# 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, Optional, Union from torch.nn import Module from torch.optim import Optimizer import pytorch_lightning as pl from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin from pytorch_lightning.utilities import GradClipAlgorithmType from pytorch_lightning.utilities.exceptions import MisconfigurationException from pytorch_lightning.utilities.model_helpers import is_overridden from pytorch_lightning.utilities.warnings import WarningCache warning_cache = WarningCache() class IPUPrecisionPlugin(PrecisionPlugin): def __init__(self, precision: int) -> None: super().__init__() self.precision = precision def backward(self, model: "pl.LightningModule", *args: Any, **kwargs: Any) -> None: if is_overridden("backward", model): warning_cache.warn( "You have overridden the `LightningModule.backward` hook but it will be ignored since IPUs handle" " the backward logic internally." ) def clip_gradients( self, optimizer: Optimizer, clip_val: Union[int, float], gradient_clip_algorithm: GradClipAlgorithmType = GradClipAlgorithmType.NORM, model: Optional[Module] = None, ) -> None: """Clips the gradients.""" if clip_val is None: return clip_val = float(clip_val) if clip_val <= 0: return raise MisconfigurationException("IPUs currently do not support clipping gradients.")