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* Support dynamic loss scale args in fp16 optimizers

* Update names

* add basic post-install test

* update apex version to feb 5th commit

* use gradient clipping instead of max grad norm in tests

* add warning when user provides max_grad_norm

* update examples commit

1) CSR parameter names should end with .weight. 
2) When using basic optimizer directly, DeepSpeed should handle zero_grad. Letting the basic optimizer do the zero_grad resulted in residual gradients in the embedding layer due to unknown reasons.

Remove explicit torch version requirement so that we can more easily support other versions

Co-authored-by: Shaden Smith <Shaden.Smith@microsoft.com>

* Push to remote

* Correctly handle multi output models by doing loss scaling in backward()
Unit tests for multi output models

* Fix formatting issues

* Formatting issues fix

* Fix formatting

* Update DeepSpeedExamples submodule
Enable Megatron model tests

* added zero_allow_untested_optimizer flag helpers

* add zero_allow_untested_optimizer config constants

* zero_allow_untested_optimizer logic with assertion

* Added unit test and CustomOptimizer helper class

* remove session_params in deepspeed_constants.py

* add constants info at README.md

* Better config filename

* Clean up configuration ToC

* fix docs permalink

* fix docs permalink

* Add coming soon to posts

* Add what's new section to main page

GitHub created a CNAME for us automatically. Cool.