[Bugfix] Fix BNB loader target_modules (vllm-project#10720)

Signed-off-by: Jee Jee Li <[email protected]>

vllm/model_executor/model_loader/loader.py

@@ -6,7 +6,6 @@
 import glob
 import inspect
 import itertools
-import json
 import math
 import os
 import warnings
@@ -18,7 +17,7 @@
 import huggingface_hub
 import numpy as np
 import torch
-from huggingface_hub import HfApi, hf_hub_download
+from huggingface_hub import HfApi
 from torch import nn
 from transformers import AutoModelForCausalLM
 from transformers.utils import SAFE_WEIGHTS_INDEX_NAME
@@ -704,51 +703,9 @@ def __init__(self, load_config: LoadConfig):
         self.unsharded_weights_modules: List[str] = []
         # Save the module names that are sharded by column.
         self.column_sharded_weights_modules: List[str] = []
-        # we don't need to quantize the whole model, only the target modules
-        # that are specified in the adapter config file. If the adapter config
-        # file is not provided, we will quantize the default modules.
-        if (not load_config.model_loader_extra_config
-                or "qlora_adapter_name_or_path"
-                not in load_config.model_loader_extra_config):
-            self.target_modules = []
-            return
-
-        qlora_adapter = load_config.model_loader_extra_config[
-            "qlora_adapter_name_or_path"]
-
-        config_file_path = self._get_config_file(qlora_adapter)
-
-        with open(config_file_path) as f:
-            config = json.load(f)
-            self.target_modules = config["target_modules"]
-            # TODO: target_modules could be either a list or a regex string.
-            # We need to handle both cases.
-            assert isinstance(self.target_modules,
-                              list), "Unsupported target_modules: "
-            f"{self.target_modules}"
-
-    def _get_config_file(self, qlora_adapter: str) -> str:
-        is_local = os.path.isdir(qlora_adapter)
-        config_file_path = None
-        if is_local:
-            for file in self.possible_config_file_names:
-                config_file_path = os.path.join(qlora_adapter, file)
-                if os.path.exists(config_file_path):
-                    break
-        else:
-            hf_api = HfApi()
-            repo_files = hf_api.list_repo_files(repo_id=qlora_adapter)
-            for file in self.possible_config_file_names:
-                if file in repo_files:
-                    config_file_path = hf_hub_download(repo_id=qlora_adapter,
-                                                       filename=file)
-                    break
-
-        if not config_file_path:
-            raise ValueError(
-                f"Cannot find adapter config file in {qlora_adapter}")
-
-        return config_file_path
+        # Store all module names (from transformers) that support
+        # BNB quantization.
+        self.target_modules: List[str] = []
 
     def _get_weight_files(
         self,
@@ -1030,25 +987,16 @@ def _get_bnb_target_modules(self, model: nn.Module) -> None:
                 inverse_stacked_mapping[packed] = []
             inverse_stacked_mapping[packed].insert(idx, orig)
 
-        linear_module_lst = []
         for name, module in model.named_modules():
             if isinstance(module, (LinearBase, )):
                 last_name = name.split(".")[-1]
                 if sub_modules := inverse_stacked_mapping.get(last_name, []):
                     # Map vllm's names to transformers' names.
                     for sub_name in sub_modules:
-                        linear_module_lst.append(
+                        self.target_modules.append(
                             name.replace(last_name, sub_name))
                 else:
-                    linear_module_lst.append(name)
-        if self.target_modules:
-            # Update self.target_modules
-            self.target_modules = [
-                qual_name for qual_name in linear_module_lst
-                if any(t in qual_name for t in self.target_modules)
-            ]
-        else:
-            self.target_modules = linear_module_lst
+                    self.target_modules.append(name)
         assert (self.target_modules
                 ), "vllm currently does not support BNB quantization for"
         f" {type(model).__name__}"