GitLab

* bfloat16 support for apex DDP

* enable mgpu tests for fp16 and bf16

* update Dockerfile

* fix dropout scaling from p to 1/(1-p) (#816)
Co-authored-by: Sukru Eryilmaz <seryilmaz@computelab-dgx1v-32.nvidia.com>

* Improvements to apex.mlp (#804)

* update fused bias relu backward kernel

* adding support for not require first layer dgrad

* fix bug: wrong layer in requires grad

* add infrastructure for optional bias and activation, currently only support no bias and no relu

* make bias and relu optional separately

* add sigmoid activation option

* enable wider load/store for multi_tensor_apply kernels (#763)

* modify MTA axpby for wider load/store

* Make scale/axpby/l2/adam/lamb multi_tensor uses wider load

* Changes to make xentropysoftmax load/store vectorized when possible: (#725)

* Changes to make xentropysoftmax load/store vectorized when possible:
Increase default ILP so that each thread handle 16 Bytes data in one step
Make thread load/store longest vector possible
Make unroll case handle adjacent data instead of strided...

* update fused bias relu backward kernel

* adding support for not require first layer dgrad

* fix bug: wrong layer in requires grad

* add infrastructure for optional bias and activation, currently only support no bias and no relu

* make bias and relu optional separately

* add sigmoid activation option

The LARC optimizer wraps an underlying optimizer and then needs to be passed
to amp.initialize for mixed precision. There were 3 different crashes happening
in this situation, fix all of them and add a unit test.

I don't know if the 'LARC' in sys.modules check ever worked. In my setup, the
entry in sys.modules is 'apex.parallel.LARC'. Checking if the variable is
defined seems more reliable though.

* NHWC support for multi tensor apply

* compilation fix for version<=1.4

* increase atol for Half-Float comparison to 1.5e-4

* disable tests for different opt_levels

* reset atol

* add bitwise accurate comparison

* Pushing for build tests

* Contrib files

* Removing deprecated checks

* move import of amp_C to __init__()

* make fp16/32 separate lists to support mixed param types, disable double test

* make zero_grad consistent between adam/novograd/lamb

* add state_dict, load_state_dict

* add test_restoring, test_loss_scale_decrease

* disable amp outputs for checkpoint tests

* add test for amp.state_dict, cleanup

* add state_dict patch, add test

* fixed testing, cleanup

* add readme for checkpointing

* add docs to source/amp

* add review changes to doc

FusedSGD now work as before
FusedAdam now work with o1/o2, no longer fuse scaling and casting
Removed special backend handling for FusedAdam
Moved and updated test for FusedAdam into run_optimizers
Removed legacy tests for optimizers.FP16_optimizer and FusedAdam in run_mixed_adam

Co-authored-by: Aditya Agrawal <aditya.iitb@gmail.com>
Co-authored-by: Marek Kolodziej <mkolod@gmail.com>

* Bug fix for non-affine layer-norm + add backward unit test

* clean up tests and add tests for a large batch

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

* Existing tests passing, still need to add per-tensor tests

* Test is passing, still need to measure performance

* ILP for l2norm functor