65 lines
2.6 KiB
Python
65 lines
2.6 KiB
Python
# Copyright The PyTorch Lightning team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from abc import ABC
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from typing import List, Optional, Tuple
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from torch.optim import Optimizer
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import pytorch_lightning as pl
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from pytorch_lightning.core.optimizer import _init_optimizers_and_lr_schedulers, LightningOptimizer
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from pytorch_lightning.utilities import rank_zero_deprecation
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class TrainerOptimizersMixin(ABC):
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r"""
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.. deprecated:: v1.6
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The `TrainerOptimizersMixin` was deprecated in v1.6 and will be removed in v1.8.
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"""
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def init_optimizers(self, model: Optional["pl.LightningModule"]) -> Tuple[List, List, List]:
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r"""
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.. deprecated:: v1.6
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`TrainerOptimizersMixin.init_optimizers` was deprecated in v1.6 and will be removed in v1.8.
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"""
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rank_zero_deprecation(
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"`TrainerOptimizersMixin.init_optimizers` was deprecated in v1.6 and will be removed in v1.8."
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)
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pl_module = self.lightning_module or model
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return _init_optimizers_and_lr_schedulers(pl_module)
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def convert_to_lightning_optimizers(self):
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r"""
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.. deprecated:: v1.6
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`TrainerOptimizersMixin.convert_to_lightning_optimizers` was deprecated in v1.6 and will be removed in v1.8.
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"""
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rank_zero_deprecation(
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"`TrainerOptimizersMixin.convert_to_lightning_optimizers` was deprecated in v1.6 and will be removed in "
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"v1.8."
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)
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def _convert_to_lightning_optimizer(optimizer: Optimizer) -> LightningOptimizer:
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if not isinstance(optimizer, LightningOptimizer):
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optimizer = LightningOptimizer(optimizer) # type: ignore [assignment]
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optimizer._trainer = self
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for opt_idx, opt in enumerate(self.optimizers):
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if opt == optimizer._optimizer:
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optimizer._optimizer_idx = opt_idx
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break
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return optimizer # type: ignore [return-value]
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self.strategy._cached_lightning_optimizers = { # type: ignore [assignment]
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idx: _convert_to_lightning_optimizer(opt) for idx, opt in enumerate(self.optimizers)
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}
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