Reduction the dimension of input using Conv 1x1

I have an input x by dimension 128x512x1x1 and I need to reduce it to 10x10x1x1, how can I do that using Conv 1x1 in Pytorch?
any help would be appreciated.

I’m assuming the given dimensions are in y, x, c, n or y, x, n, c (which seems to be an unusual ordering) as otherwise it would imply a reduction in the batch dimension which seems unintended.

A simple method would be to simply increase the stride:

>>> import torch
>>> a = torch.randn(1, 1, 128, 512)
>>> c = torch.nn.Conv2d(1, 1, 1, (13, 52))
>>> o = c(a)
>>> o.shape
torch.Size([1, 1, 10, 10])

However, you may wish to downsample in a “smoother” way, so you might want to take a look at e.g., AdaptiveAvgPool2D:

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thank you very much.