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Clean up environment access in plugins (Lightning-AI#6941)
Co-authored-by: ananthsub <ananth.subramaniam@gmail.com> Co-authored-by: Kaushik B <45285388+kaushikb11@users.noreply.github.com>
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pytorch_lightning/plugins/environments/lightning_environment.py
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# 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. | ||
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import os | ||
import socket | ||
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from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment | ||
from pytorch_lightning.utilities import rank_zero_only | ||
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class LightningEnvironment(ClusterEnvironment): | ||
""" | ||
The default environment used by Lightning for a single node or free cluster (not managed). | ||
The master process must be launched by the user and Lightning will spawn new | ||
worker processes for distributed training, either in a single node or across multiple nodes. | ||
If the master 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 the most convenient way to launch the training script. | ||
""" | ||
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def __init__(self): | ||
super().__init__() | ||
self._master_port = None | ||
self._global_rank: int = 0 | ||
self._world_size: int = 1 | ||
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def creates_children(self) -> bool: | ||
return False | ||
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def master_address(self) -> str: | ||
return os.environ.get("MASTER_ADDR", "127.0.0.1") | ||
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def master_port(self) -> int: | ||
if self._master_port is None: | ||
self._master_port = os.environ.get("MASTER_PORT", find_free_network_port()) | ||
return int(self._master_port) | ||
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def world_size(self) -> int: | ||
return self._world_size | ||
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def set_world_size(self, size: int) -> None: | ||
self._world_size = size | ||
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def global_rank(self) -> int: | ||
return self._global_rank | ||
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def set_global_rank(self, rank: int) -> None: | ||
self._global_rank = rank | ||
rank_zero_only.rank = rank | ||
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def local_rank(self) -> int: | ||
return int(os.environ.get("LOCAL_RANK", 0)) | ||
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def node_rank(self) -> int: | ||
group_rank = os.environ.get("GROUP_RANK", 0) | ||
return int(os.environ.get("NODE_RANK", group_rank)) | ||
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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 master node but | ||
have to set the `MASTER_PORT` environment variable. | ||
""" | ||
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) | ||
s.bind(("", 0)) | ||
s.listen(1) | ||
port = s.getsockname()[1] | ||
s.close() | ||
return port |
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