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

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### 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 <3337230449@qq.com>
Signed-off-by: offline893 <158537145+offline893@users.noreply.github.com>
Co-authored-by: offline0806 <3337230449@qq.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
This commit is contained in:
offline893
2025-12-05 21:15:32 +08:00
committed by GitHub
parent c4a11a745a
commit 350999c4ef
1 changed files with 9 additions and 4 deletions
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13
vllm_ascend/ops/common_fused_moe.py
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@@ -169,11 +169,15 @@ class AscendFusedMoE(FusedMoE):
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 @@ class AscendFusedMoE(FusedMoE):
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 @@ class AscendFusedMoE(FusedMoE):
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