF5UbTwHOv38CAlWicY8BKRERENASiKAYD0XBkWYbT6RwwiG1qakJlZSUcDkefINZgMAwpiFWpDu9XuE2bNuHll1/G6aefjpaWFsTHx6O6uhqLFi3CP//5T1gsFrS3tzOAojHNaDRi/vz5mD9/Pmw2G3bs2IGysjK89tprUKvVmDZtGkpLSzF58uTD/l4iorHPtW3rgOEqADzV3oYMtRp3WSzB27I1mpBj/t7aguONRvy6V7nf3EOO6Y9n504ogQCEGFxYRURENJG5t24N22t9KK/337pcWGmOx3xDHADg/AQNXrV2YLvLPXDAqihwbd8ORVEghLvwiojGNJ5RICIiIoogURSDQail15u0QymKEjaIbWlpwb59++BwOCAf8oZQr9cPGMSmp6f3W+p37969eP7557Fo0SKYTCY8/vjjMJlMaGhogNVqRWNjIywWC5KSkiL+NSEaKfHx8Vi0aBEWLVqE9vZ2lJeXo6ysDC+//DK0Wi2KiopQUlKCSZMmxWQHORGNDorXC0/l3rDHrHE4cFxcHH5ZV4fNLifSVCpcmJCI8xISAACyouBTRxeuTErC1bW12OlxI0utxtVJyThxkIuxFK8X3v37oZ0yJVJPiYiIiA4RsNvhq68Pe8xgr/cAMFuvx9ouB34YH480lQqbXE5UeX24NS0u7Niy1Qp/czPU6emReDpENAoxYCUiIiIaAT09XOPi4pCRkTHgcYqiwOVyDRjEtrW1oaqqCg6HA4FAAIsWLcKJJ54Y0vdVURQ88sgjOOqoo3DhhRfimWeeQW5uLkwmE8xmM9xuN6688kpotVrcdNNNOP/882PxJSCKqaSkJCxevBiLFy9GS0sLysrKUFZWhu+++w4GgwFFRUUoLS1Fbm7uqOubTESR5e/oCLt7FQAO+Hx42WrFZYlJuCY5GWVuN+5qboJaELAyPh5tgQCciown29twQ0oqbk5NxYauLtxYX4enc3Ixz2AIO76vsYkBKxERURT5m5oGPWaw13sA+H1aOv5fUyOW7dsLFbrfy/8pPQNHD/JaDwD+xkYGrETjGANWIiIiolFMEAQYDAYYDAakh3ljpigK3G53vyWIKioqsGbNGrz99tv49NNPsW3bNmg0GrzzzjtYvnw5vvjiCwDdJYRvuukmJCYm4qSTTgoZQ5Zlhk40bqSmpmLZsmVYunQpGhsbUVZWhvLycnzzzTcwGo0oKSlBaWkpsrKyWNKLaBxSvN5Bj5EVBaU6PW5KTQUAFOt0qPB48Iq1Ayvj46Ggu8z/cqMJlx2s/lCk0+E7lwuvWDsGDViHsgYiIiL6nqIo8Pv98Pl8Q/qQ9+5FwiBjDvZ6DwDPWzuw1eXGP7OykKlSY7PLhTubmpCqUuGYuPC7WPl6TzS+MWAlIiIiGgcEQYBer+/3vqlTp2L16tWorKyE3W7HnXfeCa/Xi7179+LEE08EAAQCAcyfPx9utxv1h5RRkmUZZWVleO+99/r0g+35vHeZYq1WG/XnSxQJgiDAYrHAYrHgxBNPRF1dXTBs3bhxIxISEoJha3p6OsNWonFCGEKv8VSVCpO1oT3YJms0+NhhBwAkSCqogD7HFGg12OJ0RWQNREREY4WiKEMKPb1eb7+3+/3+Ae/r/TFUKpUKiQ4Hlg1y3GCv925ZxkMtLfhHVjaWGI0AgGk6HXZ53Hi6vX3QgJWv90TjGwNWIiIiogkgJSUFKSkpAIAHHngAl1xyCa655hqsWbMGGRkZmDx5MrZv3476+nqUlpaGPLYnhFqyZElIieL6+no4HA54D7kqV61WDzmIZWBFo4UgCMjOzkZ2djZOPvlk1NTUoKysDFu2bMHnn3+O5OTkYNiaevAKdyIa/RRFgd1uR3t7O9ra2tDW1oaOpibMABDuFWiO3oD9h7y+Vfm8yFR1nyjVCAJKdfq+x3i9yBzCyVRVMnueExFRbMiyPOSg83A//IOU3u9No9FArVb3+6HRaBAXFzfg/f0df+htKpUKgiDA396OijffCruWwV7v/YoCP/r+ziBCgHywmkU4UnLykL8uRDT2MGAlIiIimiB6ygf/9Kc/RVZWFvx+P55++mns2bMHfr8fWq0Wjz/+OGbPnh3yOEEQkJqaOmCo5PF4gqHroT1i7XY7Ghsb4XA44PF4Qh6nUqmGFMTqdDoGsRRToigiPz8f+fn5WLFiBfbv3x/c1frZZ58hPT09GLYmJiaO9HKJCIDT6URbW1tIkNrz954dL4IgICEhAcnJyfCnpUHd3DzgeJcmJuLimmo83taKU01mbHe78B+rFX/s1Tf9J0lJuLm+DkfrDZhvMGBDVxfWORx4Oic3/GJVKvZfJSIiKIqCQCAQ0aCzvwBVluUhrUcUxbBhpk6ng9lshkqlGnLYeeiHJEkxe2+nSkqClJKMQGvbgMcM9npvlCTM0+vxt5Zm6EQBmSo1vnY5sarTht+mpoWdX4yLgzo7O6LPiYhGF0FRlMEvtSAiIiKicc/v90Olit71d16vN2wQ2/N3t9sd8jhJkoYUxOr1egaxFFV+vx+VlZUoLy/H7t274fP5kJWVhZKSEpSUlMBsNo/0EonGNa/X2yc87fm7y/V9WV6z2Yzk5GQkJSUhOTk5+PfExERIkgQAqL/1NtjeeQcIBAacb53DgQdbWlDt8yJbrcZliUk4LyEh5JjXbVY80daGJr8f+RoNrk9OwQkmU9jnoZ0+HQVvvXn4XwgiIoq64fT77G83aM9jB9spOtRT85IkDWnn5nDCzv7Cz/Gm9rrr4Fi7DggTMg/2et/i9+PBlhZ84eyCLRBAplqN8+ITcFliYtj3n4b585H37DMRfDZENNowYCUiIiKiUcXn84UNYnv+7H0yHeg+6dATtoYLYg0GA4NYOmJerxcVFRUoKytDRUUFAoEAcnNzUVpaiuLiYsQN0o+JiPrn9/vR0dERDE97h6kOhyN4nMFgCAlPe/9dPYQSvdY33kTD734XzafSP0lC0mWXIf03t8R+biKicUKW5X7Dz0iXvR2q4QaZwy1/q1KpIIpiFL+i41f7s8+i6e57gFhHIKKI1F9cj5Sf/Sy28xJRTDFgJSIiIqIxye/3D7gLtvefTqcz5HGiKA45iOWJDBoKt9uN3bt3o6ysDPv27YOiKJg0aRJKS0sxffp06PX6kV4i0agiyzJsNlu/IarNZgvu5tFoNAOGqEf6fSW7XKg4bjHkrq5IPKVhmfzfD6DJz4/5vEREsSDLcsSDzkMD1ECY6gO9CYIQ8bBzoH6fNDoFbDZULD4eyiF9VqNOFDFl7Vqo08OXESaisY0BKxERERGNa4FAoN8gtufzntu6DjnJLgjCkILYuLg4BrEU5HQ6sXPnTpSXl2P//v0QRRFTpkxBSUkJpk2bBq1WO9JLJIoJRVFgt9v77Yna0dERPDkuSVIwPO0doiYnJyMuLi6qJ62b7r4H7c8/H7ZMcESJIgwLFiDv3/8Xm/mIiHoZbr/PQ0PS3jtGwwWokej32TvMPLTf53BK38ay3yeNXvW/+z1sb78du9d7SYLpxBOR/feHYjMfEY0YBqxEREREROgOYru6uoYUxPb+FVoQBMTFxQ0piB2PfY1oYHa7HTt27EB5eTlqa2uhUqkwdepUlJSUoLCwcEhlTIlGO6fT2W9P1La2tmB5RUEQkJCQ0O9uVLPZPGIXqfgaGrB3xWlQDun9HU15zz8Hw9FHx2w+IhobwvX7jORu0OH2+wwXZqpUqsPq8zme+33S6OTZtw/7zjob8PtjM6EoYtJr/4GuuDg28xHRiGHASkREREQ0DLIsDymIdTgcfU5iDSWINRqNPOE0DlmtVpSXl6O8vBwNDQ3QaDSYNm0aSktLMXnyZP6b0xGRZTkY5qenp2Pp0qURHd/r9fYJT3v+3rsfttls7recb2Ji4qj9P97x8ito/OMfoz+RKCLxoouQ8YffR38uGlcCgQCcTicURYHZbAbQfQHPtm3b4HK5YLPZoNPpsGDBAqSkpIzwasennn6f0Sx76x9G8BOtPp+9g1NWZ6Hxpu3JJ9H8t/ujP5EgIPmn1yLtxhujPxcRjTgGrEREREREUSDLMpxO55CC2ENLqRkMhj6ha39BrEqlGqFnR0eira0N5eXlKCsrQ0tLC3Q6HYqKilBSUoJJkybxpCYNqLKyEhUVFdixYwdSU1NxySWXQBRFvPDCC7j77rsxefJkaDQaLFmyBNdffz1kWR7y/ye/34+Ojo5++6I6HI7gcQaDYcC+qGNxV7aiKKi54idwfv119EoHShLU6ekoePcdiAZDdOagcclut+PCCy/E+++/jzlz5mDt2rUwmUxYtWoVVq5cibPPPhtqtRpTp07FVVddhfwJ2Nt3OCVvD7fsbST7fWo0mj4lb4dT/pb9PokOjxIIoOpHF8C9c2dUX+81+fkoePMNCBpNdOYgolGFASsRERER0QhSFGVIQazdbu8TxOr1+n6D2EMD2bEYekwUzc3NKCsrQ3l5Odrb22EwGFBcXIzS0lLk5uaOiZOoiqIgYLVCcToBQYAYFwcpPn6klzXuVFRU4PLLL0dWVhYyMzPhdruh1+tx9913Y8mSJfj3v/+N4uJibNiwARdccAH27t3bp+evLMuw2Wz9hqg2my24616j0QwYour1+pF4+lEVsFpRdeFF8NbURP6kqyRBNBqR/9JL0BZMiuzYNO55vV5UVVVhz549uOeee/D+++/DbDbj448/xr333otPPvlkpJc4oMH6fUZqN+iR9PvsL8zsCT8Pp/Qt+30SjW6+5mZUX3AhfE1NUXm9lxITMemVl6HOyors2EQ0ajFgJSIiIiIaAxRFgcvlGlIQe+hOC51ON+Au2N63aXil9YhRFAUNDQ3BsLWzsxMmkwklJSUoLS1FZmbmqDpp66msROf778O1dRtc27dD7uwMuV9KSoL+qKOgnzUT5jPOgCY7e4RWOn598MEHuPrqq7F161ZMnjwZVqsVgUAAkiRhxowZePjhh7Fs2bLg8Yqi4L333sM333wDoLu/Xk942jtETU5ORlxc3Kj6/xYL/tZWVF/xE3j37gWGGNgMSpIgxccj9+l/Qzd1amTGpAnp888/x/XXX481a9YgMTERn3/+OS644AI88MADUKvVKCwsRElJyZDH693vM1plb4fb7/NIenkOZcfoaC1TTkSx5WtoQPWll8FXXx+5kFWSoEpJQd6zz0CTlxeZMYloTGDASkREREQ0jiiKArfbPaQg9tB+X1qtdtAg1mQyMYiNMkVRUFtbG+zZ2tXVhcTExGDYmpaWNiLhl6IosH/8MdqfeRaub74BJKk7iBroLaUgdH8oCuIWH4ekyy6D8dhjY7vocWjz5s1Yt24d3n//fVx//fWYM2cOTjvtNHzyySfIzMwEAJx99tk4++yzcfnllwdLBMuyjKamJjidTiQnJ8NsNrMc9SECdjua/nIXbG+9Ffy/eyQMCxYg8+67oD7470J0uL777jtccsklWLduHVJSUrBv3z5cfvnlyM3NhcvlQlxcHH7605/imGOOCXlcIBDAli1bsHHjxj5lcYcqWn0+2e+TiEaKv6MDjX+8A/YPPzyy1/ue33OXLEHmn++EKjU1sgslolGPTZuIiIiIiMYRQRCg1+uh1+uRlpY24HGKosDj8QwYxHZ2dqKurg52ux0+ny/ksRqNZshB7ETbBRcJgiAgNzcXubm5OOWUU1BdXY2ysjJ888032LBhA1JSUlBaWoqSkhKkpKQMe3yr1YpVq1bhtNNOG/LjfQ0NaPjD7ej6/HOg50T4YFf9K0rwhFXX51+g67P1MJ92GtJv/wNUiYnDXvdEpygKBEHAxo0bUV1djYyMDKxduxYWiwUZGRmoqKgIBqwajQZtbW0hoYUoirBYLCO1/DFBMpmQec/dMK84FfW//wMCra3d/9+HuqP14M87QadD+v9v795j67zrPI9/js/x9SRxbCfNpaFJU9IkJC2lhKots6UMBa0QJVQs09lpGTJCoNXMaigjMTtcdkv/mNlh0XLZXWl2hkUTFtB2ZldatWVp6YUBsUtJoW2gCUnaEuKKNiFN7Dh2Yuf4cvaPNFacOM6TxE6b5vWSrNrnPOc5j53E1vG7v9/3L/4ic3/vQ74Hvs6cbt7nuawGffvb355169ZNutKyra1twizQyy+/PD/84Q/H/3594QtfyCc/+cls2rRpwuzlUqmUjo6OrFix4ozmfJr3CbyeVTo6suSrX8nBh76XPZ+/O6MH+s4stL5ybEO1moX/7t9mzq23+l4JFykrWAEAgClNFWKPv61Wq014XGNjY6EQ29zc7JcSBYyOjmbnzp3ZsmVLtm/fnlqtloULF46vbJ07d26h8xw5ciRf//rXMzQ0lA0bNqSzs3PK4w8+9FBe+vRnUq/Vzn0rtXI55dmzcumXvpTqCSutLlYjIyPp7e2dMBd18eLFufbaa0+7qut973tf3v/+9+eJJ57IpZdemnvuuSdJ8sEPfjDXXnttPvvZz46HWc7MWK2W/ocfSe+3vpXBzZuP3lipJCeu/DvutqZly9Lx4TvTvn59yrNmnd8LvshNNu9zJra+PZt5n1PFzEqlMn7/8uXLs2TJkkn/3e/Zsyc33XRTHn/88XR1dZ10/6OPPpqPfvSj6e7unhBYAZja2NBQDj74UHq/+c0M/fKXR288zc/75hUrjv68f9/70tDWdp6vGHgtEVgBAIBpUavVCoXYI0eOTHhcpVIpFGJbWlqEoleMjIzkueeey9atW7Njx46MjIxkyZIlWbNmTdasWZPZs2dP+fiBgYF84xvfSK1Wy4YNG9JxihWlvf/4j9lz9+ePfjBdLx1LpaShIUu++pXMvuWW6Tnna9zY2Fj6+vomRNSenp7s378/fX1943MKm5qa0tXVlauuuio33HDDac97++23Z8WKFbnlllvyxS9+Mbfddlv27duXzZs35+67787q1atn+lO7KNReeCGDv3gmQ1u3ZmjbtowN9Cdj9TS0taX5yhVpWbMmLWvXpvnKK32PmkS9Xj/roFmr1cZnhZ5utWhRlUpl2md8nhhNp3veZ3d3d2688cbce++9WbRoUTo6OrJp06a0tLRk3759ue+++/K2t70td91117Q+L8DF5MjOX2doyys/77fvyNjAQJKjK1Wbr1yZljVr0nrV2jRdcYWf90ASgRUAADjPhoeHTwqxx94//rahoaEJjyuXy4VCbGtr60X1S49arZYdO3Zk69atef755zM6OpqlS5dm7dq1Wb16darV6qSP6+/vz8aNGzM6OpoNGzactAK274Hv5KVPfWpmLvqVyHrZ1/7udbOStV6vp7+/fzycHh9Re3p6xle+lcvldHZ2pqura/y/x96q1eop/+4em827ZcuW9Pf35/HHH8+ePXtyzz33ZOXKlXnsscfy5S9/OYsWLcptt92W9773vefz0+cCNTY2dkax88TbjsXPqVaLTue8z6amplMG0iLb3l6I8z43bNiQxx57LMPDw5k1a1YWL16cb3/72/n4xz+etra2tLS05LrrrssnPvGJV/tSAQAuKgIrAADwmjQ8PHzS6tfJQuzg4OCExzU0NBQKsW1tba+7EDs0NJTt27dny5Yt2blzZ5Jk+fLlWbt2bVatWpWWlpYJxx88eDAbN25MvV7Phg0b0t7eniSpdXdn563vP7ot8EwpldIwZ06uePC7qZxmm+L9+/dn06ZNeec735nW1taZu6YCDh8+PCGeHv/+sVV0x+YeHh9Qj70/Z86csw48P/rRj3L33XfnjW98Y6688srcfPPNWbdu3XR+erxG1Ov1U8bP6dz6drTgtt+lUqlQzDx+y9szfTPvEwCAC4nACgAAXNBGRkYKhdjDhw9PeFxDQ0Oq1WqhEHuhrXhKkkOHDmXbtm3ZsmVLuru709DQkIULF+b666/PypUr09TUlCTp6+vLxo0bUyqVsmHDhsyeNSvdd344gz//+bnPXD2dcjmzb7klS776lUnvrtfrefLJJ/Pwww9n9uzZ+djHPnZSJJ4JtVpt0u189+/fP2Fl9Zw5c05aidrZ2ZmOjo5p3yKU147j533OxJzPY+ct+uuacrk8rVveThZQGxoaxE8AADiOwAoAAFwURkdHC4XYQ4cOTXhcqVQqFGKr1eprNsT29/fnvvvuy69+9askR2cQrly5MmvWrMmKFSsyMDCQjRs3plwu50Nz56b3L//qvF7fG/72v2bWO94x4baBgYE88MADefbZZ/PWt7417373u1Mul1OpVKblOUdGRtLb2ztpSB0YGBg/rq2t7aRVqMfeb2xsnJZrYfqczbzP4yPpifM+TxVQizrXeZ9FVoO+Vr/vAADA65nACgAAcJyxsbHCIfbEl1NFQ+yrtbpx+/bt+c53vpPBwcFUq9X09/enqakpq1atytKlS/ODf/qn3PQ//1eqfX3J+XqpWC6n7W1vy9KNfz9+044dO3L//fenVCrl1ltvzZw5c/LII4/kpZdeyqc+9anCX7+xsbH09fVNGlH7+vrG//yamppOGVFf7S2JX0+KzPs81xWhZzvvc6otb4uGzsnerPoEAIDXJ4EVAADgLIyNjeXQoUOnDbEDAwMnhdi2trbThthZs2bNSIg9cuRIvv/97+eJJ57I/Pnzc9lll6W7uzv79u3L4t7e/M5D35vy8b8dHs5/fPnl/OjQQIbq9VzW2JS/XLQwa1uOhsh9IyP50st78/8OHU7/2GjWtbblMwsWZNkrWxKfyvIHv5ssXpzvfe97efrpp7Ny5cq84x3vyE9+8pP84he/yLx58/Ke97wnK1asmPC4er2e/v7+SWei9vT0ZGxsLMnRbVQnm4na1dWVarV6UYewyeZ9zsTWt2cy7/Nsg2bR1aDlcvmi/jMHAADOjcAKAAAwg8bGxnL48OFCIfZYDDymtbV1yhB77P2z2Tb3hRdeyP3335/9+/dn2bJlmT17dtq/+c0s3L4jDad4mdg3OpoP7vp1rmur5vfnzk1nuZzu4eG8obExlzU1pV6v5w9e6E6lVMqfz78ks8oN2djTm/97aCAPXL48bafayrRcTuPv357vtrdnYGAg73rXu3Lw4MFs2rQpLS0tufnmm7Nq1arxLX1PjKnHtmwtlUrp6OiYNKS2t7dfkEGtXq+fdN3Hz/8cGhrK4ODgeOw/PozWarWTtrw9VUQ9n/M+TxdPza8FAABe6wRWAACA14B6vV44xJ64ErClpWXKEHv48OHs3bs3fX196e3tTW9v74QtcpOkoaEh7/0/303bgQOnvMYvvbw3Tw0O5luXLZ30/l21Wt776525b9nlWdHcnCQZq9dz06+ez13z5udfzJ07+eeeZO+CBXn2jj/IwoULs3Xr1oyMjGTevHkpl8vp7e3N0NDQ+PFz5sw5aRVqV1dX5s6de17j3JnM+5xsReix+DnVatFKpZJFixalqakpBw4cSE9PT2q12qTXc+K8z8lC5vHHnM0qUfM+AQAAkjP/35wBAACYdqVSKdVqNdVqNQsWLDjlcfV6PYODg6cMsb29vXnhhRcyMDBw0jzKUqmUxsbGtLa2ZvHixWlvbx+fM7pt8+a0ThFXk+T7AwP5nWo1d734Yn42eDiXVCr5l3M78qFXwmmtfnQFbvNxKy4bSqU0lUp5avDwKQNrKUlnT092v/RSdu/eneRoNG5ubk5XV1dWr149YUVqY2Pj1F/MTD3vc7q2vz2TeZ9TxcympqZUq9VzWg1aqVQuyBW6AAAAFyKBFQAA4AJSKpXS1taWtra2XHLJJac8rl6vZ2hoKAMDAzl48GAGBgZOWhG7e/fuPPvssxkZGUnH/p6cLs/9Zng49x44kI90dObjXV3ZMjSUv9r72zSWSvlAe3sub2rOokolX973cj6/YGFaGxry33t6smdkJC+PTD1/s3F4OHNGR3PpVVfliiuuSENDw4SY+eKLL2bXrl2FV4ueuN3yVF/PqeLnsdXB57LtrXmfAAAAry8CKwAAwOtQqVRKa2trWltbM3/+/FMe19vbmyeffDK/efDB055zrF7P2pbWfPKV872ppSXPHTmSfzjQmw+0t6exVMp/unRJPrdnd254/rmUk9zQVs0/q1ZTZDZN/fDhbNu2Ldu2bUtydNviE8Pl8R9Xq9Vz3vLWvE8AAADOlMAKAABwkRkeHs727duzefPm7Ny5M01NTVm3+NLTPm5+pZIrmpsm3HZFU1MeGegf/3hNS0v+97LL0z86muF6PZ2VSm7v3pW1LS2nPf/sWbOy+rrrUq/X8/zzz6e3t/foc1xxRVavXp3ly5enUvEyFgAAgFeXV6YAAAAXgXq9nt27d+fpp5/OM888kyNHjmTp0qVZv3593vSmN2Vk69Z0f+1rU57j2ta2/LpWm3DbruFaFldOnok6+5WVobtqtWwdGsqfzjv1KtpjLlnyhvz0pz9NS0tL1q1bl2XLlmXXrl355S9/mc2bN6e5uTk33nhjbrrppjP4zAEAAGB6ler1epGdmgAAALhAbdu2LT/4wQ+yd+/ezJ49O29+85tzzTXXpKura/yY0QMH8uz1N0x5nmcGB3PHC935k3nz8s9nz8kzQ4O5e8+efH7hwtw6pz1J8lD/wXSWy1lUacyzR47k3+/9bda0tOSrly6Z8tyl5uasfOrJHDh4MJs2bcpTTz2VsbGxXH311bn++uuTJFu3bk21Ws111113jl8RAAAAOHsCKwAAwOvcgw8+mIGBgbzlLW/J8uXL09DQMOlxz938zozs2TPluX4wMJAvv/xyuodrWdLYmI90dOZDc+eO3//N3p78fU9P9o2MZH6lkvXt7flXXfPSVCpNed7Wa67Jsnv/x/jHg4ODefLJJ/PEE0+kv78/K1asyA033JBly5aldJpzAQAAwEwSWAEAAEiS/Oauu9L/yKPJ6Oj5feJyOZ133pEFn/70SXeNjo5my5Yt+fGPf5y9e/dm/fr1ueaaa87v9QEAAMBxBFYAAACSJAcffjgv/uknXpXnXvYP96b1zW8+5f31ej0vvvhiOjs709bWdh6vDAAAACaafF8oAAAALjqzf/d3Uz5uLut50dCQ5pUr03L11VMeViqVsmTJEnEVAACAV53ACgAAQJKkVKmk8847klPMaJ0RY2Pp/MM/NFcVAACAC4bACgAAwLjOP/qjNF566fmJrOVyWq6+Ou0fWD/zzwUAAADTRGAFAABgXENLSxZ/4a+Ten3Gn6vU0JDFX/jrlMrlGX8uAAAAmC4CKwAAABO0XXtt5v3xH8/48yz43OfSfPnlM/48AAAAMJ0EVgAAAE4y71//STruvGPGzj//z/4sHbf/3oydHwAAAGZKqV4/D/s+AQAAcMGp1+vZ95//S/b9zd8kpVIyNnZuJyyXk3o9Cz77mXTeMXPxFgAAAGaSwAoAAMCUDv/sZ3npz/9NhvfsOfvIWiql+Y1vzOIv/oe0rFo1vRcIAAAA55HACgAAwGmNDQ5m/3/7enq//e2MHjiQNDScPra+ckxlwYJ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", 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", 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" ] @@ -75,29 +75,29 @@ "name": "stdout", "output_type": "stream", "text": [ - "{'2': 11, '4': 6, '10': 2, '17': 10, '49': 1, '54': 13, '55': 12, '26': 5, '7': 3, '12': 7, '35': 0, '44': 4, '46': 8, '56': 9, '62': 14, '0': 15}\n", - "{'0': [0, 1], '10': [10, 11], '12': [12, 13, 14, 15, 16], '17': [17, 18, 19, 20, 21, 22, 23, 24, 25], '26': [26, 27, 28, 29, 30, 31, 32, 33, 34], '2': [2, 3], '35': [35, 36, 37, 38, 39, 40, 41, 42, 43], '44': [44, 45, 51, 52], '46': [46, 47, 48, 53], '49': [49, 50], '4': [4, 5, 6], '54': [54], '55': [55], '56': [56, 57, 58, 59, 60, 61, 67, 68, 69], '62': [62, 63, 64, 65, 66], '7': [7, 8, 9]}\n", + "{'2': 15, '7': 7, '10': 6, '11': 3, '17': 5, '54': 9, '26': 10, '62': 1, '4': 11, '12': 2, '35': 13, '44': 12, '55': 4, '59': 0, '49': 8, '0': 14}\n", + "{'0': [0, 1], '10': [10, 8, 9], '11': [11], '12': [12, 13, 14, 15, 16], '17': [17, 18, 19, 20, 21, 22, 23, 24, 25], '26': [26, 27, 28, 29, 30, 31, 32, 33, 34], '2': [2, 3], '35': [35, 36, 37, 38, 39, 40, 41, 42, 43], '44': [44, 45, 46, 47, 48, 53], '49': [49, 50, 51, 52], '4': [4, 5, 6], '54': [54], '55': [55, 56, 57, 58], '59': [59, 60, 61, 66, 67, 68, 69], '62': [62, 63, 64, 65], '7': [7]}\n", "Independent paths for accelerator [[0, 1]]:\n", - "Independent paths for accelerator [[10, 11]]:\n", + "Independent paths for accelerator [[8, 9, 10]]:\n", + "Independent paths for accelerator []:\n", "Independent paths for accelerator [[12, 13, 15, 16], [12, 14, 15, 16]]:\n", "Independent paths for accelerator [[17, 18, 24, 