[EPLB]

SignedFix ci.-off-by: offline0806 <z00858301@china.huawei.com>

Author: offline0806

vllm_ascend/ascend_config.py

@@ -49,7 +49,7 @@ def __init__(self, vllm_config):
             "expert_map_record_path",
             None)  # Provide path to export expert map
         self.init_redundancy_expert = additional_config.get(
-            "init_redundancy_expert",0)
+            "init_redundancy_expert", 0)
         self.dynamic_eplb = additional_config.get("dynamic_eplb", False)
         self.num_iterations_eplb_update = additional_config.get(
             "num_iterations_eplb_update", 400)

vllm_ascend/torchair/ops/torchair_fused_moe.py

@@ -37,12 +37,12 @@
     FusedMoE, UnquantizedFusedMoEMethod, determine_expert_map)
 from vllm.model_executor.layers.quantization.base_config import \
     QuantizationConfig
-from vllm_ascend.eplb.core.eplb_utils import (
-    determine_default_expert_map,
-    determine_default_log2phy_map)
+
 from vllm_ascend.ascend_config import get_ascend_config
 from vllm_ascend.ascend_forward_context import FusedMoEState
 from vllm_ascend.distributed.parallel_state import get_mc2_group
+from vllm_ascend.eplb.core.eplb_utils import (determine_default_expert_map,
+                                              determine_default_log2phy_map)
 from vllm_ascend.ops.expert_load_balancer import ExpertLoadBalancer
 from vllm_ascend.ops.sequence_parallel import MetadataForPadding
 from vllm_ascend.quantization.quant_config import AscendFusedMoEMethod
@@ -1080,7 +1080,8 @@ def __init__(
         assert self.quant_method is not None
 
         self.moe_load = None
-        local_num_experts = (torch.sum(self.expert_map != -1) if self.expert_map is not None else num_experts)
+        local_num_experts = (torch.sum(self.expert_map != -1)
+                             if self.expert_map is not None else num_experts)
         if self.dynamic_eplb:
             self.moe_load = torch.zeros(local_num_experts, dtype=torch.int64)