[CI][Bugfix] Quickfix for DPMetaData (#3234)

### What this PR does / why we need it?
Fix `dpmetadata` and `Qwen3MoeSparseMoeBlock` break introduced by
26a7a33b88 (diff-c1550d0a38469d039370567d8981969530cbfffc7302cd1778e7c2c8a9322dea)

NOTE: we maintain a different sp in vllm-ascend with vllm, thus we can
just use `cu_tokens_across_sp(1)` as `cu_tokens_across_dp_cpu`

close https://github.com/vllm-project/vllm-ascend/issues/3236,
https://github.com/vllm-project/vllm-ascend/issues/3239
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?


- vLLM version: v0.10.2
- vLLM main:
https://github.com/vllm-project/vllm/commit/releases/v0.11.0

---------

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

tests/ut/ops/test_fused_ops.py

@@ -28,7 +28,7 @@ from vllm_ascend.ops.fused_moe import (AscendFusedMoE,
                                        AscendUnquantizedFusedMoEMethod)
 from vllm_ascend.ops.moe.experts_selector import select_experts
 from vllm_ascend.ops.moe.moe_mlp import cumsum_group_list, unified_apply_mlp
-from vllm_ascend.utils import AscendSocVersion, adapt_patch
+from vllm_ascend.utils import AscendSocVersion, adapt_patch, vllm_version_is
 
 adapt_patch(True)
 
@@ -93,14 +93,18 @@ def mock_dist_env(mocker: MockerFixture):
 
     mock_moe_comm_method.finalize.side_effect = mock_finalize
 
-    mock_forward_context_obj = MagicMock(
-        moe_comm_method=mock_moe_comm_method,
-        moe_comm_type=MoECommType.MC2,
-        max_tokens_across_dp=10,
-        dp_metadata=MagicMock(cu_tokens_across_dp_cpu=[5, 10]),
-        mc2_mask=torch.zeros(16, dtype=torch.bool),
-        padded_num_tokens=16,
-        with_quant=False)
+    if vllm_version_is("0.10.2"):
+        dp_metadata = MagicMock(cu_tokens_across_dp_cpu=[5, 10])
+    else:
+        dp_metadata = MagicMock(num_tokens_across_dp_cpu=[5, 5])
+    mock_forward_context_obj = MagicMock(moe_comm_method=mock_moe_comm_method,
+                                         moe_comm_type=MoECommType.MC2,
+                                         max_tokens_across_dp=10,
+                                         dp_metadata=dp_metadata,
+                                         mc2_mask=torch.zeros(
+                                             16, dtype=torch.bool),
+                                         padded_num_tokens=16,
+                                         with_quant=False)
 
     with patch('torch.distributed.get_rank', return_value=0), \
         patch('torch.distributed.get_world_size', return_value=4), \