[TEST]Add initial prefix cache case for nightly test (#3709)
### What this PR does / why we need it? This PR adds the initial prefix cache case for nightly test for Qwen3-32b-int8 on A3, we need test them daily. ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? By running the test - vLLM version: v0.11.0rc3 - vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0 Signed-off-by: jiangyunfan1 <jiangyunfan1@h-partners.com>
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tests/e2e/nightly/features/test_prefix_cache_qwen3_32b_int8.py
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tests/e2e/nightly/features/test_prefix_cache_qwen3_32b_int8.py
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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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# This file is a part of the vllm-ascend project.
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#
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import json
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import pytest
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from vllm.utils import get_open_port
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from tests.e2e.conftest import RemoteOpenAIServer
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from tools.aisbench import get_TTFT, run_aisbench_cases
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MODELS = [
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"vllm-ascend/Qwen3-32B-W8A8",
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]
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aisbench_warm_up = [{
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"case_type": "performance",
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"dataset_path": "vllm-ascend/GSM8K-in1024-bs210",
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"request_conf": "vllm_api_stream_chat",
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"dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_str_perf",
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"num_prompts": 210,
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"max_out_len": 2,
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"batch_size": 1000,
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"baseline": 0,
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"threshold": 0.97
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}]
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aisbench_cases0 = [{
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"case_type": "performance",
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"dataset_path": "vllm-ascend/prefix0-in3500-bs210",
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"request_conf": "vllm_api_stream_chat",
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"dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_str_perf",
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"num_prompts": 210,
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"max_out_len": 1500,
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"batch_size": 48,
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"baseline": 1,
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"threshold": 0.97
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}]
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aisbench_cases75 = [{
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"case_type": "performance",
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"dataset_path": "vllm-ascend/prefix75-in3500-bs210",
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"request_conf": "vllm_api_stream_chat",
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"dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_str_perf",
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"num_prompts": 210,
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"max_out_len": 1500,
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"batch_size": 48,
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"baseline": 1,
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"threshold": 0.97
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}]
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@pytest.mark.asyncio
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@pytest.mark.parametrize("model", MODELS)
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async def test_models(model: str) -> None:
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port = get_open_port()
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env_dict = {"TASK_QUEUE_ENABLE": "1", "HCCL_OP_EXPANSION_MODE": "AIV"}
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additional_config = {
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"ascend_scheduler_config": {
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"enabled": False
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},
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"enable_weight_nz_layout": True
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}
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server_args = [
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"--quantization", "ascend", "--reasoning-parser", "qwen3",
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"--tensor-parallel-size", "4", "--port",
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str(port), "--max-model-len", "8192", "--max-num-batched-tokens",
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"8192", "--max-num-seqs", "256", "--trust-remote-code",
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"--gpu-memory-utilization", "0.9", "--additional-config",
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json.dumps(additional_config)
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]
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with RemoteOpenAIServer(model,
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server_args,
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server_port=port,
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env_dict=env_dict,
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auto_port=False):
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run_aisbench_cases(model, port, aisbench_warm_up)
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result = run_aisbench_cases(model, port, aisbench_cases0)
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TTFT0 = get_TTFT(result)
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with RemoteOpenAIServer(model,
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server_args,
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server_port=port,
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env_dict=env_dict,
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auto_port=False):
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run_aisbench_cases(model, port, aisbench_warm_up)
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result = run_aisbench_cases(model, port, aisbench_cases75)
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TTFT75 = get_TTFT(result)
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assert TTFT75 < 0.4 * TTFT0, f"The TTFT for prefix75 {TTFT75} is not less than 0.4*TTFT for prefix0 {TTFT0}."
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print(
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f"The TTFT for prefix75 {TTFT75} is less than 0.4*TTFT for prefix0 {TTFT0}."
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)
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