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
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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.")
def set_global_rank(self, rank: int) -> None:
log.debug(
"TorchElasticEnvironment.set_global_rank was called, but setting global rank is not allowed. Ignored."
)