PyTorch vs. Tensorflow eager
One the key advantages that is I use a lot is that is compatible with pdb, so that

pdb.set_trace # To the rescue


Permits the use of python data structures

and let us to use pythonic control flow instead of using the main tf equivalents.

Also it allows to avoid metaprogramming issues such as "lazy loading" and adding a bunch of operations to my graph. Also autograd similarities