Merge pull request #2 from sywangyi/align_hub_change

fix the import error of

Author: jiqing-feng

optimum/intel/neural_compressor/configuration.py

@@ -17,7 +17,7 @@
 from functools import reduce
 from typing import Any, Optional, Union
 
-from transformers.file_utils import cached_path, hf_bucket_url
+from transformers.utils import cached_file
 
 import yaml
 from neural_compressor.conf.config import Conf, Distillation_Conf, Pruning_Conf, Quantization_Conf
@@ -97,16 +97,11 @@ def from_pretrained(cls, config_name_or_path: str, config_file_name: Optional[st
         revision = kwargs.get("revision", None)
 
         config_file_name = config_file_name if config_file_name is not None else CONFIG_NAME
-        if os.path.isdir(config_name_or_path):
-            config_file = os.path.join(config_name_or_path, config_file_name)
-        elif os.path.isfile(config_name_or_path):
-            config_file = config_name_or_path
-        else:
-            config_file = hf_bucket_url(config_name_or_path, filename=config_file_name, revision=revision)
 
         try:
-            resolved_config_file = cached_path(
-                config_file,
+            resolved_config_file = cached_file(
+                config_name_or_path,
+                config_file_name,
                 cache_dir=cache_dir,
                 force_download=force_download,
                 resume_download=resume_download,

optimum/intel/neural_compressor/quantization.py

@@ -33,7 +33,7 @@
     AutoModelForTokenClassification,
     XLNetLMHeadModel,
 )
-from transformers.file_utils import cached_path, hf_bucket_url
+from transformers.utils import cached_file
 from transformers.models.auto.auto_factory import _get_model_class
 from transformers.utils.versions import require_version
 
@@ -271,15 +271,9 @@ def from_pretrained(
 
             q_model_name = q_model_name if q_model_name is not None else WEIGHTS_NAME
             revision = download_kwargs.pop("revision", None)
-            if os.path.isdir(model_name_or_path):
-                state_dict_path = os.path.join(model_name_or_path, q_model_name)
-            elif os.path.isfile(model_name_or_path):
-                state_dict_path = model_name_or_path
-            else:
-                state_dict_path = hf_bucket_url(model_name_or_path, filename=q_model_name, revision=revision)
 
             try:
-                state_dict_path = cached_path(state_dict_path, **download_kwargs)
+                state_dict_path = cached_file(model_name_or_path, q_model_name, **download_kwargs)
             except EnvironmentError as err:
                 logger.error(err)
                 msg = (