-
Notifications
You must be signed in to change notification settings - Fork 3.4k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Co-authored-by: HELSON <[email protected]> Co-authored-by: rohitgr7 <[email protected]> Co-authored-by: otaj <[email protected]> Co-authored-by: Carlos Mocholí <[email protected]>
- Loading branch information
5 people
authored
Oct 11, 2022
1 parent
6f16e46
commit 2fef6d9
Showing
16 changed files
with
933 additions
and
8 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,90 @@ | ||
| # Copyright The PyTorch Lightning team. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| from typing import Any, Callable, Optional, Union | ||
|
|
||
| from lightning_utilities.core.rank_zero import WarningCache | ||
| from torch import Tensor | ||
| from torch.optim import Optimizer | ||
|
|
||
| import pytorch_lightning as pl | ||
| from lightning_lite.utilities.types import Steppable | ||
| from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin | ||
| from pytorch_lightning.utilities.enums import PrecisionType | ||
|
|
||
| warning_cache = WarningCache() | ||
|
|
||
|
|
||
| class ColossalAIPrecisionPlugin(PrecisionPlugin): | ||
| """Precision plugin for ColossalAI integration. | ||
| Args: | ||
| precision: Half precision (16). | ||
| Raises: | ||
| ValueError: | ||
| If precison is not 16. | ||
| """ | ||
|
|
||
| def __init__(self, precision: Union[str, int] = 16) -> None: | ||
| if not (precision == PrecisionType.HALF): | ||
| raise ValueError( | ||
| f"`Trainer(strategy='colossalai', precision={precision!r})` is not supported." | ||
| " Consider setting `precision=16`." | ||
| ) | ||
| super().__init__() | ||
| self.precision = precision | ||
|
|
||
| def backward( # type: ignore[override] | ||
| self, | ||
| tensor: Tensor, | ||
| model: "pl.LightningModule", | ||
| optimizer: Optional[Steppable], | ||
| optimizer_idx: Optional[int], | ||
| *args: Any, | ||
| **kwargs: Any, | ||
| ) -> None: | ||
| assert optimizer is not None | ||
| optimizer.backward(tensor) | ||
|
|
||
| def clip_grad_by_norm(self, optimizer: Optimizer, clip_val: Union[int, float]) -> None: | ||
| optimizer.clip_grad_norm(None, clip_val) | ||
|
|
||
| def clip_grad_by_value(self, optimizer: Optimizer, clip_val: Union[int, float]) -> None: | ||
| raise NotImplementedError("`clip_grad_by_value` is not supported by `ColossalAI`") | ||
|
|
||
| def optimizer_step( # type: ignore[override] | ||
| self, | ||
| optimizer: Steppable, | ||
| model: "pl.LightningModule", | ||
| optimizer_idx: int, | ||
| closure: Callable[[], Any], | ||
| **kwargs: Any, | ||
| ) -> Any: | ||
| closure_result = closure() | ||
| self._after_closure(model, optimizer, optimizer_idx) | ||
| skipped_backward = closure_result is None | ||
| if isinstance(model, pl.LightningModule) and model.automatic_optimization and skipped_backward: | ||
| raise ValueError( | ||
| "Skipping backward by returning `None` from your `training_step` is not supported by `ColossalAI`." | ||
| ) | ||
| optimizer.step() | ||
|
|
||
| def _track_grad_norm(self, trainer: "pl.Trainer") -> None: | ||
| if trainer.track_grad_norm == -1: | ||
| return | ||
| # the gradients are not available in the model due to gradient partitioning in zero stage >= 2 | ||
| warning_cache.warn( | ||
| f"You set `Trainer(track_grad_norm={trainer.track_grad_norm!r})' but this is not supported for ColossalAI." | ||
| " The setting will be ignored." | ||
| ) |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.