GitLab

* pass `self.mask_additive`

* clang-format

* removing THCState

* Add fused mixed precision lamb optimizer.

* Fix device usage in constructor.

* Fix sending param_group tensor state to device.

* Remove unneeded device set.

IFU-2021-10-15 (+ remove redundant defines + C10_CUDA_CHECK)

Changes include
- THC headers removal
- TH macros replacement
- fix some typo in comment
 Conflicts:
	apex/contrib/csrc/multihead_attn/additive_masked_softmax_dropout_cuda.cu
	apex/contrib/csrc/multihead_attn/encdec_multihead_attn_cuda.cu
	apex/contrib/csrc/multihead_attn/encdec_multihead_attn_norm_add_cuda.cu
	apex/contrib/csrc/multihead_attn/masked_softmax_dropout_cuda.cu
	apex/contrib/csrc/multihead_attn/self_multihead_attn_bias_additive_mask_cuda.cu
	apex/contrib/csrc/multihead_attn/self_multihead_attn_bias_cuda.cu
	apex/contrib/csrc/multihead_attn/self_multihead_attn_cuda.cu
	apex/contrib/csrc/multihead_attn/self_multihead_attn_norm_add_cuda.cu
	apex/contrib/csrc/multihead_attn/strided_batched_gemm.h

* Use --cuda_ext flag to build all supported extensions

* Don't remove --cuda_ext since it'll be needed to build other extensions

* Need to clear all cmdline args so setup.py doesn't complain

Add more unit tests for both distributed and extensions

Change python3.6 to python

* minimal bert pipeline parallel test

* fix global and cleanup

* use get_forward_backward_func

* cleanup and fix some tests

Co-authored-by: Sangkug Lym <slym@nvidia.com>
Co-authored-by: Sangkug Lym <slym@nvidia.com>

* init logging use

* fix

* clean up

* fp32 p2p comm

* init

* Dynamic global batch size with `MegatronPretrainingSampler`

I couldn't make this script work with `MegatronPretrainingRandomSampler` because the random sampler seems to have some requirement for
global batch size, total number of samples, local minibatch size, etc. which I'm not familiar with for now

* revive original pipeline parallel test

* update MULTIGPU_TEST: add dynamic batchsize test

* run MegatronPretrainingRandomSampler

* fix comment

* fix

* update

* cosmetic

* add note

* Apply 2 suggestion(s) to 2 file(s)

* change following https://github.com/NVIDIA/apex/pull/1210

* fix

Enable multihead atten

Co-authored-by: Jeff Daily <jeff.daily@amd.com>

Fix rocblas_gemmex namespace

Fix namespace

Clean up comments

Enable HIP floa to hald conversion

Fix some spacing

* Persistent LayerNorm: Multi-CTA Rewrite

* autocast support
Co-authored-by: Young-Jun Ko <youngjun.ko@gmail.com>

* Init apex.ppu (pipeline model parallel utility)

Reference commit:

```
commit 5ab646376d67831601d5552c193241d017f1b35c (HEAD -> main, internal/main)
Merge: 14f2c684 7b293d9b
Author: Mohammad Shoeybi <mshoeybi@nvidia.com>
Date:   Wed Sep 22 22:57:54 2021 -0700

    Merge branch 'add_BOS' into 'main'

    Add Beginning of Sentence token option and adding semaphore while multi-threading to prevent crashes and hangs due to connection keep-alives

    See merge request ADLR/megatron-lm!328
```

* removing get_args and replace import - phase 1

* removing get_args and replace import - phase 2

* move ppu to apex.transformer.pipeline_parallel

* update two __init__.py

* update READMEs

* mpu -> parallel_state & tensor_parallel

* fix

* remove not pipeline files

* separate schedules.py - phase 1

* dissect schedules.py

* data_iterators -> batch

* remove optimizer from forward_backward_step funcs

* init test

* Apply 2 suggestion(s) to 2 file(s)

* fix cyclic import

* fix syntax of Callable

* fix - 1

* move directory as testing used for pp test as well

* add some functions for num microbatches calculator

* model is a list in pipeline parallel

* skip build num microbatch calculator

* fix test

* assert -> raise

* skip args printing

* specify tensor shape everywhere even if None - phase 1

* private timers

* passing tensor shape & dtype around

* update dtype handling by introducing helper func

* write helper func to reduce cyclomatic complexity

* remove duplicate

* update

* move split_tensor_into_1d_equal_chunks to avoid cyclic import

* tmp

* cosmetic

* move gather_split_1d_tensor to avoid cyclic imports

* remove debug print

* add outer loop

* early return if possible

* cosmetic

* passing around tensor shape

* refactor test

* add script to learn batch sampler behavior

* update

* minibatch splitter

* add minibatch splitter

* split minibatch into microbatches

* minor changes

* uncomment split batch for test sake

* set as attribute

* study the behavior of no pipelining

* debug 1

* reflect test util namespace change

* update readme

* cosmetic in test

* add model build helper func for interleaving shced

* adding model builder from megatron

* canbe cyclic import

* fix

* enable interleaving test, but failing even if forward only

* fix batch preparation

* add explanation

* print data parallel size

* fix typo

* Add Megatron style GPT model by Rishi
Co-authored-by: Rishi Puri <riship@nvidia.com>

* update

* type hint for jit

* fix forward_backward_no_pipelining test

* pipeline forward backward seem to hang if not forward only

* fix typo

* debug

* add p2p test

* simplify

* fix

* tentative

* set both tmp and pmp to 1

* init

* fix typo

* fix

* fix path of divide

* set seed for tmp

* update upon Eddie comment

* fix typo

* adding failing data loader test

* fix

* megatron still failing

* check in

* with the nested loop of new order, interleaving seems fine

* cosmetic change

* make `forward_backward_pipelining_with_interleaving private

* warn users that interleaving sched is unstable

* move noop handler to no pipelining

* comment out rank_print

* make `build_model` more flexible

* skip megatron test tentatively

* correctly comment out rank_print

* correctly comment out rank_print

* correctly comment out rank_print

* skip appropriately

* remove wip p2p comm test

* update type hint of model_provider_func

* disable tf32 in each test script

* skip interleaving w/ backward

* rename as mpu is the old name

* remove broken case

* expose build_model func

* delete `dist.ring_exchange` func call and `use_ring_exchange` argument

* nit fixes

* check in

* remove unused file

* update the list

* update tensor shape

* remove mixed dtype case

* use torch.distributed.run

* 2020 -> 2021

* another 2020 -> 2021

* docstring & type hint

* fix teardown

* update

* change to experimental

* check if warned
Co-authored-by: Rishi Puri <riship@nvidia.com>
Co-authored-by: Eddie Yan <eddiey@nvidia.com>

This reverts commit 964e61f1.