Hi,
I found two differences that might be relevant. The first one is different epsilon for the batch norm layers, mentioned in your first post. The second one is how the padding works. Pytorch add equal padding on all the sides whilst tensorflow’s “same” padding will not do this. This goes into effect when stride=2 for resnet.
If you have compared a specific input in both of the models and seen that they produce the same output I guess that this is not the problem.
Let us know if you figure it out