adjusting the communication method in graph mode (#1194)

### What this PR does / why we need it?
Communication performance optimization: replace allreduce with
reduce_scatter+all_gather in MLA layer's TP group，to remove
stridedsliced and all_gather in MOE layer.
when tp > 1, It is enabled during the decode phase of the graph mode
when enable_multistream_moe、MLA, use_v1, and MC2 are used.
According to the end-to-end RL inference test results, this PR can bring
3% gain in the decode stage.

**Before Improvement**
Profiling kernel_details

![image](https://github.com/user-attachments/assets/1bb5dfa1-809b-410a-90c9-c5fd23cff003)
Evaluation

![image](https://github.com/user-attachments/assets/0b8ea0c7-88e7-410f-9ef4-f0cfe910cdc7)

![image](https://github.com/user-attachments/assets/94fde910-c125-4c2e-8de4-88fc3fafc057)

**After Improvement**
Profiling kernel_details

![image](https://github.com/user-attachments/assets/55fac0e0-11f2-4654-8fd4-287949e0b29e)
Evaluation

![image](https://github.com/user-attachments/assets/e923f74b-29c4-4171-9382-40a00cf05df0)

![image](https://github.com/user-attachments/assets/5dba7967-07ea-4926-a8be-804bfd34e3e4)

### Does this PR introduce _any_ user-facing change?
Users need to configure enable_multistream_moe=True

### How was this patch tested?
Add e2e test cases to cover code logic

Signed-off-by: sharonyunyun <zhangying134@huawei.com>

vllm_ascend/models/deepseek_dbo.py

@@ -42,8 +42,7 @@ from vllm.distributed.parallel_state import get_dp_group
 from vllm.forward_context import get_forward_context
 from vllm.model_executor.layers.layernorm import RMSNorm
 from vllm.model_executor.layers.linear import (ColumnParallelLinear,
-                                               ReplicatedLinear,
-                                               RowParallelLinear)
+                                               ReplicatedLinear)
 from vllm.model_executor.layers.logits_processor import LogitsProcessor
 from vllm.model_executor.layers.quantization import QuantizationConfig
 from vllm.model_executor.layers.rotary_embedding import get_rope
@@ -64,7 +63,8 @@ from vllm.sequence import IntermediateTensors
 
 import vllm_ascend.envs as envs_ascend
 from vllm_ascend.ascend_config import get_ascend_config
-from vllm_ascend.models.deepseek_v2 import CustomDeepseekV2MLP
+from vllm_ascend.models.deepseek_v2 import (CustomDeepseekV2MLP,
+                                            CustomDeepseekV2RowParallelLinear)
 from vllm_ascend.multistream.base import MSEventKey
 from vllm_ascend.multistream.context import (
     advance_step_multistream_layer_context, get_multistream_comm_context,
@@ -325,11 +325,12 @@ class CustomDeepseekDBOMLAAttention(DeepseekV2MLAAttention):
             bias=False,
             quant_config=quant_config,
             prefix=f"{prefix}.kv_b_proj")
-        self.o_proj = RowParallelLinear(self.num_heads * self.v_head_dim,
-                                        self.hidden_size,
-                                        bias=False,
-                                        quant_config=quant_config,
-                                        prefix=f"{prefix}.o_proj")
+        self.o_proj = CustomDeepseekV2RowParallelLinear(
+            self.num_heads * self.v_head_dim,
+            self.hidden_size,
+            bias=False,
+            quant_config=quant_config,
+            prefix=f"{prefix}.o_proj")
 
         if rope_scaling:
             rope_scaling["rope_type"] = 'deepseek_yarn'