diff --git a/tests/onnx/test_auto_scan_unsqueeze.py b/tests/onnx/test_auto_scan_unsqueeze_13.py
similarity index 60%
rename from tests/onnx/test_auto_scan_unsqueeze.py
rename to tests/onnx/test_auto_scan_unsqueeze_13.py
index 169252f9766e3fad600ec29def244419c9aa84ef..b73d7fdd1772f7312608be0a7dd9a0c9eca94953 100644
--- a/tests/onnx/test_auto_scan_unsqueeze.py
+++ b/tests/onnx/test_auto_scan_unsqueeze_13.py
@@ -15,66 +15,11 @@
 from auto_scan_test import OPConvertAutoScanTest
 from hypothesis import reproduce_failure
 import hypothesis.strategies as st
-import onnx
-from onnx import helper
-from onnx import TensorProto
 import numpy as np
 import unittest
 
 
-class TestUnsqueezeConvert0(OPConvertAutoScanTest):
-    """
-    ONNX op: Unsqueeze
-    OPset version: 7~12
-    """
-
-    def sample_convert_config(self, draw):
-        input_shape = draw(
-            st.lists(
-                st.integers(
-                    min_value=2, max_value=6), min_size=2, max_size=5))
-
-        input_dtype = draw(
-            st.sampled_from(["int32", "int64", "float32", "float64"]))
-
-        axis = draw(
-            st.integers(
-                min_value=-len(input_shape), max_value=len(input_shape) - 1))
-
-        if len(input_shape) == 5:
-            axis = [0]
-        if len(input_shape) == 4:
-            axis = [0, 1]
-        if len(input_shape) == 3:
-            axis = [1, 2, 3]
-        if len(input_shape) == 2:
-            if draw(st.booleans()):
-                axis = [0, 1, 2]
-            else:
-                axis = [1, 3]
-
-        config = {
-            "op_names": ["Unsqueeze"],
-            "test_data_shapes": [input_shape],
-            "test_data_types": [[input_dtype]],
-            "inputs_shape": [input_shape],
-            "min_opset_version": 7,
-            "max_opset_version": 12,
-            "inputs_name": ["x"],
-            "outputs_name": ["y"],
-            "delta": 1e-4,
-            "rtol": 1e-4
-        }
-
-        attrs = {"axes": axis, }
-
-        return (config, attrs)
-
-    def test(self):
-        self.run_and_statis(max_examples=30)
-
-
-class TestUnsqueezeConvert1(OPConvertAutoScanTest):
+class TestUnsqueezeConvert(OPConvertAutoScanTest):
     """
     ONNX op: Unsqueeze
     OPset version: 13~15
diff --git a/tests/onnx/test_auto_scan_unsqueeze_7.py b/tests/onnx/test_auto_scan_unsqueeze_7.py
new file mode 100644
index 0000000000000000000000000000000000000000..db837dd3ab7dfe42124e7b8583da451639992453
--- /dev/null
+++ b/tests/onnx/test_auto_scan_unsqueeze_7.py
@@ -0,0 +1,75 @@
+# Copyright (c) 2022  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from auto_scan_test import OPConvertAutoScanTest
+from hypothesis import reproduce_failure
+import hypothesis.strategies as st
+import numpy as np
+import unittest
+
+
+class TestUnsqueezeConvert(OPConvertAutoScanTest):
+    """
+    ONNX op: Unsqueeze
+    OPset version: 7~12
+    """
+
+    def sample_convert_config(self, draw):
+        input_shape = draw(
+            st.lists(
+                st.integers(
+                    min_value=2, max_value=6), min_size=2, max_size=5))
+
+        input_dtype = draw(
+            st.sampled_from(["int32", "int64", "float32", "float64"]))
+
+        axis = draw(
+            st.integers(
+                min_value=-len(input_shape), max_value=len(input_shape) - 1))
+
+        if len(input_shape) == 5:
+            axis = [0]
+        if len(input_shape) == 4:
+            axis = [0, 1]
+        if len(input_shape) == 3:
+            axis = [1, 2, 3]
+        if len(input_shape) == 2:
+            if draw(st.booleans()):
+                axis = [0, 1, 2]
+            else:
+                axis = [1, 3]
+
+        config = {
+            "op_names": ["Unsqueeze"],
+            "test_data_shapes": [input_shape],
+            "test_data_types": [[input_dtype]],
+            "inputs_shape": [input_shape],
+            "min_opset_version": 7,
+            "max_opset_version": 12,
+            "inputs_name": ["x"],
+            "outputs_name": ["y"],
+            "delta": 1e-4,
+            "rtol": 1e-4
+        }
+
+        attrs = {"axes": axis, }
+
+        return (config, attrs)
+
+    def test(self):
+        self.run_and_statis(max_examples=30)
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/x2paddle/convert.py b/x2paddle/convert.py
index 7ddaf8c01afac8c3fa0d31e7554b53444c77b90f..a14a0af1a98b96992ba3e773a3dd3889b3f86919 100644
--- a/x2paddle/convert.py
+++ b/x2paddle/convert.py
@@ -95,6 +95,11 @@ def arg_parser():
         "-co",
         default=True,
         help="Turn on code optimization")
+    parser.add_argument(
+        "--enable_onnx_checker",
+        "-oc",
+        default=True,
+        help="Turn on onnx model checker")
     parser.add_argument(
         "--disable_feedback",
         "-df",
@@ -479,7 +484,8 @@ def main():
                 convert_to_lite=args.to_lite,
                 lite_valid_places=args.lite_valid_places,
                 lite_model_type=args.lite_model_type,
-                disable_feedback=args.disable_feedback)
+                disable_feedback=args.disable_feedback,
+                enable_onnx_checker=args.enable_onnx_checker)
         elif args.framework == "paddle2onnx":
             logging.info(
                 "Paddle to ONNX tool has been migrated to the new github: https://github.com/PaddlePaddle/paddle2onnx"