lightning.fabric.plugins.environments.torchelastic — PyTorch Lightning 2.5.1.post0 documentation (original) (raw)

Copyright The Lightning AI 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

import torch.distributed from typing_extensions import override

from lightning.fabric.plugins.environments.cluster_environment import ClusterEnvironment from lightning.fabric.utilities.rank_zero 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/>_"""

@property
@override
def creates_processes_externally(self) -> bool:
    return True

@property
@override
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
@override
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 @override def detect() -> bool: """Returns True if the current process was launched using the torchelastic command.""" # if not available (for example on MacOS), is_torchelastic_launched is not defined return torch.distributed.is_available() and torch.distributed.is_torchelastic_launched()

[docs] @override def world_size(self) -> int: return int(os.environ["WORLD_SIZE"])

@override
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] @override def global_rank(self) -> int: return int(os.environ["RANK"])

@override
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] @override def local_rank(self) -> int: return int(os.environ["LOCAL_RANK"])

[docs] @override def node_rank(self) -> int: return int(os.environ.get("GROUP_RANK", 0))

[docs] @override def validate_settings(self, num_devices: int, num_nodes: int) -> None: if num_devices * num_nodes != self.world_size(): raise ValueError( f"You set devices={num_devices} and num_nodes={num_nodes} in Lightning, but the product" f" ({num_devices} * {num_nodes}) does not match the world size ({self.world_size()})." )