25], [19, 20, 21, 24, 25], [22, 23, 24, 25]]:\n", "Independent paths for accelerator [[26, 27, 33, 34], [28, 29, 30, 33, 34], [31, 32, 33, 34]]:\n", "Independent paths for accelerator [[2, 3]]:\n", "Independent paths for accelerator [[35, 36, 42, 43], [37, 38, 39, 42, 43], [40, 41, 42, 43]]:\n", - "Independent paths for accelerator [[44, 45, 51, 52]]:\n", - "Independent paths for accelerator [[46, 47, 48]]:\n", - "Independent paths for accelerator [[49, 50]]:\n", + "Independent paths for accelerator [[44, 45], [46, 47, 48]]:\n", + "Independent paths for accelerator [[49, 50, 51, 52]]:\n", "Independent paths for accelerator [[4, 5, 6]]:\n", "Independent paths for accelerator []:\n", - "Independent paths for accelerator []:\n", - "Independent paths for accelerator [[56, 57, 58, 69], [56, 57, 59, 60, 61, 69], [56, 57, 67, 68, 69]]:\n", - "Independent paths for accelerator [[62, 63, 64, 65, 66]]:\n", - "Independent paths for accelerator [[8, 9]]:\n" + "Independent paths for accelerator [[55, 57, 58], [56, 57, 58]]:\n", + "Independent paths for accelerator [[59, 60, 61, 69], [66, 69], [67, 68, 69]]:\n", + "Independent paths for accelerator [[62, 63, 64, 65]]:\n", + "Independent paths for accelerator []:\n" ] }, { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -129,9 +129,8 @@ "Edge: (8, 9), Attributes: {'flits': 137, 'datatype': 8}\n", "Edge: (8, 5), Attributes: {'flits': 1, 'datatype': 1008}\n", "Edge: (9, 10), Attributes: {'flits': 137, 'datatype': 9}\n", - "Edge: (9, 8), Attributes: {'flits': 1, 'datatype': 1009}\n", "Edge: (10, 11), Attributes: {'flits': 137, 'datatype': 10}\n", - "Edge: (10, 9), Attributes: {'flits': 1, 'datatype': 1010}\n", + "Edge: (10, 8), Attributes: {'flits': 1, 'datatype': 1010}\n", "Edge: (11, 12), Attributes: {'flits': 194, 'datatype': 11}\n", "Edge: (11, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", "Edge: (12, 13), Attributes: {'flits': 388, 'datatype': 12}\n", @@ -206,6 +205,7 @@ "Edge: (44, 45), Attributes: {'flits': 32, 'datatype': 44}\n", "Edge: (44, 42), Attributes: {'flits': 1, 'datatype': 1044}\n", "Edge: (45, 51), Attributes: {'flits': 48, 'datatype': 45}\n", + "Edge: (45, 44), Attributes: {'flits': 1, 'datatype': 1045}\n", "Edge: (46, 47), Attributes: {'flits': 32, 'datatype': 46}\n", "Edge: (46, 42), Attributes: {'flits': 1, 'datatype': 1046}\n", "Edge: (47, 48), Attributes: {'flits': 48, 'datatype': 47}\n", @@ -214,15 +214,14 @@ "Edge: (49, 50), Attributes: {'flits': 189, 'datatype': 49}\n", "Edge: (49, 42), Attributes: {'flits': 1, 'datatype': 1049}\n", "Edge: (50, 51), Attributes: {'flits': 48, 'datatype': 50}\n", - "Edge: (50, 49), Attributes: {'flits': 1, 'datatype': 1050}\n", "Edge: (51, 52), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 53), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 56), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 43), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (51, 45), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (51, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (51, 50), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (52, 57), Attributes: {'flits': 45, 'datatype': 52}\n", - "Edge: (52, 44), Attributes: {'flits': 1, 'datatype': 1052}\n", + "Edge: (52, 49), Attributes: {'flits': 1, 'datatype': 1052}\n", "Edge: (53, 54), Attributes: {'flits': 95, 'datatype': 53}\n", "Edge: (53, 51), Attributes: {'flits': 1, 'datatype': 1053}\n", "Edge: (54, 55), Attributes: {'flits': 110, 'datatype': 54}\n", @@ -236,9 +235,11 @@ "Edge: (57, 62), Attributes: {'flits': 119, 'datatype': 57}\n", "Edge: (57, 67), Attributes: {'flits': 119, 'datatype': 57}\n", "Edge: (57, 52), Attributes: {'flits': 1, 'datatype': 1057}\n", - "Edge: (57, 55), Attributes: {'flits': 1, 'datatype': 1057}\n", "Edge: (58, 69), Attributes: {'flits': 45, 'datatype': 58}\n", + "Edge: (58, 55), Attributes: {'flits': 1, 'datatype': 1058}\n", + "Edge: (58, 56), Attributes: {'flits': 1, 'datatype': 1058}\n", "Edge: (59, 60), Attributes: {'flits': 23, 'datatype': 59}\n", + "Edge: (59, 57), Attributes: {'flits': 1, 'datatype': 1059}\n", "Edge: (60, 61), Attributes: {'flits': 26, 'datatype': 60}\n", "Edge: (61, 69), Attributes: {'flits': 30, 'datatype': 61}\n", "Edge: (62, 63), Attributes: {'flits': 23, 'datatype': 62}\n", @@ -246,34 +247,38 @@ "Edge: (63, 64), Attributes: {'flits': 23, 'datatype': 63}\n", "Edge: (64, 65), Attributes: {'flits': 26, 'datatype': 64}\n", "Edge: (65, 66), Attributes: {'flits': 26, 'datatype': 65}\n", + "Edge: (65, 62), Attributes: {'flits': 1, 'datatype': 1065}\n", "Edge: (66, 69), Attributes: {'flits': 30, 'datatype': 66}\n", - "Edge: (66, 62), Attributes: {'flits': 1, 'datatype': 1066}\n", + "Edge: (66, 65), Attributes: {'flits': 1, 'datatype': 1066}\n", "Edge: (67, 68), Attributes: {'flits': 119, 'datatype': 67}\n", + "Edge: (67, 57), Attributes: {'flits': 1, 'datatype': 1067}\n", "Edge: (68, 69), Attributes: {'flits': 15, 'datatype': 68}\n", - "Edge: (69, 56), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 59), Attributes: {'flits': 1, 'datatype': 1069}\n", "Edge: (69, 66), Attributes: {'flits': 1, 'datatype': 1069}\n", - "Edge: (69, 118), Attributes: {'flits': 1, 'datatype': 118}\n", + "Edge: (69, 67), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 58), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 120), Attributes: {'flits': 1, 'datatype': 120}\n", "Edge: (70, 0), Attributes: {'flits': 1, 'datatype': 1001}\n", - "Edge: (71, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", + "Edge: (71, 8), Attributes: {'flits': 1, 'datatype': 1010}\n", "Edge: (72, 12), Attributes: {'flits': 1, 'datatype': 1016}\n", "Edge: (73, 17), Attributes: {'flits': 1, 'datatype': 1025}\n", "Edge: (74, 26), Attributes: {'flits': 1, 'datatype': 1034}\n", "Edge: (75, 2), Attributes: {'flits': 1, 'datatype': 1003}\n", "Edge: (76, 35), Attributes: {'flits': 1, 'datatype': 1043}\n", - "Edge: (77, 44), Attributes: {'flits': 1, 'datatype': 1052}\n", + "Edge: (77, 44), Attributes: {'flits': 1, 'datatype': 1045}\n", "Edge: (78, 46), Attributes: {'flits': 1, 'datatype': 1048}\n", - "Edge: (79, 49), Attributes: {'flits': 1, 'datatype': 1050}\n", + "Edge: (79, 49), Attributes: {'flits': 1, 'datatype': 1052}\n", "Edge: (80, 4), Attributes: {'flits': 1, 'datatype': 1006}\n", - "Edge: (81, 56), Attributes: {'flits': 1, 'datatype': 1069}\n", - "Edge: (82, 62), Attributes: {'flits': 1, 'datatype': 1066}\n", - "Edge: (83, 8), Attributes: {'flits': 1, 'datatype': 1009}\n", + "Edge: (81, 55), Attributes: {'flits': 1, 'datatype': 1058}\n", + "Edge: (82, 59), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (83, 62), Attributes: {'flits': 1, 'datatype': 1065}\n", "Edge: (84, 1), Attributes: {'flits': 1, 'datatype': 1002}\n", "Edge: (85, 2), Attributes: {'flits': 1, 'datatype': 1004}\n", "Edge: (86, 3), Attributes: {'flits': 1, 'datatype': 1005}\n", "Edge: (87, 5), Attributes: {'flits': 1, 'datatype': 1008}\n", "Edge: (88, 6), Attributes: {'flits': 1, 'datatype': 1007}\n", "Edge: (89, 7), Attributes: {'flits': 1, 'datatype': 1012}\n", - "Edge: (90, 9), Attributes: {'flits': 1, 'datatype': 1010}\n", + "Edge: (90, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", "Edge: (91, 11), Attributes: {'flits': 1, 'datatype': 1012}\n", "Edge: (92, 15), Attributes: {'flits': 1, 'datatype': 1017}\n", "Edge: (93, 15), Attributes: {'flits': 1, 'datatype': 1019}\n", @@ -291,21 +296,23 @@ "Edge: (105, 42), Attributes: {'flits': 1, 'datatype': 1046}\n", "Edge: (106, 42), Attributes: {'flits': 1, 'datatype': 1049}\n", "Edge: (107, 43), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (108, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (109, 50), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (108, 45), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (109, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (110, 51), Attributes: {'flits': 1, 'datatype': 1053}\n", "Edge: (111, 51), Attributes: {'flits': 1, 'datatype': 1056}\n", "Edge: (112, 52), Attributes: {'flits': 1, 'datatype': 1057}\n", "Edge: (113, 53), Attributes: {'flits': 1, 'datatype': 1054}\n", "Edge: (114, 54), Attributes: {'flits': 1, 'datatype': 1055}\n", - "Edge: (115, 55), Attributes: {'flits': 1, 'datatype': 1057}\n", + "Edge: (115, 57), Attributes: {'flits': 1, 'datatype': 1059}\n", "Edge: (116, 57), Attributes: {'flits': 1, 'datatype': 1062}\n", - "Edge: (117, 66), Attributes: {'flits': 1, 'datatype': 1069}\n" + "Edge: (117, 57), Attributes: {'flits': 1, 'datatype': 1067}\n", + "Edge: (118, 58), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (119, 65), Attributes: {'flits': 1, 'datatype': 1066}\n" ] }, { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -463,7 +470,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 54, "metadata": {}, "outputs": [], "source": [ @@ -473,14 +480,14 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 55, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "DiGraph with 119 nodes and 192 edges DiGraph with 70 nodes and 143 edges\n", + "DiGraph with 121 nodes and 199 edges DiGraph with 70 nodes and 148 edges\n", "DEBUG: Edge (node, suc) (0, 1) has datatype: 0\n", "successor of node: 0 1\n", "0\n", @@ -539,16 +546,13 @@ "successor of node: 8 5\n", "1008\n", "DEBUG: Edge (node, suc) (9, 10) has datatype: 9\n", - "DEBUG: Edge (node, suc) (9, 8) has datatype: 1009\n", "successor of node: 9 10\n", "9\n", - "successor of node: 9 8\n", - "1009\n", "DEBUG: Edge (node, suc) (10, 11) has datatype: 10\n", - "DEBUG: Edge (node, suc) (10, 9) has datatype: 1010\n", + "DEBUG: Edge (node, suc) (10, 8) has datatype: 1010\n", "successor of node: 10 11\n", "10\n", - "successor of node: 10 9\n", + "successor of node: 10 8\n", "1010\n", "DEBUG: Edge (node, suc) (11, 12) has datatype: 11\n", "DEBUG: Edge (node, suc) (11, 10) has datatype: 1011\n", @@ -728,14 +732,13 @@ "DEBUG: Edge (node, suc) (42, 43) has datatype: 42\n", "DEBUG: Edge (node, suc) (42, 44) has datatype: 42\n", "DEBUG: Edge (node, suc) (42, 46) has datatype: 42\n", + "Duplicate successor removed: 46 with Accel: 44\n", "DEBUG: Edge (node, suc) (42, 49) has datatype: 42\n", "DEBUG: Edge (node, suc) (42, 34) has datatype: 1042\n", "successor of node: 42 43\n", "42\n", "successor of node: 42 44\n", "42\n", - "successor of node: 42 46\n", - "42\n", "successor of node: 42 49\n", "42\n", "successor of node: 42 34\n", @@ -757,8 +760,11 @@ "successor of node: 44 42\n", "1044\n", "DEBUG: Edge (node, suc) (45, 51) has datatype: 45\n", + "DEBUG: Edge (node, suc) (45, 44) has datatype: 1045\n", "successor of node: 45 51\n", "45\n", + "successor of node: 45 44\n", + "1045\n", "DEBUG: Edge (node, suc) (46, 47) has datatype: 46\n", "DEBUG: Edge (node, suc) (46, 42) has datatype: 1046\n", "successor of node: 46 47\n", @@ -781,17 +787,15 @@ "successor of node: 49 42\n", "1049\n", "DEBUG: Edge (node, suc) (50, 51) has datatype: 50\n", - "DEBUG: Edge (node, suc) (50, 49) has datatype: 1050\n", "successor of node: 50 51\n", "50\n", - "successor of node: 50 49\n", - "1050\n", "DEBUG: Edge (node, suc) (51, 52) has datatype: 51\n", "DEBUG: Edge (node, suc) (51, 53) has datatype: 51\n", "DEBUG: Edge (node, suc) (51, 56) has datatype: 51\n", "DEBUG: Edge (node, suc) (51, 43) has datatype: 1051\n", + "DEBUG: Edge (node, suc) (51, 45) has datatype: 1051\n", "DEBUG: Edge (node, suc) (51, 48) has datatype: 1051\n", - "DEBUG: Edge (node, suc) (51, 50) has datatype: 1051\n", + "Duplicate successor removed: 48 with Accel: 44\n", "successor of node: 51 52\n", "51\n", "successor of node: 51 53\n", @@ -800,15 +804,13 @@ "51\n", "successor of node: 51 43\n", "1051\n", - "successor of node: 51 48\n", - "1051\n", - "successor of node: 51 50\n", + "successor of node: 51 45\n", "1051\n", "DEBUG: Edge (node, suc) (52, 57) has datatype: 52\n", - "DEBUG: Edge (node, suc) (52, 44) has datatype: 1052\n", + "DEBUG: Edge (node, suc) (52, 49) has datatype: 1052\n", "successor of node: 52 57\n", "52\n", - "successor of node: 52 44\n", + "successor of node: 52 49\n", "1052\n", "DEBUG: Edge (node, suc) (53, 54) has datatype: 53\n", "DEBUG: Edge (node, suc) (53, 51) has datatype: 1053\n", @@ -836,26 +838,32 @@ "1056\n", "DEBUG: Edge (node, suc) (57, 58) has datatype: 57\n", "DEBUG: Edge (node, suc) (57, 59) has datatype: 57\n", - "Duplicate successor removed: 59 with Accel: 56\n", "DEBUG: Edge (node, suc) (57, 62) has datatype: 57\n", "DEBUG: Edge (node, suc) (57, 67) has datatype: 57\n", - "Duplicate successor removed: 67 with Accel: 56\n", + "Duplicate successor removed: 67 with Accel: 59\n", "DEBUG: Edge (node, suc) (57, 52) has datatype: 1057\n", - "DEBUG: Edge (node, suc) (57, 55) has datatype: 1057\n", "successor of node: 57 58\n", "57\n", + "successor of node: 57 59\n", + "57\n", "successor of node: 57 62\n", "57\n", "successor of node: 57 52\n", "1057\n", - "successor of node: 57 55\n", - "1057\n", "DEBUG: Edge (node, suc) (58, 69) has datatype: 58\n", + "DEBUG: Edge (node, suc) (58, 55) has datatype: 1058\n", + "DEBUG: Edge (node, suc) (58, 56) has datatype: 1058\n", + "Duplicate successor removed: 56 with Accel: 55\n", "successor of node: 58 69\n", "58\n", + "successor of node: 58 