GitLab

* enable reduce scatter overlap with other operations

* fixed unit tests and added docstrings for the new parameters for fsdp

* fixed more unit tests

* fixed unit tests

* avoided the pickle error on process_group_reduce_scatter

* removed an unnecessary parameter in unit tests

* remove unnecessary prints

* fixed the docstring

* skipped the test_offload unit test because this unit test failed in the main branch

* removed the enable_reduce_scatter_overlap API parameter

* added doc string for the defualt value of process_group_reduce_scatter parameter

* fixed a syntax bug

* fixed a bug which cause unitest failure

* removed the all_gather in the ProcessGroupName enum

* added more comment

* changed the default value of process_group_reduce_scatter from None to ProcessGroupName.reduce_scatter

* FullyShardedDataParallel: only return full state dict on rank 0

* Add flag and make rank 0 only optional

* Add tests

* Add docs

* address comments

* update comments

* update torch nightly version

* update torchvision number for torch nightly dependence

* add changelog

* Update CHANGELOG.md

* Update CHANGELOG.md

* Enabling ssd_offload training and test via tests/nn/data_parallel/test_fsdp_offload.py.
* Removed unused classes: SsdBuffer, SsdTensorHandleView, SsdParameter, SsdTensor
* Enhance test coverage of test_ssd_offloading_train_flatten_params_wrapper
* Modifications from PR #887 review comments.
* Update Changelog

Fix for Key Error that can happen in certain FSDP wrapping scenarios of Huggingface model sub-modules (issue #876) (#881)

* Fix for Key Error that can happen in certain FSDP wrapping scenarios of Huggingface model sub-modules (issue #876)

* Styling fixes

* Updated the test to be independent of the Huggingface transformers package

* Added test for issue #876

* Small error message fix

* Skip test when CUDA is not available

* Fixed naming of model

* [fix]: fix eval for shared weight FSDP

* fixing optim state saving

* add changelog

* reformat with newer local isort

* update test

* avoid computing reference state unless we are testing training

* added optim_state test

* make mypy happy

* move tests; maybe we need to CUDA memory related tests in the first of the lists
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* fixed lint issues

* remove unused print statements

* add changelog entry

* [skip ci] fix lint errors

* first commit

* sharded scaler hitting nan assertions

* adding test for sharded grad scaler without cpu offload

* ddp grad scaler and fsdp sharded grad scaler test failing

* removing test_output

* fix no cpu offload test

* changing optimizer from OSS to SGD

* all tests passing, code cleanup pending

* code cleanup

* fix pyproject.toml

* removing .isort.cfg

* running isort linter

* resolving isort issues

* resolving black linter issue

* resolving mypy issues

* fix import statement

* fix mypy error

* modifying import statement

* adding pytorch version requirement

* fixing pytest skip test decorator

* apply version guard for ShardedGradScaler

* removing test_fsdp_grad_scaler

* increasing num_epochs for ShardedGradScaler so that updates are not skipped

* adding support for torch 1.8

* minor edit

* [skip ci] more torch 1.8 changes

* parametrizing the tests

* cleanup code with linters

* [skip ci] update doc string

* [skip ci] addressing some more comments

* 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

* CI config changes

* changing params for failing tests

* [skip ci] minor edit

* update release notes

* initial commit

* lint cleanup etc.

* helper functions; lint errors

* lint errors

* lint errors

* add back the boolean for named_parameters

* address comments and fix lint

* remove unused functions and class

* remove unused state

Add SlowMo Distributed Data Parallel for clusters with slow interconnects
Co-authored-by: Vinayak Tantia <tantia.vinayak1@gmail.com>

* [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>

* added a new test, passing without shared weights

* tested weight sharing

* added the test to test list file

* extended to world_size = 2

* fixed test

* [feat]: add limited and experimental support for shared parameter

* fixed tests

* simplify to work with layer with at least 1 non-shared params and add code to pick up linked_param field for sharding the shared param

* fixed the case where linked param is not in separate FSDP

* changelog and remove old code
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* [fix] fix test on main

* [fix] fix test on main
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* remove offload dependency on fp16

* update python version for cpu tess

* run CPU tests with updated PyTorch version

* split changes

* revert tests config

* fix lint errors

* update nightly and test PyTorch versions

* skip failing multiprocess pipe test

* always skip test

* always skip test

* always skip test

* lint error

* skip unsupported versions

* improve skip message

* lint errors

* modify docs

* add tests

* fix test failures

* modify comments

* fix lint errors

* fix lint errors

* checkpoint + nonflat + mixed_precision

* make tests pass with expected errors

* addressed comments

* add a comment
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* added the failing test

* fixed the bug

* fine-tune the condition

* typo

* typo

* changelog and added test to test files
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* [fix] FSDP intra-backwards gradient accumulation.

Ensure gradient reduction accumulates into the unsharded gradient tensor
within a backwards pass. This matters when an FSDP module is called
multiple times within a forward pass, and reduction is _not_ deferred
using activation checkpoint forward counters, bucketing or some other
mechanism.

Closes #780

* [refactor] Remove forward counters. Comments.

