AdaptiveAvgPool1d#

classtorch.nn.modules.pooling.AdaptiveAvgPool1d(output_size)[source]#

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

The output size is$L_{out}$Lout​, for any input size.The number of output features is equal to the number of input planes.

Parameters:

output_size (int |tuple[int]) – the target output size$L_{out}$Lout​.

Shape:

• Input:$(N,C,L_{in})$(N,C,Lin​) or$(C,L_{in})$(C,Lin​).

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

Examples

>>># target output size of 5>>>m=nn.AdaptiveAvgPool1d(5)>>>input=torch.randn(1,64,8)>>>output=m(input)

forward(input)[source]#

Runs the forward pass.

Return type:

Tensor