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However, I am getting the error below.
Which I guess has to do with upsampling the GCAM to the original input size.
I am not sure if the upsampling should also get updated after this merge #466?
I have also tested this out #67 (comment)
I am not sure how it should work in my case,
If I understand correctly,
In X3D architecture, the model performs convolution in the temporal dimension, so a forward pass with one frame would fail because the input size will be smaller than the kernel in the temporal direction.
Hi,
Thanks for the Repo
I am trying to use GradCAM on the X3D model from the tutorial below.
https://pytorch.org/hub/facebookresearch_pytorchvideo_x3d/#define-input-transform
However, I am getting the error below.
Which I guess has to do with upsampling the GCAM to the original input size.
I am not sure if the upsampling should also get updated after this merge #466?
Thanks,
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