Select Git revision
log_train.txt
-
Gaspard Goupy authoredGaspard Goupy authored
log_train.txt 2.19 KiB
10:48:52 20/7/2023
Random seed: 0
Run start at 10:48:52 20/7/2023
Input data [28, 28, 1]
Train:
#1: MNIST(/home/ggoupy/phd/SNN-PCN/datasets/mnist/with-val//X_train.bin, /home/ggoupy/phd/SNN-PCN/datasets/mnist/with-val//y_train.bin)
Test:
DefaultOnOffFilter 1: [28, 28, 2]
Process.DefaultOnOffFilter {
center_dev: 1.000000
filter_size: 7
surround_dev: 2.000000
}
FeatureScaling 2: [28, 28, 2]
Process.FeatureScaling {
}
LatencyCoding 3: [28, 28, 2]
InputConverter.LatencyCoding {
}
Convolution 4: conv1 [24, 24, 16]
Layer.Convolution (conv1) {
annealing: 0.950000
epoch: 25
filter_height: 5
filter_number: 16
filter_width: 5
lr_th: 1.000000
min_th: 2.000000
padding_x: 0
padding_y: 0
stdp: STDP.Multiplicative {
am: 0.100000
ap: 0.100000
beta: 1.000000
}
stride_x: 1
stride_y: 1
t_obj: 0.750000
th: 5.000000 [16]
w: Gaussian(mean: 0.500000, dev: 0.010000) [5, 5, 2, 16]
wta_infer: 0
}
Pooling 5: pool1 [6, 6, 16]
Layer.Pooling (pool1) {
filter_height: 4
filter_number: 16
filter_width: 4
padding_x: 0
padding_y: 0
stride_x: 4
stride_y: 4
}
Output 1 of conv1 [24, 24, 16]: train-conv1
OutputConverter.DefaultOutput {
max: 1.000000
min: 0.000000
}
Output 1, Analysis: 1
Analysis.Coherence {
}
Output 2 of pool1 [6, 6, 16]: train-pool1
OutputConverter.DefaultOutput {
max: 1.000000
min: 0.000000
}
Output 2, Analysis: 1
Analysis.Activity {
}
Output 3 of pool1 [6, 6, 16]: train-pool1
OutputConverter.SpikeTiming {
}
Output 3, Analysis: 1
Analysis.SaveFeatureNumpy {
}
Load 54000 train samples from MNIST(/home/ggoupy/phd/SNN-PCN/datasets/mnist/with-val//X_train.bin, /home/ggoupy/phd/SNN-PCN/datasets/mnist/with-val//y_train.bin)
Save trained parameters at /home/ggoupy/phd/SNN-PCN/scripts/tmp2//csnn//model//Process.FeatureScaling/
train-conv1, analysis Coherence:
===Coherence===
Mean weights: 0.248656
------
N: 120
Min: 0.000932025
Q1: 0.0853569
Q2: 0.307391
Q3: 0.466387
Max: 0.822632
Save trained parameters at /home/ggoupy/phd/SNN-PCN/scripts/tmp2//csnn//model//Layer.Convolution.conv1/
train-pool1, analysis Activity:
===Activity===
* train set:
Sparsity: 0.47984
Active unit: 48.2265%
Quiet: 0%
train-pool1, analysis SaveFeatureNumpy:
Run end at 10:49:21 20/7/2023
Duration: 0h 0m 29s