gloo_init_parallel_env¶

paddle.distributed. gloo_init_parallel_env ( rank_id, rank_num, server_endpoint ) [source]

Initialize parallel environment with gloo for cpu only.

Parameters

• rank_id（int (-) –

• rank; (required) - the index of current) –

• rank_num (-) –

• server_endpoint (-) – port format;

Returns

None

Examples

>>> import paddle
>>> import multiprocessing
>>> from contextlib import closing
>>> import socket

>>> port_set = set()

>>> def find_free_port():
...     def _free_port():
...         with closing(socket.socket(socket.AF_INET,
...             socket.SOCK_STREAM)) as s:
...             s.bind(('', 0))
...             return s.getsockname()[1]
...     while True:
...         port = _free_port()
...         if port not in port_set:
...             port_set.add(port)
...             return port

>>> def test_gloo_init(id, rank_num, server_endpoint):
...     paddle.distributed.gloo_init_parallel_env(
...         id, rank_num, server_endpoint)

>>> def test_gloo_init_with_multiprocess(num_of_ranks):
...     jobs = []
...     server_endpoint = "127.0.0.1:%s" % (find_free_port())
...     for id in range(num_of_ranks):
...         p = multiprocessing.Process(
...             target=test_gloo_init,
...             args=(id, num_of_ranks, server_endpoint))
...         jobs.append(p)
...         p.start()
...     for proc in jobs:
...         proc.join()

>>> if __name__ == '__main__':
...     # Arg: number of ranks (processes)
...     test_gloo_init_with_multiprocess(2)