indices along with the outputs. Useful to pass to
        nn.MaxUnpool3d. Default: "False"
Shape:
      * Input: (N, C, D_{in}, H_{in}, W_{in}) or (C, D_{in}, H_{in},
        W_{in}).
  * Output: (N, C, D_{out}, H_{out}, W_{out}) or (C, D_{out},
    H_{out}, W_{out}), where (D_{out}, H_{out},
    W_{out})=\text{output\_size}.

-[ Examples ]-



target output size of 5x7x9
m = nn.AdaptiveMaxPool3d((5, 7, 9))
input = torch.randn(1, 64, 8, 9, 10)
output = m(input)
target output size of 7x7x7 (cube)
m = nn.AdaptiveMaxPool3d(7)
input = torch.randn(1, 64, 10, 9, 8)
output = m(input)
target output size of 7x9x8
m = nn.AdaptiveMaxPool3d((7, None, None))
input = torch.randn(1, 64, 10, 9, 8)
output = m(input)


