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Signed-off-by: hfadzxy <starmoon_zhang@163.com>
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.github/workflows/vllm_ascend_test_long_term.yaml

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@@ -96,8 +96,8 @@ jobs:
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- name: Run vllm-project/vllm-ascend long term test
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run: |
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if [[ "${{ matrix.os }}" == "linux-arm64-npu-1" ]]; then
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pytest -sv tests/e2e/long_term/test_accuracy.py
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# else
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pytest -sv tests/e2e/long_term/accuracy/accuracy_singlecard.py
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else
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# accuracy test multi card
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# VLLM_USE_MODELSCOPE=True pytest -sv tests/e2e/long_term/test_deepseek_v2_lite_tp2_accuracy.py
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pytest -sv tests/e2e/long_term/accuracy/accuracy_multicard.py
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fi

tests/e2e/long_term/accuracy/accuracy_multicard.py

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@@ -18,7 +18,6 @@
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#
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import gc
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import multiprocessing
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import os
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import signal
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import subprocess
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import sys
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EXPECTED_VALUE = {
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"Qwen/Qwen2.5-0.5B-Instruct": 0.316,
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"Qwen/Qwen3-30B-A3B": 0.888,
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"deepseek-ai/DeepSeek-V2-Lite": 0.376
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"deepseek-ai/DeepSeek-V2-Lite": 0.375
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}
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# Maximum context length configuration for each model.
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MAX_MODEL_LEN = {
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}
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multiprocessing.set_start_method("spawn", force=True)
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os.environ["VLLM_USE_V1"] = "1"
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def run_test(queue, model, max_model_len, model_type, more_args):

tests/e2e/long_term/accuracy/accuracy_singlecard.py

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@@ -98,10 +98,8 @@ def run_test(queue, model, max_model_len, model_type):
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@pytest.mark.parametrize("model", MODEL_NAME)
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@pytest.mark.parametrize("VLLM_USE_V1", ["0", "1"])
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def test_lm_eval_accuracy(monkeypatch: pytest.MonkeyPatch, model, VLLM_USE_V1):
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def test_lm_eval_accuracy(monkeypatch: pytest.MonkeyPatch, model):
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with monkeypatch.context() as m:
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m.setenv("VLLM_USE_V1", VLLM_USE_V1)
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result_queue: Queue[float] = multiprocessing.Queue()
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p = multiprocessing.Process(target=run_test,
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args=(result_queue, model,

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