[Test] Add e2e test cases for the Qwen-VL model adaptation to Ascend 310p (#6977)
### What this PR does / why we need it?
Add e2e test cases for the Qwen-VL model adaptation to Ascend 310p
- vLLM version: v0.16.0
- vLLM main:
15d76f74e2
Signed-off-by: gcw_61wqY8cy <wanghengkang1@huawei.com>
This commit is contained in:
6
.github/workflows/_e2e_test.yaml
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6
.github/workflows/_e2e_test.yaml
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@@ -517,7 +517,8 @@ jobs:
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PYTORCH_NPU_ALLOC_CONF: max_split_size_mb:256
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PYTORCH_NPU_ALLOC_CONF: max_split_size_mb:256
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VLLM_WORKER_MULTIPROC_METHOD: spawn
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VLLM_WORKER_MULTIPROC_METHOD: spawn
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run: |
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run: |
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pytest -sv --durations=0 tests/e2e/310p/singlecard/test_dense_model_singlecard.py
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pytest -sv --durations=0 tests/e2e/310p/singlecard/test_dense_model_singlecard.py \
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tests/e2e/310p/singlecard/test_vl_model_singlecard.py
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e2e_310p-4cards:
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e2e_310p-4cards:
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name: 310p multicards 4cards
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name: 310p multicards 4cards
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@@ -577,4 +578,5 @@ jobs:
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run: |
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run: |
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pytest -sv --durations=0 \
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pytest -sv --durations=0 \
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tests/e2e/310p/multicard/test_dense_model_multicard.py \
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tests/e2e/310p/multicard/test_dense_model_multicard.py \
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tests/e2e/310p/multicard/test_moe_model_multicard.py
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tests/e2e/310p/multicard/test_moe_model_multicard.py \
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tests/e2e/310p/multicard/test_vl_model_multicard.py
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1
.github/workflows/pr_test_light.yaml
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1
.github/workflows/pr_test_light.yaml
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@@ -77,6 +77,7 @@ jobs:
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- '.github/workflows/pr_test_light.yaml'
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- '.github/workflows/pr_test_light.yaml'
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_310_tracker:
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_310_tracker:
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- 'vllm_ascend/_310p/**'
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- 'vllm_ascend/_310p/**'
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- 'tests/e2e/310p/**'
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- 'vllm_ascend/worker/model_runner_v1.py'
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- 'vllm_ascend/worker/model_runner_v1.py'
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- 'vllm_ascend/attention/attention_v1.py'
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- 'vllm_ascend/attention/attention_v1.py'
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- 'vllm_ascend/ops/fused_moe/**'
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- 'vllm_ascend/ops/fused_moe/**'
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BIN
tests/e2e/310p/data/qwen.png
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BIN
tests/e2e/310p/data/qwen.png
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Binary file not shown.
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After Width: | Height: | Size: 17 KiB |
42
tests/e2e/310p/multicard/test_vl_model_multicard.py
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42
tests/e2e/310p/multicard/test_vl_model_multicard.py
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@@ -0,0 +1,42 @@
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#
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# Copyright (c) 2026 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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import sys
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import os
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# Add 310p directory to sys.path
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current_dir = os.path.dirname(os.path.abspath(__file__))
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parent_dir = os.path.dirname(current_dir) # 310p directory
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sys.path.insert(0, parent_dir)
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from test_utils import run_vl_model_test
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def test_qwen3_vl_8b_tp2_fp16():
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"""Qwen3-VL-8B dual-card FP16 test"""
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run_vl_model_test(
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model_name="Qwen/Qwen3-VL-8B-Instruct",
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tensor_parallel_size=2,
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max_tokens=5
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)
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def test_qwen3_vl_32b_tp1_fp16():
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"""Qwen3-VL-32B 4-card FP16 test"""
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run_vl_model_test(
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model_name="Qwen/Qwen3-VL-32B-Instruct",
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tensor_parallel_size=4,
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max_tokens=5
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)
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34
tests/e2e/310p/singlecard/test_vl_model_singlecard.py
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34
tests/e2e/310p/singlecard/test_vl_model_singlecard.py
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@@ -0,0 +1,34 @@
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#
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# Copyright (c) 2026 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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import sys
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import os
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# Add 310p directory to sys.path
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current_dir = os.path.dirname(os.path.abspath(__file__))
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parent_dir = os.path.dirname(current_dir) # 310p directory
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sys.path.insert(0, parent_dir)
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from test_utils import run_vl_model_test
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def test_qwen3_vl_8b_tp1_fp16():
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"""Qwen3-VL-8B single-card FP16 test"""
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run_vl_model_test(
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model_name="Qwen/Qwen3-VL-8B-Instruct",
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tensor_parallel_size=1,
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max_tokens=5
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)
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60
tests/e2e/310p/test_utils.py
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60
tests/e2e/310p/test_utils.py
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@@ -0,0 +1,60 @@
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#
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# Copyright (c) 2026 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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from tests.e2e.conftest import VllmRunner
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from PIL import Image
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import os
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def get_test_image():
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"""Get the image object for testing"""
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current_dir = os.path.dirname(os.path.abspath(__file__))
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image_path = os.path.join(current_dir, "data", "qwen.png")
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return Image.open(image_path)
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def get_test_prompts():
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"""Get the prompts for testing"""
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return ["<|image_pad|>Describe this image in detail."]
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def run_vl_model_test(model_name: str,
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tensor_parallel_size: int,
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max_tokens: int,
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dtype: str = "float16",
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enforce_eager: bool = True):
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"""
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Generic visual language model test function
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Args:
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model_name: Model name, e.g., "Qwen/Qwen3-VL-4B"
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tensor_parallel_size: Tensor parallel size
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max_tokens: Maximum number of generated tokens
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dtype: Data type, default is float16
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enforce_eager: Whether to enforce eager mode
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"""
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image = get_test_image()
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images = [image]
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prompts = get_test_prompts()
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with VllmRunner(
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model_name,
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tensor_parallel_size=tensor_parallel_size,
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enforce_eager=enforce_eager,
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dtype=dtype
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) as vllm_model:
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vllm_model.generate_greedy(prompts, max_tokens, images=images)
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