55\n", + "1058\n", "DEBUG: Edge (node, suc) (59, 60) has datatype: 59\n", + "DEBUG: Edge (node, suc) (59, 57) has datatype: 1059\n", "successor of node: 59 60\n", "59\n", + "successor of node: 59 57\n", + "1059\n", "DEBUG: Edge (node, suc) (60, 61) has datatype: 60\n", "successor of node: 60 61\n", "60\n", @@ -875,35 +883,45 @@ "successor of node: 64 65\n", "64\n", "DEBUG: Edge (node, suc) (65, 66) has datatype: 65\n", + "DEBUG: Edge (node, suc) (65, 62) has datatype: 1065\n", "successor of node: 65 66\n", "65\n", + "successor of node: 65 62\n", + "1065\n", "DEBUG: Edge (node, suc) (66, 69) has datatype: 66\n", - "DEBUG: Edge (node, suc) (66, 62) has datatype: 1066\n", + "DEBUG: Edge (node, suc) (66, 65) has datatype: 1066\n", "successor of node: 66 69\n", "66\n", - "successor of node: 66 62\n", + "successor of node: 66 65\n", "1066\n", "DEBUG: Edge (node, suc) (67, 68) has datatype: 67\n", + "DEBUG: Edge (node, suc) (67, 57) has datatype: 1067\n", "successor of node: 67 68\n", "67\n", + "successor of node: 67 57\n", + "1067\n", "DEBUG: Edge (node, suc) (68, 69) has datatype: 68\n", "successor of node: 68 69\n", "68\n", - "DEBUG: Edge (node, suc) (69, 56) has datatype: 1069\n", + "DEBUG: Edge (node, suc) (69, 59) has datatype: 1069\n", "DEBUG: Edge (node, suc) (69, 66) has datatype: 1069\n", - "DEBUG: Edge (node, suc) (69, 118) has datatype: 118\n", - "successor of node: 69 56\n", + "Duplicate successor removed: 66 with Accel: 59\n", + "DEBUG: Edge (node, suc) (69, 67) has datatype: 1069\n", + "Duplicate successor removed: 67 with Accel: 59\n", + "DEBUG: Edge (node, suc) (69, 58) has datatype: 1069\n", + "DEBUG: Edge (node, suc) (69, 120) has datatype: 120\n", + "successor of node: 69 59\n", "1069\n", - "successor of node: 69 66\n", + "successor of node: 69 58\n", "1069\n", - "successor of node: 69 118\n", - "118\n", + "successor of node: 69 120\n", + "120\n", "DEBUG: Edge (node, suc) (70, 0) has datatype: 1001\n", "successor of node: 70 0\n", "1001\n", - "DEBUG: Edge (node, suc) (71, 10) has datatype: 1011\n", - "successor of node: 71 10\n", - "1011\n", + "DEBUG: Edge (node, suc) (71, 8) has datatype: 1010\n", + "successor of node: 71 8\n", + "1010\n", "DEBUG: Edge (node, suc) (72, 12) has datatype: 1016\n", "successor of node: 72 12\n", "1016\n", @@ -919,27 +937,27 @@ "DEBUG: Edge (node, suc) (76, 35) has datatype: 1043\n", "successor of node: 76 35\n", "1043\n", - "DEBUG: Edge (node, suc) (77, 44) has datatype: 1052\n", + "DEBUG: Edge (node, suc) (77, 44) has datatype: 1045\n", "successor of node: 77 44\n", - "1052\n", + "1045\n", "DEBUG: Edge (node, suc) (78, 46) has datatype: 1048\n", "successor of node: 78 46\n", "1048\n", - "DEBUG: Edge (node, suc) (79, 49) has datatype: 1050\n", + "DEBUG: Edge (node, suc) (79, 49) has datatype: 1052\n", "successor of node: 79 49\n", - "1050\n", + "1052\n", "DEBUG: Edge (node, suc) (80, 4) has datatype: 1006\n", "successor of node: 80 4\n", "1006\n", - "DEBUG: Edge (node, suc) (81, 56) has datatype: 1069\n", - "successor of node: 81 56\n", + "DEBUG: Edge (node, suc) (81, 55) has datatype: 1058\n", + "successor of node: 81 55\n", + "1058\n", + "DEBUG: Edge (node, suc) (82, 59) has datatype: 1069\n", + "successor of node: 82 59\n", "1069\n", - "DEBUG: Edge (node, suc) (82, 62) has datatype: 1066\n", - "successor of node: 82 62\n", - "1066\n", - "DEBUG: Edge (node, suc) (83, 8) has datatype: 1009\n", - "successor of node: 83 8\n", - "1009\n", + "DEBUG: Edge (node, suc) (83, 62) has datatype: 1065\n", + "successor of node: 83 62\n", + "1065\n", "DEBUG: Edge (node, suc) (84, 1) has datatype: 1002\n", "successor of node: 84 1\n", "1002\n", @@ -958,9 +976,9 @@ "DEBUG: Edge (node, suc) (89, 7) has datatype: 1012\n", "successor of node: 89 7\n", "1012\n", - "DEBUG: Edge (node, suc) (90, 9) has datatype: 1010\n", - "successor of node: 90 9\n", - "1010\n", + "DEBUG: Edge (node, suc) (90, 10) has datatype: 1011\n", + "successor of node: 90 10\n", + "1011\n", "DEBUG: Edge (node, suc) (91, 11) has datatype: 1012\n", "successor of node: 91 11\n", "1012\n", @@ -1012,11 +1030,11 @@ "DEBUG: Edge (node, suc) (107, 43) has datatype: 1051\n", "successor of node: 107 43\n", "1051\n", - "DEBUG: Edge (node, suc) (108, 48) has datatype: 1051\n", - "successor of node: 108 48\n", + "DEBUG: Edge (node, suc) (108, 45) has datatype: 1051\n", + "successor of node: 108 45\n", "1051\n", - "DEBUG: Edge (node, suc) (109, 50) has datatype: 1051\n", - "successor of node: 109 50\n", + "DEBUG: Edge (node, suc) (109, 48) has datatype: 1051\n", + "successor of node: 109 48\n", "1051\n", "DEBUG: Edge (node, suc) (110, 51) has datatype: 1053\n", "successor of node: 110 51\n", @@ -1033,15 +1051,21 @@ "DEBUG: Edge (node, suc) (114, 54) has datatype: 1055\n", "successor of node: 114 54\n", "1055\n", - "DEBUG: Edge (node, suc) (115, 55) has datatype: 1057\n", - "successor of node: 115 55\n", - "1057\n", + "DEBUG: Edge (node, suc) (115, 57) has datatype: 1059\n", + "successor of node: 115 57\n", + "1059\n", "DEBUG: Edge (node, suc) (116, 57) has datatype: 1062\n", "successor of node: 116 57\n", "1062\n", - "DEBUG: Edge (node, suc) (117, 66) has datatype: 1069\n", - "successor of node: 117 66\n", + "DEBUG: Edge (node, suc) (117, 57) has datatype: 1067\n", + "successor of node: 117 57\n", + "1067\n", + "DEBUG: Edge (node, suc) (118, 58) has datatype: 1069\n", + "successor of node: 118 58\n", "1069\n", + "DEBUG: Edge (node, suc) (119, 65) has datatype: 1066\n", + "successor of node: 119 65\n", + "1066\n", "\n", "Edges and their attributes in task_graph_update:\n", "Edge: (0, 1), Attributes: {'flits': 285, 'datatype': 0}\n", @@ -1064,9 +1088,8 @@ "Edge: (8, 9), Attributes: {'flits': 137, 'datatype': 8}\n", "Edge: (8, 5), Attributes: {'flits': 1, 'datatype': 1008}\n", "Edge: (9, 10), Attributes: {'flits': 137, 'datatype': 9}\n", - "Edge: (9, 8), Attributes: {'flits': 1, 'datatype': 1009}\n", "Edge: (10, 11), Attributes: {'flits': 137, 'datatype': 10}\n", - "Edge: (10, 9), Attributes: {'flits': 1, 'datatype': 1010}\n", + "Edge: (10, 8), Attributes: {'flits': 1, 'datatype': 1010}\n", "Edge: (11, 12), Attributes: {'flits': 194, 'datatype': 11}\n", "Edge: (11, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", "Edge: (12, 13), Attributes: {'flits': 388, 'datatype': 12}\n", @@ -1141,6 +1164,7 @@ "Edge: (44, 45), Attributes: {'flits': 32, 'datatype': 44}\n", "Edge: (44, 42), Attributes: {'flits': 1, 'datatype': 1044}\n", "Edge: (45, 51), Attributes: {'flits': 48, 'datatype': 45}\n", + "Edge: (45, 44), Attributes: {'flits': 1, 'datatype': 1045}\n", "Edge: (46, 