Source code for lightning_lite.plugins.environments.lightning
# 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 os
import socket
from lightning_lite.plugins.environments.cluster_environment import ClusterEnvironment
from lightning_lite.utilities.rank_zero import rank_zero_only
[docs]class LightningEnvironment(ClusterEnvironment):
"""The default environment used by Lightning for a single node or free cluster (not managed).
There are two modes the Lightning environment can operate with:
1. The user only launches the main process by :code:`python train.py ...` with no additional environment variables
set. Lightning will spawn new worker processes for distributed training in the current node.
2. The user launches all processes manually or with utilities like :code:`torch.distributed.launch`.
The appropriate environment variables need to be set, and at minimum :code:`LOCAL_RANK`.
If the main address and port are not provided, the default environment will choose them
automatically. It is recommended to use this default environment for single-node distributed
training as it provides a convenient way to launch the training script.
"""
def __init__(self) -> None:
super().__init__()
self._main_port: int = -1
self._global_rank: int = 0
self._world_size: int = 1
@property
def creates_processes_externally(self) -> bool:
"""Returns whether the cluster creates the processes or not.
If at least :code:`LOCAL_RANK` is available as environment variable, Lightning assumes the user acts as the
process launcher/job scheduler and Lightning will not launch new processes.
"""
return "LOCAL_RANK" in os.environ
@property
def main_address(self) -> str:
return os.environ.get("MASTER_ADDR", "127.0.0.1")
@property
def main_port(self) -> int:
if self._main_port == -1:
self._main_port = int(os.environ.get("MASTER_PORT", find_free_network_port()))
return self._main_port
def set_world_size(self, size: int) -> None:
self._world_size = size
def set_global_rank(self, rank: int) -> None:
self._global_rank = rank
rank_zero_only.rank = rank
[docs] def node_rank(self) -> int:
group_rank = os.environ.get("GROUP_RANK", 0)
return int(os.environ.get("NODE_RANK", group_rank))
def find_free_network_port() -> int:
"""Finds a free port on localhost.
It is useful in single-node training when we don't want to connect to a real main node but have to set the
`MASTER_PORT` environment variable.
"""
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind(("", 0))
port = s.getsockname()[1]
s.close()
return port