diff --git a/neural_compressor/model/tensorflow_model.py b/neural_compressor/model/tensorflow_model.py
index c9a92220b5d..063b95ab052 100644
--- a/neural_compressor/model/tensorflow_model.py
+++ b/neural_compressor/model/tensorflow_model.py
@@ -313,17 +313,10 @@ def load_saved_model(model, saved_model_tags, input_tensor_names, output_tensor_
 def _get_graph_from_saved_model_v2(saved_model_dir, input_tensor_names, output_tensor_names):
     from tensorflow.python.saved_model import signature_constants, tag_constants
 
-    from neural_compressor.adaptor.tf_utils.util import parse_saved_model
-
     saved_model_exported_names = [signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY]
     saved_model_tags = set([tag_constants.SERVING])
-    try:
-        graph_def, _saved_model, _, _, input_names, output_names = parse_saved_model(
-            saved_model_dir, True, input_tensor_names, output_tensor_names
-        )
-    except:
-        return load_saved_model(saved_model_dir, saved_model_tags, input_tensor_names, output_tensor_names)
-    return graph_def, input_names, output_names
+
+    return load_saved_model(saved_model_dir, saved_model_tags, input_tensor_names, output_tensor_names)
 
 
 def _get_graph_from_original_keras_v2(model, output_dir):
@@ -467,6 +460,15 @@ def keras_session(model, input_tensor_names, output_tensor_names, **kwargs):
             try:
                 tf.keras.backend.set_learning_phase(0)
                 graph_def, input_names, output_names = _get_graph_from_saved_model_v1(model)
+            except:
+                keras_format = "saved_model_general"
+        if keras_format == "saved_model_general":  # pargma: no cover
+            try:
+                from neural_compressor.adaptor.tf_utils.util import parse_saved_model
+
+                graph_def, _saved_model, _, _, input_names, output_names = parse_saved_model(
+                    temp_dir, True, input_tensor_names, output_tensor_names
+                )
             except:
                 raise ValueError("Not supported keras model type...")