@@ -122,9 +122,10 @@ def forward(
122122
123123    def  load_fused_expert_weights (self , name : str , params_dict : dict ,
124124                                  loaded_weight : torch .Tensor , shard_id : str ,
125-                                   num_experts : int ):
125+                                   num_experts : int )  ->   bool :
126126        param  =  params_dict [name ]
127127        weight_loader  =  typing .cast (Callable [..., bool ], param .weight_loader )
128+         loaded_local_expert  =  False 
128129        for  expert_id  in  range (num_experts ):
129130            curr_expert_weight  =  loaded_weight [expert_id ]
130131            success  =  weight_loader (param ,
@@ -133,9 +134,10 @@ def load_fused_expert_weights(self, name: str, params_dict: dict,
133134                                    shard_id ,
134135                                    expert_id ,
135136                                    return_success = True )
136-             if  not  success :
137-                 return  False 
138-         return  True 
137+             if  success :
138+                 loaded_local_expert  =  True 
139+ 
140+         return  loaded_local_expert 
139141
140142    def  load_weights (self , weights : Iterable [tuple [str ,
141143                                                   torch .Tensor ]]) ->  set [str ]:
@@ -345,4 +347,4 @@ def __init__(self, *, vllm_config: VllmConfig, prefix: str = ""):
345347            for  _  in  range (self .deepstack_num_level )
346348        ] if  self .use_deepstack  else  None 
347349        self .visual_dim  =  config .vision_config .out_hidden_size 
348-         self .multiscale_dim  =  self .visual_dim  *  self .deepstack_num_level 
350+         self .multiscale_dim  =  self .visual_dim  *  self .deepstack_num_level 
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