AdaptiveMaxPool3d
class torch.nn.AdaptiveMaxPool3d(output_size, return_indices=False)
Applies a 3D adaptive max pooling over an input signal composed of
   several input planes.
The output is of size D_{out} \times 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],
        Optional[int]]]) -- the target output size of the
        image of the form D_{out} \times H_{out} \times W_{out}. Can
        be a tuple (D_{out}, H_{out}, W_{out}) or a single D_{out} for
        a cube D_{out} \times D_{out} \times D_{out}. D_{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
