3 ms·
Why?
by qwerty456127 7y ago
Why?
- hprotagonist 7y agoresearch: the API. industry: tensorRT.
- chillee 7y agoWell, you could read the article :^) As a summary, though: PyTorch has become dominant in research because of its API (both its stability + having eager mode). TF has become dominant in industry because A. it came out several years before PyTorch and industry is slow to move, B. It supported a lot of production use cases (mobile, serving, removing Python overhead) that PyTorch didn't for a long time.
- enriquto 7y agowell, for one pytorch added the python overhead over an otherwise very clean lua jit
- mruts 7y agoPyTorch wraps THNN, not Torch. Moreover, even if this was true, it wouldn't matter at all. Practically 0% of the overhead is related to Python in the first place, all of the time is dominated by the underlying C implementation.
- qwerty456127 7y agoIf only articles were as concise as your summary is I would enjoy reading them but as long as they are many pages long I have no time to read beyond the titles, abstracts, conclusions and comments. BTW I've also read (here on HN) PyTorch learns much faster than TensorFlow does.
- tecleandor 7y agoThen it wouldn't be an article, it would be a summary :)
- nknealk 7y ago100% anecdotal -- The Keras interface for tensorflow makes it easy & fast to make "good enough" models. That is often a driving factor
- mruts 7y agoI've personally found pytorch easier to use than Keras. It's undoubtably easier to use than Tensorflow, of course.