Closed jmhessel closed 7 years ago
Hi @jmhessel,
I'm now going through what you have done, I wanna to know whether you have trained a reasonable model? and what dataset are you training on?
Best, Zehao
@jmhessel I have validated it on mnist dataset, got 97.64% accuracy on test set.
Hi @Zehaos @jmhessel,
Thanks for helping us validating and integrating.
@jmhessel For the three points, I think we can add here the first two points. For the last one, it would be the best practice to request Keras team to integrate. We could try to reach out. What do you think?
Cheers,
Jian
@jmhessel Could you please do a pull request with your modification for the first two points?
Thanks.
@JianGoForIt Sure -- I can do a quick PR (I actually didn't even bother saving the code because the modifications were so minor, but it will be easy to re-do once I get the chance in the next few days). With respect to point 3, I don't think you'll need to get in contact with the keras folks -- when I say that the YFOptimizer is wrapped in the TFOptimizer, I mean that it is done programmatically (i.e., it's not a subclass if TFOptimizer or anything, you simply write opt=TFOptimizer(YFOptimizer())
which is pretty clean, as is.
@jmhessel Ha, got your point right this time. That sounds great! I will merge your PR as soon as it is done.
Keras support added using commits for pull request here https://github.com/JianGoForIt/YellowFin/commit/0949dfe2e674e1b83bdd06bbc21cf9b2d920ae1f
Hi! Thanks for posting this code. I thought that I would give YF a try as a drop-in optimizer. Currently, I am using Keras, and I was able to modify your code to run on Keras models by doing the following:
compute_gradients
standalone methodapply_gradients
andafter_apply
YFOptimizer
object in a Keras TFOptimizerHowever, while it runs and my loss goes down -- I am not 100% I did everything properly. Do you think you might consider adding this support?