lightning/pytorch_lightning/utilities/distributed.py

# 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 warnings
from functools import wraps

from pytorch_lightning import _logger as log


def rank_zero_only(fn):

    @wraps(fn)
    def wrapped_fn(*args, **kwargs):
        if rank_zero_only.rank == 0:
            return fn(*args, **kwargs)

    return wrapped_fn


# add the attribute to the function but don't overwrite in case Trainer has already set it
rank_zero_only.rank = getattr(rank_zero_only, 'rank', int(os.environ.get('LOCAL_RANK', 0)))


def _warn(*args, **kwargs):
    warnings.warn(*args, **kwargs)


def _info(*args, **kwargs):
    log.info(*args, **kwargs)


def _debug(*args, **kwargs):
    log.debug(*args, **kwargs)


rank_zero_debug = rank_zero_only(_debug)
rank_zero_info = rank_zero_only(_info)
rank_zero_warn = rank_zero_only(_warn)


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.
    """
    import socket
    s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
    s.bind(("", 0))
    s.listen(1)
    port = s.getsockname()[1]
    s.close()
    return port