2870f7c8ad
### What this PR does / why we need it?
[Feat] Support routing replay
same as https://github.com/vllm-project/vllm-ascend/pull/6666
resubmit because of DOC failure
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.15.0
- vLLM main:
9562912cea
---------
Signed-off-by: liyongwen <1310439159@qq.com>
Signed-off-by: Li-Yongwen <63399187+Li-Yongwen@users.noreply.github.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
33 lines
1.1 KiB
Python
33 lines
1.1 KiB
Python
import os
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from unittest.mock import patch
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from tests.e2e.conftest import VllmRunner
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from vllm import SamplingParams
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from vllm.sampling_params import RequestOutputKind
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@patch.dict(os.environ, {"OMP_NUM_THREADS": "1"})
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def test_qwen3_moe_routing_replay():
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prompts = [
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"Hello, please introduce yourself.",
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]
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with VllmRunner(
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"Qwen/Qwen3-30B-A3B",
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tensor_parallel_size=2,
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enable_expert_parallel=True,
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cudagraph_capture_sizes=[1, 2, 4, 8],
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distributed_executor_backend="mp",
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enable_return_routed_experts=True,
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) as vllm_model:
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sampling_params = SamplingParams(
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max_tokens=5,
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temperature=0.8,
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top_p=0.95,
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output_kind=RequestOutputKind.FINAL_ONLY
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)
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inputs = vllm_model.get_inputs(prompts=prompts)
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outputs = vllm_model.model.generate(prompts=inputs, sampling_params=sampling_params)
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assert outputs[0].finished
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assert len(outputs[0].outputs[0].text) > 0
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assert outputs[0].outputs[0].routed_experts.size > 0
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