AdaptiveAvgPool2d
class torch.nn.AdaptiveAvgPool2d(output_size)
Applies a 2D adaptive average pooling over an input signal composed
   of several input planes.
The output is of size H x W, for any input size. The number of
   output features is equal to the number of input planes.
Parameters:
      output_size (Union[int, None,
      Tuple[Optional[int], Optional[int]]])
      -- the target output size of the image of the form H x W. Can be
      a tuple (H, W) or a single H for a square image H x H. H and W
      can be either a "int", or "None" which means the size will be
      the same as that of the input.
Shape:
      * Input: (N, C, H_{in}, W_{in}) or (C, H_{in}, W_{in}).
  * Output: (N, C, S_{0}, S_{1}) or (C, S_{0}, S_{1}), where
    S=\text{output\_size}.

-[ Examples ]-



target output size of 5x7
m = nn.AdaptiveAvgPool2d((5, 7))
input = torch.randn(1, 64, 8, 9)
output = m(input)


