GitLab

* bfloat16 support for apex DDP

* enable mgpu tests for fp16 and bf16

* update Dockerfile

fixing empty return from python implementation
  adding proper test to verify functional correctness for python implementation

fixing empty return from python implementation
  adding proper test to verify functional correctness for python implementation

* Refactor to allow more flexible treatment of multiple optimizers/models/losses

* Adding _process_optimizers.py

* Created L0 tests (now passing).

* fix: minor print typo (#234)

* make L1 results easier to read

* L0 multiple model/optimizer/loss test fleshed out

* Adding test that master params remain synced across distributed processes

* Docstring updates

* Docstring updates

* test passes

* notes

* Using C++-side flatten and unflatten functions

* Adding csrc

* Persistent synchronization event so it doesn't need to be created and destroyed each time

* Interop with parameter flattening in SSD

* Added deterministic option to imagenet main.py

* Adding options to split gradient averaging and allreduce in pure fp32

* Fixing allreduce_maybe_retain call

* Fixing allreduce_fallback

* Also sync active_i_buckets from rank 0

* Making retain_allreduce_buffers compatible with/orthogonal to delay_allreduce=True|False

* Correcting syntax error, now all seems to work with SSD

* Optional cpp extension build

* Add mixed precision adam optimizer (#59)

* Add FusedAdam Optimizer to Apex that places all the math into a cuda kernel.

* Added fixes to fused_adam to get it to work with network.

* wip work on python interface for adam with options

* fix dispatch for halfs, add python options to handle optional half gradients and params

* cleanup, get rid of grid-stride loop

* beautiful

* IT'S WORKING

* Hopefully fix race condition for fallback hook

* Updating test

* shared_param -> delayed_allreduce

* Adding a safety check

* One more check

* syntax...