ResNet(
  3.86 M, 104.773% Params, 247.73 MMac, 100.000% MACs, 
  (conv1): Conv2d(448, 0.012% Params, 458.75 KMac, 0.185% MACs, 3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (bn1): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  (relu): ReLU(0, 0.000% Params, 16.38 KMac, 0.007% MACs, )
  (layer1): MakeLayer(
    15.58 k, 0.423% Params, 16.25 MMac, 6.561% MACs, 
    (downsample): Sequential(
      1.22 k, 0.033% Params, 1.25 MMac, 0.503% MACs, 
      (0): Conv2d(1.09 k, 0.030% Params, 1.11 MMac, 0.450% MACs, 16, 64, kernel_size=(1, 1), stride=(1, 1))
      (1): BatchNorm2d(128, 0.003% Params, 131.07 KMac, 0.053% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (blockdict): ModuleDict(
      14.37 k, 0.390% Params, 15.01 MMac, 6.058% MACs, 
      (block1): Bottleneck(
        5.09 k, 0.138% Params, 5.31 MMac, 2.143% MACs, 
        (conv1): Conv2d(272, 0.007% Params, 278.53 KMac, 0.112% MACs, 16, 16, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(2.32 k, 0.063% Params, 2.38 MMac, 0.959% MACs, 16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(1.09 k, 0.030% Params, 1.11 MMac, 0.450% MACs, 16, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(128, 0.003% Params, 131.07 KMac, 0.053% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 98.3 KMac, 0.040% MACs, )
       
      )
      (block2): Bottleneck(
        4.64 k, 0.126% Params, 4.85 MMac, 1.958% MACs, 
        (conv1): Conv2d(1.04 k, 0.028% Params, 1.06 MMac, 0.430% MACs, 64, 16, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(2.32 k, 0.063% Params, 2.38 MMac, 0.959% MACs, 16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(1.09 k, 0.030% Params, 1.11 MMac, 0.450% MACs, 16, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(128, 0.003% Params, 131.07 KMac, 0.053% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 98.3 KMac, 0.040% MACs, )
      )
      (block3): Bottleneck(
        4.64 k, 0.126% Params, 4.85 MMac, 1.958% MACs, 
        (conv1): Conv2d(1.04 k, 0.028% Params, 1.06 MMac, 0.430% MACs, 64, 16, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(2.32 k, 0.063% Params, 2.38 MMac, 0.959% MACs, 16, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(32, 0.001% Params, 32.77 KMac, 0.013% MACs, 16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(1.09 k, 0.030% Params, 1.11 MMac, 0.450% MACs, 16, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(128, 0.003% Params, 131.07 KMac, 0.053% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 98.3 KMac, 0.040% MACs, )
      )
    )
  )
  (layer2): MakeLayer(
    158.98 k, 4.313% Params, 42.76 MMac, 17.262% MACs, 
    (downsample): Sequential(
      8.58 k, 0.233% Params, 2.2 MMac, 0.886% MACs, 
      (0): Conv2d(8.32 k, 0.226% Params, 2.13 MMac, 0.860% MACs, 64, 128, kernel_size=(1, 1), stride=(2, 2))
      (1): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (blockdict): ModuleDict(
      150.4 k, 4.080% Params, 40.57 MMac, 16.375% MACs, 
      (block1): Bottleneck(
        24.51 k, 0.665% Params, 8.0 MMac, 3.227% MACs, 
        (conv1): Conv2d(2.08 k, 0.056% Params, 2.13 MMac, 0.860% MACs, 64, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 65.54 KMac, 0.026% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 73.73 KMac, 0.030% MACs, )
      
      )
      (block2): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
      (block3): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
      (block4): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
      (block5): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
      (block6): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
      (block7): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
      (block8): Bottleneck(
        17.98 k, 0.488% Params, 4.65 MMac, 1.878% MACs, 
        (conv1): Conv2d(4.13 k, 0.112% Params, 1.06 MMac, 0.427% MACs, 128, 32, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(9.25 k, 0.251% Params, 2.37 MMac, 0.956% MACs, 32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(64, 0.002% Params, 16.38 KMac, 0.007% MACs, 32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(4.22 k, 0.115% Params, 1.08 MMac, 0.436% MACs, 32, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(256, 0.007% Params, 65.54 KMac, 0.026% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 49.15 KMac, 0.020% MACs, )
      )
    )
  )
  (layer3): MakeLayer(
    2.61 M, 70.724% Params, 169.36 MMac, 68.365% MACs, 
    (downsample): Sequential(
      33.54 k, 0.910% Params, 2.15 MMac, 0.866% MACs, 
      (0): Conv2d(33.02 k, 0.896% Params, 2.11 MMac, 0.853% MACs, 128, 256, kernel_size=(1, 1), stride=(2, 2))
      (1): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (blockdict): ModuleDict(
      2.57 M, 69.815% Params, 167.22 MMac, 67.499% MACs, 
      (block1): Bottleneck(
        96.13 k, 2.608% Params, 7.8 MMac, 3.148% MACs, 
        (conv1): Conv2d(8.26 k, 0.224% Params, 2.11 MMac, 0.853% MACs, 128, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 32.77 KMac, 0.013% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 36.86 KMac, 0.015% MACs, )
       
