Executing method neural_path_kmeans on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.70
Ratio, Val accuracy: 0.900 76.64
Ratio, Test accuracy: 0.900 75.64
Ratio, Val accuracy: 0.700 74.76
Ratio, Test accuracy: 0.700 74.44
Ratio, Val accuracy: 0.500 68.97
Ratio, Test accuracy: 0.500 68.43
Ratio, Val accuracy: 0.300 43.82
Ratio, Test accuracy: 0.300 43.58
Ratio, Val accuracy: 0.200 18.97
Ratio, Test accuracy: 0.200 19.35
Ratio, Val accuracy: 0.150 12.50
Ratio, Test accuracy: 0.150 12.41
Ratio, Val accuracy: 0.100 10.22
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 10.22
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 10.22
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 10.22
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 10.22
Ratio, Test accuracy: 0.005 10.00
Executing method random_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.70
Ratio, Val accuracy: 0.900 75.29
Ratio, Test accuracy: 0.900 74.72
Ratio, Val accuracy: 0.700 73.06
Ratio, Test accuracy: 0.700 72.56
Ratio, Val accuracy: 0.500 65.87
Ratio, Test accuracy: 0.500 65.70
Ratio, Val accuracy: 0.300 35.30
Ratio, Test accuracy: 0.300 35.99
Ratio, Val accuracy: 0.200 19.96
Ratio, Test accuracy: 0.200 20.26
Ratio, Val accuracy: 0.150 12.18
Ratio, Test accuracy: 0.150 11.99
Ratio, Val accuracy: 0.100 10.37
Ratio, Test accuracy: 0.100 10.13
Ratio, Val accuracy: 0.050 10.22
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 10.22
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 10.22
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 10.22
Ratio, Test accuracy: 0.005 10.00
Executing method l1_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.70
Ratio, Val accuracy: 0.900 75.55
Ratio, Test accuracy: 0.900 75.33
Ratio, Val accuracy: 0.700 72.59
Ratio, Test accuracy: 0.700 71.82
Ratio, Val accuracy: 0.500 66.79
Ratio, Test accuracy: 0.500 66.97
Ratio, Val accuracy: 0.300 43.85
Ratio, Test accuracy: 0.300 43.78
Ratio, Val accuracy: 0.200 17.11
Ratio, Test accuracy: 0.200 17.24
Ratio, Val accuracy: 0.150 12.28
Ratio, Test accuracy: 0.150 12.39
Ratio, Val accuracy: 0.100 10.28
Ratio, Test accuracy: 0.100 10.01
Ratio, Val accuracy: 0.050 10.22
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 10.22
Ratio, Test accuracy: 0.020 10.00
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.69
Ratio, Val accuracy: 0.900 76.50
Ratio, Test accuracy: 0.900 75.95
Ratio, Val accuracy: 0.700 75.40
Ratio, Test accuracy: 0.700 74.81
Ratio, Val accuracy: 0.500 70.39
Ratio, Test accuracy: 0.500 69.97
Ratio, Val accuracy: 0.300 45.98
Ratio, Test accuracy: 0.300 46.26
Ratio, Val accuracy: 0.200 26.72
Ratio, Test accuracy: 0.200 27.77
Ratio, Val accuracy: 0.150 11.40
Ratio, Test accuracy: 0.150 11.30
Ratio, Val accuracy: 0.100 9.91
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.91
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.91
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.91
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.91
Ratio, Test accuracy: 0.005 10.00
Executing method random_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.69
Ratio, Val accuracy: 0.900 75.81
Ratio, Test accuracy: 0.900 75.26
Ratio, Val accuracy: 0.700 73.20
Ratio, Test accuracy: 0.700 72.36
Ratio, Val accuracy: 0.500 68.26
Ratio, Test accuracy: 0.500 67.52
Ratio, Val accuracy: 0.300 49.59
Ratio, Test accuracy: 0.300 49.37
Ratio, Val accuracy: 0.200 13.42
Ratio, Test accuracy: 0.200 13.48
Ratio, Val accuracy: 0.150 11.32
Ratio, Test accuracy: 0.150 11.48
Ratio, Val accuracy: 0.100 9.94
Ratio, Test accuracy: 0.100 10.03
Ratio, Val accuracy: 0.050 9.91
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.91
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.91
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.91
Ratio, Test accuracy: 0.005 10.00
Executing method l1_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.69
Ratio, Val accuracy: 0.900 75.46
Ratio, Test accuracy: 0.900 74.87
Ratio, Val accuracy: 0.700 74.47
Ratio, Test accuracy: 0.700 73.72
Ratio, Val accuracy: 0.500 65.53
Ratio, Test accuracy: 0.500 65.05
Ratio, Val accuracy: 0.300 42.51
Ratio, Test accuracy: 0.300 42.50
Ratio, Val accuracy: 0.200 12.99
Ratio, Test accuracy: 0.200 13.14
Ratio, Val accuracy: 0.150 10.78
Ratio, Test accuracy: 0.150 11.00
Ratio, Val accuracy: 0.100 9.91
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.91
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.91
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.91
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.91
Ratio, Test accuracy: 0.005 10.00
AlexNet(
  (features): Sequential(
