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[Bugfix] Fix for multinode crash on 4 PP #6495

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merged 3 commits into from
Jul 17, 2024
Merged

[Bugfix] Fix for multinode crash on 4 PP #6495

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4e98d1f
Fix for multinode crash 4 pp
andoorve Jul 17, 2024
b5154cc
Update comment
andoorve Jul 17, 2024
d88b958
Reenable tests
andoorve Jul 17, 2024
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8 changes: 3 additions & 5 deletions tests/distributed/test_pipeline_parallel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,14 +4,12 @@


@pytest.mark.parametrize(
"TP_SIZE, PP_SIZE, EAGER_MODE, CHUNKED_PREFILL, MODEL_NAME",
[
"TP_SIZE, PP_SIZE, EAGER_MODE, CHUNKED_PREFILL, MODEL_NAME", [
(2, 2, 0, 1, "meta-llama/Meta-Llama-3-8B"),
(2, 2, 1, 0, "meta-llama/Meta-Llama-3-8B"),
(1, 3, 0, 0, "meta-llama/Meta-Llama-3-8B"),
# TODO: figure out why PP=4 tests are flaky
# (1, 4, 0, 1, "meta-llama/Meta-Llama-3-8B"),
# (1, 4, 1, 0, "meta-llama/Meta-Llama-3-8B"),
(1, 4, 0, 1, "meta-llama/Meta-Llama-3-8B"),
(1, 4, 1, 0, "meta-llama/Meta-Llama-3-8B"),
])
def test_compare_tp(TP_SIZE, PP_SIZE, EAGER_MODE, CHUNKED_PREFILL, MODEL_NAME):
pp_args = [
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14 changes: 14 additions & 0 deletions vllm/executor/ray_gpu_executor.py
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Expand Up @@ -224,13 +224,27 @@ def _init_workers_ray(self, placement_group: "PlacementGroup",
# broadcasted to.
self.non_driver_workers: List[RayWorkerWrapper] = []

tp_driver_worker_ranks = []
non_driver_worker_ranks = []
for idx, rank in enumerate(worker_ranks[1:]):
# We need to skip the driver worker, which we
# do by skipping worker_ranks[0] which is always 0.
if rank % self.parallel_config.tensor_parallel_size == 0:
self.tp_driver_workers.append(self.workers[idx])
tp_driver_worker_ranks.append(rank)
else:
self.non_driver_workers.append(self.workers[idx])
non_driver_worker_ranks.append(rank)

# Enforce rank order for correct rank to return final output.
self.tp_driver_workers = [
worker for _, worker in sorted(
zip(tp_driver_worker_ranks, self.tp_driver_workers))
]
self.non_driver_workers = [
worker for _, worker in sorted(
zip(non_driver_worker_ranks, self.non_driver_workers))
]

def _driver_execute_model(
self, execute_model_req: Optional[ExecuteModelRequest]
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