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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.
# 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.

import logging
import os
from typing import Optional

from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment
from pytorch_lightning.utilities import rank_zero_warn

log = logging.getLogger(__name__)


[docs]class TorchElasticEnvironment(ClusterEnvironment): """Environment for fault-tolerant and elastic training with `torchelastic <https://pytorch.org/elastic/>`_"""
[docs] @staticmethod def is_using_torchelastic() -> bool: """Returns ``True`` if the current process was launched using the torchelastic command.""" required_env_vars = ("RANK", "GROUP_RANK", "LOCAL_RANK", "LOCAL_WORLD_SIZE") return all(v in os.environ for v in required_env_vars)
@property def creates_processes_externally(self) -> bool: return True
[docs] def master_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']}") master_address = os.environ.get("MASTER_ADDR") return master_address
[docs] def master_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']}") port = int(os.environ.get("MASTER_PORT")) return port
[docs] def world_size(self) -> Optional[int]: world_size = os.environ.get("WORLD_SIZE") return int(world_size) if world_size is not None else world_size
def set_world_size(self, size: int) -> None: log.debug("TorchElasticEnvironment.set_world_size was called, but setting world size is not allowed. Ignored.")
[docs] def global_rank(self) -> int: return int(os.environ["RANK"])
def set_global_rank(self, rank: int) -> None: log.debug( "TorchElasticEnvironment.set_global_rank was called, but setting global rank is not allowed. Ignored." )
[docs] def local_rank(self) -> int: return int(os.environ["LOCAL_RANK"])
[docs] def node_rank(self) -> int: return int(os.environ.get("GROUP_RANK", 0))

© Copyright Copyright (c) 2018-2022, William Falcon et al... Revision ab1c2ff2.

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