Executing method neural_path_kmeans on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.14
Ratio, Val accuracy: 0.900 49.14
Ratio, Test accuracy: 0.900 48.75
Ratio, Val accuracy: 0.700 46.62
Ratio, Test accuracy: 0.700 46.66
Ratio, Val accuracy: 0.500 39.36
Ratio, Test accuracy: 0.500 39.65
Ratio, Val accuracy: 0.300 23.63
Ratio, Test accuracy: 0.300 23.86
Ratio, Val accuracy: 0.200 5.74
Ratio, Test accuracy: 0.200 5.65
Ratio, Val accuracy: 0.150 2.23
Ratio, Test accuracy: 0.150 2.07
Ratio, Val accuracy: 0.100 0.99
Ratio, Test accuracy: 0.100 1.02
Ratio, Val accuracy: 0.050 0.98
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method random_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.14
Ratio, Val accuracy: 0.900 48.58
Ratio, Test accuracy: 0.900 48.38
Ratio, Val accuracy: 0.700 45.26
Ratio, Test accuracy: 0.700 44.84
Ratio, Val accuracy: 0.500 37.19
Ratio, Test accuracy: 0.500 38.07
Ratio, Val accuracy: 0.300 18.42
Ratio, Test accuracy: 0.300 17.74
Ratio, Val accuracy: 0.200 8.90
Ratio, Test accuracy: 0.200 9.49
Ratio, Val accuracy: 0.150 7.20
Ratio, Test accuracy: 0.150 7.34
Ratio, Val accuracy: 0.100 1.52
Ratio, Test accuracy: 0.100 1.73
Ratio, Val accuracy: 0.050 1.14
Ratio, Test accuracy: 0.050 1.24
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method l1_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.14
Ratio, Val accuracy: 0.900 48.06
Ratio, Test accuracy: 0.900 47.94
Ratio, Val accuracy: 0.700 43.90
Ratio, Test accuracy: 0.700 44.48
Ratio, Val accuracy: 0.500 37.51
Ratio, Test accuracy: 0.500 37.68
Ratio, Val accuracy: 0.300 23.87
Ratio, Test accuracy: 0.300 24.19
Ratio, Val accuracy: 0.200 11.33
Ratio, Test accuracy: 0.200 11.59
Ratio, Val accuracy: 0.150 3.39
Ratio, Test accuracy: 0.150 3.33
Ratio, Val accuracy: 0.100 2.11
Ratio, Test accuracy: 0.100 2.11
Ratio, Val accuracy: 0.050 0.98
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 50.00
Ratio, Val accuracy: 0.900 49.13
Ratio, Test accuracy: 0.900 49.20
Ratio, Val accuracy: 0.700 46.11
Ratio, Test accuracy: 0.700 46.59
Ratio, Val accuracy: 0.500 39.27
Ratio, Test accuracy: 0.500 39.55
Ratio, Val accuracy: 0.300 20.01
Ratio, Test accuracy: 0.300 21.11
Ratio, Val accuracy: 0.200 9.25
Ratio, Test accuracy: 0.200 9.91
Ratio, Val accuracy: 0.150 4.62
Ratio, Test accuracy: 0.150 4.70
Ratio, Val accuracy: 0.100 1.90
Ratio, Test accuracy: 0.100 1.94
Ratio, Val accuracy: 0.050 0.96
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.96
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.96
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.96
Ratio, Test accuracy: 0.005 1.00
Executing method random_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 50.00
Ratio, Val accuracy: 0.900 48.74
Ratio, Test accuracy: 0.900 48.94
Ratio, Val accuracy: 0.700 45.52
Ratio, Test accuracy: 0.700 45.63
Ratio, Val accuracy: 0.500 37.93
Ratio, Test accuracy: 0.500 38.30
Ratio, Val accuracy: 0.300 20.51
Ratio, Test accuracy: 0.300 21.12
Ratio, Val accuracy: 0.200 10.58
Ratio, Test accuracy: 0.200 10.81
Ratio, Val accuracy: 0.150 6.24
Ratio, Test accuracy: 0.150 6.44
Ratio, Val accuracy: 0.100 2.56
Ratio, Test accuracy: 0.100 2.44
Ratio, Val accuracy: 0.050 1.01
Ratio, Test accuracy: 0.050 1.03
Ratio, Val accuracy: 0.020 0.96
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.96
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.96
Ratio, Test accuracy: 0.005 1.00
Executing method l1_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 50.00
Ratio, Val accuracy: 0.900 48.45
Ratio, Test accuracy: 0.900 48.56
