model =  Sequential (
  (conv1_1): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu1_1): ReLU (inplace)
  (conv1_2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu1_2): ReLU (inplace)
  (pool1): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv2_1): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu2_1): ReLU (inplace)
  (conv2_2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu2_2): ReLU (inplace)
  (pool2): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv3_1): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3_1): ReLU (inplace)
  (conv3_2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3_2): ReLU (inplace)
  (conv3_3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3_3): ReLU (inplace)
  (pool3): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv4_1): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4_1): ReLU (inplace)
  (conv4_2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4_2): ReLU (inplace)
  (conv4_3): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4_3): ReLU (inplace)
  (pool4): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv5_1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5_1): ReLU (inplace)
  (conv5_2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5_2): ReLU (inplace)
  (conv5_3): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5_3): ReLU (inplace)
  (pool5): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (fc6): Conv2d(512, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu6): ReLU (inplace)
  (drop6): Dropout (p = 0.5, inplace)
  (fc7): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1), padding=(1, 1))
  (relu7): ReLU (inplace)
  (drop7): Dropout (p = 0.5, inplace)
  (fc8): Conv2d(1024, 21, kernel_size=(1, 1), stride=(1, 1), padding=(1, 1))
)

model =  Sequential (
  (conv1_1): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu1_1): ReLU (inplace)
  (conv1_2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu1_2): ReLU (inplace)
  (pool1): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv2_1): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu2_1): ReLU (inplace)
  (conv2_2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu2_2): ReLU (inplace)
  (pool2): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv3_1): Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3_1): ReLU (inplace)
  (conv3_2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3_2): ReLU (inplace)
  (conv3_3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu3_3): ReLU (inplace)
  (pool3): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv4_1): Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4_1): ReLU (inplace)
  (conv4_2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4_2): ReLU (inplace)
  (conv4_3): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu4_3): ReLU (inplace)
  (pool4): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (conv5_1): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5_1): ReLU (inplace)
  (conv5_2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5_2): ReLU (inplace)
  (conv5_3): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu5_3): ReLU (inplace)
  (pool5): MaxPool2d (size=(2, 2), stride=(2, 2), dilation=(1, 1))
  (fc6): Conv2d(512, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (relu6): ReLU (inplace)
  (drop6): Dropout (p = 0.5, inplace)
  (fc7): Conv2d(1024, 1024, kernel_size=(1, 1), stride=(1, 1), padding=(1, 1))
  (relu7): ReLU (inplace)
  (drop7): Dropout (p = 0.5, inplace)
  (fc8): Conv2d(1024, 21, kernel_size=(1, 1), stride=(1, 1), padding=(1, 1))
)
