)
        >>> # non-square kernels and unequal stride and with padding and dilation
        >>> m = nn.Conv2d(16, 33, (3, 5), stride=(2, 1), padding=(4, 2), dilation=(3, 1))
        >>> input = torch.randn(20, 16, 50, 100)
        >>> output = m(input)

    .. _cross-correlation:
        https://en.wikipedia.org/wiki/Cross-correlation

    .. _link:
        https://github.com/vdumoulin/conv_arithmetic/blob/master/README.md
    r