a1f142b7ad
There is a lot hack code for v0.11.0, which makes the code hard to
upgrade to newer vLLM version. Since v0.11.0 will release soon. Let's
drop v0.11.0 support first. Then we'll upgrade to v0.11.2 soon.
- vLLM version: v0.11.0
- vLLM main:
2918c1b49c
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
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# Copyright 2023 The vLLM team.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# This file is a part of the vllm-ascend project.
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#
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import asyncio
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from typing import Any
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import openai
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import pytest
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from vllm.utils.network_utils import get_open_port
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from tests.e2e.conftest import RemoteOpenAIServer
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MODELS = ["Qwen/Qwen3-30B-A3B", "vllm-ascend/DeepSeek-V2-Lite-W8A8"]
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DATA_PARALLELS = [2]
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prompts = [
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"San Francisco is a",
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]
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api_keyword_args = {
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"max_tokens": 10,
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}
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@pytest.mark.asyncio
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("dp_size", DATA_PARALLELS)
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async def test_single_request_aclgraph(model: str, dp_size: int) -> None:
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port = get_open_port()
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env_dict = {
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"TASK_QUEUE_ENABLE": "1",
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"HCCL_OP_EXPANSION_MODE": "AIV",
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}
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if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8":
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server_args = [
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"--no-enable-prefix-caching", "--tensor-parallel-size", "1",
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"--data-parallel-size",
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str(dp_size), "--quantization", "ascend", "--max-model-len",
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"1024", "--port",
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str(port), "--trust-remote-code", "--gpu-memory-utilization", "0.9"
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]
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else:
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server_args = [
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"--no-enable-prefix-caching", "--tensor-parallel-size", "1",
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"--data-parallel-size",
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str(dp_size), "--port",
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str(port), "--trust-remote-code", "--gpu-memory-utilization", "0.9"
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]
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request_keyword_args: dict[str, Any] = {
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**api_keyword_args,
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}
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with RemoteOpenAIServer(model,
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vllm_serve_args=server_args,
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server_port=port,
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env_dict=env_dict,
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auto_port=False) as server:
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client = server.get_async_client()
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try:
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batch = await asyncio.wait_for(client.completions.create(
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model=model,
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prompt=prompts,
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**request_keyword_args,
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),
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timeout=10.0)
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except asyncio.TimeoutError:
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pytest.fail("Model did not return response within 10 seconds")
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choices: list[openai.types.CompletionChoice] = batch.choices
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assert choices[0].text, "empty response"
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