    (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))
    (1): ReLU(inplace=True)
    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
    (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))
    (4): ReLU(inplace=True)
    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
    (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (7): ReLU(inplace=True)
    (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (9): ReLU(inplace=True)
    (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (11): ReLU(inplace=True)
    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  )
  (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))
  (classifier): Sequential(
    (0): Dropout(p=0.5, inplace=False)
    (1): Linear(in_features=256, out_features=512, bias=True)
    (2): ReLU(inplace=True)
    (3): Dropout(p=0.5, inplace=False)
    (4): Linear(in_features=512, out_features=512, bias=True)
    (5): ReLU(inplace=True)
    (6): Linear(in_features=512, out_features=10, bias=True)
  )
)
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 76.04
Ratio, Val accuracy: 0.900 76.61
Ratio, Test accuracy: 0.900 75.77
Ratio, Val accuracy: 0.700 75.38
Ratio, Test accuracy: 0.700 75.08
Ratio, Val accuracy: 0.500 69.64
Ratio, Test accuracy: 0.500 69.73
Ratio, Val accuracy: 0.300 46.66
Ratio, Test accuracy: 0.300 47.30
Ratio, Val accuracy: 0.200 20.09
Ratio, Test accuracy: 0.200 20.41
Ratio, Val accuracy: 0.150 11.40
Ratio, Test accuracy: 0.150 11.43
Ratio, Val accuracy: 0.100 9.91
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.91
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.91
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.91
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.91
Ratio, Test accuracy: 0.005 10.00
Executing method random_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 76.04
Ratio, Val accuracy: 0.900 75.86
Ratio, Test accuracy: 0.900 75.15
Ratio, Val accuracy: 0.700 74.33
Ratio, Test accuracy: 0.700 74.07
Ratio, Val accuracy: 0.500 68.13
Ratio, Test accuracy: 0.500 67.58
Ratio, Val accuracy: 0.300 40.57
Ratio, Test accuracy: 0.300 40.64
Ratio, Val accuracy: 0.200 21.76
Ratio, Test accuracy: 0.200 22.15
Ratio, Val accuracy: 0.150 11.83
Ratio, Test accuracy: 0.150 11.95
Ratio, Val accuracy: 0.100 9.91
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.91
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.91
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.91
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.91
Ratio, Test accuracy: 0.005 10.00
Executing method l1_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 76.04
Ratio, Val accuracy: 0.900 76.00
Ratio, Test accuracy: 0.900 75.33
Ratio, Val accuracy: 0.700 73.48
Ratio, Test accuracy: 0.700 72.94
Ratio, Val accuracy: 0.500 60.31
Ratio, Test accuracy: 0.500 60.31
Ratio, Val accuracy: 0.300 39.90
Ratio, Test accuracy: 0.300 40.49
Ratio, Val accuracy: 0.200 24.89
Ratio, Test accuracy: 0.200 25.45
Ratio, Val accuracy: 0.150 10.52
Ratio, Test accuracy: 0.150 10.67
Ratio, Val accuracy: 0.100 10.03
Ratio, Test accuracy: 0.100 10.10
Ratio, Val accuracy: 0.050 9.91
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.91
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.91
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.91
Ratio, Test accuracy: 0.005 10.00
Ratio, Val accuracy: 0.010 10.22
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 10.22
Ratio, Test accuracy: 0.005 10.00
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.86
Ratio, Val accuracy: 0.900 76.02
Ratio, Test accuracy: 0.900 75.45
Ratio, Val accuracy: 0.700 74.17
Ratio, Test accuracy: 0.700 73.79
Ratio, Val accuracy: 0.500 66.58
Ratio, Test accuracy: 0.500 66.61
Ratio, Val accuracy: 0.300 48.00
Ratio, Test accuracy: 0.300 47.98
Ratio, Val accuracy: 0.200 24.22
Ratio, Test accuracy: 0.200 24.55
Ratio, Val accuracy: 0.150 20.30
Ratio, Test accuracy: 0.150 20.90
Ratio, Val accuracy: 0.100 9.55
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.55
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.55
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.55
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.55
Ratio, Test accuracy: 0.005 10.00
Executing method random_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.86
Ratio, Val accuracy: 0.900 75.79
Ratio, Test accuracy: 0.900 75.27
Ratio, Val accuracy: 0.700 72.65
Ratio, Test accuracy: 0.700 72.25
Ratio, Val accuracy: 0.500 64.20
Ratio, Test accuracy: 0.500 64.56
Ratio, Val accuracy: 0.300 39.46
Ratio, Test accuracy: 0.300 39.56
Ratio, Val accuracy: 0.200 19.38
