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Representatin extraction #10
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these questions would be interesting to get awsered |
Hi, that part is in the .ipynb file cell 6: def concat_features(features):
h = max([f.shape[-2] for f in features])
w = max([f.shape[-1] for f in features])
return torch.cat([torch.nn.functional.interpolate(f, (h,w), mode='nearest') for f in features], dim=1) |
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Hello,
I have an question about the representation extraction. I didn't find the code for the upsampling activation maps. So my first question is the activation maps the same with the ouputs of each self.convs layers. Second is which method did you use for the upsamplinig, Upsample or Convtranspose2D? And the mode for upsampling contains 5 options, which one did you choose?
Many thanks.
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