Can anyone explain the diff between nn.Linear(in_features, out_features) vs nn.conv2d(in_channels, out_channels, kernel_size)
I believe the kernel_size is easy to understand as the size of the kernel window to compute content for next layer.
is the in_features same as in_channels, and out_features same as out_channels?
Thank you