47), Attributes: {'flits': 32, 'datatype': 46}\n", "Edge: (46, 42), Attributes: {'flits': 1, 'datatype': 1046}\n", "Edge: (47, 48), Attributes: {'flits': 48, 'datatype': 47}\n", @@ -1149,15 +1173,14 @@ "Edge: (49, 50), Attributes: {'flits': 189, 'datatype': 49}\n", "Edge: (49, 42), Attributes: {'flits': 1, 'datatype': 1049}\n", "Edge: (50, 51), Attributes: {'flits': 48, 'datatype': 50}\n", - "Edge: (50, 49), Attributes: {'flits': 1, 'datatype': 1050}\n", "Edge: (51, 52), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 53), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 56), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 43), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (51, 45), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (51, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (51, 50), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (52, 57), Attributes: {'flits': 45, 'datatype': 52}\n", - "Edge: (52, 44), Attributes: {'flits': 1, 'datatype': 1052}\n", + "Edge: (52, 49), Attributes: {'flits': 1, 'datatype': 1052}\n", "Edge: (53, 54), Attributes: {'flits': 95, 'datatype': 53}\n", "Edge: (53, 51), Attributes: {'flits': 1, 'datatype': 1053}\n", "Edge: (54, 55), Attributes: {'flits': 110, 'datatype': 54}\n", @@ -1171,9 +1194,11 @@ "Edge: (57, 62), Attributes: {'flits': 119, 'datatype': 57}\n", "Edge: (57, 67), Attributes: {'flits': 119, 'datatype': 57}\n", "Edge: (57, 52), Attributes: {'flits': 1, 'datatype': 1057}\n", - "Edge: (57, 55), Attributes: {'flits': 1, 'datatype': 1057}\n", "Edge: (58, 69), Attributes: {'flits': 45, 'datatype': 58}\n", + "Edge: (58, 55), Attributes: {'flits': 1, 'datatype': 1058}\n", + "Edge: (58, 56), Attributes: {'flits': 1, 'datatype': 1058}\n", "Edge: (59, 60), Attributes: {'flits': 23, 'datatype': 59}\n", + "Edge: (59, 57), Attributes: {'flits': 1, 'datatype': 1059}\n", "Edge: (60, 61), Attributes: {'flits': 26, 'datatype': 60}\n", "Edge: (61, 69), Attributes: {'flits': 30, 'datatype': 61}\n", "Edge: (62, 63), Attributes: {'flits': 23, 'datatype': 62}\n", @@ -1181,34 +1206,38 @@ "Edge: (63, 64), Attributes: {'flits': 23, 'datatype': 63}\n", "Edge: (64, 65), Attributes: {'flits': 26, 'datatype': 64}\n", "Edge: (65, 66), Attributes: {'flits': 26, 'datatype': 65}\n", + "Edge: (65, 62), Attributes: {'flits': 1, 'datatype': 1065}\n", "Edge: (66, 69), Attributes: {'flits': 30, 'datatype': 66}\n", - "Edge: (66, 62), Attributes: {'flits': 1, 'datatype': 1066}\n", + "Edge: (66, 65), Attributes: {'flits': 1, 'datatype': 1066}\n", "Edge: (67, 68), Attributes: {'flits': 119, 'datatype': 67}\n", + "Edge: (67, 57), Attributes: {'flits': 1, 'datatype': 1067}\n", "Edge: (68, 69), Attributes: {'flits': 15, 'datatype': 68}\n", - "Edge: (69, 56), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 59), Attributes: {'flits': 1, 'datatype': 1069}\n", "Edge: (69, 66), Attributes: {'flits': 1, 'datatype': 1069}\n", - "Edge: (69, 118), Attributes: {'flits': 1, 'datatype': 118}\n", + "Edge: (69, 67), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 58), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 120), Attributes: {'flits': 1, 'datatype': 120}\n", "Edge: (70, 0), Attributes: {'flits': 1, 'datatype': 1001}\n", - "Edge: (71, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", + "Edge: (71, 8), Attributes: {'flits': 1, 'datatype': 1010}\n", "Edge: (72, 12), Attributes: {'flits': 1, 'datatype': 1016}\n", "Edge: (73, 17), Attributes: {'flits': 1, 'datatype': 1025}\n", "Edge: (74, 26), Attributes: {'flits': 1, 'datatype': 1034}\n", "Edge: (75, 2), Attributes: {'flits': 1, 'datatype': 1003}\n", "Edge: (76, 35), Attributes: {'flits': 1, 'datatype': 1043}\n", - "Edge: (77, 44), Attributes: {'flits': 1, 'datatype': 1052}\n", + "Edge: (77, 44), Attributes: {'flits': 1, 'datatype': 1045}\n", "Edge: (78, 46), Attributes: {'flits': 1, 'datatype': 1048}\n", - "Edge: (79, 49), Attributes: {'flits': 1, 'datatype': 1050}\n", + "Edge: (79, 49), Attributes: {'flits': 1, 'datatype': 1052}\n", "Edge: (80, 4), Attributes: {'flits': 1, 'datatype': 1006}\n", - "Edge: (81, 56), Attributes: {'flits': 1, 'datatype': 1069}\n", - "Edge: (82, 62), Attributes: {'flits': 1, 'datatype': 1066}\n", - "Edge: (83, 8), Attributes: {'flits': 1, 'datatype': 1009}\n", + "Edge: (81, 55), Attributes: {'flits': 1, 'datatype': 1058}\n", + "Edge: (82, 59), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (83, 62), Attributes: {'flits': 1, 'datatype': 1065}\n", "Edge: (84, 1), Attributes: {'flits': 1, 'datatype': 1002}\n", "Edge: (85, 2), Attributes: {'flits': 1, 'datatype': 1004}\n", "Edge: (86, 3), Attributes: {'flits': 1, 'datatype': 1005}\n", "Edge: (87, 5), Attributes: {'flits': 1, 'datatype': 1008}\n", "Edge: (88, 6), Attributes: {'flits': 1, 'datatype': 1007}\n", "Edge: (89, 7), Attributes: {'flits': 1, 'datatype': 1012}\n", - "Edge: (90, 9), Attributes: {'flits': 1, 'datatype': 1010}\n", + "Edge: (90, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", "Edge: (91, 11), Attributes: {'flits': 1, 'datatype': 1012}\n", "Edge: (92, 15), Attributes: {'flits': 1, 'datatype': 1017}\n", "Edge: (93, 15), Attributes: {'flits': 1, 'datatype': 1019}\n", @@ -1226,16 +1255,18 @@ "Edge: (105, 42), Attributes: {'flits': 1, 'datatype': 1046}\n", "Edge: (106, 42), Attributes: {'flits': 1, 'datatype': 1049}\n", "Edge: (107, 43), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (108, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (109, 50), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (108, 45), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (109, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (110, 51), Attributes: {'flits': 1, 'datatype': 1053}\n", "Edge: (111, 51), Attributes: {'flits': 1, 'datatype': 1056}\n", "Edge: (112, 52), Attributes: {'flits': 1, 'datatype': 1057}\n", "Edge: (113, 53), Attributes: {'flits': 1, 'datatype': 1054}\n", "Edge: (114, 54), Attributes: {'flits': 1, 'datatype': 1055}\n", - "Edge: (115, 55), Attributes: {'flits': 1, 'datatype': 1057}\n", + "Edge: (115, 57), Attributes: {'flits': 1, 'datatype': 1059}\n", "Edge: (116, 57), Attributes: {'flits': 1, 'datatype': 1062}\n", - "Edge: (117, 66), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (117, 57), Attributes: {'flits': 1, 'datatype': 1067}\n", + "Edge: (118, 58), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (119, 65), Attributes: {'flits': 1, 'datatype': 1066}\n", "DEBUG: Edge (node, suc) (0, 1) has datatype: 0\n", "successor of node: 0 1\n", "0\n", @@ -1294,16 +1325,13 @@ "successor of node: 8 5\n", "1008\n", "DEBUG: Edge (node, suc) (9, 10) has datatype: 9\n", - "DEBUG: Edge (node, suc) (9, 8) has datatype: 1009\n", "successor of node: 9 10\n", "9\n", - "successor of node: 9 8\n", - "1009\n", "DEBUG: Edge (node, suc) (10, 11) has datatype: 10\n", - "DEBUG: Edge (node, suc) (10, 9) has datatype: 1010\n", + "DEBUG: Edge (node, suc) (10, 8) has datatype: 1010\n", "successor of node: 10 11\n", "10\n", - "successor of node: 10 9\n", + "successor of node: 10 8\n", "1010\n", "DEBUG: Edge (node, suc) (11, 12) has datatype: 11\n", "DEBUG: Edge (node, suc) (11, 10) has datatype: 1011\n", @@ -1483,14 +1511,13 @@ "DEBUG: Edge (node, suc) (42, 43) has datatype: 42\n", "DEBUG: Edge (node, suc) (42, 44) has datatype: 42\n", "DEBUG: Edge (node, suc) (42, 46) has datatype: 42\n", + "Duplicate successor removed: 46 with Accel: 44\n", "DEBUG: Edge (node, suc) (42, 49) has datatype: 42\n", "DEBUG: Edge (node, suc) (42, 34) has datatype: 1042\n", "successor of node: 42 43\n", "42\n", "successor of node: 42 44\n", "42\n", - "successor of node: 42 46\n", - "42\n", "successor of node: 42 49\n", "42\n", "successor of node: 42 34\n", @@ -1512,8 +1539,11 @@ "successor of node: 44 42\n", "1044\n", "DEBUG: Edge (node, suc) (45, 51) has datatype: 45\n", + "DEBUG: Edge (node, suc) (45, 44) has datatype: 1045\n", "successor of node: 45 51\n", "45\n", + "successor of node: 45 44\n", + "1045\n", "DEBUG: Edge (node, suc) (46, 47) has datatype: 46\n", "DEBUG: Edge (node, suc) (46, 42) has datatype: 1046\n", "successor of node: 46 47\n", @@ -1536,17 +1566,15 @@ "successor of node: 49 42\n", "1049\n", "DEBUG: Edge (node, suc) (50, 51) has datatype: 50\n", - "DEBUG: Edge (node, suc) (50, 49) has datatype: 1050\n", "successor of node: 50 51\n", "50\n", - "successor of node: 50 49\n", - "1050\n", "DEBUG: Edge (node, suc) (51, 52) has datatype: 51\n", "DEBUG: Edge (node, suc) (51, 53) has datatype: 51\n", "DEBUG: Edge (node, suc) (51, 56) has datatype: 51\n", "DEBUG: Edge (node, suc) (51, 43) has datatype: 1051\n", + "DEBUG: Edge (node, suc) (51, 45) has datatype: 1051\n", "DEBUG: Edge (node, suc) (51, 48) has datatype: 1051\n", - "DEBUG: Edge (node, suc) (51, 50) has datatype: 1051\n", + "Duplicate successor removed: 48 with Accel: 44\n", "successor of node: 51 52\n", "51\n", "successor of node: 51 53\n", @@ -1555,15 +1583,13 @@ "51\n", "successor of node: 51 43\n", "1051\n", - "successor of node: 51 48\n", - "1051\n", - "successor of node: 51 50\n", + "successor of node: 51 45\n", "1051\n", "DEBUG: Edge (node, suc) (52, 57) has datatype: 52\n", - "DEBUG: Edge (node, suc) (52, 44) has datatype: 1052\n", + "DEBUG: Edge (node, suc) (52, 49) has datatype: 1052\n", "successor of node: 52 57\n", "52\n", - "successor of node: 52 44\n", + "successor of node: 52 49\n", "1052\n", "DEBUG: Edge (node, suc) (53, 54) has datatype: 53\n", "DEBUG: Edge (node, suc) (53, 51) has datatype: 1053\n", @@ -1591,26 +1617,32 @@ "1056\n", "DEBUG: Edge (node, suc) (57, 58) has datatype: 57\n", "DEBUG: Edge (node, suc) (57, 59) has datatype: 57\n", - "Duplicate successor removed: 59 with Accel: 56\n", "DEBUG: Edge (node, suc) (57, 62) has datatype: 57\n", "DEBUG: Edge (node, suc) (57, 67) has datatype: 57\n", - "Duplicate successor removed: 67 with Accel: 56\n", + "Duplicate successor removed: 67 with Accel: 59\n", "DEBUG: Edge (node, suc) (57, 52) has datatype: 1057\n", - "DEBUG: Edge (node, suc) (57, 55) has datatype: 1057\n", "successor of node: 57 58\n", "57\n", + "successor of node: 57 59\n", + "57\n", "successor of node: 57 62\n", "57\n", "successor of node: 57 52\n", "1057\n", - "successor of node: 57 55\n", - "1057\n", "DEBUG: Edge (node, suc) (58, 69) has datatype: 58\n", + "DEBUG: Edge (node, suc) (58, 55) has datatype: 1058\n", + "DEBUG: Edge (node, suc) (58, 56) has datatype: 1058\n", + "Duplicate successor removed: 56 with Accel: 55\n", "successor of node: 58 69\n", "58\n", + "successor of node: 58 55\n", + "1058\n", "DEBUG: Edge (node, suc) (59, 60) has datatype: 59\n", + "DEBUG: Edge (node, suc) (59, 57) has datatype: 1059\n", "successor of node: 59 60\n", "59\n", + "successor of node: 59 57\n", + "1059\n", "DEBUG: Edge (node, suc) (60, 61) has datatype: 60\n", "successor of node: 60 61\n", "60\n", @@ -1630,25 +1662,35 @@ "successor of node: 64 65\n", "64\n", "DEBUG: Edge (node, suc) (65, 66) has datatype: 65\n", + "DEBUG: Edge (node, suc) (65, 62) has datatype: 1065\n", "successor of node: 65 66\n", "65\n", + "successor of node: 65 62\n", + "1065\n", "DEBUG: Edge (node, suc) (66, 69) has datatype: 66\n", - "DEBUG: Edge (node, suc) (66, 62) has datatype: 1066\n", + "DEBUG: Edge (node, suc) (66, 65) has datatype: 1066\n", "successor of node: 66 69\n", "66\n", - "successor of node: 66 62\n", + "successor of node: 66 65\n", "1066\n", "DEBUG: Edge (node, suc) (67, 68) has datatype: 67\n", + "DEBUG: Edge (node, suc) (67, 57) has datatype: 1067\n", "successor of node: 67 68\n", "67\n", + "successor of node: 67 57\n", + "1067\n", "DEBUG: Edge (node, suc) (68, 69) has datatype: 68\n", "successor of node: 68 69\n", "68\n", - "DEBUG: Edge (node, suc) (69, 56) has datatype: 1069\n", + "DEBUG: Edge (node, suc) (69, 59) has datatype: 1069\n", "DEBUG: Edge (node, suc) (69, 66) has datatype: 1069\n", - "successor of node: 69 56\n", + "Duplicate successor removed: 66 with Accel: 59\n", + "DEBUG: Edge (node, suc) (69, 67) has datatype: 1069\n", + "Duplicate successor removed: 67 with Accel: 59\n", + "DEBUG: Edge (node, suc) (69, 58) has datatype: 1069\n", + "successor of node: 69 59\n", "1069\n", - "successor of node: 69 66\n", + "successor of node: 69 58\n", "1069\n", "\n", "Edges and their attributes in task_graph_update:\n", @@ -1672,9 +1714,8 @@ "Edge: (8, 9), Attributes: {'flits': 137, 'datatype': 8}\n", "Edge: (8, 5), Attributes: {'flits': 1, 'datatype': 1008}\n", "Edge: (9, 10), Attributes: {'flits': 137, 'datatype': 9}\n", - "Edge: (9, 8), Attributes: {'flits': 1, 'datatype': 1009}\n", "Edge: (10, 11), Attributes: {'flits': 137, 'datatype': 10}\n", - "Edge: (10, 9), Attributes: {'flits': 1, 'datatype': 1010}\n", + "Edge: (10, 8), Attributes: {'flits': 1, 'datatype': 1010}\n", "Edge: (11, 12), Attributes: {'flits': 194, 'datatype': 11}\n", "Edge: (11, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", "Edge: (12, 13), Attributes: {'flits': 388, 'datatype': 12}\n", @@ -1749,6 +1790,7 @@ "Edge: (44, 45), Attributes: {'flits': 32, 'datatype': 44}\n", "Edge: (44, 42), Attributes: {'flits': 1, 'datatype': 1044}\n", "Edge: (45, 51), Attributes: {'flits': 48, 'datatype': 45}\n", + "Edge: (45, 44), Attributes: {'flits': 1, 'datatype': 