[Main] [Refactor] Enable MoECommMethod in Eager Mode (#2791)

### What this PR does / why we need it?
1. Replace prepare/finalize operation in fused_moe.py by
moe_comm_method.prepare()/finalize()
2. Replace unified_fused_experts by moe_comm_method.fused_experts() in
fused_moe.py/w8a8_dynamic.py/w4a8_dynamic.py
3. Add calling _select_moe_comm_method in spec-decode proposers.
4. Currently, w4a8_dynamic does not support gatherep, use all2allv
instead.
5. Remove redundant code.
### Does this PR introduce _any_ user-facing change?
AllgatherEP switch is disabled in aclgraph/eager mode, just follow the
rules in modelrunner_v1._select_moe_comm_method()
### How was this patch tested?
e2e & ut


- vLLM version: v0.10.2
- vLLM main:
7f6f2c1182

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

vllm_ascend/ops/moe/moe_mlp.py

@@ -21,7 +21,6 @@ import torch_npu
 from torch.nn.functional import pad
 from vllm.forward_context import get_forward_context
 
-from vllm_ascend.ascend_forward_context import FusedMoEState
 from vllm_ascend.utils import dispose_tensor, is_310p
 
 
@@ -77,7 +76,7 @@ def quant_apply_mlp(hidden_states: torch.Tensor,
     bias1, bias2 = None, None
     _output_dtype = w2_scale.dtype
 
-    is_mc2 = get_forward_context().fused_moe_state == FusedMoEState.MC2
+    is_mc2 = get_forward_context().moe_comm_method_name == "mc2commimpl"
     if w1_scale_bias is None and is_mc2:
         if w1_scale.dtype != torch.float32:
             w1_scale = w1_scale.to(torch.float32)