[Python] What is Adaptive Average Pooling and how does it work?

I recently came across a method in Pytorch when I try to implement AlexNet.
I don't understand how it works. Please explain the idea behind it (with some examples) and how it is different from Max Pooling or Average Pooling in terms of Neural Network functionality.

nn.AdaptiveAvgPool2d((6, 6))
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