be zero-ed.
  * **inplace** (*bool**, **optional*) -- If set to "True", will
    do this operation in-place

Warning:
 Due to historical reasons, this class will perform 1D channel-
 wise dropout for 3D inputs (as done by "nn.Dropout1d"). Thus, it
 currently does NOT support inputs without a batch dimension of
 shape (C, H, W). This behavior will change in a future release to
 interpret 3D inputs as no-batch-dim inputs. To maintain the old
 behavior, switch to "nn.Dropout1d".

Shape:
      * Input: (N, C, H, W) or (N, C, L).
  * Output: (N, C, H, W) or (N, C, L) (same shape as input).

Examples:
  >>> m = nn.Dropout2d(p=0.2)
  >>> input = torch.randn(20, 16, 32, 32)
  >>> output = m(input)
