Files
xc-llm-ascend/tests/e2e/multicard/test_data_parallel.py
Yizhou 134e011896 [Test] Temporarily skips Qwen3-30B-A3B-W8A8 data parallel test case (#4857)
### What this PR does / why we need it?
This case is breaking CI, please see
https://github.com/vllm-project/vllm-ascend/actions/runs/20084930558/job/57620266368?pr=4854

### Does this PR introduce _any_ user-facing change?
None.

### How was this patch tested?
None.

Signed-off-by: Yizhou Liu <liu_yizhou@outlook.com>
2025-12-10 11:05:32 +08:00

84 lines
2.3 KiB
Python

#
# 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.
#
"""
Compare the outputs of vLLM with and without aclgraph.
Run `pytest tests/multicard/test_data_parallel.py`.
"""
import os
import subprocess
import sys
from unittest.mock import patch
import pytest
MODELS = [
"Qwen/Qwen3-0.6B",
"Qwen/Qwen3-30B-A3B",
# FIXME(Potabk): Skip this case for now
# "vllm-ascend/Qwen3-30B-A3B-W8A8"
]
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("max_tokens", [32])
@patch.dict(os.environ, {"ASCEND_RT_VISIBLE_DEVICES": "0,1"})
def test_data_parallel_inference(model, max_tokens):
moe_models = ["Qwen/Qwen3-30B-A3B", "vllm-ascend/Qwen3-30B-A3B-W8A8"]
quantization_models = ["vllm-ascend/Qwen3-30B-A3B-W8A8"]
script = "examples/offline_data_parallel.py"
env = os.environ.copy()
cmd = [
sys.executable,
script,
"--model",
model,
"--dp-size",
"2",
"--tp-size",
"1",
"--node-size",
"1",
"--node-rank",
"0",
"--trust-remote-code",
]
if model in moe_models:
cmd.append("--enable-expert-parallel")
if model in quantization_models:
cmd.append("--quantization")
cmd.append("ascend")
print(f"Running subprocess: {' '.join(cmd)}")
proc = subprocess.run(cmd,
env=env,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
timeout=600)
output = proc.stdout.decode(errors='ignore')
print(output)
assert "DP rank 0 needs to process" in output
assert "DP rank 1 needs to process" in output
assert "Generated text:" in output
assert proc.returncode == 0