[E2E] Refactor the e2e testcases. (#4789)
### What this PR does / why we need it?
Refactor the e2e testcases.
- tests/e2e/multicard/test_weight_loader.py: Remove the unused code.
- tests/e2e/singlecard/multi-modal/test_internvl.py: Move to accuracy
test.
- tests/e2e/singlecard/test_aclgraph.py: Rename the file.
- tests/e2e/singlecard/test_embedding_aclgraph.py : Combine with
tests/e2e/singlecard/test_bge_model.py
- tests/e2e/singlecard/test_completion_with_prompt_embeds.py: Delete
eager mode and modify model to Qwen3-0.6B
- tests/e2e/singlecard/test_quantization.py: Modify model to
Qwen3-0.6B-W8A8
- tests/e2e/singlecard/test_vlm.py: Modify model to Qwen3-VL-8B
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: menogrey <1299267905@qq.com>
This commit is contained in:
zhangyiming
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tests/e2e/singlecard/test_aclgraph_accuracy.py
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tests/e2e/singlecard/test_aclgraph_accuracy.py
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#
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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 aclgraph.
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Run `pytest tests/compile/test_aclgraph_accuracy.py`.
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"""
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import os
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import pytest
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from vllm import SamplingParams
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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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MODELS = [
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"Qwen/Qwen3-0.6B",
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"vllm-ascend/DeepSeek-V2-Lite-W8A8",
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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_output_between_eager_and_aclgraph(
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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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sampling_params = SamplingParams(max_tokens=max_tokens, temperature=0.0)
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if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8":
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with VllmRunner(
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model,
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max_model_len=1024,
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enforce_eager=False,
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quantization="ascend",
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) as runner:
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vllm_aclgraph_outputs = runner.model.generate(
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prompts, sampling_params)
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with VllmRunner(
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model,
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max_model_len=1024,
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enforce_eager=True,
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quantization="ascend",
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) as runner:
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vllm_eager_outputs = runner.model.generate(prompts,
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sampling_params)
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else:
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with VllmRunner(
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model,
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max_model_len=1024,
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enforce_eager=False,
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) as runner:
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vllm_aclgraph_outputs = runner.model.generate(
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prompts, sampling_params)
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with VllmRunner(
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model,
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max_model_len=1024,
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enforce_eager=True,
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) as runner:
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vllm_eager_outputs = runner.model.generate(prompts,
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sampling_params)
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vllm_aclgraph_outputs_list = []
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for output in vllm_aclgraph_outputs:
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vllm_aclgraph_outputs_list.append(
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(output.outputs[0].index, output.outputs[0].text))
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vllm_eager_outputs_list = []
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for output in vllm_eager_outputs:
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vllm_eager_outputs_list.append(
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(output.outputs[0].index, output.outputs[0].text))
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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_aclgraph_outputs_list,
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name_0="vllm_eager_outputs",
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name_1="vllm_aclgraph_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_output_between_eager_and_full_decode_only(
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model: str,
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max_tokens: int,
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) -> None:
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if 'HCCL_OP_EXPANSION_MODE' in os.environ:
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del os.environ['HCCL_OP_EXPANSION_MODE']
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# NOTE: Randomly fill the prompt with the requested amount for
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# the specified capture shape to prevent accuracy issues caused by padding
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prompts = [
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('Solve the following math problem step by step.'
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'The last line of your response should be of the form Answer: '
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'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
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'In triangle $ABC$, $\\sin \\angle A = \\frac{4}{5}$ and $\\angle A < 90^\\circ$. Let $D$'
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'be a point outside triangle $ABC$ such that $\\angle BAD = \\angle DAC$,'
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'$\\angle BDC = 90^\\circ$. Suppose $AD = 1$ and $\\frac{BD}{CD} = \\frac{3}{2}$.'
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'If $AB + AC$ can be expressed in the form $\\frac{a\\sqrt{b}}{c}$,'
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'where $a, b, c$ are pairwise relatively prime integers, find $a + b + c$.'
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),
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('Solve the following math problem step by step.'
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'The last line of your response should be of the form Answer: '
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'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
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'Let $ABCD$ be a unit square in the plane. Points $X$ and $Y$ are chosen'
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'independently and uniformly at random on the perimeter of $ABCD$.'
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'If the expected value of the area of triangle $\\triangle AXY$'
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'can be expressed as $\\frac{m}{n}$, for relatively prime positive'
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'integers $m$ and $n$, compute $m+n$.'),
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('Solve the following math problem step by step.'
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'The last line of your response should be of the form Answer: '
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'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
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'Let $a, b, c$ be distinct numbers such that the equations $x^2 + ax + 1 = 0$'
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'and $x^2 + bx + c = 0$ have a common real root, and the equations $x^2 + x + a = 0$'
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'and $x^2 + cx + b = 0$ also have a common real root.'
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'Compute the sum $a + b + c$.')
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]
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vllm_aclgraph_qwen_answers = [
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' \n\nTo solve this problem, we need to use the Law of Sines and Law of Cosines. Let me start by drawing triangle $ABC$ with the',
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" \n\nTo solve this problem, we can use the fact that the expected value of the area of a triangle formed by two random points on a square's perimeter is",
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' \n\nTo solve this problem, we can use the following approach: Let $ \\alpha $ be the common real root of the two equations. Then, we can'
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]
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vllm_aclgraph_ds_answers = [
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'\n\nSelect an assignment template',
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'\n\nSelect an assignment template',
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'\n\nSelect an assignment template'
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]
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sampling_params = SamplingParams(max_tokens=max_tokens,
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n=1,
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temperature=0.0,
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top_p=1.0,
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top_k=1)
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if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8":
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with VllmRunner(
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model,
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max_model_len=1024,
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enforce_eager=False,
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compilation_config={"cudagraph_mode": "FULL_DECODE_ONLY"},
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quantization="ascend",
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) as runner:
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vllm_aclgraph_outputs = runner.model.generate(
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prompts, sampling_params)
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else:
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with VllmRunner(
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model,
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max_model_len=1024,
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enforce_eager=False,
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compilation_config={
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"cudagraph_capture_sizes": [4, 8, 32, 64],
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"cudagraph_mode": "FULL_DECODE_ONLY"
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},
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) as runner:
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vllm_aclgraph_outputs = runner.model.generate(
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prompts, sampling_params)
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vllm_aclgraph_outputs_list = []
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for output in vllm_aclgraph_outputs:
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vllm_aclgraph_outputs_list.append(
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([output.outputs[0].index], output.outputs[0].text))
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vllm_eager_outputs_list = []
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vllm_eager_outputs_list = ([
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([0], answer) for answer in vllm_aclgraph_ds_answers
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] if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8" else [
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([0], answer) for answer in vllm_aclgraph_qwen_answers
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])
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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_aclgraph_outputs_list,
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name_0="vllm_eager_outputs",
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name_1="vllm_aclgraph_outputs",
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)
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