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Convert formatting to use ruff instead of yapf + isort (#26247)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions
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67
tests/distributed/test_utils.py
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@@ -10,21 +10,22 @@ import torch
import vllm.envs as envs
from vllm.distributed.device_communicators.pynccl import PyNcclCommunicator
from vllm.distributed.utils import StatelessProcessGroup
from vllm.utils import (cuda_device_count_stateless, get_open_port,
update_environment_variables)
from vllm.utils import (
cuda_device_count_stateless,
get_open_port,
update_environment_variables,
)
from ..utils import multi_gpu_test
@ray.remote
class _CUDADeviceCountStatelessTestActor:
def get_count(self):
return cuda_device_count_stateless()
def set_cuda_visible_devices(self, cuda_visible_devices: str):
update_environment_variables(
{"CUDA_VISIBLE_DEVICES": cuda_visible_devices})
update_environment_variables({"CUDA_VISIBLE_DEVICES": cuda_visible_devices})
def get_cuda_visible_devices(self):
return envs.CUDA_VISIBLE_DEVICES
@@ -34,10 +35,9 @@ def test_cuda_device_count_stateless():
"""Test that cuda_device_count_stateless changes return value if
CUDA_VISIBLE_DEVICES is changed."""
actor = _CUDADeviceCountStatelessTestActor.options( # type: ignore
num_gpus=2).remote()
assert len(
sorted(ray.get(
actor.get_cuda_visible_devices.remote()).split(","))) == 2
num_gpus=2
).remote()
assert len(sorted(ray.get(actor.get_cuda_visible_devices.remote()).split(","))) == 2
assert ray.get(actor.get_count.remote()) == 2
ray.get(actor.set_cuda_visible_devices.remote("0"))
assert ray.get(actor.get_count.remote()) == 1
@@ -46,15 +46,13 @@ def test_cuda_device_count_stateless():
def cpu_worker(rank, WORLD_SIZE, port1, port2):
pg1 = StatelessProcessGroup.create(host="127.0.0.1",
port=port1,
rank=rank,
world_size=WORLD_SIZE)
pg1 = StatelessProcessGroup.create(
host="127.0.0.1", port=port1, rank=rank, world_size=WORLD_SIZE
)
if rank <= 2:
pg2 = StatelessProcessGroup.create(host="127.0.0.1",
port=port2,
rank=rank,
world_size=3)
pg2 = StatelessProcessGroup.create(
host="127.0.0.1", port=port2, rank=rank, world_size=3
)
data = torch.tensor([rank])
data = pg1.broadcast_obj(data, src=2)
assert data.item() == 2
@@ -68,16 +66,14 @@ def cpu_worker(rank, WORLD_SIZE, port1, port2):
def gpu_worker(rank, WORLD_SIZE, port1, port2):
torch.cuda.set_device(rank)
pg1 = StatelessProcessGroup.create(host="127.0.0.1",
port=port1,
rank=rank,
world_size=WORLD_SIZE)
pg1 = StatelessProcessGroup.create(
host="127.0.0.1", port=port1, rank=rank, world_size=WORLD_SIZE
)
pynccl1 = PyNcclCommunicator(pg1, device=rank)
if rank <= 2:
pg2 = StatelessProcessGroup.create(host="127.0.0.1",
port=port2,
rank=rank,
world_size=3)
pg2 = StatelessProcessGroup.create(
host="127.0.0.1", port=port2, rank=rank, world_size=3
)
pynccl2 = PyNcclCommunicator(pg2, device=rank)
data = torch.tensor([rank]).cuda()
pynccl1.all_reduce(data)
@@ -96,10 +92,9 @@ def gpu_worker(rank, WORLD_SIZE, port1, port2):
def broadcast_worker(rank, WORLD_SIZE, port1, port2):
pg1 = StatelessProcessGroup.create(host="127.0.0.1",
port=port1,
rank=rank,
world_size=WORLD_SIZE)
pg1 = StatelessProcessGroup.create(
host="127.0.0.1", port=port1, rank=rank, world_size=WORLD_SIZE
)
if rank == 2:
pg1.broadcast_obj("secret", src=2)
else:
@@ -109,10 +104,9 @@ def broadcast_worker(rank, WORLD_SIZE, port1, port2):
def allgather_worker(rank, WORLD_SIZE, port1, port2):
pg1 = StatelessProcessGroup.create(host="127.0.0.1",
port=port1,
rank=rank,
world_size=WORLD_SIZE)
pg1 = StatelessProcessGroup.create(
host="127.0.0.1", port=port1, rank=rank, world_size=WORLD_SIZE
)
data = pg1.all_gather_obj(rank)
assert data == list(range(WORLD_SIZE))
pg1.barrier()
@@ -121,7 +115,8 @@ def allgather_worker(rank, WORLD_SIZE, port1, port2):
@pytest.mark.skip(reason="This test is flaky and prone to hang.")
@multi_gpu_test(num_gpus=4)
@pytest.mark.parametrize(
"worker", [cpu_worker, gpu_worker, broadcast_worker, allgather_worker])
"worker", [cpu_worker, gpu_worker, broadcast_worker, allgather_worker]
)
def test_stateless_process_group(worker):
port1 = get_open_port()
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
@@ -129,12 +124,14 @@ def test_stateless_process_group(worker):
port2 = get_open_port()
WORLD_SIZE = 4
from multiprocessing import get_context
ctx = get_context("fork")
processes = []
for i in range(WORLD_SIZE):
rank = i
processes.append(
ctx.Process(target=worker, args=(rank, WORLD_SIZE, port1, port2)))
ctx.Process(target=worker, args=(rank, WORLD_SIZE, port1, port2))
)
for p in processes:
p.start()
for p in processes: