I am new to PyTorch.
I see that nn.Conv2d function takes as argument a pytorch tensor  x, and params as in_channels, along with others.
My question is that, since the function performs a 2D convolution, the in_channels would always be equal to the channel depth of the input tensor x, so why do we need to specify the same as a parameter?
Thanks