Yet in my experience PyTorch is much nicer to use. Its API feels very natural and easy to extend -- it feels very Pythonic.
TensorFlow's API, on the other hand, seems to get in my way whenever I try to do anything new that isn't already built into one of its higher-level APIs (e.g., Keras). I frequently I find myself fighting with TensorFlow's API.
For iterative R&D/exploratory work, I find I'm more productive -- and happier -- with PyTorch than TensorFlow.
Agreed that pytorch feels “pythonic”. I think tensorflow doesn’t because it’s really a C++ API with an extensive set of wrappers and it shows. Pytorch feels like they started with python and added in the C extensions after the fact.
Yet in my experience PyTorch is much nicer to use. Its API feels very natural and easy to extend -- it feels very Pythonic.
TensorFlow's API, on the other hand, seems to get in my way whenever I try to do anything new that isn't already built into one of its higher-level APIs (e.g., Keras). I frequently I find myself fighting with TensorFlow's API.
For iterative R&D/exploratory work, I find I'm more productive -- and happier -- with PyTorch than TensorFlow.