AdaptiveMaxPool1d
class torch.nn.AdaptiveMaxPool1d(output_size, return_indices=False)
Applies a 1D adaptive max pooling over an input signal composed of
   several input planes.
The output size is L_{out}, for any input size. The number of
   output features is equal to the number of input planes.
Parameters:
      * output_size (Union[int, Tuple[int]]) --
        the target output size L_{out}.
  * **return_indices** (*bool*) -- if "True", will return the
    indices along with the outputs. Useful to pass to
    nn.MaxUnpool1d. Default: "False"

Shape:
      * Input: (N, C, L_{in}) or (C, L_{in}).
  * Output: (N, C, L_{out}) or (C, L_{out}), where
    L_{out}=\text{output\_size}.

-[ Examples ]-



target output size of 5
m = nn.AdaptiveMaxPool1d(5)
input = torch.randn(1, 64, 8)
output = m(input)


