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Delete network/test_settings_fashion directory

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David Rotermund 2023-01-15 03:01:07 +01:00 committed by GitHub
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commit 6b95fd08df
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6 changed files with 0 additions and 245 deletions
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4
network/test_settings_fashion/dataset.json
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@ -1,4 +0,0 @@
{
"data_path": "./DATA_FASHION_MNIST/",
"data_mode": "MNIST_FASHION"
}

29
network/test_settings_fashion/def_approx_cnn.json
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@ -1,29 +0,0 @@
{
"epoch_id_max": 200,
"batch_size": 24,
"stage_id": 0,
"simulation_id": 0,
"learning_parameters": {
"loss_mode": 1, // X-Entropy
"number_of_batches_for_one_update": 20,
"learning_rate_gamma_w": 0.001,
"lr_scheduler_patience_w": -1,
"adapt_learning_rate_after_minibatch": false,
"w_trainable": [
true
]
},
"augmentation": {},
"image_statistics": {},
"approximation_setting": {
"number_of_frac_bits": [
30
], // Quantization of the mantissa
"approximation_enable": [
true
], // In addition to the quantization more approx
"number_of_trunc_bits": [
1
]
}
}

24
network/test_settings_fashion/def_sbs_ap.json
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@ -1,24 +0,0 @@
{
"epoch_id_max": 200,
"number_of_spikes": [
1600
],
"batch_size": 24,
"forgetting_offset": 0.0,
"stage_id": 0,
"simulation_id": 0,
"learning_parameters": {
"learning_rate_threshold_w": 0.001,
"eps_xy_intitial": 1.0,
"number_of_batches_for_one_update": 20,
"learning_rate_gamma_w": 0.1,
"lr_scheduler_patience_w": 250,
"adapt_learning_rate_after_minibatch": true,
"w_trainable": [
true
]
},
"augmentation": {},
"image_statistics": {},
"approximation_setting": {}
}

97
network/test_settings_fashion/network_approx_cnn.json
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@ -1,97 +0,0 @@
{
"network_structure": {
"number_of_output_neurons": 10,
"layer_type": [
"APPROX CONV2D",
"RELU",
"MAX POOLING",
"APPROX CONV2D",
"RELU",
"MAX POOLING",
"APPROX CONV2D",
"RELU",
"APPROX CONV2D"
],
"strides": [
[
1,
1
], // "CONV2D"
[], // "RELU",
[
2,
2
], // "MAX POOLING",
[
1,
1
], // "CONV2D"
[], // "RELU",
[
2,
2
], // "MAX POOLING",
[
1,
1
], // "CONV2D"
[], // "RELU",
[
1,
1
] // "CONV2D"
],
"forward_neuron_numbers": [
[
1,
32
], // "CONV2D",
[], // "RELU",
[], // "MAX POOLING",
[
32,
64
], // "CONV2D",
[], // "RELU",
[], // "MAX POOLING",
[
64,
96
], // "CONV2D",
[], // "RELU",
[
96,
10
] // "CONV2D",
],
"forward_kernel_size": [
[
5,
5
], // "CONV2D",
[], // "RELU",
[
2,
2
], // "MAX POOLING",
[
5,
5
], // "CONV2D",
[], // "RELU",
[
2,
2
], // "MAX POOLING",
[
3,
3
], // "CONV2D",
[], // "RELU",
[
1,
1
] // "CONV2D",
]
}
}

91
network/test_settings_fashion/network_sbs_ap.json
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@ -1,91 +0,0 @@
{
"network_structure": {
"number_of_output_neurons": 10,
"layer_type": [
"SbS",
"Average POOLING",
"SbS",
"Average POOLING",
"SbS",
"SbS"
],
"strides": [
[
1,
1
], // "SbS"
[
2,
2
], // POOLING
[
1,
1
], // "SbS"
[
2,
2
], // POOLING
[
1,
1
], // "SbS"
[
1,
1
] // "SbS"
],
"forward_neuron_numbers": [
[
1,
32
], // "SbS"
[
32,
32
], // POOLING
[
32,
64
], // "SbS"
[
64,
64
], // POOLING
[
64,
96
], // "SbS"
[
96,
10
] // "SbS"
],
"forward_kernel_size": [
[
5,
5
], // "SbS"
[
2,
2
], // POOLING
[
5,
5
], // "SbS"
[
2,
2
], // POOLING
[
3,
3
], // "SbS"
[
1,
1
] // "SbS"
]
}
}

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network/test_settings_fashion/sbs_ap_weights.zip
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