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[1/N][CI] Refactor accuracy test (#5400)

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### What this PR does / why we need it?
1. Accuracy testing no longer compares eager and graph modes; instead,
it directly extracts the golden result under the graph mode
configuration (the implicit purpose of this case is to verify whether
modifications affect existing results)
2. Next step: finer-grained supervision of logits/sampler results
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: release/v0.13.0
- vLLM main:
254f6b9867

Signed-off-by: wangli <wangli858794774@gmail.com>
This commit is contained in:
Li Wang
2026-01-07 20:58:15 +08:00
committed by GitHub
parent b94fc13d3f
commit 1165b2c863
4 changed files with 231 additions and 353 deletions
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352
tests/e2e/singlecard/test_aclgraph_accuracy.py
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@@ -14,298 +14,122 @@
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""
Compare the outputs of vLLM with and without aclgraph.
Run `pytest tests/compile/test_aclgraph_accuracy.py`.
"""
import os
import pytest
from vllm import SamplingParams
from tests.e2e.conftest import VllmRunner
from tests.e2e.model_utils import check_outputs_equal
from tests.e2e.singlecard.utils import (PROMPTS_LONG, PROMPTS_SHORT,
LLMTestCase, gen_and_valid)
MODELS = [
"Qwen/Qwen3-0.6B",
"vllm-ascend/DeepSeek-V2-Lite-W8A8",
]
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("max_tokens", [32])
def test_models_output(
model: str,
max_tokens: int,
) -> None:
prompts = [
"Hello, my name is", "The president of the United States is",
"The capital of France is", "The future of AI is"
]
vllm_aclgraph_qwen_answers = [
CASE_QWEN_ACLGRAPH = LLMTestCase(
model="Qwen/Qwen3-0.6B",
prompts=PROMPTS_SHORT,
golden_answers=[
" Lina. I'm a 22-year-old student from China. I'm interested in studying in the US. I want to know if there are any",
' 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',
' Paris. The capital of France is also the capital of the Republic of France. The capital of France is also the capital of the European Union. The capital of',
' not just a technological frontier but a profound transformation of how we live, work, and interact with the world. As we stand at the intersection of artificial intelligence and'
]
],
)
vllm_aclgraph_ds_answers = [
CASE_DS_ACLGRAPH = LLMTestCase(
model="vllm-ascend/DeepSeek-V2-Lite-W8A8",
quantization="ascend",
prompts=PROMPTS_SHORT,
golden_answers=[
'\nI am a 20 year old student from the UK. I am currently studying for a degree in English Literature and Creative Writing. I have a passion',
' a man who has been in the public eye for decades. He has been a senator, a governor, and a businessman. He has also been married to the',
' Paris, which is also the largest city in the country. The city is located on the River Seine and is known for its beautiful architecture, museums, and art',
' here.\nThe future of AI is here.\nThe future of AI is here.\nThe future of AI is here.\nThe future of AI is'
]
],
)
sampling_params = SamplingParams(max_tokens=max_tokens, temperature=0.0)
if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8":
with VllmRunner(
model,
max_model_len=1024,
cudagraph_capture_sizes=[1, 2, 4, 8],
quantization="ascend",
) as runner:
vllm_aclgraph_outputs = runner.model.generate(
prompts, sampling_params)
else:
with VllmRunner(
model,
max_model_len=1024,
cudagraph_capture_sizes=[1, 2, 4, 8],
) as runner:
vllm_aclgraph_outputs = runner.model.generate(
prompts, sampling_params)
vllm_aclgraph_outputs_list = []
for output in vllm_aclgraph_outputs:
vllm_aclgraph_outputs_list.append(
([output.outputs[0].index], output.outputs[0].text))
vllm_eager_outputs_list = ([
([0], answer) for answer in vllm_aclgraph_ds_answers
] if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8" else [
([0], answer) for answer in vllm_aclgraph_qwen_answers
CASE_QWEN_FULL_DECODE_ONLY = LLMTestCase(
model="Qwen/Qwen3-0.6B",
prompts=PROMPTS_LONG,
golden_answers=[
' \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',
" \n\nTo solve this problem, we can use the following approach: Let $ABCD$ be a unit square with coordinates $A(0,0), B",
' \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'
])
check_outputs_equal(
outputs_0_lst=vllm_eager_outputs_list,
outputs_1_lst=vllm_aclgraph_outputs_list,
name_0="vllm_eager_outputs",
name_1="vllm_aclgraph_outputs",
)
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("max_tokens", [32])
def test_models_output_between_eager_and_full_decode_only(
model: str,
max_tokens: int,
) -> None:
if 'HCCL_OP_EXPANSION_MODE' in os.environ:
del os.environ['HCCL_OP_EXPANSION_MODE']
# NOTE: Randomly fill the prompt with the requested amount for
# the specified capture shape to prevent accuracy issues caused by padding
prompts = [
('Solve the following math problem step by step.'
