GitLab

* fixing bug in setting dependancies in parition handler

* modifying unit test to need the fix

* black

* Preparing pipeline for newer versions of pytorch

* updated error message

* Update torch to 1.9.0.dev20210614+cu102

* Update config.yml

* Update config.yml

* Update setup.py

* Update config.yml

* Update config.yml

* Update config.yml

* Update config.yml

[Offload][feature] Add auto shard functionality to remove requirement of nn.Sequential models. (#695)

* auto wrap functionality

* lint and doc strings

* fix lint errors

* lint errors and version skips

* remove mypy checking and add conditional import

* another math.prod instance

* another import fix

* address comments

* lint errors

* address comments

* fix lint errors

* add placeholder nodes to tracker list

This change also ensure that we calculate running_{mean,var} correctly
when wrapped.

* [feat] experimental.nn.SyncBatchNorm: initial commit

Fast/simple re-implementation of SyncBatchNorm.

When profiling SSL Vision, I was seeing a majority of cycles spent in
SyncBatchNorm. With this change, I see a 10% to 20% speedup on the
model I was profiling.

When running benchmarks/experimental/sync_batchnorm.py on 8 x V100,
I get a 6x speedup:

<class 'torch.nn.modules.batchnorm.BatchNorm2d'>
Elapsed time is  0.08709120750427246
Elapsed time is  0.12632274627685547
Elapsed time is  0.14095258712768555
Elapsed time is  0.16529417037963867
Elapsed time is  0.1419970989227295
Elapsed time is  0.15166854858398438
Elapsed time is  0.12000870704650879
Elapsed time is  0.17534875869750977
<class 'torch.nn.modules.batchnorm.SyncBatchNorm'>
Elapsed time is  2.5087168216705322
Elapsed time is  2.497001886367798
Elapsed time is  2.5204885005950928
Elapsed time is  2.526789903640747
Elapsed time is  2.5080230236053467
Elapsed time is  2.524489641189575
Elapsed time is  2.513214588165283
Elapsed time is  2.5359973907470703
<class 'fairscale.experimental.nn.sync_batchnorm.SyncBatchNorm'>
Elapsed time is  0.4126114845275879
Elapsed time is  0.39051294326782227
Elapsed time is  0.40685415267944336
Elapsed time is  0.4159870147705078
Elapsed time is  0.42383885383605957
Elapsed time is  0.4080159664154053
Elapsed time is  0.41202712059020996
Elapsed time is  0.42400121688842773

* dynamic loss scaler

* isort

* black

* flake8

* comments

* added the test to ci file, added a line to catch the overflow error, fixed some formatting errors

* adding type annotation

* added todo for adding more test cases for handling Nan gradients

* fix some doc string and comments, add more tods

* fix two doc strings

* adding auto graph generation for distributed pipeline

* ignore trace.py for my for now, since it needs pytorch 1.8

* fixing tests

* simplifying graph api

* remove unused debug utilities

* use inspect to find argument lists

* use sharded linear layer

* flkae8

* comment

* polishing

* polishing

[fix] Revert change that removed the option to run OffloadModel with out activation checkpointing. (#608)

* revert change made

* add tests and revert sync shard changes

* add tests

* remove file checked in by error

* inine var

* fix lint errors

* add checkpoint activation

* fix mypy

* use a bigger model

* modify tests for now

* resolve conflicts
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>

replacing multip-process pipe implementation with more flexible one

Initial implementation of proposal pytorch/pytorch#55256

* renaming/adding error messages

* address comments

* address comments

* add more comments

* add more comments

* Fix ampnet unit test by adding delegate object

* Remove comments

* [chores]: CI py39 on GPU and more efficiency

* add test list files

* fix

* add test list files

* split benchmark run into 2 runs

* fix 1.8 version and balance benchmarks

* fix

* fix

* fix

* fix

* recording tests

* py39 install fix

* test again

* move tests

* reorg tests

* skip tests for torch 1.8 due to an upstream bug

* removed __init__.py from tests since it confuses pytest

* Revert "removed __init__.py from tests since it confuses pytest"

This reverts commit 7e156ba33dfaa5ed052031780613ec0cb57a45b0.

* don't include __init__ in file list

* notes on __init__.py and added missing ones

* fixed mypy in a test file

* balance test runtime

* better pip install

* balance more

* pip fix

* balance

* balance more, all test should finish within 20m now

* minor license update

* trying cu102

* more doc and addressed Ben's comments

* debugging

* debugging...

* clean start

* removing per layer split strategy, probably not that useful indeed

* initial transformer benchmark

* hack, enable testing ViT + offload, python3 benchmarks/oss.py  --epochs 2 --optim_type oss_offload_ddp --batch_size=32 --model vit_large_patch16_224

* proper cuda streams and device, something off in terms of mems consumption

* minor, stashing

* unit test fix

* removing all the distributed parts

* simpler test, needs debugging

* working OOP, running a model which does not fit on the gpu memory

* spring cleaning

* removing the ill-advised optimizer bits, better keep that orthogonal

* [offload] Add support for activation offloading + other changes (#367)

* initial fwd/bwd commit

* checkpoint work

* modify shard loop

* activation offloading and test to start with

* fix lint errors

* update comments

* fix lint

* remove unused var

* remove commented out lines

* modify name

* remove break

* remove profiler comments

* avoid saving inputs

* fix lint errors
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>

* [offload] Add support for fp16 training (#374)

* initial fwd/bwd commit

* checkpoint work

* modify shard loop

* activation offloading and test to start with

* fix lint errors

* update comments

* fix lint

* remove unused var

* remove commented out lines

* modify name

* remove break

* remove profiler comments

* add support for fp16

* add unit tests

* fix lint errors

* fix test failure
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>

* [offload] Add support for activation checkpointing for all layers. (#381)

* initial fwd/bwd commit

* checkpoint work

* modify shard loop

* activation offloading and test to start with

* fix lint errors

* update comments

* fix lint

* remove unused var

* remove commented out lines

* modify name

* remove break

* remove profiler comments

* add support for fp16

* add unit tests

* fix lint errors

* fix test failure

* cp work, incorrect output dimensions still need to be fixed

* fixed activation outputs

* intermediate cp of work

* add tests

* fix lint errors
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>

* add support for microbatches

* revert benchmark config changes

* add parametrization

* fix lint errors and tests

* skip test for 1.5

* fix lint errors

* skip test if there are no GPUs

* fix lint errors

* fix lint errors

* move experimental to the fairscale repo

* lint error fixes

* modify test imports

* lint error fixes

* move offload files to the experimental directory

* move tests and benchmarks to their forlder

* fix mypy errors

* cp intermediate working benchmarks

* more changes

* split benchmark configs

* remove print statements

* fix lint errors

* remove unused print

* stress testing

* remove unused file

* change param nae

* lint fixes

* move file to the right folder

* offload_experimental

* add doc string

* add error message
Co-authored-by: Benjamin Lefaudeux <benjamin.lefaudeux@gmail.com>
Co-authored-by: Benjamin Lefaudeux <benjamin.lefaudeux@protonmail.com>
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>

* refactor experimental file locations

* refactor fix

* disable test temporarily

* lint error fix

* make the change in the right file

* fix lint errors

* skip failing tests
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>