Hi,
PyTorch does not support same
padding the way Keras does, but still you can manage it easily using explicit padding before passing the tensor to convolution layer. Here, symmetric padding is not possible so by padding only one side, in your case, top bottom of tensor, we can achieve same
padding.
import torch
import torch.nn.functional as F
x = torch.randn(64, 32, 100, 20)
x = F.pad(x, (0, 0, 2, 1)) # [left, right, top, bot]
nn.Conv2d(32, 32, (4, 1))(x).shape
Please see these post about calculations Converting tensorflow model to pytorch: issue with padding
Bests