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

* 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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* [chore] 0.3.9 release

* update changelog

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

* [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>

misspelled name

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

* Fixing memory lead in distributed pipeline

* fix mypy error

* fixing bug in setting dependancies in parition handler

* modifying unit test to need the fix

* black

* set numpy version

* remove numpy requirement

* remove numpy plugin

* add numpy requirements

* 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

* [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>

* migrate away from legacy iterators

* fix lint error

[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

* 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>

_SyncBatchNormFunction is a little complex in that it does the
full backward, including mean and var, but does not calculate
statistics in the forward path. Statistics are calculated outside
in the SyncBatchNorm nn.module.

This change does not impact functionality.

* add failing test for buffer dtype

* fix buffer dtype issue

* update CHANGELOG

* fix

* [test] fixing 1.9 nightly install

* update cache version so that we don't keep reinstall
Co-authored-by: Min Xu <min.xu.public@gmail.com>

* [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>

* update installation instructions

* modify README

* fix heading

* add tutorials

* add new context, modify and delete existing docs

* remove duplicate labels

* modify layout and more nits

* address comments

* fix merge conflicts

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

Make ShardedGradScaler __init__ mirror GradScaler so super can forward parameters. Without this one cannot configure a ShardedGradScaler object like one can with the PyTorch native GradScaler object.
Updated with black linter.
Added stub for GradScaler __init__ which solves mypy issues and removed
ignore comment.

* rename codecov yaml file

* remove status checks

* [chore] 0.3.7 release

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