59f11dd1cb
### What this PR does / why we need it?
fix xlite decode-only e2e test, xlite decode-only mode utilizes
aclgraph's prefill and will be affected by aclgraph, so shortened test
length.
- vLLM version: release/v0.13.0
- vLLM main:
bc0a5a0c08
Signed-off-by: changdawei1 <changdawei3@huawei.com>
Co-authored-by: changdawei1 <changdawei3@huawei.com>
127 lines
4.6 KiB
Python
127 lines
4.6 KiB
Python
#
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# 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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#
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"""
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Compare the outputs of vLLM with and without xlite.
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Run `pytest tests/e2e/singlecard/test_xlite.py`.
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"""
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import os
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import pytest
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from tests.e2e.conftest import VllmRunner
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from tests.e2e.model_utils import check_outputs_equal
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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os.environ["VLLM_ASCEND_ENABLE_NZ"] = "2"
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MODELS = [
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"Qwen/Qwen3-0.6B",
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]
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("max_tokens", [15])
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def test_models_with_xlite_decode_only(
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model: str,
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max_tokens: int,
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) -> None:
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prompts = [
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"Hello, my name is", "The president of the United States is",
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"The capital of France is", "The future of AI is"
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]
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with VllmRunner(
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model,
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block_size=128,
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max_model_len=1024,
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additional_config={"xlite_graph_config": {
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"enabled": True
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}},
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) as runner:
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vllm_xlite_outputs_list = runner.generate_greedy(prompts,
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max_tokens=max_tokens)
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for idx in range(len(vllm_xlite_outputs_list)):
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vllm_xlite_outputs_list[idx] = ([0],
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vllm_xlite_outputs_list[idx][1])
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vllm_xlite_answers = [
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"Hello, my name is Lina. I'm a 22-year-old student from China.",
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'The president of the United States is the same as the president of the United Nations. This is because the president',
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'The capital of France is Paris. The capital of Italy is Rome. The capital of Spain is Madrid',
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'The future of AI is not just a technological challenge but a profound transformation of how we live, work'
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]
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vllm_eager_outputs_list = []
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vllm_eager_outputs_list = ([([0], answer)
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for answer in vllm_xlite_answers])
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check_outputs_equal(
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outputs_0_lst=vllm_eager_outputs_list,
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outputs_1_lst=vllm_xlite_outputs_list,
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name_0="vllm_eager_outputs",
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name_1="vllm_xlite_outputs",
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)
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@pytest.mark.parametrize("model", MODELS)
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@pytest.mark.parametrize("max_tokens", [32])
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def test_models_with_xlite_full_mode(
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model: str,
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max_tokens: int,
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) -> None:
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prompts = [
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"Hello, my name is", "The president of the United States is",
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"The capital of France is", "The future of AI is"
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]
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with VllmRunner(
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model,
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block_size=128,
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max_model_len=1024,
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additional_config={
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"xlite_graph_config": {
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"enabled": True,
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"full_mode": True
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}
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},
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) as runner:
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vllm_xlite_outputs_list = runner.generate_greedy(prompts,
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max_tokens=max_tokens)
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for idx in range(len(vllm_xlite_outputs_list)):
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vllm_xlite_outputs_list[idx] = ([0],
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vllm_xlite_outputs_list[idx][1])
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vllm_xlite_answers = [
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"Hello, my name is Lina. I'm a 22-year-old student from China. I'm interested in studying in the US. I'm looking for a job in the",
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'The president of the United States is the same as the president of the United Nations. This is because the president of the United States is the same as the president of the United Nations. The president',
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'The capital of France is Paris. The capital of Italy is Rome. The capital of Spain is Madrid. The capital of China is Beijing. The capital of Japan is Tokyo. The capital',
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"The future of AI is not just about the technology itself, but about how we use it to solve real-world problems. As AI continues to evolve, it's important to consider the ethical"
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]
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vllm_eager_outputs_list = []
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vllm_eager_outputs_list = ([([0], answer)
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for answer in vllm_xlite_answers])
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check_outputs_equal(
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outputs_0_lst=vllm_eager_outputs_list,
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outputs_1_lst=vllm_xlite_outputs_list,
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name_0="vllm_eager_outputs",
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name_1="vllm_xlite_outputs",
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)
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