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 LoutL_{out}Lout, 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}Lout. Shape: Input: (N,C,Lin)(N, C, L_{in})(N,C,Lin) or (C,Lin)(C, L_{in})(C,Lin). Output: (N,C,Lout)(N, C, L_{out})(N,C,Lout) or (C,Lout)(C, L_{out})(C,Lout), where Lout=output_sizeL_{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