ReplicationPad1d
class torch.nn.ReplicationPad1d(padding)
Pads the input tensor using replication of the input boundary.
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 2-tuple,
      uses (\text{padding_left}, \text{padding_right})
Shape:
      * Input: (C, W_{in}) or (N, C, W_{in}).
  * Output: (C, W_{out}) or (N, C, W_{out}), where

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

Examples:
  >>> m = nn.ReplicationPad1d(2)
  >>> input = torch.arange(8, dtype=torch.float).reshape(1, 2, 4)
  >>> input
  tensor([[[0., 1., 2., 3.],
           [4., 5., 6., 7.]]])
  >>> m(input)
  tensor([[[0., 0., 0., 1., 2., 3., 3., 3.],
           [4., 4., 4., 5., 6., 7., 7., 7.]]])
  >>> # using different paddings for different sides
