I am trying to convert a pre-trained TensorFlow model to PyTorch and evaluate it. I import the TensorFlow model and then convert each layer into Numpy arrays. My PyTorch model has the exact same set up except all the layer shapes are flipped. I convert each Numpy array into the appropriate shape (using the torch permute function) and insert it into my PyTorch model, but the accuracy is nowhere near what it was on TensorFlow. I have a feeling it has something to do with the flipped shapes, but I’m not quite sure how to fix it. Is there something I’m missing?