[Bugfix]Fix eplb enable when using mtp float weights. (#4576)

### What this PR does / why we need it?
Fix eplb enable when using mtp float weights. It will be remove when
eplb supporting mtp and float weights.

### How was this patch tested?
Deepseek-V3 + MTP + EPLB in A3.
---------

Signed-off-by: offline0806 <[email protected]>
Signed-off-by: offline893 <[email protected]>
Co-authored-by: offline0806 <[email protected]>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

Author: 3 people

vllm_ascend/ops/common_fused_moe.py

@@ -169,11 +169,15 @@ def __init__(self, *args, **kwargs):
         self.expert_map_path = ascend_config.expert_map_path
         self.global_redundant_expert_num = ascend_config.init_redundancy_expert
         self.global_num_experts = num_experts + self.global_redundant_expert_num
+        # TODO: Flag for static expert placement. This is a temporary workaround
+        # to allow dynamic EPLB with float weights by skipping quantization checks.
+        self.static_eplb_enabled = False
         if self.custom_routing_function is None and self.e_score_correction_bias is not None:
             vllm_config = get_current_vllm_config()
             self.e_score_correction_bias.data = self.e_score_correction_bias.data.to(
                 dtype=vllm_config.model_config.dtype)
         # static eplb initializing with expert_map_path
+        init_eplb_enable = False
         if self.expert_map_path and os.path.exists(
                 self.expert_map_path) and os.access(self.expert_map_path,
                                                     os.R_OK):
@@ -189,6 +193,7 @@ def __init__(self, *args, **kwargs):
                         self.moe_instance_id, self.ep_rank))
                 self.log2phy = self.expert_load_balancer.get_rank_log2phy_map(
                     self.moe_instance_id, self.ep_rank).npu()
+                init_eplb_enable = True
             except Exception as e:
                 logger.warning(
                     f"Init expert map of mtp/eagle when using sample.{e}")
@@ -219,10 +224,10 @@ def __init__(self, *args, **kwargs):
             self.moe_load = torch.zeros(local_num_experts,
                                         dtype=torch.int64).npu()
 
-        eplb_enable = self.dynamic_eplb or (self.expert_map_path is not None)
-        if eplb_enable and (not hasattr(self.quant_method, "quant_method") or
-                            not isinstance(self.quant_method.quant_method,
-                                           AscendW8A8DynamicFusedMoEMethod)):
+        if init_eplb_enable and (
+                not hasattr(self.quant_method, "quant_method")
+                or not isinstance(self.quant_method.quant_method,
+                                  AscendW8A8DynamicFusedMoEMethod)):
             raise ValueError("Eplb supports only w8a8_dynamic quantization.")
 
         self.moe_config.num_experts = self.global_num_experts