[MoE][Dist] Fix Qwen MoE accuracy bug in DP scenario (#1856)

### What this PR does / why we need it?
Fix Qwen MoE accuracy bug in DP scenario.

Now the implentment of `FusedMoE` in vLLM use `All2AllManager` to
manager different all2all algorithm branch. And the default branch use
`Multicast` in `dispatch` phase and `all_reduce` in `combine` phase,
which are not implented in vLLM-Ascend. This leading to invoking into a
default implentment in `base_communicator`, with empty `dispatch` and
`combine` operations, thus causing the accuracy issue on it.

This pr is a temporary workaround, refacting all2all in vLLM-Ascend
could be a better way.


- vLLM version: v0.10.0
- vLLM main:
ad57f23f6a

---------

Signed-off-by: MengqingCao <cmq0113@163.com>

tests/e2e/multicard/test_data_parallel.py

@@ -27,7 +27,7 @@ from unittest.mock import patch
 
 import pytest
 
-MODELS = ["Qwen/Qwen2.5-0.5B-Instruct"]
+MODELS = ["Qwen/Qwen2.5-0.5B-Instruct", "Qwen/Qwen3-30B-A3B"]
 
 
 @pytest.mark.parametrize("model", MODELS)
@@ -54,6 +54,8 @@ def test_data_parallel_inference(model, max_tokens):
         "--trust-remote-code",
         "--enforce-eager",
     ]
+    if model == "Qwen/Qwen3-30B-A3B":
+        cmd.append("--enable-expert-parallel")
 
     print(f"Running subprocess: {' '.join(cmd)}")
     proc = subprocess.run(cmd,