Basically, one can read up on how Tensorflow and PyTorch typically order their batches of images (TF: NHWC, PyTorch: NCHW) and weights (TF: HWCiCo, PyTorch CoCiHW) and then implement it and fix anything that went wrong.
When porting a complex model – like when @ptrblck and I did ported StyleGAN 25 – I usually find a couple of things where my first attempt is wrong. This can be tedious and error-prone when you don’t have a comparison point, which is why people would love first class named tensors 27.
Best regards
Thomas