100 lines
3.4 KiB
Python
100 lines
3.4 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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"""Utilities that can be used for calling functions on a particular rank."""
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import logging
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import os
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import warnings
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from functools import partial, wraps
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from platform import python_version
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from typing import Any, Callable, Optional, Union
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log = logging.getLogger(__name__)
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def rank_zero_only(fn: Callable) -> Callable:
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"""Function that can be used as a decorator to enable a function/method being called only on rank 0."""
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@wraps(fn)
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def wrapped_fn(*args: Any, **kwargs: Any) -> Optional[Any]:
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if rank_zero_only.rank == 0:
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return fn(*args, **kwargs)
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return None
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return wrapped_fn
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# TODO: this should be part of the cluster environment
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def _get_rank() -> int:
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# SLURM_PROCID can be set even if SLURM is not managing the multiprocessing,
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# therefore LOCAL_RANK needs to be checked first
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rank_keys = ("RANK", "LOCAL_RANK", "SLURM_PROCID")
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for key in rank_keys:
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rank = os.environ.get(key)
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if rank is not None:
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return int(rank)
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return 0
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# add the attribute to the function but don't overwrite in case Trainer has already set it
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rank_zero_only.rank = getattr(rank_zero_only, "rank", _get_rank())
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def _info(*args: Any, stacklevel: int = 2, **kwargs: Any) -> None:
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if python_version() >= "3.8.0":
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kwargs["stacklevel"] = stacklevel
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log.info(*args, **kwargs)
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def _debug(*args: Any, stacklevel: int = 2, **kwargs: Any) -> None:
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if python_version() >= "3.8.0":
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kwargs["stacklevel"] = stacklevel
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log.debug(*args, **kwargs)
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@rank_zero_only
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def rank_zero_debug(*args: Any, stacklevel: int = 4, **kwargs: Any) -> None:
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"""Function used to log debug-level messages only on rank 0."""
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_debug(*args, stacklevel=stacklevel, **kwargs)
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@rank_zero_only
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def rank_zero_info(*args: Any, stacklevel: int = 4, **kwargs: Any) -> None:
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"""Function used to log info-level messages only on rank 0."""
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_info(*args, stacklevel=stacklevel, **kwargs)
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def _warn(message: Union[str, Warning], stacklevel: int = 2, **kwargs: Any) -> None:
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if type(stacklevel) is type and issubclass(stacklevel, Warning):
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rank_zero_deprecation(
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"Support for passing the warning category positionally is deprecated in v1.6 and will be removed in v1.8"
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f" Please, use `category={stacklevel.__name__}`."
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)
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kwargs["category"] = stacklevel
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stacklevel = kwargs.pop("stacklevel", 2)
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warnings.warn(message, stacklevel=stacklevel, **kwargs)
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@rank_zero_only
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def rank_zero_warn(message: Union[str, Warning], stacklevel: int = 4, **kwargs: Any) -> None:
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"""Function used to log warn-level messages only on rank 0."""
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_warn(message, stacklevel=stacklevel, **kwargs)
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class LightningDeprecationWarning(DeprecationWarning):
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"""Deprecation warnings raised by PyTorch Lightning."""
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rank_zero_deprecation = partial(rank_zero_warn, category=LightningDeprecationWarning)
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