Removed forward counters from the activation checkpointing utility, now
that FSDP does not require them for correct operation. Add more detailed
comment about memory usage behaviour with gradient reduction.

* [refactor] Delete deprecated forward counter usage.

* [refactor] Add state assertion as end of pre-backward hook.

Before this commit, output tensors of checkpointed modules always
require grad, even if they shouldn't. This commit makes it so that
the outputs of checkpointed modules only require grad if either
the input requires grad or if the parameters require grad.

To achieve this, this commit also adds a new _unflattened_param_views
attribute to modules being flattened. This allows the checkpointing
to still access the parameters and check if gradients need to be
computed.
Co-authored-by: Alex Xiao <axiao@fb.com>

* [test] Added disable_checkpointing unit test

* [test] Added disable_checkpointing unit test (Clean-up)

* [test] Added disable_checkpointing unit test (Clean-up)

[cleanup] CI test updates; mypy cleanup; partial broadcast_object cleanup; pre-commit documentation (#744)

* changelog; mypy; oss cleanup

* more broadcast_object cleanup in FSDP

* one more mypy fix

* retire pytorch 1.6 from circleci, add new lightly, add 1.8 LTS and 1.9 stable release

* update torch version for LTS

* minor fixes

* update cache key

* trying newer gpu VMs

* bump the cache

* update to gpu.medium, which should be 2 GPUs

* update nightly version

* add pre-commit instruction

* fixed CHANGELOG after merging

* updated to newer nightly

* retained the older broadcast function for older GPUs for oss.py

* fixed a bug

* added a comment

* fixing a test for pytorch 1.10

* testing a fix

* Update fairscale/optim/oss.py

* Update CONTRIBUTING.md
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* add additional assert for checking if the requires_grad field is set.

* fix lint errors

* add unit tests and address comments

[FSDP][feature] Support returning the original parameter names after a model has been wrapped with FSDP (#755)

* checkpoint work

* fix lint issues

* remove debug statement

* remove print

* fix lint errors

* fix lint errors

* fix lint errors

* add comments and fix lint errors

* modified comments and tests

* Add test (broken) for gradient accumulation without no_sync context manager

* changelog

* no_sync to grad_acc renaming for tests

* clean up tmp files

* support grad acc without no_sync

* minor

* update changelog

* Update fairscale/nn/data_parallel/fully_sharded_data_parallel.py

Better assertion from Sam.
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* lint
Co-authored-by: Min Xu <min.xu.public@gmail.com>
Co-authored-by: Min Xu <24926999+min-xu-ai@users.noreply.github.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

Move final backward callback to pre-backward hook of root FSDP instance

Summary:

Move final backward callback to pre-backward hook of root FSDP instance,
so that it is always attached to the outer most backward call and fired
after all backward calls are completed.

Also added flags to check final backward callback is fired when final
backward callback is required.

If root FSDP is checkpointed and called multiple times in forward,
check pointer counter is used to make sure final backward callback is queued inside last inner backward
call as well.

Test Plan: unit tests

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* reformat

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* nits and unit tests

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* address some comments

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* replace m with self
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* reformat

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* nits

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* remove the fired flag

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* assert state on root only

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* comments

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* [feat] FSDP: supporting multiple flatten parameter groups

- step 3: make FSDP use FlattenParamModule unconditionally

* fixing the auto_wrap tests

* minor

* rewrite local_metadata_dict

- updated FPW so that custom flat param name is also supported

* bug fix

* mypy

* rewrote consolidate_shard_weights

- test_consolidate passes

* comments

* fixing pickling

* Fix shared params and MoE logic (#749)

* add strict kwarg to support fairseq:gshard MoE saving logic

* Test fairseq style shard

* style

* formatting and address comments

* added changelog

* fixing a test after padding renaming
Co-authored-by: Min Xu <min.xu.public@gmail.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Update fully_sharded_data_parallel.py

update fully_sharded_data_parallel to use _allgather_base

* Update reduce_scatter_bucketer.py

Use reduce_scatter_base

* Update fully_sharded_data_parallel.py

nonblocking gradient cpu copy, and nonblocking param rebulds

* Update reduce_scatter_bucketer.py

lints

* Update fully_sharded_data_parallel.py

* Update reduce_scatter_bucketer.py

* Update reduce_scatter_bucketer.py

* lints

* linter, test fix

* linter

* LINTERgit add fairscale/utils/reduce_scatter_bucketer.pygit add fairscale/utils/reduce_scatter_bucketer.py

* LINTERgit add tests/nn/data_parallel/test_fsdp_overlap.pygit add tests/nn/data_parallel/test_fsdp_overlap.py

* Update test_fsdp_overlap.py

* Update fairscale/utils/reduce_scatter_bucketer.py
Co-authored-by: Min Xu <24926999+min-xu-ai@users.noreply.github.com>

* Update fairscale/nn/data_parallel/fully_sharded_data_parallel.py
Co-authored-by: Min Xu <24926999+min-xu-ai@users.noreply.github.com>

* Update reduce_scatter_bucketer.py

* isort
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-185.ec2.internal>
Co-authored-by: Min Xu <24926999+min-xu-ai@users.noreply.github.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-77-164.ec2.internal>

