56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
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# 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 Optional, Union
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from pytorch_lightning.plugins.precision.precision_plugin import PrecisionPlugin
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from pytorch_lightning.utilities.exceptions import MisconfigurationException
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from pytorch_lightning.utilities.imports import _HPU_AVAILABLE
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if _HPU_AVAILABLE:
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from habana_frameworks.torch.hpex import hmp
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class HPUPrecisionPlugin(PrecisionPlugin):
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"""Plugin that enables bfloat/half support on HPUs.
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Args:
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precision: The precision to use.
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opt_level: Choose optimization level for hmp.
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bf16_file_path: Path to bf16 ops list in hmp O1 mode.
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fp32_file_path: Path to fp32 ops list in hmp O1 mode.
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verbose: Enable verbose mode for hmp.
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"""
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def __init__(
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self,
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precision: Union[str, int],
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opt_level: str = "O2",
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bf16_file_path: Optional[str] = None,
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fp32_file_path: Optional[str] = None,
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verbose: bool = False,
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) -> None:
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if not _HPU_AVAILABLE:
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raise MisconfigurationException("HPU precision plugin requires HPU devices.")
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supported_precision_values = (16, 32, "bf16")
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if precision not in supported_precision_values:
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raise ValueError(
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f"`Trainer(accelerator='hpu', precision={precision!r})` is not supported."
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f" `precision` must be one of: {supported_precision_values}."
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)
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super().__init__()
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self.precision = precision
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hmp.convert(
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opt_level=opt_level, bf16_file_path=bf16_file_path, fp32_file_path=fp32_file_path, isVerbose=verbose
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)
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