'The last line of your response should be of the form Answer: '
'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
'In triangle $ABC$, $\\sin \\angle A = \\frac{4}{5}$ and $\\angle A < 90^\\circ$. Let $D$'
'be a point outside triangle $ABC$ such that $\\angle BAD = \\angle DAC$,'
'$\\angle BDC = 90^\\circ$. Suppose $AD = 1$ and $\\frac{BD}{CD} = \\frac{3}{2}$.'
'If $AB + AC$ can be expressed in the form $\\frac{a\\sqrt{b}}{c}$,'
'where $a, b, c$ are pairwise relatively prime integers, find $a + b + c$.'
),
('Solve the following math problem step by step.'
'The last line of your response should be of the form Answer: '
'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
'Let $ABCD$ be a unit square in the plane. Points $X$ and $Y$ are chosen'
'independently and uniformly at random on the perimeter of $ABCD$.'
'If the expected value of the area of triangle $\\triangle AXY$'
'can be expressed as $\\frac{m}{n}$, for relatively prime positive'
'integers $m$ and $n$, compute $m+n$.'),
('Solve the following math problem step by step.'
'The last line of your response should be of the form Answer: '
'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
'Let $a, b, c$ be distinct numbers such that the equations $x^2 + ax + 1 = 0$'
'and $x^2 + bx + c = 0$ have a common real root, and the equations $x^2 + x + a = 0$'
'and $x^2 + cx + b = 0$ also have a common real root.'
'Compute the sum $a + b + c$.')
]
vllm_aclgraph_qwen_answers = [
' \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',
' \n\nTo solve this problem, we can use the following approach: Let $ABCD$ be a unit square with coordinates $A(0,0), B',
' \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'
]
vllm_aclgraph_ds_answers = [
CASE_DS_FULL_DECODE_ONLY = LLMTestCase(
model="vllm-ascend/DeepSeek-V2-Lite-W8A8",
quantization="ascend",
prompts=PROMPTS_LONG,
golden_answers=[
'\n\nSelect an assignment template',
'\n\nSelect an assignment template',
'\n\nSelect an assignment template'
]
sampling_params = SamplingParams(max_tokens=max_tokens,
n=1,
temperature=0.0,
top_p=1.0,
top_k=1)
if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8":
with VllmRunner(
model,
max_model_len=1024,
compilation_config={
"cudagraph_capture_sizes": [4, 8, 32, 64],
"cudagraph_mode": "FULL_DECODE_ONLY"
},
quantization="ascend",
) as runner:
vllm_aclgraph_outputs = runner.model.generate(
prompts, sampling_params)
else:
with VllmRunner(
model,
max_model_len=1024,
compilation_config={
"cudagraph_capture_sizes": [4, 8, 32, 64],
"cudagraph_mode": "FULL_DECODE_ONLY"
},
) as runner:
vllm_aclgraph_outputs = runner.model.generate(
prompts, sampling_params)
vllm_aclgraph_outputs_list = []
for output in vllm_aclgraph_outputs:
vllm_aclgraph_outputs_list.append(
([output.outputs[0].index], output.outputs[0].text))
vllm_eager_outputs_list = []
vllm_eager_outputs_list = ([
([0], answer) for answer in vllm_aclgraph_ds_answers
] if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8" else [
([0], answer) for answer in vllm_aclgraph_qwen_answers
])
check_outputs_equal(
outputs_0_lst=vllm_eager_outputs_list,
outputs_1_lst=vllm_aclgraph_outputs_list,
name_0="vllm_eager_outputs",
name_1="vllm_aclgraph_outputs",
)
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("max_tokens", [32])
def test_models_output_between_eager_and_fullgraph_npugraph_ex(
model: str,
max_tokens: int,
) -> None:
if 'HCCL_OP_EXPANSION_MODE' in os.environ:
del os.environ['HCCL_OP_EXPANSION_MODE']
# NOTE: Randomly fill the prompt with the requested amount for
# the specified capture shape to prevent accuracy issues caused by padding
prompts = [
('Solve the following math problem step by step.'
