Aaron Orenstein
00ffeca1b1
PEP585 update - torch/distributed ( #145164 )
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See #145101 for details.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145164
Approved by: https://github.com/bobrenjc93
2025-01-21 04:23:29 +00:00
PyTorch MergeBot
6374332d33
Revert "PEP585 update - torch/distributed ( #145164 )"
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This reverts commit 6cb186e279https://github.com/pytorch/pytorch/pull/145164 on behalf of https://github.com/huydhn due to Sorry for reverting your change but it is failing an inductor test ([comment](https://github.com/pytorch/pytorch/pull/145164#issuecomment-2602875679 ))
2025-01-20 16:46:46 +00:00
Aaron Orenstein
6cb186e279
PEP585 update - torch/distributed ( #145164 )
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See #145101 for details.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/145164
Approved by: https://github.com/bobrenjc93
2025-01-20 00:19:01 +00:00
Yifu Wang
3d26c08dda
Fix unintended deprecation warning in torch.distributed.optim ( #140889 )
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We have a deprecation warning for scripted functional optimizer at module level in `torch/distributed/optim/__init__.py`. However, not all optimizers exposed by the module are scripted functional optimizers, causing some false deprecation warning (e.g. https://github.com/pytorch/pytorch/issues/139661 ).
This PR moves the deprecation warning to the `__init__` functions of the deprecated scripted functional optimizers.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/140889
Approved by: https://github.com/d4l3k , https://github.com/kwen2501 , https://github.com/XilunWu
2024-11-18 02:34:51 +00:00
Xuehai Pan
3b798df853
[BE][Easy] enable UFMT for torch/distributed/{fsdp,optim,rpc}/ ( #128869 )
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Part of #123062
- #123062
Pull Request resolved: https://github.com/pytorch/pytorch/pull/128869
Approved by: https://github.com/fegin
ghstack dependencies: #128868
2024-06-18 21:49:08 +00:00
Aaron Orenstein
7c12cc7ce4
Flip default value for mypy disallow_untyped_defs [6/11] ( #127843 )
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See #127836 for details.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127843
Approved by: https://github.com/oulgen
ghstack dependencies: #127842
2024-06-08 18:49:29 +00:00
Michael Lazos
365e89a591
Add tensor step to adadelta ( #122252 )
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Towards fixing https://github.com/pytorch/pytorch/issues/115679
Fixes Adadelta step update while compiling
Pull Request resolved: https://github.com/pytorch/pytorch/pull/122252
Approved by: https://github.com/janeyx99
2024-03-21 07:28:47 +00:00
Jon Chuang
57e9969021
feat(optim): Add adadelta multi_tensor support for complex, with has_complex shortcut ( #110631 )
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Partial fix: https://github.com/pytorch/pytorch/issues/110606
More on `has_complex` shortcut: https://github.com/pytorch/pytorch/pull/110613#issuecomment-1749314805
CC: @janeyx99, @mlazos, @lezcano
Pull Request resolved: https://github.com/pytorch/pytorch/pull/110631
Approved by: https://github.com/lezcano
2023-10-06 03:34:41 +00:00
Aaron Gokaslan
8fce9a09cd
[BE]: pyupgrade Python to 3.8 - imports and object inheritance only ( #94308 )
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Apply parts of pyupgrade to torch (starting with the safest changes).
