AlexNet(
  3.87 M, 100.000% Params, 70.08 MMac, 100.000% MACs, 
  (conv1): Conv2d(896, 0.023% Params, 917.5 KMac, 1.309% MACs, 3, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu1): ReLU(0, 0.000% Params, 32.77 KMac, 0.047% MACs, inplace=True)
  (pool1): MaxPool2d(0, 0.000% Params, 32.77 KMac, 0.047% MACs, kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv2): Conv2d(18.5 k, 0.478% Params, 4.73 MMac, 6.756% MACs, 32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu2): ReLU(0, 0.000% Params, 16.38 KMac, 0.023% MACs, inplace=True)
  (pool2): MaxPool2d(0, 0.000% Params, 16.38 KMac, 0.023% MACs, kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  (conv3): Conv2d(73.86 k, 1.909% Params, 4.73 MMac, 6.745% MACs, 64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3): ReLU(0, 0.000% Params, 8.19 KMac, 0.012% MACs, inplace=True)
  (conv4): Conv2d(295.17 k, 7.630% Params, 18.89 MMac, 26.955% MACs, 128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4): ReLU(0, 0.000% Params, 16.38 KMac, 0.023% MACs, inplace=True)
  (conv5): Conv2d(590.08 k, 15.252% Params, 37.77 MMac, 53.887% MACs, 256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5): ReLU(0, 0.000% Params, 16.38 KMac, 0.023% MACs, inplace=True)
  (pool5): MaxPool2d(0, 0.000% Params, 16.38 KMac, 0.023% MACs, kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)
  (drop1): Dropout(0, 0.000% Params, 0.0 Mac, 0.000% MACs, p=0.5, inplace=False)
  (fc1): Linear(2.36 M, 61.010% Params, 2.36 MMac, 3.368% MACs, in_features=2304, out_features=1024, bias=True)
  (relu6): ReLU(0, 0.000% Params, 1.02 KMac, 0.001% MACs, inplace=True)
  (drop2): Dropout(0, 0.000% Params, 0.0 Mac, 0.000% MACs, p=0.5, inplace=False)
  (fc2): Linear(524.8 k, 13.565% Params, 524.8 KMac, 0.749% MACs, in_features=1024, out_features=512, bias=True)
  (relu7): ReLU(0, 0.000% Params, 512.0 Mac, 0.001% MACs, inplace=True)
  (fc3): Linear(5.13 k, 0.133% Params, 5.13 KMac, 0.007% MACs, in_features=512, out_features=10, bias=True)
)
