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I think people mostly refer to the debugging part while developing, not any other capabilities or API issues. So for example building a larger (monolithic) appl
by college_physics 4y ago
I 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.