'The last line of your response should be of the form Answer: '
'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
'In triangle $ABC$, $\\sin \\angle A = \\frac{4}{5}$ and $\\angle A < 90^\\circ$. Let $D$'
'be a point outside triangle $ABC$ such that $\\angle BAD = \\angle DAC$,'
'$\\angle BDC = 90^\\circ$. Suppose $AD = 1$ and $\\frac{BD}{CD} = \\frac{3}{2}$.'
'If $AB + AC$ can be expressed in the form $\\frac{a\\sqrt{b}}{c}$,'
'where $a, b, c$ are pairwise relatively prime integers, find $a + b + c$.'
),
('Solve the following math problem step by step.'
'The last line of your response should be of the form Answer: '
'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
'Let $ABCD$ be a unit square in the plane. Points $X$ and $Y$ are chosen'
'independently and uniformly at random on the perimeter of $ABCD$.'
'If the expected value of the area of triangle $\\triangle AXY$'
'can be expressed as $\\frac{m}{n}$, for relatively prime positive'
'integers $m$ and $n$, compute $m+n$.'),
('Solve the following math problem step by step.'
'The last line of your response should be of the form Answer: '
'$Answer (without quotes) where $Answer is the answer to the problem.\n\n'
'Let $a, b, c$ be distinct numbers such that the equations $x^2 + ax + 1 = 0$'
'and $x^2 + bx + c = 0$ have a common real root, and the equations $x^2 + x + a = 0$'
'and $x^2 + cx + b = 0$ also have a common real root.'
'Compute the sum $a + b + c$.')
]
vllm_aclgraph_qwen_answers = [
CASE_QWEN_EX = LLMTestCase(
model="Qwen/Qwen3-0.6B",
prompts=PROMPTS_LONG,
golden_answers=[
' \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',
" \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",
' \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'
]
vllm_aclgraph_ds_answers = [
'\n\nSelect an assignment template',
'\n\nSelect an assignment template',
'\n\nSelect an assignment template'
]
sampling_params = SamplingParams(max_tokens=max_tokens,
n=1,
temperature=0.0,
top_p=1.0,
top_k=1)
if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8":
with VllmRunner(
model,
max_model_len=1024,
compilation_config={
"cudagraph_capture_sizes": [4, 8, 32, 64],
"cudagraph_mode": "FULL_DECODE_ONLY"
},
additional_config={"enable_npugraph_ex": True},
quantization="ascend",
) as runner:
vllm_aclgraph_outputs = runner.model.generate(
prompts, sampling_params)
else:
with VllmRunner(
model,
max_model_len=1024,
compilation_config={
"cudagraph_capture_sizes": [4, 8, 32, 64],
"cudagraph_mode": "FULL_DECODE_ONLY"
},
additional_config={"enable_npugraph_ex": True},
) as runner:
vllm_aclgraph_outputs = runner.model.generate(
prompts, sampling_params)
vllm_aclgraph_outputs_list = []
for output in vllm_aclgraph_outputs:
vllm_aclgraph_outputs_list.append(
([output.outputs[0].index], output.outputs[0].text))
vllm_eager_outputs_list = []
vllm_eager_outputs_list = ([
([0], answer) for answer in vllm_aclgraph_ds_answers
] if model == "vllm-ascend/DeepSeek-V2-Lite-W8A8" else [
