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)