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AdaptiveMaxPool1d

class torch.nn.AdaptiveMaxPool1d(output_size, return_indices=False)[source]

Applies a 1D adaptive max pooling over an input signal composed of several input planes.

The output size is LoutL_{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 LoutL_{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,Lin)(N, C, L_{in}) or (C,Lin)(C, L_{in}).

  • Output: (N,C,Lout)(N, C, L_{out}) or (C,Lout)(C, L_{out}), where Lout=output_sizeL_{out}=\text{output\_size}.

Examples

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

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