([0], answer) for answer in vllm_aclgraph_qwen_answers
])
check_outputs_equal(
outputs_0_lst=vllm_eager_outputs_list,
outputs_1_lst=vllm_aclgraph_outputs_list,
name_0="vllm_eager_outputs",
name_1="vllm_aclgraph_outputs",
)
CASE_DS_EX = LLMTestCase(model="vllm-ascend/DeepSeek-V2-Lite-W8A8",
quantization="ascend",
prompts=PROMPTS_LONG,
golden_answers=[
'\n\nSelect an assignment template',
'\n\nSelect an assignment template',
'\n\nSelect an assignment template'
])
def test_aclgraph_enable():
# Generally, this test is not belong to e2e, but it is a good way to check if
# aclgraph is enabled in real environment
from vllm.config.compilation import CompilationMode, CUDAGraphMode
from vllm.engine.arg_utils import EngineArgs
@pytest.mark.parametrize("cur_case", [CASE_QWEN_ACLGRAPH, CASE_DS_ACLGRAPH])
def test_piecewise_res_consistency(cur_case: LLMTestCase):
runner_kwargs = {
"model_name": cur_case.model,
"max_model_len": 1024,
"cudagraph_capture_sizes": [1, 2, 4, 8],
"quantization": cur_case.quantization,
}
gen_and_valid(runner_kwargs=runner_kwargs,
prompts=cur_case.prompts,
sampling_params=cur_case.sampling_params,
golden_answers=cur_case.golden_answers)
from vllm_ascend.platform import NPUPlatform
# vLLM default mode is piecewise cudagraph
config = EngineArgs()
VllmConfig = config.create_engine_config()
assert VllmConfig.compilation_config.cudagraph_mode == CUDAGraphMode.PIECEWISE
@pytest.mark.parametrize(
"cur_case", [CASE_QWEN_FULL_DECODE_ONLY, CASE_DS_FULL_DECODE_ONLY])
def test_full_decode_only_res_consistency(cur_case: LLMTestCase, monkeypatch):
monkeypatch.delenv("HCCL_OP_EXPANSION_MODE", raising=False)
runner_kwargs = {
"model_name": cur_case.model,
"max_model_len": 1024,
"compilation_config": {
"cudagraph_capture_sizes": [4, 8, 32, 64],
"cudagraph_mode": "FULL_DECODE_ONLY"
},
"quantization": cur_case.quantization,
}
gen_and_valid(runner_kwargs=runner_kwargs,
prompts=cur_case.prompts,
sampling_params=cur_case.sampling_params,
golden_answers=cur_case.golden_answers)
# after check_and_update_config, mode should be VLLM_COMPILE and piecewise cudagraph
NPUPlatform.check_and_update_config(VllmConfig)
assert VllmConfig.compilation_config.mode == CompilationMode.VLLM_COMPILE
assert VllmConfig.compilation_config.cudagraph_mode == CUDAGraphMode.PIECEWISE
@pytest.mark.parametrize("cur_case", [CASE_QWEN_EX, CASE_DS_EX])
def test_npugraph_ex_res_consistency(cur_case: LLMTestCase, monkeypatch):
monkeypatch.delenv("HCCL_OP_EXPANSION_MODE", raising=False)
runner_kwargs = {
"model_name": cur_case.model,
"quantization": cur_case.quantization,
"max_model_len": 1024,
"compilation_config": {
"cudagraph_capture_sizes": [4, 8, 32, 64],
"cudagraph_mode": "FULL_DECODE_ONLY"
},
"additional_config": {
"enable_npugraph_ex": True
},
}
gen_and_valid(runner_kwargs=runner_kwargs,
prompts=cur_case.prompts,
sampling_params=cur_case.sampling_params,
golden_answers=cur_case.golden_answers)