Update import message

Signed-off-by: Cheng, Penghui <penghui.cheng@intel.com>

Author: PenghuiCheng

examples/neural_compressor/language-modeling/run_clm.py

@@ -57,7 +57,10 @@
 from transformers.utils.versions import require_version
 
 from optimum.intel.neural_compressor import INCModelForCausalLM, INCQuantizer, INCTrainer
-from optimum.intel.utils.import_utils import is_intel_extension_for_transformers_available
+from optimum.intel.utils.import_utils import (
+    INTEL_EXTENSION_FOR_TRANSFORMERS_IMPORT_ERROR,
+    is_intel_extension_for_transformers_available,
+)
 
 
 if is_intel_extension_for_transformers_available():
@@ -656,10 +659,7 @@ def compute_metrics(eval_preds):
                 recipes = {}
             if optim_args.quantization_approach == "weight_only":
                 if not is_intel_extension_for_transformers_available():
-                    raise ImportError(
-                        "Didn't find out intel-etension-for-transformers package. "
-                        "Please install packages: pip install intel-etension-for-transformers and pip install peft."
-                    )
+                    raise ImportError(INTEL_EXTENSION_FOR_TRANSFORMERS_IMPORT_ERROR.format("WeightOnly quantization"))
                 if optim_args.apply_pruning or optim_args.apply_distillation:
                     raise ValueError("Weight only quantization and pruning or distillation cannot be combined.")
                 if optim_args.quantization_methodology == "GPTQ":

optimum/intel/neural_compressor/modeling_base.py

@@ -43,7 +43,12 @@
 from optimum.intel.generation import BaseModelForCausalLM
 
 from ...modeling_base import OptimizedModel
-from ..utils.import_utils import _torch_version, is_intel_extension_for_transformers_available, is_torch_version
+from ..utils.import_utils import (
+    _torch_version,
+    is_intel_extension_for_transformers_available,
+    is_torch_version,
+    requires_backends,
+)
 from .configuration import INCConfig
 from .utils import WEIGHTS_NAME
 
@@ -137,15 +142,11 @@ def _from_pretrained(
         inc_config = None
         msg = None
         try:
+            requires_backends(cls, ["intel_extension_for_transformers"])
             quantization_config = WeightOnlyQuantConfig.from_pretrained(model_id)
             if getattr(
                 quantization_config, "algorithm", None
             ) is not None and quantization_config.algorithm.lower() in ["rtn", "gptq", "awq", "autoaround"]:
-                if not is_intel_extension_for_transformers_available():
-                    raise ImportError(
-                        "Didn't find out intel-etension-for-transformers package. "
-                        "Please install packages: pip install intel-etension-for-transformers and pip install peft."
-                    )
                 return ITREX_WOQ_MODEL.from_pretrained(
                     pretrained_model_name_or_path=model_id,
                     use_auth_token=use_auth_token,

optimum/intel/utils/import_utils.py

@@ -66,6 +66,7 @@
 if _intel_extension_for_transformers_available:
     try:
         _intel_extension_for_transformers_version = importlib_metadata.version("intel_extension_for_transformers")
+        logging.warn("`transformers` version >= 4.31 is requirements by intel-extension-for-transformers.")
     except importlib_metadata.PackageNotFoundError:
         _intel_extension_for_transformers_available = False
 
@@ -350,7 +351,7 @@ def is_timm_version(operation: str, version: str):
 
 INTEL_EXTENSION_FOR_TRANSFORMERS_IMPORT_ERROR = """
 {0} requires the intel-extension-for-transformers library but it was not found in your environment. You can install it with pip:
-`pip install intel-extension-for-transformers`. Please note that you may need to restart your runtime after installation.
+`pip install intel-extension-for-transformers` and `pip install peft`. Please note that you may need to restart your runtime after installation.
 """
 
 DATASETS_IMPORT_ERROR = """