GitLab

* adding pre-commit files

* applying pre-commit to all files

* adding no-strict-optional argument to mypy in circle ci config

* fix typo

* updating python versions

* [skip ci] remove extra args

* adding python 3.9

* [skip ci] set pre-commit version in requirements-dev.txt

* set CACHE_VERSION

* move linters from circleci to github actions

* update python version

* update python version in benchmarks_2

* moving to python 3.9.7

* [feat] MEVO kernel

- initial import from min/softmax and min/testing branches
- need to rename and further cleanup

* only test with newer pytorch

* renamed and added comments and code cleanup

* rename and reduce test memory

* testing

* minor fixing

* fixing

* more fix

* changelog

* more 1.7 and 1.8 paper cuts

* remove dead code

* addressed Benjamin's comments

* addressed more comments
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* relax speed constraints

* relax the regressions constraints

* update pytorch version for benchmarks

* reduce golden data precision check

* migrate away from legacy iterators

* fix lint error

* add license file headers for all files

* fix lint

* [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

[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>

* debugging

* debugging activation issue

* fix activation loading

* remove changes used for testing

* remove comment

* add model

* add offload regression benchmarks

* add golden data

* remove mp pipe benchmark

* fix lint

* remove rank

* add check for model type

* lint errors

* fixing given torchvision's change

* add record_function support

* add more record_function cutpoints

* add more record_function cutpoints

* lint errors

* make string ids more specific

* renaming/adding error messages

* address comments

* address comments

* add more comments

* add more comments

* debugging statements

* fix index inputs and streams

* fix lint errors

* remove print

* lint errors

* address comments

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

* experimental: Add spectrain support

* Address review comments

* Address review comments

* smal fix, remove unused flags

* remove usused flag

* add back max_batch flag

* adding back lazy_construction

* adding back lazy_construction

* add missing device arg
Co-authored-by: Anjali Sridhar <anj@devfair0443.h2.fair>

:(

[refactor] Use logging in place of print statements, remove unused functions and other minor refactoring changes. (#461)

* fix pipe logging and other cleanups

* more log/debug changes

* [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>

* move experimental to the fairscale repo

* lint error fixes

* modify test imports

* lint error fixes

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

* restoring the regression test, adding a test of the for_each optims
* fix the regression test on circleci
* removing unused flags

* mp cleanup

* round of multiprocess refactoring

* test golden run

* print cuda stats

* fix lint errors

* enable multiprocess pipe benchmarks

* set world size to be available gpus

* more changes

* use synthetic loaders for intermediate pipeline stages

* merged master

* fix for the devices property

* dataloader fix

* modify rank check

* print wps stats

* enable verification

* fix logging

* fix flag name

* fix flag name

* check for rank

* fix indent

* pass args

* pass args

* modify golden data

* remove unused print messsage

* fix lint errors

* add comments

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

* [refactor]Remove unused variables and refactor common configurations

* move helper function to call site

* fixed lint errors

* fix lint errors

* fix lint errors

* fix lint errors

* fix import order

* format files

* remove unused imports

* fix lint errors

* fix lint errors

* refactor common utilities

* address PR comments

* sorted imports

* add space

* modify comment

* added doc strings and addressed PR comments.

* addressed PR comments

* added another comment to clarify.

* fixing lint errors

* addressed PR comments

* addressed PR comments

* fixed typos

* initialize var

* rename seq_pred to lm

* fix lint errors

* move datasets and models into separate folders

* add the folders created

* fix lint errors

* create golden config to stats mapping

* add common batching for both synthetic and real data

* fixed lint errors

* enable real pipe benchmakrs with new golden data

* reduce seq len to avoid OOM

* updated golden data

* add logging

* add golden data

* add golden data

* fix lint errors

* add doc string

* remove unused class

* add seq len and batch size to the config

* remove commented out line

* address comments

* rename imports

* refactor common logic in dataloaders

* add golden configs

* lint changes

* merge latest changes

* lint errors

* address PR comments

* initial refactoring

* lint fixes

* fix lint errors

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

* Add AMPnet implementation (clean version)

* Move ampnet to experimental

* Move stuff around pipeline

* Address review comments and fix pre-commit errors

* Refactor and modify delegate functionality

* Modify header in pipe.py