Hi, what would you do if you have PyTorch and TensorFlow models that are supposed to be replicas of each other and you wanted to test that they are exact replicas in terms of layer, weight initialization, loss functions, etc? I converted a TF model into PyTorch but PyTorch accuracy is far off from that of TensorFlow. I thought about using one sample or any kind of seed to force the same sample for both models, same seed for weight initialization and then observe the values for the tensors and see where they diverge? Do you think this is a good idea and is it doable? or would you have done something else?
Two challenges I will face in that case:

How to seed both models to act exactly the same?
debugging is a big challenge in tf compared to PyTorch

I would appreciate your input.
Thanks!