This PR only does two things: removes the need to inherit from object and removes unused future imports.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/94308
Approved by: https://github.com/ezyang , https://github.com/albanD
2023-02-07 21:10:56 +00:00
fduwjj
1a48ae96ba
[PT-D][Easy] Reformat the optim code within PTD code base ( #90399 )
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Just run two commands:
```
ufmt format torch/distributed/optim/
ufmt format test/distributed/optim/
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/90399
Approved by: https://github.com/awgu
2022-12-08 06:38:59 +00:00
anjali411
93912b1a73
Add __all__ to torch.distributed submodules ( #80523 )
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/80523
Approved by: https://github.com/rohan-varma
2022-07-11 06:54:24 +00:00
francescocastelli
58a44523c1
Add maximize flag to Adadelta
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Added the maximize flag to Adadelta optimizer (#68052 ) and adjusted tests to take maximize into account.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75330
Approved by: https://github.com/cpuhrsch
2022-04-08 20:32:35 +00:00
Mikayla Gawarecki
8e8d170674
Optim foreach cleanup for Adadelta ( #69980 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69980
- Merged `torch/optim/adadelta.py` and `torch/optim/_multitensor/adadelta.py` into `torch/optim/adadelta.py`
- Moved adadelta functional forms from `torch/optim/_functional.py` and `torch/optim/_multi_tensor/_functional.py` to `torch/optim/adadelta.py`
- `torch/optim/_functional.py` just imports from `torch/optim/adadelta.py`
- Added a test `test_optimizers_foreach_flag` which replicates `test_multi_tensor_optimizers` in `test/test_optim.py`
- Add a test `test_adadelta_new` that replicates the behavior of `test_adadelta` but with `foreach` flag instead of using the multitensor adadleta class. If we delete `_multitensor/` we could replace `test_adadelta` with this
Remaining TODO:
- [ ] single_tensor adadelta supports complex but multitensor does not, need to integrate the singletensor logic in multitensor and switch the `test_adadelta_complex` to test for foreach in [True, False]
Test Plan: Imported from OSS
Reviewed By: VitalyFedyunin, albanD
Differential Revision: D33413059
Pulled By: mikaylagawarecki
fbshipit-source-id: 92a9fa98705762bb6bd464261671e49aef40070e
(cherry picked from commit a008227d22
2022-02-09 16:52:12 +00:00
Andrew Gu
1b1f1e36b4
Add `allow_empty_param_list` to functional optimizers ( #62522 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62522
Addresses https://github.com/pytorch/pytorch/issues/62481
Test Plan: Imported from OSS
Reviewed By: zou3519
Differential Revision: D30072074
Pulled By: andwgu
fbshipit-source-id: 1a5da21f9636b8d74a6b00c0f029427f0edff0e3
2021-08-09 11:18:56 -07:00
Wanchao Liang
af0f083d42
[dist_optim] fix the bug of none grads on functional optimizers ( #62249 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62249
parameter and grads passed to torch.optim.functional should always match, we should skip the parameters that have none gradients to avoid the size mismatch
ghstack-source-id: 134452467
Test Plan: test_dist_optim_none_grads
Reviewed By: mrshenli
Differential Revision: D29929653
fbshipit-source-id: 4ca6167fecdfe1db422236655edee3aa59b8b044
2021-07-27 18:10:51 -07:00
Wanchao Liang
4611387608
[optim] take kw-only argument for functional optim APIs ( #56185 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/56185
ghstack-source-id: 126670123
Reviewed By: albanD
Differential Revision: D27802169
fbshipit-source-id: f5e1cb2046dcdeecf5f6b0f70892828bf0adb22f
2021-04-15 20:08:04 -07:00
Vincent Quenneville-Belair
50d903f19f
[optim] make functional api be private ( #51316 ) ( #51665 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51665
This reverts commit 896f82aa92
2021-02-03 17:59:05 -08:00
Vincent Quenneville-Belair
896f82aa92
[optim] make functional api be private ( #51316 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/51316
Make optim functional API be private until we release with beta
Test Plan: Imported from OSS
Reviewed By: albanD
Differential Revision: D26213469
fbshipit-source-id: b0fd001a8362ec1c152250bcd57c7205ed893107
2021-02-03 09:29:33 -08:00
Wanchao Liang
6c81b4d917
[dist_optim] add distributed functional Adadelta optimizer ( #50623 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50623
Add TorchScript compatible Adadelta functional optimizer to distributed optimizer
Test Plan: Imported from OSS
Reviewed By: rohan-varma
Differential Revision: D25932772
Pulled By: wanchaol
fbshipit-source-id: d59b04e5f0b6bab7e0d1c5f68e66249a65958e0b
2021-01-23 01:04:36 -08:00
