Solved by ptrblck in post #2 
              
              
                The error is raised by a conv layer, which is expecting 128 input channels and returns 16 output channels. 
Did you modify the model in any way and if so, could you post the applied changes? 
The torchvision implementation work fine for me: 
model = models.squeezenet1_0()
x = torch.randn(1, 3, 224, …