AdaptiveAvgPool1d

class torch.nn.AdaptiveAvgPool1d(output_size) [source]

Applies a 1D adaptive average 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 $L_{out}$.

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.AdaptiveAvgPool1d(5)
>>> input = torch.randn(1, 64, 8)
>>> output = m(input)