[Feature] Support moe multi-stream for aclgraph. (#2946)

This PR puts the calculation of shared experts into a separate stream,
overlaping with routing experts.

- vLLM version: v0.10.2
- vLLM main:
fbd6523ac0

---------

Signed-off-by: whx-sjtu <2952154980@qq.com>

tests/e2e/multicard/test_offline_inference_distributed.py

@@ -66,8 +66,8 @@ def test_models_distributed_DeepSeek_multistream_moe():
             additional_config={
                 "torchair_graph_config": {
                     "enabled": True,
-                    "enable_multistream_moe": True,
                 },
+                "enable_multistream_moe": True,
                 "ascend_scheduler_config": {
                     "enabled": True,
                 },

tests/e2e/singlecard/test_multistream_overlap_shared_expert.py

@@ -0,0 +1,103 @@
+#
+# 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 multistream_overlap_shared_expert
+enabled and disabled.
+
+Run `pytest tests/e2e/singlecard/test_multistream_overlap_shared_expert.py`.
+"""
+
+import pytest
+from vllm import SamplingParams
+
+from tests.e2e.conftest import VllmRunner
+from tests.e2e.model_utils import check_outputs_equal
+
+MODELS = [
+    "Qwen/Qwen3-0.6B",
+]
+
+
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("max_tokens", [32])
+def test_models_with_multistream_overlap_shared_expert(
+    model: str,
+    max_tokens: int,
+) -> None:
+    prompts = [
+        "Hello, my name is", "The president of the United States is",
+        "The capital of France is", "The future of AI is"
+    ]
+
+    sampling_params = SamplingParams(max_tokens=max_tokens, temperature=0.0)
+    with VllmRunner(
+            model,
+            max_model_len=1024,
+            enforce_eager=True,
+            additional_config={
+                "multistream_overlap_shared_expert": True,
+            },
+    ) as runner:
+        vllm_moe_ms_eager_outputs = runner.model.generate(
+            prompts, sampling_params)
+
+    with VllmRunner(
+            model,
+            max_model_len=1024,
+            enforce_eager=False,
+            additional_config={
+                "multistream_overlap_shared_expert": True,
+            },
+    ) as runner:
+        vllm_moe_ms_aclgraph_outputs = runner.model.generate(
+            prompts, sampling_params)
+
+    with VllmRunner(
+            model,
+            max_model_len=1024,
+            enforce_eager=True,
+    ) as runner:
+        vllm_eager_outputs = runner.model.generate(prompts, sampling_params)
+
+    vllm_moe_ms_eager_outputs_list = []
+    for output in vllm_moe_ms_eager_outputs:
+        vllm_moe_ms_eager_outputs_list.append(
+            (output.outputs[0].index, output.outputs[0].text))
+
+    vllm_moe_ms_aclgraph_outputs_list = []
+    for output in vllm_moe_ms_aclgraph_outputs:
+        vllm_moe_ms_aclgraph_outputs_list.append(
+            (output.outputs[0].index, output.outputs[0].text))
+
+    vllm_eager_outputs_list = []
+    for output in vllm_eager_outputs:
+        vllm_eager_outputs_list.append(
+            (output.outputs[0].index, output.outputs[0].text))
+
+    check_outputs_equal(
+        outputs_0_lst=vllm_eager_outputs_list,
+        outputs_1_lst=vllm_moe_ms_eager_outputs_list,
+        name_0="vllm_eager_outputs",
+        name_1="vllm_moe_ms_eager_outputs",
+    )
+
+    check_outputs_equal(
+        outputs_0_lst=vllm_eager_outputs_list,
+        outputs_1_lst=vllm_moe_ms_aclgraph_outputs_list,
+        name_0="vllm_eager_outputs",
+        name_1="vllm_moe_ms_aclgraph_outputs",
+    )