feat: resolve precommit

Signed-off-by: Brayden Zhong <b8zhong@uwaterloo.ca>

Author: b8zhong

vllm/model_executor/models/llama4.py

@@ -444,7 +444,7 @@ def load_moe_expert_weights(
 
             loaded_params.add(full_param_name)
             expert_param_loaded = True
-            is_expert = True
+            is_expert = True  # noqa: F841
         return expert_param_loaded
 
     def load_weights(self, weights: Iterable[tuple[str,
@@ -474,7 +474,7 @@ def load_weights(self, weights: Iterable[tuple[str,
         loaded_params: set[str] = set()
         for name, loaded_weight in weights:
             if "experts.gate_up_proj" in name or "experts.down_proj" in name:
-                fused_experts_params = True
+                fused_experts_params = True  # noqa: F841
                 expert_params_mapping = expert_params_mapping_fused
             if (self.quant_config is not None and
                 (scale_name := self.quant_config.get_cache_scale(name))):
@@ -508,7 +508,7 @@ def load_weights(self, weights: Iterable[tuple[str,
                     weight_loader(param, loaded_weight)
                 else:
                     weight_loader(param, loaded_weight, shard_id)
-                is_expert = False
+                is_expert = False  # noqa: F841
                 loaded_params.add(name)
                 break
             else:
@@ -544,7 +544,7 @@ def load_weights(self, weights: Iterable[tuple[str,
                                   shard_id=shard_id,
                                   expert_id=expert_id)
                     loaded_params.add(name_mapped)
-                    is_expert = True
+                    is_expert = True  # noqa: F841
                     break
                 else:
                     # If we've identified this as an expert weight but couldn't
@@ -593,15 +593,14 @@ def load_weights(self, weights: Iterable[tuple[str,
                             # Regular weight loader (handles both
                             # param.weight_loader and default_weight_loader)
                             weight_loader(param, loaded_weight)
-                        is_expert = True
+                        is_expert = True  # noqa: F841
                         loaded_params.add(name)
                         continue
 
                     param = params_dict[name]
                     weight_loader = getattr(param, "weight_loader",
                                             default_weight_loader)
                     weight_loader(param, loaded_weight)
-                    is_expert = False
                     loaded_params.add(name)
         return loaded_params