A question about the method to get output from specific layer about pytorch-cnn-visualizations HOT 4 CLOSED

Net(
  (features): Sequential(
    (0): Conv2d(1, 20, kernel_size=(5, 5), stride=(1, 1))
    (1): ReLU(inplace=True)
    (2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
    (3): Conv2d(20, 50, kernel_size=(5, 5), stride=(1, 1))
    (4): ReLU(inplace=True)
    (5): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)
  )
  (classifier): Sequential(
    (0): Linear(in_features=800, out_features=500, bias=True)
    (1): ReLU(inplace=True)
    (2): Linear(in_features=500, out_features=10, bias=True)
  )
)
State dict  features.0.weight 	 torch.Size([20, 1, 5, 5])
State dict  features.0.bias 	 torch.Size([20])
State dict  features.3.weight 	 torch.Size([50, 20, 5, 5])
State dict  features.3.bias 	 torch.Size([50])
State dict  classifier.0.weight 	 torch.Size([500, 800])
State dict  classifier.0.bias 	 torch.Size([500])
State dict  classifier.2.weight 	 torch.Size([10, 500])
State dict  classifier.2.bias 	 torch.Size([10])

  x = layer(x)
TypeError: 'Tensor' object is not callable

def get_output_from_specific_layer(self, x, layer_id):
        layer_output = None
        for index, layer in enumerate(self.model.features[3].weight):
            x = layer(x)
	    #print(‘Layer is: ’, layer) #All layers will be printed out 
            if str(index) == str(layer_id):
                #x = layer(x)
                layer_output = x[0]
                #print('Layer is: ', layer)
                break
        return layer_output

        for index, layer in enumerate(self.model.features[3].weight):

        for index, layer in enumerate(self.model.features.weight):