Hello @ptrblck,
Taking advantage of your answer, I would like to know how to apply a CNN for text processing.
Imagine that I have the pre-processed text (tokenized + PAD):
input = torch.tensor(
    [
     [1, 2, 0, 0],
     [3, 4, 5, 6],
     [7, 0, 0, 0]
    ]
)

What would the Conv1D layer look like for this scenario? I mean, what would the in_channels, out_channels, and kernel_size parameters be configured?
Thanks in advance