aphrodite-engine/tests/distributed/test_multi_node_assignment.py

"""Make sure ray assigns GPU workers to the correct node.
Run:
```sh
cd $APHRODITE_PATH/tests
pytest distributed/test_multi_node_assignment.py
```
"""
import os

import pytest
import ray
from ray.util.scheduling_strategies import PlacementGroupSchedulingStrategy

from aphrodite import initialize_ray_cluster
from aphrodite.common.config import ParallelConfig
from aphrodite.common.utils import get_ip
from aphrodite.executor.ray_utils import _wait_until_pg_removed

APHRODITE_MULTI_NODE = os.getenv("APHRODITE_MULTI_NODE", "0") == "1"
@pytest.mark.skipif(not APHRODITE_MULTI_NODE,
                    reason="Need at least 2 nodes to run the test.")
def test_multi_node_assignment() -> None:
    # NOTE: important to keep this class definition here
    # to let ray use cloudpickle to serialize it.
    class Actor:
        def get_ip(self):
            return get_ip()
    for _ in range(10):
        config = ParallelConfig(1, 2)
        initialize_ray_cluster(config)
        current_ip = get_ip()
        workers = []
        for bundle_id, bundle in enumerate(
                config.placement_group.bundle_specs):
            if not bundle.get("GPU", 0):
                continue
            scheduling_strategy = PlacementGroupSchedulingStrategy(
                placement_group=config.placement_group,
                placement_group_capture_child_tasks=True,
                placement_group_bundle_index=bundle_id,
            )
            worker = ray.remote(
                num_cpus=0,
                num_gpus=1,
                scheduling_strategy=scheduling_strategy,
            )(Actor).remote()
            worker_ip = ray.get(worker.get_ip.remote())
            assert worker_ip == current_ip
            workers.append(worker)
        for worker in workers:
            ray.kill(worker)
        _wait_until_pg_removed(config.placement_group)