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125 lines
3.5 KiB
Python
125 lines
3.5 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 asyncio
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import os
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from typing import Any, Callable, Optional, Union
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import pytest
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from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
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from vllm.sampling_params import SamplingParams
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from vllm.v1.engine.async_llm import AsyncLLM
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from vllm.v1.engine.llm_engine import LLMEngine
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from vllm.v1.executor.multiproc_executor import MultiprocExecutor
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class Mock: ...
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class CustomMultiprocExecutor(MultiprocExecutor):
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def collective_rpc(
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self,
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method: Union[str, Callable],
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timeout: Optional[float] = None,
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args: tuple = (),
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kwargs: Optional[dict] = None,
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non_block: bool = False,
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unique_reply_rank: Optional[int] = None,
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) -> list[Any]:
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# Drop marker to show that this was run
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with open(".marker", "w"):
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...
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return super().collective_rpc(method, timeout, args, kwargs)
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CustomMultiprocExecutorAsync = CustomMultiprocExecutor
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MODEL = "Qwen/Qwen3-0.6B"
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def test_custom_executor_type_checking():
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with pytest.raises(ValueError):
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engine_args = EngineArgs(
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model=MODEL,
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gpu_memory_utilization=0.2,
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max_model_len=8192,
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distributed_executor_backend=Mock,
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)
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LLMEngine.from_engine_args(engine_args)
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with pytest.raises(ValueError):
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engine_args = AsyncEngineArgs(
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model=MODEL,
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gpu_memory_utilization=0.2,
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max_model_len=8192,
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distributed_executor_backend=Mock,
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)
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AsyncLLM.from_engine_args(engine_args)
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@pytest.mark.parametrize(
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"distributed_executor_backend",
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[
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CustomMultiprocExecutor,
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"tests.v1.executor.test_executor.CustomMultiprocExecutor",
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],
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)
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def test_custom_executor(distributed_executor_backend, tmp_path):
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cwd = os.path.abspath(".")
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os.chdir(tmp_path)
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try:
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assert not os.path.exists(".marker")
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engine_args = EngineArgs(
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model=MODEL,
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gpu_memory_utilization=0.2,
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max_model_len=8192,
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distributed_executor_backend=distributed_executor_backend,
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enforce_eager=True, # reduce test time
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)
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engine = LLMEngine.from_engine_args(engine_args)
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sampling_params = SamplingParams(max_tokens=1)
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engine.add_request("0", "foo", sampling_params)
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engine.step()
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assert os.path.exists(".marker")
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finally:
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os.chdir(cwd)
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@pytest.mark.parametrize(
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"distributed_executor_backend",
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[
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CustomMultiprocExecutorAsync,
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"tests.v1.executor.test_executor.CustomMultiprocExecutorAsync",
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],
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)
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def test_custom_executor_async(distributed_executor_backend, tmp_path):
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cwd = os.path.abspath(".")
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os.chdir(tmp_path)
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try:
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assert not os.path.exists(".marker")
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engine_args = AsyncEngineArgs(
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model=MODEL,
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gpu_memory_utilization=0.2,
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max_model_len=8192,
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distributed_executor_backend=distributed_executor_backend,
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enforce_eager=True, # reduce test time
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)
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engine = AsyncLLM.from_engine_args(engine_args)
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sampling_params = SamplingParams(max_tokens=1)
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async def t():
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stream = engine.generate(
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request_id="0", prompt="foo", sampling_params=sampling_params
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)
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async for x in stream:
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...
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asyncio.run(t())
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assert os.path.exists(".marker")
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finally:
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os.chdir(cwd)
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