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