code: def xception(c, k=8, n_middle=8):
      "Preview version of Xception network. Not tested yet - use at own risk. No pretrained model yet."
      layers = [
          conv(3, k*4, 3, 2),
          conv(k*4, k*8, 3),
          ConvSkip(k*8, k*16, act=False),
          ConvSkip(k*16, k*32),
          ConvSkip(k*32, k*91),
      ]
      for i in range(n_middle): layers.append(middle_flow(k*91))
      layers += [
          ConvSkip(k*91,k*128),
          sep_conv(k*128,k*192,act=False),
          sep_conv(k*192,k*256),
          nn.ReLU(),
          nn.AdaptiveAvgPool2d(1),
          Flatten(),
          nn.Linear(k*256,c)
      ]
      return nn.Sequential(*layersf xception(c, k=8, n_middle=8):
      "Preview version of Xception network. Not tested yet - use at own risk. No pretrained model yet."
      layers = [
          conv(3, k*4, 3, 2),
          conv(k*4, k*8, 3),
          ConvSkip(k*8, k*16, act=False),
          ConvSkip(k*16, k*32),
          ConvSkip(k*32, k*91),
      ]
      for i in range(n_middle): layers.append(middle_flow(k*91))
      layers += [
          ConvSkip(k*91,k*128),
          sep_conv(k*128,k*192,act=False),
          sep_conv(k*192,k*256),
          nn.ReLU(),
          nn.AdaptiveAvgPool2d(1),
          Flatten(),
          nn.Linear(k*256,c)
      ]
      return nn.Sequential(*layers)
docs: Preview version of Xception network. Not tested yet - use at own risk. No pretrained model yet.