      )
      (block2): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block3): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block4): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block5): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block6): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block7): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block8): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block9): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block10): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block11): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block12): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block13): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block14): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block15): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block16): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block17): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block18): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block19): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block20): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block21): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block22): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block23): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block24): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block25): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block26): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block27): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block28): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block29): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block30): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block31): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block32): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block33): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block34): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block35): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
      (block36): Bottleneck(
        70.78 k, 1.920% Params, 4.55 MMac, 1.839% MACs, 
        (conv1): Conv2d(16.45 k, 0.446% Params, 1.05 MMac, 0.425% MACs, 256, 64, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(36.93 k, 1.002% Params, 2.36 MMac, 0.954% MACs, 64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(128, 0.003% Params, 8.19 KMac, 0.003% MACs, 64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(16.64 k, 0.451% Params, 1.06 MMac, 0.430% MACs, 64, 256, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(512, 0.014% Params, 32.77 KMac, 0.013% MACs, 256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 24.58 KMac, 0.010% MACs, )
      )
    )
  )
  (layer4): MakeLayer(
    1.07 M, 29.161% Params, 18.83 MMac, 7.602% MACs, 
    (downsample): Sequential(
      132.61 k, 3.597% Params, 2.12 MMac, 0.856% MACs, 
      (0): Conv2d(131.58 k, 3.570% Params, 2.11 MMac, 0.850% MACs, 256, 512, kernel_size=(1, 1), stride=(2, 2))
      (1): BatchNorm2d(1.02 k, 0.028% Params, 16.38 KMac, 0.007% MACs, 512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (blockdict): ModuleDict(
      942.34 k, 25.563% Params, 16.71 MMac, 6.746% MACs, 
      (block1): Bottleneck(
        380.67 k, 10.327% Params, 7.7 MMac, 3.108% MACs, 
        (conv1): Conv2d(32.9 k, 0.892% Params, 2.11 MMac, 0.850% MACs, 256, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(256, 0.007% Params, 16.38 KMac, 0.007% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(147.58 k, 4.004% Params, 2.36 MMac, 0.953% MACs, 128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
        (bn2): BatchNorm2d(256, 0.007% Params, 4.1 KMac, 0.002% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(66.05 k, 1.792% Params, 1.06 MMac, 0.427% MACs, 128, 512, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(1.02 k, 0.028% Params, 16.38 KMac, 0.007% MACs, 512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 18.43 KMac, 0.007% MACs, )
       
      )
      (block2): Bottleneck(
        280.83 k, 7.618% Params, 4.51 MMac, 1.819% MACs, 
        (conv1): Conv2d(65.66 k, 1.781% Params, 1.05 MMac, 0.424% MACs, 512, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(256, 0.007% Params, 4.1 KMac, 0.002% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(147.58 k, 4.004% Params, 2.36 MMac, 0.953% MACs, 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(256, 0.007% Params, 4.1 KMac, 0.002% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(66.05 k, 1.792% Params, 1.06 MMac, 0.427% MACs, 128, 512, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(1.02 k, 0.028% Params, 16.38 KMac, 0.007% MACs, 512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 12.29 KMac, 0.005% MACs, )
      )
      (block3): Bottleneck(
        280.83 k, 7.618% Params, 4.51 MMac, 1.819% MACs, 
        (conv1): Conv2d(65.66 k, 1.781% Params, 1.05 MMac, 0.424% MACs, 512, 128, kernel_size=(1, 1), stride=(1, 1))
        (bn1): BatchNorm2d(256, 0.007% Params, 4.1 KMac, 0.002% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv2): Conv2d(147.58 k, 4.004% Params, 2.36 MMac, 0.953% MACs, 128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
        (bn2): BatchNorm2d(256, 0.007% Params, 4.1 KMac, 0.002% MACs, 128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (conv3): Conv2d(66.05 k, 1.792% Params, 1.06 MMac, 0.427% MACs, 128, 512, kernel_size=(1, 1), stride=(1, 1))
        (bn3): BatchNorm2d(1.02 k, 0.028% Params, 16.38 KMac, 0.007% MACs, 512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (relu): ReLU(0, 0.000% Params, 12.29 KMac, 0.005% MACs, )
      )
    )
  )
  (avgpool): AdaptiveAvgPool2d(0, 0.000% Params, 8.19 KMac, 0.003% MACs, output_size=(1, 1))
  (fc): Linear(5.13 k, 0.139% Params, 5.13 KMac, 0.002% MACs, in_features=512, out_features=10, bias=True)
)