Summary:
There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports:
```2to3 -f future -w caffe2```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033
Reviewed By: seemethere
Differential Revision: D23808648
Pulled By: bugra
fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/9905
This diff improves lars operator in Caffe2 by applying clipping to the computed learning rate
Reviewed By: pjh5
Differential Revision: D9020606
fbshipit-source-id: b579f1d628113c09366feac9406002f1ef4bd54f
* [C2] Implement Layer-wise Adaptive Rate Scaling (LARS)
* [C2] Implement Layer-wise Adaptive Rate Scaling (LARS)
* add unit test for Lars
* set default value for lars to be None
* remove lars for subclasses of SgdOptimizer