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I don't get the more native part - you can call a TensorFlow or a PyTorch model and get results from either in Python - what kind of integration are you imagini
by jstx1 4y ago
I don't get the more native part - you can call a TensorFlow or a PyTorch model and get results from either in Python - what kind of integration are you imagining where the internal implementation of the model makes a difference?
- college_physics 4y agoI think people mostly refer to the debugging part while developing, not any other capabilities or API issues. So for example building a larger (monolithic) application entirely in python, where ML is only a part might be easier using pytorch.
- jstx1 4y agoWhy though? What specific thing does PyTorch do that TensorFlow doesn't do in a large monolithic Python application?
- college_physics 4y agoLike said, debugging that application is one difference [0] [0] https://sites.google.com/site/wildml2016nips/SculleySlides2.pdf https://sites.google.com/site/wildml2016nips/SculleySlides2....
- albertzeyer 4y agoThis is from 2016, i.e. really ages ago. This is for TensorFlow 1, graph mode. Now with eager mode TensorFlow 2, there is not much difference between debugging TensorFlow vs debugging PyTorch.