Refer to torch.nn.ZeroPad 404, the asymmetric padding is now available by passing a tuple to the Pad function.
For example:
>>> input = torch.randn(1, 1, 3, 3)
>>> input
tensor([[[[-1.7800,  0.6112, -0.0166],
          [-2.1496, -0.5789,  0.8997],
          [-0.5621,  0.9050,  0.4039]]]])
>>> m = torch.nn.ZeroPad2d((1, 2, 1, 2))
>>> m
tensor([[[[ 0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000],
          [ 0.0000, -1.7800,  0.6112, -0.0166,  0.0000,  0.0000],
          [ 0.0000, -2.1496, -0.5789,  0.8997,  0.0000,  0.0000],
          [ 0.0000, -0.5621,  0.9050,  0.4039,  0.0000,  0.0000],
          [ 0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000],
          [ 0.0000,  0.0000,  0.0000,  0.0000,  0.0000,  0.0000]]]])