Merge pull request vllm-project#8 from Snowflake-Labs/remove-dummy

remove dummy path in arctic

vllm/model_executor/models/arctic.py

@@ -481,53 +481,49 @@ def load_weights(self, weights: Iterable[Tuple[str, torch.Tensor]]):
 
         params_dict = dict(self.named_parameters())
 
-        if use_dummy:
-            logger.info("Using dummy weights. Skip loading weights.")
-        else:
-            logger.info(
-                "It takes ~10 minutes to load the weights. Please be patient.")
-            for name, loaded_weight in weights:
-                for (param_name, weight_name,
-                     shard_id) in stacked_params_mapping:
+        logger.info(
+            "It takes ~10 minutes to load the weights. Please be patient.")
+        for name, loaded_weight in weights:
+            for (param_name, weight_name,
+                    shard_id) in stacked_params_mapping:
+                if weight_name not in name:
+                    continue
+                name = name.replace(weight_name, param_name)
+                # Skip loading extra bias for GPTQ models.
+                if name.endswith(".bias") and name not in params_dict:
+                    continue
+                param = params_dict[name]
+                weight_loader = param.weight_loader
+                weight_loader(param, loaded_weight, shard_id)
+                break
+            else:
+                for param_name, weight_name, shard_id in mlp_params_mapping:
                     if weight_name not in name:
                         continue
                     name = name.replace(weight_name, param_name)
-                    # Skip loading extra bias for GPTQ models.
-                    if name.endswith(".bias") and name not in params_dict:
-                        continue
                     param = params_dict[name]
                     weight_loader = param.weight_loader
                     weight_loader(param, loaded_weight, shard_id)
                     break
                 else:
-                    for param_name, weight_name, shard_id in mlp_params_mapping:
+                    for param_name, weight_name, shard_id \
+                            in expert_params_mapping:
                         if weight_name not in name:
                             continue
                         name = name.replace(weight_name, param_name)
                         param = params_dict[name]
                         weight_loader = param.weight_loader
-                        weight_loader(param, loaded_weight, shard_id)
+                        weight_loader(param,
+                                        loaded_weight,
+                                        weight_name,
+                                        expert_id=shard_id)
                         break
                     else:
-                        for param_name, weight_name, shard_id \
-                                in expert_params_mapping:
-                            if weight_name not in name:
-                                continue
-                            name = name.replace(weight_name, param_name)
-                            param = params_dict[name]
-                            weight_loader = param.weight_loader
-                            weight_loader(param,
-                                          loaded_weight,
-                                          weight_name,
-                                          expert_id=shard_id)
-                            break
-                        else:
-                            if name.endswith(
-                                    ".bias") and name not in params_dict:
-                                continue
-                            param = params_dict[name]
-
-                            weight_loader = getattr(param, "weight_loader",
-                                                    default_weight_loader)
-                            weight_loader(param, loaded_weight)
+                        if name.endswith(
+                                ".bias") and name not in params_dict:
+                            continue
+                        param = params_dict[name]
 
+                        weight_loader = getattr(param, "weight_loader",
+                                                default_weight_loader)
+                        weight_loader(param, loaded_weight)