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
6374332d33
Revert "PEP585 update - torch/distributed ( #145164 )"
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This reverts commit 6cb186e279bc179a6bb63f0226e24ab42a07b394.
Reverted https://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
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
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
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
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
f9d107af66
[optim] add fused_adagrad support for CPU device ( #124905 )
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Support fused_sgd_kernel support for CPU.
## Bench result:
32 core/sockets ICX
Test Scripts:
https://gist.github.com/zhuhaozhe/79e842e0a6e25d6d7fa1e4598807272c
https://gist.github.com/zhuhaozhe/b4c6998a509dcea1796dd05b3005c969
```
Tensor Size: 262144, Num Tensor 4, Num Threads: 1
_single_tensor_adagrad time: 0.2500 seconds
_fused_adagrad time: 0.0933 seconds
Tensor Size: 4194304, Num Tensor 32, Num Threads: 32
_single_tensor_adagrad time: 2.8819 seconds
_fused_adagrad time: 1.7591 seconds
```
## Test Plan:
```
python test_optim.py -k test_fused_matches_forloop
python test_optim.py -k test_fused_large_tensor
python test_optim.py -k test_can_load_older_state_dict
python test_optim.py -k test_grad_scaling_autocast_fused_optimizers
python test_torch.py -k test_grad_scaling_autocast_fused
python test_torch.py -k test_params_invalidated_with_grads_invalidated_between_unscale_and_step
```
Co-authored-by: Jane (Yuan) Xu <31798555+janeyx99@users.noreply.github.com >
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124905
Approved by: https://github.com/jgong5 , https://github.com/janeyx99
2024-05-16 01:11:51 +00:00
bd3cbdba2f
Revert "[optim] add fused_adagrad support for CPU device ( #124905 )"
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This reverts commit 1c3fe8403365db3cc9b75524ae742e3027b745e2.
Reverted https://github.com/pytorch/pytorch/pull/124905 on behalf of https://github.com/huydhn due to Sorry for reverting your change, but it is failing distributed multigpu test in trunk 1c3fe84033
([comment](https://github.com/pytorch/pytorch/pull/124905#issuecomment-2108777063 ))
2024-05-13 20:53:22 +00:00
1c3fe84033
[optim] add fused_adagrad support for CPU device ( #124905 )
...
Support fused_sgd_kernel support for CPU.
## Bench result:
32 core/sockets ICX
Test Scripts:
https://gist.github.com/zhuhaozhe/79e842e0a6e25d6d7fa1e4598807272c
https://gist.github.com/zhuhaozhe/b4c6998a509dcea1796dd05b3005c969
```
Tensor Size: 262144, Num Tensor 4, Num Threads: 1
_single_tensor_adagrad time: 0.2500 seconds
_fused_adagrad time: 0.0933 seconds
Tensor Size: 4194304, Num Tensor 32, Num Threads: 32
_single_tensor_adagrad time: 2.8819 seconds
_fused_adagrad time: 1.7591 seconds
```
## Test Plan:
```
python test_optim.py -k test_fused_matches_forloop
python test_optim.py -k test_fused_large_tensor
python test_optim.py -k test_can_load_older_state_dict
python test_optim.py -k test_grad_scaling_autocast_fused_optimizers
python test_torch.py -k test_grad_scaling_autocast_fused
python test_torch.py -k test_params_invalidated_with_grads_invalidated_between_unscale_and_step
```
Co-authored-by: Jane (Yuan) Xu <31798555+janeyx99@users.noreply.github.com >
Pull Request resolved: https://github.com/pytorch/pytorch/pull/124905
Approved by: https://github.com/jgong5 , https://github.com/janeyx99
2024-05-13 01:16:20 +00:00
954cba2ede
[optim/dynamo] shortcut adagrad with has_complex
( #112722 )
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Follow up to https://github.com/pytorch/pytorch/pull/110706 , it was missed as depended on another fix
Pull Request resolved: https://github.com/pytorch/pytorch/pull/112722
Approved by: https://github.com/albanD
2023-11-02 16:50:45 +00:00
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
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
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
6642e88ad2
Adding maximize flag to Adagrad
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This adds maximize to Adagrad (#68052 ) along with updates the respective tests.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75968
Approved by: https://github.com/albanD
2022-04-20 08:29:03 +00:00
dabfea8363
Optim foreach cleanup for Adagrad ( #69981 )
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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/69981
Test Plan: Imported from OSS
Reviewed By: anjali411
Differential Revision: D33767863
Pulled By: mikaylagawarecki
fbshipit-source-id: 1c99abe4ac4eb2a9eb896dff4837b539b94f68e7
(cherry picked from commit 61c28d0645046b67050efaf0d4617203126cbd30)
2022-02-09 16:52:12 +00:00
7176c92687
[optim] update step in functional and pass state_steps instead of state ( #71333 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71333
Updated
- Adagrad
- Adamax
- Adam
- AdamW
- RAdam
make multi_tensor functionals take `state_steps: List[Tensor]` instead of taking `states: List[Dict]`
make `state_steps: List[int]s -> state_steps:List[Tensor]` where each is a Singleton tensor so step can be updated within the functional
(NAdam and ASGD) were updated in separate diffs to fold their handling of state into the functionals
Test Plan: Imported from OSS
Reviewed By: anjali411
Differential Revision: D33767872
Pulled By: mikaylagawarecki
fbshipit-source-id: 9baa7cafb6375eab839917df9287c65a437891f2
(cherry picked from commit 831c02b3d0f585f61165ead368213f94b97a99ee)
2022-02-08 16:51:19 +00:00
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
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
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 896f82aa92eb7557229053a21da786f5927e64e0.
Test Plan: Imported from OSS
Reviewed By: gchanan
Differential Revision: D26232608
Pulled By: vincentqb
fbshipit-source-id: ca006baf4fb672c11c1bb003c39a29cbadb63dd3
2021-02-03 17:59:05 -08:00
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
32c355af5b
[dist_optim] introduce distributed functional optimizer ( #45221 )
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Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45221
This PR introduces a distributed functional optimizer, so that
distributed optimizer can reuse the functional optimizer APIs and
maintain their own states. This could enable the torchscript compatible
functional optimizer when using distributed optimizer, helps getting rid
of GIL and improve overall performance of training, especially distributed
model parallel training
Test Plan: Imported from OSS
Reviewed By: ailzhang
Differential Revision: D23935256
Pulled By: wanchaol
fbshipit-source-id: 59b6d77ff4693ab24a6e1cbb6740bcf614cc624a
2020-09-25 17:13:10 -07:00