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David Rotermund 2023-07-23 14:07:20 +02:00 committed by GitHub
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1 changed files with 49 additions and 25 deletions
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config.json
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@ -1,49 +1,57 @@
{
"data_path": "/home/kk/Documents/Semester4/code/RenderStimuli/Output/",
"model_continue": false, // true, (false)
"save_logging_messages": true, // (true), false
"display_logging_messages": true, // (true), false
"max_epochs": 5000,
"batch_size_train": 250,
"batch_size_test": 500,
"max_epochs": 5000,
"save_model": true,
"conv_0_kernel_size": 11,
"mp_1_kernel_size": 3,
"mp_1_stride": 2,
"use_plot_intermediate": false, // true, (false)
// data source ->
"data_path": "/home/kk/Documents/Semester4/code/RenderStimuli/Output/",
"stimuli_per_pfinkel": 30000,
"num_pfinkel_start": 0,
"num_pfinkel_stop": 10,
"num_pfinkel_step": 10,
"precision_100_percent": 4, // (4)
"train_first_layer": true, // true, (false)
"save_ever_x_epochs": 10, // (10)
"activation_function": "leaky relu", // tanh, relu, (leaky relu), none
"leak_relu_negative_slope": 0.1, // (0.1)
"condition": "Coignless",
"scale_data": 255.0, // (255.0)
// <- data source
// optimizer ->
"use_adam": true, // (true) => adam, false => SGD
// <- optimizer
// LR Scheduler ->
"use_scheduler": true, // (true), false
"scheduler_verbose": true,
"scheduler_factor": 0.025, //(0.1)
"scheduler_patience": 100, // (10)
"scheduler_threshold": 1e-5, // (1e-4)
"scheduler_patience": 10, // (10)
"scheduler_threshold": 1e-5, // (1e-5)
"minimum_learning_rate": 1e-10,
"learning_rate": 1e-4,
// <- LR Scheduler
// type of pooling layer ->
// pooling layer ->
"pooling_type": "max", // (max), average, none
// <- type of pooling layer
// <- pooling layer
// activation function ->
"activation_function": "leaky relu", // tanh, relu, (leaky relu), none
"leak_relu_negative_slope": 0.1, // (0.1)
// <- activation function
// convolution layer 0 softmax parameters ->
"conv_0_enable_softmax": true, // true, (false)
"conv_0_power_softmax": 0.0, // (0.0) = Exp
"conv_0_meanmode_softmax": false, // true, false
"conv_0_enable_softmax": false, // true, (false)
"conv_0_power_softmax": 4.0, // (0.0) = Exp
"conv_0_meanmode_softmax": true, // true, false
"conv_0_no_input_mode_softmax": false, // true, (false)
// <- convolution layer 0 softmax parameters
"use_adam": true, // (true) => adam, false => SGD
"condition": "Coignless",
"scale_data": 255.0, // (255.0)
// network definion ->
"train_first_layer": true, // true, (false)
"mp_1_kernel_size": 3,
"mp_1_stride": 2,
"conv_0_kernel_size": 11,
"conv_out_channels_list": [
[
32,
8,
8,
8
]
@ -57,8 +65,24 @@
"conv_stride_sizes": [
1
],
// <- network definion
// logging ->
"save_logging_messages": true, // (true), false
"display_logging_messages": true, // (true), false
// <- logging
// saving the model and co ->
"save_model": true,
"use_plot_intermediate": false, // true, (false)
"precision_100_percent": 4, // (4)
"save_ever_x_epochs": 10, // (10)
// <- saving the model and co
// path definitions ->
"initial_model_path": "initial_models",
"tb_runs_path": "tb_runs",
"trained_models_path": "trained_models",
"performance_data_path": "performance_data"
// <- path definitions
}