[Refactor][MoE] Reuse vLLM's all_reduce logic (#5189)

### What this PR does / why we need it?
Move all_reduce logic to AscendFusedMoE.forward, reuse vLLM's logic.

### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
e2e & ut
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: weichen <calvin_zhu0210@outlook.com>
Co-authored-by: weijinqian0 <1184188277@qq.com>

vllm_ascend/ops/fused_moe/fused_moe.py

@@ -18,7 +18,6 @@ import os.path
 from typing import Any, Callable, Optional
 
 import torch
-import torch.nn.functional as F
 from vllm.config import get_current_vllm_config
 from vllm.distributed import (get_dp_group, get_ep_group, get_tp_group,
                               tensor_model_parallel_all_reduce)
@@ -292,32 +291,6 @@ class AscendFusedMoE(FusedMoE):
         return torch.ops.vllm.maybe_all_reduce_tensor_model_parallel(
             final_hidden_states)
 
-    def forward(
-        self,
-        hidden_states: torch.Tensor,
-        router_logits: torch.Tensor,
-    ) -> torch.Tensor | tuple[torch.Tensor, torch.Tensor]:
-        og_hidden_states = hidden_states.shape[-1]
-        if self.hidden_size != og_hidden_states:
-            hidden_states = F.pad(
-                hidden_states,
-                (0, self.hidden_size - og_hidden_states),
-                mode="constant",
-                value=0.0,
-            )
-        if self.shared_experts is None:
-            fused_output = torch.ops.vllm.moe_forward(hidden_states,
-                                                      router_logits,
-                                                      self.layer_name)
-            return fused_output[..., :og_hidden_states]
-        else:
-            shared_output, fused_output = torch.ops.vllm.moe_forward_shared(
-                hidden_states, router_logits, self.layer_name)
-            return (
-                shared_output[..., :og_hidden_states],
-                fused_output[..., :og_hidden_states],
-            )
-
     def forward_impl(self, hidden_states: torch.Tensor,
                      router_logits: torch.Tensor):
         assert self.quant_method is not None