Extra check for if the files exists

Signed-off-by: Flavia Beo <[email protected]>

vllm/engine/llm_engine.py

@@ -280,8 +280,7 @@ def __init__(
             model_config.pooling_config.normalize
             if model_config.pooling_config is not None else None,
             model_config.chat_template_text_format,
-            model_config.mm_processor_kwargs
-        )
+            model_config.mm_processor_kwargs)
         # TODO(woosuk): Print more configs in debug mode.
         self.model_config = model_config
         self.cache_config = cache_config

vllm/transformers_utils/config.py

@@ -205,7 +205,7 @@ def get_config(
                     raise e
 
     elif config_format == ConfigFormat.MISTRAL:
-        config = load_params_config(model, revision)
+        config = load_params_config(model, revision, token=kwargs.get("token"))
     else:
         raise ValueError(f"Unsupported config format: {config_format}")
 
@@ -235,7 +235,10 @@ def get_config(
     return config
 
 
-def get_hf_file_to_dict(file_name, model, revision):
+def get_hf_file_to_dict(file_name,
+                        model,
+                        revision,
+                        token: Optional[str] = None):
     """
     Downloads a file from the Hugging Face Hub and returns 
     its contents as a dictionary.
@@ -244,29 +247,39 @@ def get_hf_file_to_dict(file_name, model, revision):
     - file_name (str): The name of the file to download.
     - model (str): The name of the model on the Hugging Face Hub.
     - revision (str): The specific version of the model. 
+    - token (str): The Hugging Face authentication token.
 
     Returns:
     - config_dict (dict): A dictionary containing 
     the contents of the downloaded file.
     """
     file_path = Path(model) / file_name
 
-    if not file_path.is_file():
-        try:
-            hf_hub_file = hf_hub_download(model, file_name, revision=revision)
-        except (RepositoryNotFoundError, RevisionNotFoundError,
-                EntryNotFoundError, LocalEntryNotFoundError) as e:
-            logger.debug("File or repository not found in hf_hub_download", e)
-            return None
-        file_path = Path(hf_hub_file)
-
-    with open(file_path, "r") as file:
-        config_dict = json.load(file)
+    if file_or_path_exists(model=model,
+                           config_name=file_name,
+                           revision=revision,
+                           token=token):
 
-    return config_dict
+        if not file_path.is_file():
+            try:
+                hf_hub_file = hf_hub_download(model,
+                                              file_name,
+                                              revision=revision)
+            except (RepositoryNotFoundError, RevisionNotFoundError,
+                    EntryNotFoundError, LocalEntryNotFoundError) as e:
+                logger.debug("File or repository not found in hf_hub_download",
+                             e)
+                return None
+            file_path = Path(hf_hub_file)
+
+        with open(file_path, "r") as file:
+            config_dict = json.load(file)
+
+        return config_dict
+    return None
 
 
-def get_pooling_config(model, revision='main'):
+def get_pooling_config(model, revision='main', token: Optional[str] = None):
     """
     This function gets the pooling and normalize 
     config from the model - only applies to 
@@ -283,7 +296,8 @@ def get_pooling_config(model, revision='main'):
     """
 
     modules_file_name = "modules.json"
-    modules_dict = get_hf_file_to_dict(modules_file_name, model, revision)
+    modules_dict = get_hf_file_to_dict(modules_file_name, model, revision,
+                                       token)
 
     if modules_dict is None:
         return None
@@ -299,7 +313,8 @@ def get_pooling_config(model, revision='main'):
     if pooling:
 
         pooling_file_name = "{}/config.json".format(pooling["path"])
-        pooling_dict = get_hf_file_to_dict(pooling_file_name, model, revision)
+        pooling_dict = get_hf_file_to_dict(pooling_file_name, model, revision,
+                                           token)
         pooling_type_name = next(
             (item for item, val in pooling_dict.items() if val is True), None)
 
@@ -308,7 +323,9 @@ def get_pooling_config(model, revision='main'):
     return None
 
 
-def get_sentence_transformer_tokenizer_config(model, revision='main'):
+def get_sentence_transformer_tokenizer_config(model,
+                                              revision='main',
+                                              token: Optional[str] = None):
     """
     Returns the tokenization configuration dictionary for a 
     given Sentence Transformer BERT model.
@@ -318,6 +335,7 @@ def get_sentence_transformer_tokenizer_config(model, revision='main'):
     BERT model.
     - revision (str, optional): The revision of the m
     odel to use. Defaults to 'main'.
+    - token (str): A Hugging Face access token.
 
     Returns:
     - dict: A dictionary containing the configuration parameters 
@@ -332,7 +350,7 @@ def get_sentence_transformer_tokenizer_config(model, revision='main'):
             "sentence_xlm-roberta_config.json",
             "sentence_xlnet_config.json",
     ]:
-        bert_dict = get_hf_file_to_dict(config_name, model, revision)
+        bert_dict = get_hf_file_to_dict(config_name, model, revision, token)
         if bert_dict:
             break
 
@@ -406,13 +424,15 @@ def _reduce_modelconfig(mc: ModelConfig):
             exc_info=e)
 
 
-def load_params_config(model, revision) -> PretrainedConfig:
+def load_params_config(model,
+                       revision,
+                       token: Optional[str] = None) -> PretrainedConfig:
     # This function loads a params.json config which
     # should be used when loading models in mistral format
 
     config_file_name = "params.json"
 
-    config_dict = get_hf_file_to_dict(config_file_name, model, revision)
+    config_dict = get_hf_file_to_dict(config_file_name, model, revision, token)
 
     config_mapping = {
         "dim": "hidden_size",