Fix default ov config (#600)

huggingface · Mar 11, 2024 · 36459a1 · 36459a1
1 parent 5c683a3
commit 36459a1
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Showing 5 changed files with 9 additions and 9 deletions.
diff --git a/optimum/intel/openvino/modeling.py b/optimum/intel/openvino/modeling.py
@@ -434,8 +434,8 @@ def _from_transformers(
         save_dir = TemporaryDirectory()
         save_dir_path = Path(save_dir.name)
 
-        # If load_in_8bit or 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 or not quantization_config:
+        # 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")

diff --git a/optimum/intel/openvino/modeling_base.py b/optimum/intel/openvino/modeling_base.py
@@ -314,8 +314,8 @@ def _from_transformers(
         save_dir = TemporaryDirectory()
         save_dir_path = Path(save_dir.name)
 
-        # If load_in_8bit or 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 or not quantization_config:
+        # 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")

diff --git a/optimum/intel/openvino/modeling_base_seq2seq.py b/optimum/intel/openvino/modeling_base_seq2seq.py
@@ -258,8 +258,8 @@ def _from_transformers(
             if use_cache:
                 task = task + "-with-past"
 
-        # If load_in_8bit or 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 or not quantization_config:
+        # 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")

diff --git a/optimum/intel/openvino/modeling_decoder.py b/optimum/intel/openvino/modeling_decoder.py
@@ -260,7 +260,7 @@ def _from_transformers(
             if use_cache:
                 task = task + "-with-past"
 
-        # If load_in_8bit or 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 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:

diff --git a/optimum/intel/openvino/modeling_diffusion.py b/optimum/intel/openvino/modeling_diffusion.py
@@ -321,8 +321,8 @@ def _from_transformers(
         save_dir = TemporaryDirectory()
         save_dir_path = Path(save_dir.name)
 
-        # If load_in_8bit or 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 or not quantization_config:
+        # 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")