Ratio, Val accuracy: 0.700 43.64
Ratio, Test accuracy: 0.700 43.90
Ratio, Val accuracy: 0.500 38.42
Ratio, Test accuracy: 0.500 38.30
Ratio, Val accuracy: 0.300 19.84
Ratio, Test accuracy: 0.300 19.94
Ratio, Val accuracy: 0.200 9.28
Ratio, Test accuracy: 0.200 9.96
Ratio, Val accuracy: 0.150 5.55
Ratio, Test accuracy: 0.150 5.95
Ratio, Val accuracy: 0.100 1.22
Ratio, Test accuracy: 0.100 1.31
Ratio, Val accuracy: 0.050 0.96
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.96
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.96
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.96
Ratio, Test accuracy: 0.005 1.00
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=100, bias=True)
  )
)
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.13
Ratio, Val accuracy: 0.900 48.70
Ratio, Test accuracy: 0.900 49.14
Ratio, Val accuracy: 0.700 46.55
Ratio, Test accuracy: 0.700 46.95
Ratio, Val accuracy: 0.500 40.14
Ratio, Test accuracy: 0.500 40.48
Ratio, Val accuracy: 0.300 20.93
Ratio, Test accuracy: 0.300 21.60
Ratio, Val accuracy: 0.200 8.47
Ratio, Test accuracy: 0.200 8.74
Ratio, Val accuracy: 0.150 2.70
Ratio, Test accuracy: 0.150 2.41
Ratio, Val accuracy: 0.100 2.24
Ratio, Test accuracy: 0.100 2.31
Ratio, Val accuracy: 0.050 0.96
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.96
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.96
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.96
Ratio, Test accuracy: 0.005 1.00
Executing method random_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.13
Ratio, Val accuracy: 0.900 48.00
Ratio, Test accuracy: 0.900 48.27
Ratio, Val accuracy: 0.700 43.90
Ratio, Test accuracy: 0.700 44.55
Ratio, Val accuracy: 0.500 38.37
Ratio, Test accuracy: 0.500 38.51
Ratio, Val accuracy: 0.300 22.85
Ratio, Test accuracy: 0.300 23.60
Ratio, Val accuracy: 0.200 10.81
Ratio, Test accuracy: 0.200 11.93
Ratio, Val accuracy: 0.150 4.69
Ratio, Test accuracy: 0.150 4.27
Ratio, Val accuracy: 0.100 3.66
Ratio, Test accuracy: 0.100 3.65
Ratio, Val accuracy: 0.050 0.97
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.96
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.96
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.96
Ratio, Test accuracy: 0.005 1.00
Executing method l1_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.13
Ratio, Val accuracy: 0.900 48.33
Ratio, Test accuracy: 0.900 48.59
Ratio, Val accuracy: 0.700 44.65
Ratio, Test accuracy: 0.700 44.26
Ratio, Val accuracy: 0.500 37.94
Ratio, Test accuracy: 0.500 38.66
Ratio, Val accuracy: 0.300 22.80
Ratio, Test accuracy: 0.300 23.98
Ratio, Val accuracy: 0.200 12.13
Ratio, Test accuracy: 0.200 12.17
Ratio, Val accuracy: 0.150 6.39
Ratio, Test accuracy: 0.150 6.53
Ratio, Val accuracy: 0.100 1.28
Ratio, Test accuracy: 0.100 1.33
Ratio, Val accuracy: 0.050 1.02
Ratio, Test accuracy: 0.050 1.09
Ratio, Val accuracy: 0.020 0.96
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.96
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.96
Ratio, Test accuracy: 0.005 1.00
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.74
Ratio, Val accuracy: 0.900 49.55
Ratio, Test accuracy: 0.900 49.59
Ratio, Val accuracy: 0.700 47.29
Ratio, Test accuracy: 0.700 46.64
Ratio, Val accuracy: 0.500 40.09
Ratio, Test accuracy: 0.500 40.05
Ratio, Val accuracy: 0.300 18.52
Ratio, Test accuracy: 0.300 19.06
Ratio, Val accuracy: 0.200 9.26
Ratio, Test accuracy: 0.200 9.20
Ratio, Val accuracy: 0.150 2.72
Ratio, Test accuracy: 0.150 2.69
Ratio, Val accuracy: 0.100 1.00
Ratio, Test accuracy: 0.100 1.01
Ratio, Val accuracy: 0.050 0.98