Ratio, Test accuracy: 0.200 19.61
Ratio, Val accuracy: 0.150 17.67
Ratio, Test accuracy: 0.150 18.23
Ratio, Val accuracy: 0.100 11.31
Ratio, Test accuracy: 0.100 12.02
Ratio, Val accuracy: 0.050 9.55
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.55
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.55
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.55
Ratio, Test accuracy: 0.005 10.00
Executing method l1_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 75.86
Ratio, Val accuracy: 0.900 75.47
Ratio, Test accuracy: 0.900 75.15
Ratio, Val accuracy: 0.700 70.58
Ratio, Test accuracy: 0.700 69.98
Ratio, Val accuracy: 0.500 63.94
Ratio, Test accuracy: 0.500 63.45
Ratio, Val accuracy: 0.300 19.04
Ratio, Test accuracy: 0.300 19.80
Ratio, Val accuracy: 0.200 20.90
Ratio, Test accuracy: 0.200 21.66
Ratio, Val accuracy: 0.150 9.66
Ratio, Test accuracy: 0.150 10.10
Ratio, Val accuracy: 0.100 9.55
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.55
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.55
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.55
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.55
Ratio, Test accuracy: 0.005 10.00
AlexNet(
  (features): Sequential(
    (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))
    (1): ReLU(inplace=True)
    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
    (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))
    (4): ReLU(inplace=True)
    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
    (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (7): ReLU(inplace=True)
    (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (9): ReLU(inplace=True)
    (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
    (11): ReLU(inplace=True)
    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  )
  (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))
  (classifier): Sequential(
    (0): Dropout(p=0.5, inplace=False)
    (1): Linear(in_features=256, out_features=512, bias=True)
    (2): ReLU(inplace=True)
    (3): Dropout(p=0.5, inplace=False)
    (4): Linear(in_features=512, out_features=512, bias=True)
    (5): ReLU(inplace=True)
    (6): Linear(in_features=512, out_features=10, bias=True)
  )
)
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 76.38
Ratio, Val accuracy: 0.900 76.47
Ratio, Test accuracy: 0.900 76.13
Ratio, Val accuracy: 0.700 74.82
Ratio, Test accuracy: 0.700 74.04
Ratio, Val accuracy: 0.500 69.94
Ratio, Test accuracy: 0.500 69.40
Ratio, Val accuracy: 0.300 43.28
Ratio, Test accuracy: 0.300 43.65
Ratio, Val accuracy: 0.200 19.87
Ratio, Test accuracy: 0.200 20.18
Ratio, Val accuracy: 0.150 15.39
Ratio, Test accuracy: 0.150 15.96
Ratio, Val accuracy: 0.100 9.62
Ratio, Test accuracy: 0.100 10.06
Ratio, Val accuracy: 0.050 9.55
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.55
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.55
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.55
Ratio, Test accuracy: 0.005 10.00
Executing method random_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 76.38
Ratio, Val accuracy: 0.900 76.26
Ratio, Test accuracy: 0.900 75.63
Ratio, Val accuracy: 0.700 74.74
Ratio, Test accuracy: 0.700 74.27
Ratio, Val accuracy: 0.500 64.28
Ratio, Test accuracy: 0.500 63.69
Ratio, Val accuracy: 0.300 30.37
Ratio, Test accuracy: 0.300 31.09
Ratio, Val accuracy: 0.200 12.17
Ratio, Test accuracy: 0.200 13.03
Ratio, Val accuracy: 0.150 11.22
Ratio, Test accuracy: 0.150 11.85
Ratio, Val accuracy: 0.100 12.98
Ratio, Test accuracy: 0.100 13.64
Ratio, Val accuracy: 0.050 9.55
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.55
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.55
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.55
Ratio, Test accuracy: 0.005 10.00
Executing method l1_structured on model AlexNet and dataset CIFAR10
Ratio, Test accuracy: 1.000 76.38
Ratio, Val accuracy: 0.900 76.38
Ratio, Test accuracy: 0.900 76.07
Ratio, Val accuracy: 0.700 73.26
Ratio, Test accuracy: 0.700 72.96
Ratio, Val accuracy: 0.500 68.35
Ratio, Test accuracy: 0.500 67.73
Ratio, Val accuracy: 0.300 36.64
Ratio, Test accuracy: 0.300 37.46
Ratio, Val accuracy: 0.200 11.32
Ratio, Test accuracy: 0.200 11.84
Ratio, Val accuracy: 0.150 9.71
Ratio, Test accuracy: 0.150 10.21
Ratio, Val accuracy: 0.100 9.55
Ratio, Test accuracy: 0.100 10.00
Ratio, Val accuracy: 0.050 9.55
Ratio, Test accuracy: 0.050 10.00
Ratio, Val accuracy: 0.020 9.55
Ratio, Test accuracy: 0.020 10.00
Ratio, Val accuracy: 0.010 9.55
Ratio, Test accuracy: 0.010 10.00
Ratio, Val accuracy: 0.005 9.55
Ratio, Test accuracy: 0.005 10.00
