From 874face5877ebdb83efb52b79194b4183393d893 Mon Sep 17 00:00:00 2001 From: jiangyunfan1 Date: Mon, 9 Feb 2026 16:54:15 +0800 Subject: [PATCH] add qwen3-30b mooncake Signed-off-by: jiangyunfan1 --- .github/workflows/misc/model_list.json | 1 + .../workflows/schedule_nightly_test_a3.yaml | 3 + .../single_node/models/test_qwen3_30b_acc.py | 137 ++++++++++++++++++ 3 files changed, 141 insertions(+) create mode 100644 tests/e2e/weekly/single_node/models/test_qwen3_30b_acc.py diff --git a/.github/workflows/misc/model_list.json b/.github/workflows/misc/model_list.json index ee709ac2aa0..eb2fdd2c2c9 100644 --- a/.github/workflows/misc/model_list.json +++ b/.github/workflows/misc/model_list.json @@ -202,6 +202,7 @@ "vllm-ascend/Qwen3-235B-A22B-W8A8", "vllm-ascend/Qwen3-235B-A22B-w8a8", "vllm-ascend/Qwen3-30B-A3B", + "vllm-ascend/Qwen3-a3B_eagle3", "vllm-ascend/Qwen3-30B-A3B-Puring", "vllm-ascend/Qwen3-30B-A3B-W8A8", "vllm-ascend/Qwen3-30B-A3B-W8A8-Pruning", diff --git a/.github/workflows/schedule_nightly_test_a3.yaml b/.github/workflows/schedule_nightly_test_a3.yaml index 5f7dce93d9a..c0a28709a28 100644 --- a/.github/workflows/schedule_nightly_test_a3.yaml +++ b/.github/workflows/schedule_nightly_test_a3.yaml @@ -162,6 +162,9 @@ jobs: - name: deepseek3_2-w8a8 os: linux-aarch64-a3-16 tests: tests/e2e/nightly/single_node/models/test_deepseek_v3_2_w8a8.py + - name: qwen3-30b-acc + os: linux-aarch64-a3-4 + tests: tests/e2e/weekly/single_node/models/test_qwen3_30b_acc.py uses: ./.github/workflows/_e2e_nightly_single_node.yaml with: runner: ${{ matrix.test_config.os }} diff --git a/tests/e2e/weekly/single_node/models/test_qwen3_30b_acc.py b/tests/e2e/weekly/single_node/models/test_qwen3_30b_acc.py new file mode 100644 index 00000000000..a1b0933579d --- /dev/null +++ b/tests/e2e/weekly/single_node/models/test_qwen3_30b_acc.py @@ -0,0 +1,137 @@ +# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved. +# Copyright 2023 The vLLM team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# This file is a part of the vllm-ascend project. +# +from typing import Any + +import json +import openai +import pytest +from vllm.utils.network_utils import get_open_port + +from tests.e2e.conftest import RemoteOpenAIServer, MooncakeLauncher +from tools.aisbench import run_aisbench_cases, maybe_download_from_modelscope + +MODELS = [ + "vllm-ascend/Qwen3-30B-A3B-W8A8", +] + +eagle_model = maybe_download_from_modelscope("vllm-ascend/Qwen3-a3B_eagle3") + +TENSOR_PARALLELS = [1, 4] + +prompts = [ + "Janet\u2019s ducks lay 16 eggs per day. She eats three for breakfast every morning and bakes muffins for her friends every day with four. She sells the remainder at the farmers' market daily for $2 per fresh duck egg. How much in dollars does she make every day at the farmers' market?", +] + +api_keyword_args = { + "max_tokens": 10, +} + +mooncake_json = { + "local_hostname": "localhost", + "metadata_server": "P2PHANDSHAKE", + "protocol": "ascend", + "device_name": "", + "use_ascend_direct": True, + "master_server_address": "", + "global_segment_size": 30000000000 +} + +aisbench_cases = [{ + "case_type": "accuracy", + "dataset_path": "vllm-ascend/gsm8k-lite", + "request_conf": "vllm_api_general_chat", + "dataset_conf": "gsm8k/gsm8k_gen_0_shot_cot_chat_prompt", + "max_out_len": 32768, + "batch_size": 32, + "baseline": 95, + "threshold": 5 +}] + + +@pytest.mark.asyncio +@pytest.mark.parametrize("model", MODELS) +@pytest.mark.parametrize("tp_size", TENSOR_PARALLELS) +async def test_models(model: str, tp_size: int) -> None: + port = get_open_port() + mooncake_port = get_open_port() + mooncake_metrics_port = get_open_port() + mooncake_json["master_server_address"] = f"127.0.0.1:{mooncake_port}" + with open("mooncake.json", "w") as f: + json.dump(mooncake_json, f) + env_dict = { + "PYTHONHASHSEED": "0", + "ASCEND_CONNECT_TIMEOUT": "10000", + "ASCEND_TRANSFER_TIMEOUT": "10000", + "ASCEND_BUFFER_POOL": "4:8", + "VLLM_USE_V1": "1", + "OMP_PROC_BIND": "false", + "HCCL_OP_EXPANSION_MODE": "AIV", + "HCCL_BUFFSIZE": "1024", + "OMP_NUM_THREADS": "1", + "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True", + "VLLM_ASCEND_ENABLE_NZ": "2", + "MOONCAKE_CONFIG_PATH": "mooncake.json" + } + if tp_size != 1: + env_dict["VLLM_ASCEND_ENABLE_FLASHCOMM1"] = "1" + kv_transfer_config = { + "kv_connector": "AscendStoreConnector", + "kv_role": "kv_both", + "kv_connector_extra_config": { + "register_buffer": True, + "use_layerwise": False, + "mooncake_rpc_port": "0" + } + } + speculative_config = { + "method": "eagle3", + "model": eagle_model, + "num_speculative_tokens": 3 + } + server_args = [ + "--trust-remote-code", "--max-num-seqs", "100", "--max-model-len", + "37364", "--max-num-batched-tokens", "16384", "--tensor-parallel-size", + str(tp_size), "--enable-expert-parallel", "--port", + str(port), "--distributed_executor_backend", "mp", + "--async-scheduling", "--quantization", "ascend", + "--compilation-config", '{"cudagraph_mode": "FULL_DECODE_ONLY"}', + "--gpu-memory-utilization", "0.95", "--speculative-config", + json.dumps(speculative_config), "--kv-transfer-config", + json.dumps(kv_transfer_config) + ] + request_keyword_args: dict[str, Any] = { + **api_keyword_args, + } + with MooncakeLauncher(mooncake_port, + mooncake_metrics_port) as mooncake_server: + with RemoteOpenAIServer(model, + server_args, + server_port=port, + env_dict=env_dict, + auto_port=False) as server: + client = server.get_async_client() + for _ in range(2): + batch = await client.completions.create( + model=model, + prompt=prompts, + **request_keyword_args, + ) + choices: list[openai.types.CompletionChoice] = batch.choices + assert choices[0].text, "empty response" + # aisbench test + run_aisbench_cases(model, port, aisbench_cases) + run_aisbench_cases(model, port, aisbench_cases)