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method random_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.74
Ratio, Val accuracy: 0.900 48.73
Ratio, Test accuracy: 0.900 48.17
Ratio, Val accuracy: 0.700 44.55
Ratio, Test accuracy: 0.700 45.16
Ratio, Val accuracy: 0.500 37.86
Ratio, Test accuracy: 0.500 38.14
Ratio, Val accuracy: 0.300 22.36
Ratio, Test accuracy: 0.300 23.26
Ratio, Val accuracy: 0.200 8.33
Ratio, Test accuracy: 0.200 8.47
Ratio, Val accuracy: 0.150 5.44
Ratio, Test accuracy: 0.150 5.50
Ratio, Val accuracy: 0.100 3.34
Ratio, Test accuracy: 0.100 3.56
Ratio, Val accuracy: 0.050 1.02
Ratio, Test accuracy: 0.050 1.02
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method l1_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.74
Ratio, Val accuracy: 0.900 49.18
Ratio, Test accuracy: 0.900 49.08
Ratio, Val accuracy: 0.700 45.14
Ratio, Test accuracy: 0.700 44.98
Ratio, Val accuracy: 0.500 36.90
Ratio, Test accuracy: 0.500 37.35
Ratio, Val accuracy: 0.300 21.14
Ratio, Test accuracy: 0.300 21.11
Ratio, Val accuracy: 0.200 7.88
Ratio, Test accuracy: 0.200 8.06
Ratio, Val accuracy: 0.150 5.49
Ratio, Test accuracy: 0.150 5.58
Ratio, Val accuracy: 0.100 3.85
Ratio, Test accuracy: 0.100 3.90
Ratio, Val accuracy: 0.050 0.98
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
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=100, bias=True)
  )
)
Executing method neural_path_kmeans on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.32
Ratio, Val accuracy: 0.900 49.68
Ratio, Test accuracy: 0.900 49.06
Ratio, Val accuracy: 0.700 47.21
Ratio, Test accuracy: 0.700 46.00
Ratio, Val accuracy: 0.500 40.57
Ratio, Test accuracy: 0.500 40.22
Ratio, Val accuracy: 0.300 21.92
Ratio, Test accuracy: 0.300 22.70
Ratio, Val accuracy: 0.200 10.02
Ratio, Test accuracy: 0.200 10.43
Ratio, Val accuracy: 0.150 2.84
Ratio, Test accuracy: 0.150 2.74
Ratio, Val accuracy: 0.100 0.98
Ratio, Test accuracy: 0.100 1.00
Ratio, Val accuracy: 0.050 0.98
Ratio, Test accuracy: 0.050 1.00
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method random_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.32
Ratio, Val accuracy: 0.900 48.84
Ratio, Test accuracy: 0.900 48.65
Ratio, Val accuracy: 0.700 44.01
Ratio, Test accuracy: 0.700 44.21
Ratio, Val accuracy: 0.500 34.39
Ratio, Test accuracy: 0.500 35.30
Ratio, Val accuracy: 0.300 21.06
Ratio, Test accuracy: 0.300 21.20
Ratio, Val accuracy: 0.200 5.31
Ratio, Test accuracy: 0.200 5.59
Ratio, Val accuracy: 0.150 3.94
Ratio, Test accuracy: 0.150 4.38
Ratio, Val accuracy: 0.100 1.94
Ratio, Test accuracy: 0.100 1.98
Ratio, Val accuracy: 0.050 1.01
Ratio, Test accuracy: 0.050 0.99
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
Executing method l1_structured on model AlexNet and dataset CIFAR100
Ratio, Test accuracy: 1.000 49.32
Ratio, Val accuracy: 0.900 48.13
Ratio, Test accuracy: 0.900 47.89
Ratio, Val accuracy: 0.700 45.29
Ratio, Test accuracy: 0.700 45.05
Ratio, Val accuracy: 0.500 35.38
Ratio, Test accuracy: 0.500 35.39
Ratio, Val accuracy: 0.300 17.06
Ratio, Test accuracy: 0.300 17.22
Ratio, Val accuracy: 0.200 9.45
Ratio, Test accuracy: 0.200 10.23
Ratio, Val accuracy: 0.150 4.12
Ratio, Test accuracy: 0.150 4.37
Ratio, Val accuracy: 0.100 2.35
Ratio, Test accuracy: 0.100 2.59
Ratio, Val accuracy: 0.050 0.99
Ratio, Test accuracy: 0.050 1.01
Ratio, Val accuracy: 0.020 0.98
Ratio, Test accuracy: 0.020 1.00
Ratio, Val accuracy: 0.010 0.98
Ratio, Test accuracy: 0.010 1.00
Ratio, Val accuracy: 0.005 0.98
Ratio, Test accuracy: 0.005 1.00
