conv-neural-network pytorch max-pooling spatial-pooling

How to perform sum pooling in PyTorch

How to perform sum pooling in PyTorch. Specifically, if we have input (N, C, W_in, H_in) and want output (N, C, W_out, H_out) using a particular kernel_size and stride just like nn.Maxpool2d ?

Solution

You could use torch.nn.AvgPool1d (or torch.nn.AvgPool2d, torch.nn.AvgPool3d) which are performing mean pooling - proportional to sum pooling. If you really want the summed values, you could multiply the averaged output by the pooling surface.

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