AdaptiveMaxPool2d
class torch.nn.AdaptiveMaxPool2d(output_size, return_indices=False)
Applies a 2D adaptive max pooling over an input signal composed of
   several input planes.
The output is of size H_{out} \times W_{out}, 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_{out} \times W_{out}. Can be a tuple
        (H_{out}, W_{out}) or a single H_{out} for a square image
        H_{out} \times H_{out}. H_{out} and W_{out} can be either a
        "int", or "None" which means the size will be the same as that
        of the input.
  * **return_indices** (*bool*) -- if "True", will return the
    indices along with the outputs. Useful to pass to
    nn.MaxUnpool2d. Default: "False"

Shape: