fix mypy error

Signed-off-by: kewang2 <kewang2@amd.com>

vllm/model_executor/layers/quantization/base_config.py

@@ -134,5 +134,5 @@ def get_quant_method(self, layer: torch.nn.Module,
         """
         raise NotImplementedError
 
-    def get_cache_scale(self, name: str) -> Optional[List[str]]:
+    def get_cache_scale(self, name: str) -> Optional[str]:
         return None

vllm/model_executor/layers/quantization/compressed_tensors/compressed_tensors.py

@@ -336,7 +336,7 @@ def get_scheme(
     # utils.py to instance method of CompressedTensorsConfig
     # class. By doing this, different QuantizationConfig
     # classes can implement their own get_cache_scale method.
-    def get_cache_scale(self, name: str) -> Optional[List[str]]:
+    def get_cache_scale(self, name: str) -> Optional[str]:
         """
         Check whether the param name matches the format for k/v cache scales
         in compressed-tensors. If this is the case, return its equivalent

vllm/model_executor/layers/quantization/quark/quark.py

@@ -79,10 +79,10 @@ def from_config(cls, config: Dict[str, Any]) -> "QuarkConfig":
         kv_cache_group = cast(List[str], export_config.get("kv_cache_group"))
         pack_method = cast(str, export_config.get("pack_method"))
 
-        # In the export model of quark, the quantization configuration 
-        # of kv_cache is stored in layer_quant_config. First, it is 
-        # judged whether kv_cache_group exists, and then it is judged 
-        # whether layer_quant_config has a quantization configuration 
+        # In the export model of quark, the quantization configuration
+        # of kv_cache is stored in layer_quant_config. First, it is
+        # judged whether kv_cache_group exists, and then it is judged
+        # whether layer_quant_config has a quantization configuration
         # that matches kv_cache.
         if len(kv_cache_group) == 0:
             kv_cache_config = None
@@ -277,7 +277,7 @@ def get_scheme(self, layer: torch.nn.Module,
 
         return scheme
 
-    def get_cache_scale(self, name: str) -> Optional[List[str]]:
+    def get_cache_scale(self, name: str) -> Optional[str]:
         """
         Check whether the param name matches the format for k/v cache scales
         in quark. If this is the case, return its equivalent param name 
@@ -300,9 +300,11 @@ def get_cache_scale(self, name: str) -> Optional[List[str]]:
             elif len(kv_proj_names) == 2:
                 for kv_proj_name in kv_proj_names:
                     if kv_proj_name in name and kv_proj_name == "k_proj":
-                        return name.replace(".k_proj.output_scale", ".attn.k_scale")
+                        return name.replace(".k_proj.output_scale",
+                                            ".attn.k_scale")
                     elif kv_proj_name in name and kv_proj_name == "v_proj":
-                        return name.replace(".v_proj.output_scale", ".attn.v_scale")
+                        return name.replace(".v_proj.output_scale",
+                                            ".attn.v_scale")
 
         # If no matches, return None
         return None

vllm/model_executor/models/aria.py

@@ -395,8 +395,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/commandr.py

@@ -442,8 +442,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/dbrx.py

@@ -457,8 +457,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/exaone.py

@@ -546,8 +546,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/gpt_j.py

@@ -321,8 +321,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/granite.py

@@ -488,8 +488,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/llama.py

@@ -396,8 +396,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/mixtral.py

@@ -436,8 +436,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/mllama.py

@@ -1438,8 +1438,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 updated_params.add(scale_name)
                 continue

vllm/model_executor/models/nemotron.py

@@ -503,8 +503,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/phimoe.py

@@ -631,8 +631,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/qwen2.py

@@ -375,8 +375,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue

vllm/model_executor/models/solar.py

@@ -505,8 +505,8 @@ def load_weights(self, weights: Iterable[Tuple[str,
                 param = params_dict[scale_name]
                 weight_loader = getattr(param, "weight_loader",
                                         default_weight_loader)
-                loaded_weight = (loaded_weight if loaded_weight.dim() == 0
-                                    else loaded_weight[0])
+                loaded_weight = (loaded_weight if loaded_weight.dim() == 0 else
+                                 loaded_weight[0])
                 weight_loader(param, loaded_weight)
                 loaded_params.add(scale_name)
                 continue