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I think it makes more sense that: a) It's Google, they can throw hardware at a problem such as out of memory b) TensorFlow makes methods development so much e
by tfgg 11y ago
I think it makes more sense that:
a) It's Google, they can throw hardware at a problem such as out of memory
b) TensorFlow makes methods development so much easier that it's worth the loss of performance
c) It's early days and the compute graph scheduler has lots of opportunities, and is designed, for optimization, and in a more flexible fashion than other frameworks.
When I work on developing methods for scientific code, I worry more about whether the code is bug free/easy to understand and that it's giving the right answer. I don't usually worry about performance unless I'm actually not able to run things. Especially since when developing stuff you waste way more time on runs with bugs - I dread to think what my (published / unpublished) CPU hour ratio is. If the new approach allows less buggy implementations then that's a resource win.
- IanCal 11y ago> b) TensorFlow makes methods development so much easier that it's worth the loss of performance Indeed, if TensorFlow means I can try out an idea with 1 day of coding and 2 days of training rather than 3 days of coding and 1 day of training then I can spend a day drinking cocktails and reading books and still be finished sooner. Based on the tutorials it seems like I'd be able to pretty quickly build a translation pipeline, and in fact there's an implementation of that I think I'll try. If it takes a week or two to train, that's fine by me, I've got other things to be getting on with.