[MoE] [Refactor] Combine common_fused_moe and fused_moe (#3176)

### What this PR does / why we need it?
1. Move additional functionalities from fused_moe.py to
common_fused_moe.py and remove fused_moe.py
2. Remove unnecessary custom classes from qwen3_moe.py, and it will be
completely removed after we release vllm-ascend v0.11.0

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

### How was this patch tested?

Qwen3-30B-A3B/Qwen3-30B-A3B-W8A8/DeepSeek-V3-W4A8-Pruing/deepseek-mtp/pangu-pro-moe-pruing:

1. Enable/Disable EP
3. Aclgraph & eager
4. SP


- vLLM version: v0.11.0

---------

Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
Co-authored-by: weijinqian0 <12153182+weijinqian0@users.noreply.github.com>

vllm_ascend/torchair/ops/torchair_fused_moe.py

@@ -880,7 +880,7 @@ class TorchairAscendUnquantizedFusedMoEMethod(UnquantizedFusedMoEMethod):
         # this is a naive implementation for experts load balance so as
         # to avoid accumulating too much tokens on a single rank.
         # currently it is only activated when doing profile runs.
-        if enable_force_load_balance and not self.use_aclgraph:
+        if enable_force_load_balance:
             topk_ids = torch.randint_like(topk_ids, 0, global_num_experts)
 
         fused_moe_state = get_forward_context().fused_moe_state