ZeroPad2d
class torch.nn.ZeroPad2d(padding)
Pads the input tensor boundaries with zero.
For N-dimensional padding, use "torch.nn.functional.pad()".
Parameters:
      padding (int, tuple) -- the size of the padding. If is
      int, uses the same padding in all boundaries. If a 4-tuple,
      uses (\text{padding_left}, \text{padding_right},
      \text{padding_top}, \text{padding_bottom})
Shape:
      * Input: (N, C, H_{in}, W_{in}) or (C, H_{in}, W_{in}).
  * Output: (N, C, H_{out}, W_{out}) or (C, H_{out}, W_{out}),
    where

    H_{out} = H_{in} + \text{padding\_top} +
    \text{padding\_bottom}

    W_{out} = W_{in} + \text{padding\_left} +
    \text{padding\_right}

Examples:
  >>> m = nn.ZeroPad2d(2)
  >>> input = torch.randn(1, 1, 3, 3)
  >>> input
  tensor([[[[-0.1678, -0.4418,  1.9466],
            [ 0.9604, -0.4219, -0.5241],
            [-0.9162, -0.5436, -0.6446]]]])
  >>> m(input)
