• torch.nn.AdaptiveAvgPool3d(output_size)[SOURCE]

• Applies a 3D adaptive average pooling over an input signal composed of several input planes.

  The output is of size D x H x W, for any input size. The number of output features is equal to the number of input planes.

https://pytorch.org/docs/stable/nn.html?highlight=adaptive_avg_pool2d#torch.nn.AdaptiveAvgPool3d

you can use adaptive_avg_pool2d 390 to achieve global average pooling, just set the output size to (1, 1),

import torch.nn.functional as F x = F.adaptive_avg_pool2d(x, (1, 1))

https://discuss.pytorch.org/t/global-average-pooling-in-pytorch/6721/9