AdaptiveMaxPool1d — PyTorch 2.7 documentation (original) (raw)

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