I intend to use one of these frameworks for research purposes, where I will be writing many custom training loops, playing with the network architecture a lot, and I need a lot of flexibility. I have seen many comparisons on the web with the usual conclusion that PyTorch is more suitable for research because it is better designed and is more flexible, but these articles are usually from before Tensorflow 2.0 came out.
Can someone pitch in their opinion on the current state of these frameworks? Which one do you think is more suitable for research?