1045}\n", "Edge: (46, 47), Attributes: {'flits': 32, 'datatype': 46}\n", "Edge: (46, 42), Attributes: {'flits': 1, 'datatype': 1046}\n", "Edge: (47, 48), Attributes: {'flits': 48, 'datatype': 47}\n", @@ -1757,15 +1799,14 @@ "Edge: (49, 50), Attributes: {'flits': 189, 'datatype': 49}\n", "Edge: (49, 42), Attributes: {'flits': 1, 'datatype': 1049}\n", "Edge: (50, 51), Attributes: {'flits': 48, 'datatype': 50}\n", - "Edge: (50, 49), Attributes: {'flits': 1, 'datatype': 1050}\n", "Edge: (51, 52), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 53), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 56), Attributes: {'flits': 189, 'datatype': 51}\n", "Edge: (51, 43), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (51, 45), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (51, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (51, 50), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (52, 57), Attributes: {'flits': 45, 'datatype': 52}\n", - "Edge: (52, 44), Attributes: {'flits': 1, 'datatype': 1052}\n", + "Edge: (52, 49), Attributes: {'flits': 1, 'datatype': 1052}\n", "Edge: (53, 54), Attributes: {'flits': 95, 'datatype': 53}\n", "Edge: (53, 51), Attributes: {'flits': 1, 'datatype': 1053}\n", "Edge: (54, 55), Attributes: {'flits': 110, 'datatype': 54}\n", @@ -1779,9 +1820,11 @@ "Edge: (57, 62), Attributes: {'flits': 119, 'datatype': 57}\n", "Edge: (57, 67), Attributes: {'flits': 119, 'datatype': 57}\n", "Edge: (57, 52), Attributes: {'flits': 1, 'datatype': 1057}\n", - "Edge: (57, 55), Attributes: {'flits': 1, 'datatype': 1057}\n", "Edge: (58, 69), Attributes: {'flits': 45, 'datatype': 58}\n", + "Edge: (58, 55), Attributes: {'flits': 1, 'datatype': 1058}\n", + "Edge: (58, 56), Attributes: {'flits': 1, 'datatype': 1058}\n", "Edge: (59, 60), Attributes: {'flits': 23, 'datatype': 59}\n", + "Edge: (59, 57), Attributes: {'flits': 1, 'datatype': 1059}\n", "Edge: (60, 61), Attributes: {'flits': 26, 'datatype': 60}\n", "Edge: (61, 69), Attributes: {'flits': 30, 'datatype': 61}\n", "Edge: (62, 63), Attributes: {'flits': 23, 'datatype': 62}\n", @@ -1789,34 +1832,38 @@ "Edge: (63, 64), Attributes: {'flits': 23, 'datatype': 63}\n", "Edge: (64, 65), Attributes: {'flits': 26, 'datatype': 64}\n", "Edge: (65, 66), Attributes: {'flits': 26, 'datatype': 65}\n", + "Edge: (65, 62), Attributes: {'flits': 1, 'datatype': 1065}\n", "Edge: (66, 69), Attributes: {'flits': 30, 'datatype': 66}\n", - "Edge: (66, 62), Attributes: {'flits': 1, 'datatype': 1066}\n", + "Edge: (66, 65), Attributes: {'flits': 1, 'datatype': 1066}\n", "Edge: (67, 68), Attributes: {'flits': 119, 'datatype': 67}\n", + "Edge: (67, 57), Attributes: {'flits': 1, 'datatype': 1067}\n", "Edge: (68, 69), Attributes: {'flits': 15, 'datatype': 68}\n", - "Edge: (69, 56), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 59), Attributes: {'flits': 1, 'datatype': 1069}\n", "Edge: (69, 66), Attributes: {'flits': 1, 'datatype': 1069}\n", - "Edge: (69, 118), Attributes: {'flits': 1, 'datatype': 118}\n", + "Edge: (69, 67), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 58), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (69, 120), Attributes: {'flits': 1, 'datatype': 120}\n", "Edge: (70, 0), Attributes: {'flits': 1, 'datatype': 1001}\n", - "Edge: (71, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", + "Edge: (71, 8), Attributes: {'flits': 1, 'datatype': 1010}\n", "Edge: (72, 12), Attributes: {'flits': 1, 'datatype': 1016}\n", "Edge: (73, 17), Attributes: {'flits': 1, 'datatype': 1025}\n", "Edge: (74, 26), Attributes: {'flits': 1, 'datatype': 1034}\n", "Edge: (75, 2), Attributes: {'flits': 1, 'datatype': 1003}\n", "Edge: (76, 35), Attributes: {'flits': 1, 'datatype': 1043}\n", - "Edge: (77, 44), Attributes: {'flits': 1, 'datatype': 1052}\n", + "Edge: (77, 44), Attributes: {'flits': 1, 'datatype': 1045}\n", "Edge: (78, 46), Attributes: {'flits': 1, 'datatype': 1048}\n", - "Edge: (79, 49), Attributes: {'flits': 1, 'datatype': 1050}\n", + "Edge: (79, 49), Attributes: {'flits': 1, 'datatype': 1052}\n", "Edge: (80, 4), Attributes: {'flits': 1, 'datatype': 1006}\n", - "Edge: (81, 56), Attributes: {'flits': 1, 'datatype': 1069}\n", - "Edge: (82, 62), Attributes: {'flits': 1, 'datatype': 1066}\n", - "Edge: (83, 8), Attributes: {'flits': 1, 'datatype': 1009}\n", + "Edge: (81, 55), Attributes: {'flits': 1, 'datatype': 1058}\n", + "Edge: (82, 59), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (83, 62), Attributes: {'flits': 1, 'datatype': 1065}\n", "Edge: (84, 1), Attributes: {'flits': 1, 'datatype': 1002}\n", "Edge: (85, 2), Attributes: {'flits': 1, 'datatype': 1004}\n", "Edge: (86, 3), Attributes: {'flits': 1, 'datatype': 1005}\n", "Edge: (87, 5), Attributes: {'flits': 1, 'datatype': 1008}\n", "Edge: (88, 6), Attributes: {'flits': 1, 'datatype': 1007}\n", "Edge: (89, 7), Attributes: {'flits': 1, 'datatype': 1012}\n", - "Edge: (90, 9), Attributes: {'flits': 1, 'datatype': 1010}\n", + "Edge: (90, 10), Attributes: {'flits': 1, 'datatype': 1011}\n", "Edge: (91, 11), Attributes: {'flits': 1, 'datatype': 1012}\n", "Edge: (92, 15), Attributes: {'flits': 1, 'datatype': 1017}\n", "Edge: (93, 15), Attributes: {'flits': 1, 'datatype': 1019}\n", @@ -1834,16 +1881,18 @@ "Edge: (105, 42), Attributes: {'flits': 1, 'datatype': 1046}\n", "Edge: (106, 42), Attributes: {'flits': 1, 'datatype': 1049}\n", "Edge: (107, 43), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (108, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", - "Edge: (109, 50), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (108, 45), Attributes: {'flits': 1, 'datatype': 1051}\n", + "Edge: (109, 48), Attributes: {'flits': 1, 'datatype': 1051}\n", "Edge: (110, 51), Attributes: {'flits': 1, 'datatype': 1053}\n", "Edge: (111, 51), Attributes: {'flits': 1, 'datatype': 1056}\n", "Edge: (112, 52), Attributes: {'flits': 1, 'datatype': 1057}\n", "Edge: (113, 53), Attributes: {'flits': 1, 'datatype': 1054}\n", "Edge: (114, 54), Attributes: {'flits': 1, 'datatype': 1055}\n", - "Edge: (115, 55), Attributes: {'flits': 1, 'datatype': 1057}\n", + "Edge: (115, 57), Attributes: {'flits': 1, 'datatype': 1059}\n", "Edge: (116, 57), Attributes: {'flits': 1, 'datatype': 1062}\n", - "Edge: (117, 66), Attributes: {'flits': 1, 'datatype': 1069}\n" + "Edge: (117, 57), Attributes: {'flits': 1, 'datatype': 1067}\n", + "Edge: (118, 58), Attributes: {'flits': 1, 'datatype': 1069}\n", + "Edge: (119, 65), Attributes: {'flits': 1, 'datatype': 1066}\n" ] } ], diff --git a/XML_Scripts/mappingXML.ipynb 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