e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
119 lines
3.5 KiB
Python
119 lines
3.5 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import multiprocessing
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import random
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import time
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from typing import List
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import numpy as np
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import torch.distributed as dist
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from vllm.distributed.device_communicators.shm_broadcast import MessageQueue
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from vllm.distributed.utils import StatelessProcessGroup
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from vllm.utils import get_ip, get_open_port, update_environment_variables
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def get_arrays(n: int, seed: int = 0) -> List[np.ndarray]:
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np.random.seed(seed)
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sizes = np.random.randint(1, 10_000, n)
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# on average, each array will have 5k elements
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# with int64, each array will have 40kb
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return [np.random.randint(1, 100, i) for i in sizes]
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def distributed_run(fn, world_size):
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number_of_processes = world_size
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processes = []
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for i in range(number_of_processes):
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env = {}
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env['RANK'] = str(i)
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env['LOCAL_RANK'] = str(i)
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env['WORLD_SIZE'] = str(number_of_processes)
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env['LOCAL_WORLD_SIZE'] = str(number_of_processes)
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env['MASTER_ADDR'] = 'localhost'
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env['MASTER_PORT'] = '12345'
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p = multiprocessing.Process(target=fn, args=(env, ))
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processes.append(p)
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p.start()
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for p in processes:
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p.join()
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for p in processes:
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assert p.exitcode == 0
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def worker_fn_wrapper(fn):
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# `multiprocessing.Process` cannot accept environment variables directly
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# so we need to pass the environment variables as arguments
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# and update the environment variables in the function
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def wrapped_fn(env):
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update_environment_variables(env)
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dist.init_process_group(backend="gloo")
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fn()
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return wrapped_fn
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@worker_fn_wrapper
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def worker_fn():
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rank = dist.get_rank()
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if rank == 0:
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port = get_open_port()
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ip = get_ip()
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dist.broadcast_object_list([ip, port], src=0)
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else:
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recv = [None, None]
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dist.broadcast_object_list(recv, src=0)
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ip, port = recv
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stateless_pg = StatelessProcessGroup.create(ip, port, rank,
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dist.get_world_size())
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for pg in [dist.group.WORLD, stateless_pg]:
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writer_rank = 2
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broadcaster = MessageQueue.create_from_process_group(
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pg, 40 * 1024, 2, writer_rank)
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if rank == writer_rank:
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seed = random.randint(0, 1000)
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dist.broadcast_object_list([seed], writer_rank)
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else:
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recv = [None]
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dist.broadcast_object_list(recv, writer_rank)
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seed = recv[0] # type: ignore
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if pg == dist.group.WORLD:
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dist.barrier()
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else:
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pg.barrier()
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# in case we find a race condition
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# print the seed so that we can reproduce the error
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print(f"Rank {rank} got seed {seed}")
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# test broadcasting with about 400MB of data
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N = 10_000
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if rank == writer_rank:
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arrs = get_arrays(N, seed)
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for x in arrs:
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broadcaster.broadcast_object(x)
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time.sleep(random.random() / 1000)
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else:
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arrs = get_arrays(N, seed)
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for x in arrs:
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y = broadcaster.broadcast_object(None)
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assert np.array_equal(x, y)
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time.sleep(random.random() / 1000)
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if pg == dist.group.WORLD:
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dist.barrier()
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print("torch distributed passed the test!")
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else:
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pg.barrier()
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print("StatelessProcessGroup passed the test!")
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def test_shm_broadcast():
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distributed_run(worker_fn, 4)
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