3 Commits

Author	SHA1	Message	Date
Bor-Yiing Su	7270471ed6	Returns auxiliary parameters in the optimizers. ... Summary: 1. Adds a function to return auxiliary parameters for each optimizer. This function can be used to serialize the optimizers so that they can be recovered. 2. Fixes the bug that the iteration blob is not incremented by one in each iteration. Suppose there are k parameters using the adam learning rate optimizer, the iteration blob is incremented by k based on the original implementation. Reviewed By: azzolini Differential Revision: D4872397 fbshipit-source-id: d86711feedda2ba83af5f2a18141b06a6a473733	2017-04-17 10:16:32 -07:00
Aaron Markham	58f7f2b441	doxygen python block added ... Summary: Closes https://github.com/caffe2/caffe2/pull/226 Differential Revision: D4793550 Pulled By: JoelMarcey fbshipit-source-id: cc33e58186304fa8dcac2ee9115dcc271d785b1e	2017-03-29 06:46:16 -07:00
Huazhong Ning	83437853ad	refactor and modulize optimizers ... Summary: The current optimizer code in c2/python has the following issues: (1) the optimizers in sgd.py cannot config per param-blob optimizer; (2) sgd.py is a bad file name. optimizer.py is a better name; (3) layer_model_helper.py has another set of optimizer code (which supports per param-blob optimizer) This diff did the following (1) create optimizer objects so that we can config per param-blob optimizer and that are also compatible to the existing optimizer code (2) the new optimizer code are much more modulized (3) move the optimizer code to file with better name (optimizer.py) (4) replace the optimizer imports in the existing code will do in next diffs (1) optimizers with structured parameters for dper2 (2) get rid of the optimizer code in layer_model_helper.py Reviewed By: salexspb Differential Revision: D4609013 fbshipit-source-id: 2e2d6dfa8685d10498f89069157453d9feca3f27	2017-03-07 18:46:47 -08:00