refactoring

Author: eaidova

optimum/intel/openvino/modeling_base.py

@@ -619,13 +619,9 @@ def _from_transformers(
             )
             compile_only = False
 
-        ov_config = kwargs.get("ov_config")
-        if ov_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_config = None
-            else:
-                ov_config = OVConfig(dtype="fp32")
+        ov_config = kwargs.get("ov_export_config")
+        if ov_config is None and load_in_8bit is not None or quantization_config is not None:
+            ov_config = OVConfig(dtype="fp32")
 
         variant = kwargs.pop("variant", None)
 

optimum/intel/openvino/modeling_decoder.py

@@ -306,13 +306,9 @@ def _from_transformers(
             if use_cache:
                 task = task + "-with-past"
 
-        ov_export_config = kwargs.get("ov_config")
-        if ov_export_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_export_config = None
-            else:
-                ov_export_config = OVConfig(dtype="auto")
+        ov_export_config = kwargs.get("ov_export_config")
+        if ov_export_config is None and load_in_8bit is not None or quantization_config is not None:
+            ov_export_config = OVConfig(dtype="auto")
 
         stateful = kwargs.pop("stateful", ensure_stateful_is_available(warn=False) and use_cache)
 

optimum/intel/openvino/modeling_diffusion.py

@@ -605,15 +605,9 @@ def _from_transformers(
             )
             compile_only = False
 
-        ov_config = kwargs.get("ov_config")
-
-        if ov_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set
-            # to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_config = None
-            else:
-                ov_config = OVConfig(dtype="auto")
+        ov_config = kwargs.get("ov_export_config")
+        if ov_config is None and load_in_8bit is not None or quantization_config is not None:
+            ov_config = OVConfig(dtype="auto")
 
         torch_dtype = kwargs.pop("torch_dtype", None)
 

optimum/intel/openvino/modeling_open_clip.py

@@ -243,13 +243,9 @@ def _from_transformers(
         # would end-up removing the directory containing the underlying OpenVINO model
         cls._model_save_dir_tempdirectory_instance = save_dir
 
-        ov_config = kwargs.get("ov_config")
-        if ov_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_config = None
-            else:
-                ov_config = OVConfig(dtype="fp32")
+        ov_config = kwargs.get("ov_export_config")
+        if ov_config is None and load_in_8bit is not None or quantization_config is not None:
+            ov_config = OVConfig(dtype="fp32")
 
         def fn_get_submodels(model):
             return {"model_text": model.text}
@@ -370,14 +366,9 @@ def _from_transformers(
         # would end-up removing the directory containing the underlying OpenVINO model
         cls._model_save_dir_tempdirectory_instance = save_dir
 
-        ov_config = kwargs.get("ov_config")
-
-        if ov_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_config = None
-            else:
-                ov_config = OVConfig(dtype="fp32")
+        ov_config = kwargs.get("ov_export_config")
+        if ov_config is None and load_in_8bit is not None or quantization_config is not None:
+            ov_config = OVConfig(dtype="fp32")
 
         def fn_get_submodels(model):
             return {"model_vision": model.visual}

optimum/intel/openvino/modeling_seq2seq.py

@@ -602,13 +602,9 @@ def _from_transformers(
                 "Please provide openvino model obtained using optimum-cli or saved on disk using `save_pretrained`"
             )
             compile_only = False
-        ov_config = kwargs.get("ov_config")
-        if ov_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_config = None
-            else:
-                ov_config = OVConfig(dtype="fp32")
+        ov_config = kwargs.get("ov_export_config")
+        if ov_config is None and (load_in_8bit is not None or quantization_config is not None):
+            ov_config = OVConfig(dtype="fp32")
         stateful = kwargs.get("stateful", True)
         variant = kwargs.pop("variant", None)
 

optimum/intel/openvino/modeling_visual_language.py

@@ -660,14 +660,10 @@ def _from_transformers(
         if task is None:
             task = cls.export_feature
 
-        ov_config = kwargs.get("ov_config")
-        if ov_config is None:
-            # If load_in_8bit and quantization_config not specified then ov_config is set to None and will be set by default in convert depending on the model size
-            if load_in_8bit is None and not quantization_config:
-                ov_config = None
-            else:
-                # Export in fp32 if compression won't be applied later
-                ov_config = OVConfig(dtype="fp32" if load_in_8bit is False else "auto")
+        ov_config = kwargs.get("ov_export_config")
+        if ov_config is None and (load_in_8bit is not None or quantization_config is None):
+            # Export in fp32 if compression won't be applied later
+            ov_config = OVConfig(dtype="fp32" if load_in_8bit is False else "auto")
 
         stateful = kwargs.pop("stateful", ensure_stateful_is_available(warn=False) and use_cache)
         variant = kwargs.pop("variant", None)