See https://github.com/pytorch/pytorch/pull/59671/

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Make sure requires_grad of FlatParameter to be consistent with requires_grad of original parameters (#721)

* Make sure requires_grad of FlatParameter to be consistent with requires_grad of original parameters

* Make sure requires_grad of FlatParameter to be consistent with requires_grad of original parameters

* [feat] FSDP: supporting multiple flatten parameter groups

- step 2: extending FPW to support multiple flat params groups
- FSDP still only use one group
- unit test does this the new code paths
- updated the changelog

* first cut, mypy passed

* test_flatten_params_wrapper.py::TestFlattenParams tests pass

* added two more test cases and fixed a case in the code

* fixed one bug with param_path_infos

* fixed two more tests with hardcoded flat_param names

* Update CHANGELOG.md
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* add failing test

* add fix

* use 'torch.is_grad_enabled()' instead of 'module.training'

* Revert "add failing test"

This reverts commit 1c34242208f9b2c5fa6c8f181434c2be6d7cdbc0.

* add simple test

* improve test

* add check for fwd_counter

* revert typing/format changes

* move to new test file

* CHANGELOG

* remove old test

* fix import order

* fix test to be compat with torch 1.6.0

* clean up

* comments

* isort 🤦

* refactoring FlattenParamWrapper

- use a FlatParameter class to encapsulate the logic of
  flattening and expanding into views.
- this will make it easier to have multiple groups of flatten
  parameters

* fixed testing context issues for both temp files and temp dirs

* fixing test_fsdp_metadata

* fix pickling of FlatParameter

* fixed test_fsdp_optimizer_utils.py

* minor

* fix assert

* lint

* remove nesting from the test

* step 1.5: remove the code related unnecessary nesting support in FPW

* Update fairscale/nn/misc/flatten_params_wrapper.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* address comment
Co-authored-by: Min Xu <min.xu.public@gmail.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* add failing test for buffer dtype

* fix buffer dtype issue

* update CHANGELOG

* fix

* [do not merge] testing a corner case

* workaround

* using dummy tensor to fix

* lint

* changelog

* update a comment
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* [fix] auto_wrap: support wrapping based on wrapper_config

- user can use this to avoid assert if auto_wrap is used multiple times on a module
- user can traverse the modules multiple times and assign a wrapper_config
  to the module and then use auto_wrap once to wrap them

fix #649
fix #585

* added changelog

* fix tests

* fix a test

* added an optional assert for collision based on discussions with Quentin

* added config_auto_wrap_policy

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

* Save FSDP metadata for offline unflattening

* Complete the meta-data saving method with all the information needed to reconstruct a checkpoint offline, and implement the method that reconstruct a consolidated checkpoint from a sharded checkpoint

* Complete the meta-data saving method with all the information needed to reconstruct a checkpoint offline, and implement the method that reconstruct a consolidated checkpoint from a sharded checkpoint

* Add a unit test to show how to use the function

* Code review + improvement of the unit tests

* Code review: extract clean_path

* Make meta data and consolidation of checkpoint work for flatten_parameter=False

* Add new unit test file in CI

* Complete changelog and fix mypy issues

* Add support for module buffers in the consolidation of sharded checkpoints

* Better support for module buffers: save them in the meta data

* Refactoring: use a data-format for the meta data that is simpler to understand (move from object of array to array of object format)

* Renaming to make code clearer

* Code review: in_temporary_directory rework and typo correction

* Renaming
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: QuentinDuval <QuentinDuval@users.noreply.github.com>

* fix saving and loading checkpoints with use_sharded_state=True

* mypy fix

* better fix of the infinite recursion

- we need to specifically call FSDP.state_dict from its local state_dict
- added unit test that fails without the fix and works with the fix
- fixed mypy for the overloaded functions

* make cpu-only fsdp work for state_dict at least
Co-authored-by: Min Xu <min.xu@acm.org>
Co-authored-by: Min Xu <min.xu.public@gmail.com>
Co-authored-by: Min Xu <m1n@fb.com>

* [fix] add and use get_process_group_cached

- This commit makes FSDP avoid making too many process groups by default
- Extra process group is bad for GPU memory and init time

* add changelog

* lint

* note on speed

* add better assert output

test seems to be flaky:
https://app.circleci.com/pipelines/github/facebookresearch/fairscale/2957/workflows/383c9f9f-f1a5-461c-8c41-e2e28ece037b/jobs/26783/steps



* update test reference memory values

- With cached process groups, the memory is reduced as reported by
pytorch as well (due to bucket buffer memory for the reduction buffer)
- The effect on memory is actually more on the SMI memory, which is not
reported by pytorch and checked by this test.

* Update fairscale/nn/data_parallel/fully_sharded_data_parallel.py

* Update fairscale/nn/data_parallel/fully_sharded_data_parallel.py

* Update CHANGELOG.md

* Update fairscale/utils/parallel.py

* Update fairscale/utils/parallel.py

* Update fairscale/utils/parallel.py

* Update fairscale/utils/parallel.py

* improved changelog

* better handling of underscores in the md file
Co-authored-by: Min Xu <min.xu@acm.org>