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43721bc67f
Signed-off-by: Tahsin Tunan <tahsintunan@gmail.com> Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com> Co-authored-by: Nick Hill <nhill@redhat.com> Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import pytest
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import torch
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from vllm import LLM
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from ...utils import create_new_process_for_each_test
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@pytest.mark.parametrize("tp_size", [1, 2])
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@pytest.mark.parametrize("backend", ["mp", "ray"])
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@create_new_process_for_each_test()
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def test_collective_rpc(tp_size, backend, monkeypatch):
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if torch.cuda.device_count() < tp_size:
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pytest.skip(f"Not enough GPUs for tensor parallelism {tp_size}")
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if tp_size == 1 and backend == "ray":
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pytest.skip("Skip duplicate test case")
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if tp_size == 1:
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backend = None
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# intentionally define the method and class in the test function,
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# to test if they can be serialized and sent to the workers
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def echo_rank(self):
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return self.rank
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monkeypatch.setenv("VLLM_ALLOW_INSECURE_SERIALIZATION", "1")
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llm = LLM(
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model="hmellor/tiny-random-LlamaForCausalLM",
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enforce_eager=True,
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load_format="dummy",
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tensor_parallel_size=tp_size,
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distributed_executor_backend=backend,
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)
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assert llm.collective_rpc(echo_rank) == list(range(tp_size))
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