Source code for pytorch_lightning.plugins.environments.torchelastic_environment
# 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.
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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# See the License for the specific language governing permissions and
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import logging
import os
import torch.distributed
from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment
from pytorch_lightning.utilities.imports import _TORCH_GREATER_EQUAL_1_9_1
from pytorch_lightning.utilities.rank_zero import rank_zero_deprecation, rank_zero_warn
log = logging.getLogger(__name__)
[docs]class TorchElasticEnvironment(ClusterEnvironment):
"""Environment for fault-tolerant and elastic training with `torchelastic <https://pytorch.org/elastic/>`_"""
def __init__(self) -> None:
super().__init__()
# TODO: remove in 1.7
if hasattr(self, "is_using_torchelastic") and callable(self.is_using_torchelastic):
rank_zero_deprecation(
f"`{self.__class__.__name__}.is_using_torchelastic` has been deprecated in v1.6 and will be removed in"
" v1.7. Implement the static method `detect()` instead (do not forget to add the `@staticmethod`"
" decorator)."
)
@property
def creates_processes_externally(self) -> bool:
return True
@property
def main_address(self) -> str:
if "MASTER_ADDR" not in os.environ:
rank_zero_warn("MASTER_ADDR environment variable is not defined. Set as localhost")
os.environ["MASTER_ADDR"] = "127.0.0.1"
log.debug(f"MASTER_ADDR: {os.environ['MASTER_ADDR']}")
return os.environ["MASTER_ADDR"]
@property
def main_port(self) -> int:
if "MASTER_PORT" not in os.environ:
rank_zero_warn("MASTER_PORT environment variable is not defined. Set as 12910")
os.environ["MASTER_PORT"] = "12910"
log.debug(f"MASTER_PORT: {os.environ['MASTER_PORT']}")
return int(os.environ["MASTER_PORT"])
[docs] @staticmethod
def detect() -> bool:
"""Returns ``True`` if the current process was launched using the torchelastic command."""
if _TORCH_GREATER_EQUAL_1_9_1:
# if not available (for example on MacOS), `is_torchelastic_launched` is not defined
return torch.distributed.is_available() and torch.distributed.is_torchelastic_launched()
required_env_vars = {"RANK", "GROUP_RANK", "LOCAL_RANK", "LOCAL_WORLD_SIZE"}
return required_env_vars.issubset(os.environ.keys())
def set_world_size(self, size: int) -> None:
log.debug("TorchElasticEnvironment.set_world_size was called, but setting world size is not allowed. Ignored.")
def set_global_rank(self, rank: int) -> None:
log.debug(
"TorchElasticEnvironment.set_global_rank was called, but setting global rank is not allowed. Ignored."
)