Fixed type check in convert_model(). (#14472)

* Fixed passing Path to convert_model().

* Update tools/mo/openvino/tools/mo/convert_impl.py

Co-authored-by: Ekaterina Aidova <ekaterina.aidova@intel.com>

Co-authored-by: Ekaterina Aidova <ekaterina.aidova@intel.com>

tools/mo/openvino/tools/mo/convert_impl.py

@@ -9,6 +9,7 @@ import platform
 import sys
 from collections import OrderedDict
 from copy import deepcopy
+from pathlib import Path
 
 import numpy as np
 
@@ -831,7 +832,7 @@ def show_mo_convert_help():
 
 
 def input_model_is_object(argv):
-    if isinstance(argv['input_model'], str):
+    if isinstance(argv['input_model'], (str, Path)):
         return False
     if argv['input_model'] is None:
         return False

tools/mo/unit_tests/mo/convert/import_from_mo_test.py

@@ -3,8 +3,8 @@
 
 import os
 import tempfile
+from pathlib import Path
 
-import numpy as np
 from generator import generator, generate
 from openvino.runtime import serialize
 
@@ -19,6 +19,66 @@ from utils import create_onnx_model, save_to_onnx
 class ConvertImportMOTest(UnitTestWithMockedTelemetry):
     test_directory = os.path.dirname(os.path.realpath(__file__))
 
+    @staticmethod
+    def create_onnx_model():
+        #
+        #   Create ONNX model
+        #
+
+        import onnx
+        from onnx import helper
+        from onnx import TensorProto
+
+        shape = [1, 2, 3]
+
+        input = helper.make_tensor_value_info('input', TensorProto.FLOAT, shape)
+        output = helper.make_tensor_value_info('output', TensorProto.FLOAT, shape)
+
+        node_def = onnx.helper.make_node(
+            'Relu',
+            inputs=['input'],
+            outputs=['Relu_out'],
+        )
+        node_def2 = onnx.helper.make_node(
+            'Sigmoid',
+            inputs=['Relu_out'],
+            outputs=['output'],
+        )
+
+        # Create the graph (GraphProto)
+        graph_def = helper.make_graph(
+            [node_def, node_def2],
+            'test_model',
+            [input],
+            [output],
+        )
+
+        # Create the model (ModelProto)
+        onnx_net = helper.make_model(graph_def, producer_name='test_model')
+        return onnx_net
+
+    @staticmethod
+    def create_model_ref():
+        nodes_attributes = {
+            'input': {'kind': 'op', 'type': 'Parameter'},
+            'input_data': {'shape': [1, 2, 3], 'kind': 'data'},
+            'relu': {'kind': 'op', 'type': 'ReLU'},
+            'relu_data': {'shape': [1, 2, 3], 'kind': 'data'},
+            'sigmoid': {'kind': 'op', 'type': 'Sigmoid'},
+            'sigmoid_data': {'shape': [1, 2, 3], 'kind': 'data'},
+            'result': {'kind': 'op', 'type': 'Result'}
+        }
+
+        ref_graph = build_graph(nodes_attributes,
+                                [('input', 'input_data'),
+                                 ('input_data', 'relu'),
+                                 ('relu', 'relu_data'),
+                                 ('relu_data', 'sigmoid'),
+                                 ('sigmoid', 'sigmoid_data'),
+                                 ('sigmoid_data', 'result'),
+                                 ])
+        return ref_graph
+
     @generate(*[
         ({}),
         ({'input': InputCutInfo(name='LeakyRelu_out', shape=None, type=None, value=None)}),
@@ -37,66 +97,26 @@ class ConvertImportMOTest(UnitTestWithMockedTelemetry):
             serialize(ov_model, out_xml.encode('utf-8'), out_xml.replace('.xml', '.bin').encode('utf-8'))
             assert os.path.exists(out_xml)
 
+    def test_input_model_path(self):
+        from openvino.tools.mo import convert_model
+
+        with tempfile.TemporaryDirectory(dir=self.test_directory) as tmpdir:
+            model = self.create_onnx_model()
+            model_path = save_to_onnx(model, tmpdir)
+            out_xml = os.path.join(tmpdir, Path("model.xml"))
+
+            ov_model = convert_model(input_model=model_path)
+            serialize(ov_model, out_xml.encode('utf-8'), out_xml.replace('.xml', '.bin').encode('utf-8'))
+
+            ir = IREngine(out_xml, out_xml.replace('.xml', '.bin'))
+            ref_graph = self.create_model_ref()
+            flag, resp = ir.compare(ref_graph)
+            assert flag, '\n'.join(resp)
+
     def test_unnamed_input_model(self):
-        def create_onnx_model():
-            #
-            #   Create ONNX model
-            #
-
-            import onnx
-            from onnx import helper
-            from onnx import TensorProto
-
-            shape = [1, 2, 3]
-
-            input = helper.make_tensor_value_info('input', TensorProto.FLOAT, shape)
-            output = helper.make_tensor_value_info('output', TensorProto.FLOAT, shape)
-
-            node_def = onnx.helper.make_node(
-                'Relu',
-                inputs=['input'],
-                outputs=['Relu_out'],
-            )
-            node_def2 = onnx.helper.make_node(
-                'Sigmoid',
-                inputs=['Relu_out'],
-                outputs=['output'],
-            )
-
-            # Create the graph (GraphProto)
-            graph_def = helper.make_graph(
-                [node_def, node_def2],
-                'test_model',
-                [input],
-                [output],
-            )
-
-            # Create the model (ModelProto)
-            onnx_net = helper.make_model(graph_def, producer_name='test_model')
-            return onnx_net
-
-        nodes_attributes = {
-            'input': {'kind': 'op', 'type': 'Parameter'},
-            'input_data': {'shape': [1, 2, 3], 'kind': 'data'},
-            'relu': {'kind': 'op', 'type': 'ReLU'},
-            'relu_data': {'shape': [1, 2, 3], 'kind': 'data'},
-            'sigmoid': {'kind': 'op', 'type': 'Sigmoid'},
-            'sigmoid_data': {'shape': [1, 2, 3], 'kind': 'data'},
-            'result': {'kind': 'op', 'type': 'Result'}
-        }
-
-        ref_graph = build_graph(nodes_attributes,
-                                [('input', 'input_data'),
-                                 ('input_data', 'relu'),
-                                 ('relu', 'relu_data'),
-                                 ('relu_data', 'sigmoid'),
-                                 ('sigmoid', 'sigmoid_data'),
-                                 ('sigmoid_data', 'result'),
-                                 ])
-
         from openvino.tools.mo import convert_model
         with tempfile.TemporaryDirectory(dir=self.test_directory) as tmpdir:
-            model = create_onnx_model()
+            model = self.create_onnx_model()
             model_path = save_to_onnx(model, tmpdir)
             out_xml = os.path.join(tmpdir, "model.xml")
 
@@ -104,5 +124,6 @@ class ConvertImportMOTest(UnitTestWithMockedTelemetry):
             serialize(ov_model, out_xml.encode('utf-8'), out_xml.replace('.xml', '.bin').encode('utf-8'))
 
             ir = IREngine(out_xml, out_xml.replace('.xml', '.bin'))
+            ref_graph = self.create_model_ref()
             flag, resp = ir.compare(ref_graph)
             assert flag, '\n'.join(resp)