lightning/pytorch_lightning/trainer/optimizers.py

65 lines
2.6 KiB
Python

# 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 abc import ABC
from typing import List, Optional, Tuple
from torch.optim import Optimizer
import pytorch_lightning as pl
from pytorch_lightning.core.optimizer import _init_optimizers_and_lr_schedulers, LightningOptimizer
from pytorch_lightning.utilities import rank_zero_deprecation
class TrainerOptimizersMixin(ABC):
r"""
.. deprecated:: v1.6
The `TrainerOptimizersMixin` was deprecated in v1.6 and will be removed in v1.8.
"""
def init_optimizers(self, model: Optional["pl.LightningModule"]) -> Tuple[List, List, List]:
r"""
.. deprecated:: v1.6
`TrainerOptimizersMixin.init_optimizers` was deprecated in v1.6 and will be removed in v1.8.
"""
rank_zero_deprecation(
"`TrainerOptimizersMixin.init_optimizers` was deprecated in v1.6 and will be removed in v1.8."
)
pl_module = self.lightning_module or model
return _init_optimizers_and_lr_schedulers(pl_module)
def convert_to_lightning_optimizers(self):
r"""
.. deprecated:: v1.6
`TrainerOptimizersMixin.convert_to_lightning_optimizers` was deprecated in v1.6 and will be removed in v1.8.
"""
rank_zero_deprecation(
"`TrainerOptimizersMixin.convert_to_lightning_optimizers` was deprecated in v1.6 and will be removed in "
"v1.8."
)
def _convert_to_lightning_optimizer(optimizer: Optimizer) -> LightningOptimizer:
if not isinstance(optimizer, LightningOptimizer):
optimizer = LightningOptimizer(optimizer) # type: ignore [assignment]
optimizer._trainer = self
for opt_idx, opt in enumerate(self.optimizers):
if opt == optimizer._optimizer:
optimizer._optimizer_idx = opt_idx
break
return optimizer # type: ignore [return-value]
self.strategy._cached_lightning_optimizers = { # type: ignore [assignment]
idx: _convert_to_lightning_optimizer(opt) for idx, opt in enumerate(self.optimizers)
}