Fix of tensor names loosing for cf=True flag in MOC transformations. (#19014)

* Added shape and type infer for result nodes in MOC transformations.

* Clang format.

* Added validate_nodes_and_infer_types() pass at the end of MOC pipeline.

* Clang format.

* Added test.

* Clang format.

src/common/transformations/src/transformations/common_optimizations/moc_transformations.cpp

@@ -255,8 +255,8 @@ bool ov::pass::MOCTransformations::run_on_model(const std::shared_ptr<ngraph::Fu
         for (auto&& param : f->get_parameters()) {
             param->set_partial_shape(input_shapes.at(param.get()));
         }
-        f->validate_nodes_and_infer_types();
     }
+    f->validate_nodes_and_infer_types();
 
     return false;
 }

src/common/transformations/tests/common_optimizations/moc_transformations.cpp

@@ -0,0 +1,60 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include <gtest/gtest.h>
+
+#include <string>
+#include <transformations/common_optimizations/moc_transformations.hpp>
+
+#include "openvino/core/model.hpp"
+#include "openvino/opsets/opset12.hpp"
+#include "openvino/pass/manager.hpp"
+
+using namespace testing;
+using namespace ov;
+using namespace ov::opset12;
+
+TEST(TransformationTests, TestModelTensorsConsistencyUseShapesTrue) {
+    auto input = std::make_shared<opset12::Parameter>(element::f32, Shape{1});
+    auto const1 = opset12::Constant::create(element::f32, Shape{1}, {1});
+    auto const2 = opset12::Constant::create(element::f32, Shape{1}, {2});
+    auto const3 = opset12::Constant::create(element::f32, Shape{1}, {3});
+    auto add1 = std::make_shared<opset12::Add>(input, const1);
+    auto add2 = std::make_shared<opset12::Add>(add1, const2);
+    auto add3 = std::make_shared<opset12::Add>(add2, const3);
+
+    auto model = std::make_shared<Model>(NodeVector{add3}, ParameterVector{input});
+    ov::pass::Manager m;
+    m.register_pass<ov::pass::MOCTransformations>(true);
+    m.run_passes(model);
+
+    std::unordered_set<std::string> new_tensors = {"new_name"};
+    model->outputs()[0].set_names(new_tensors);
+    EXPECT_TRUE(model->outputs()[0].get_names() == new_tensors);
+
+    model->validate_nodes_and_infer_types();
+    EXPECT_TRUE(model->outputs()[0].get_names() == new_tensors);
+}
+
+TEST(TransformationTests, TestModelTensorsConsistencyUseShapesFalse) {
+    auto input = std::make_shared<opset12::Parameter>(element::f32, Shape{1});
+    auto const1 = opset12::Constant::create(element::f32, Shape{1}, {1});
+    auto const2 = opset12::Constant::create(element::f32, Shape{1}, {2});
+    auto const3 = opset12::Constant::create(element::f32, Shape{1}, {3});
+    auto add1 = std::make_shared<opset12::Add>(input, const1);
+    auto add2 = std::make_shared<opset12::Add>(add1, const2);
+    auto add3 = std::make_shared<opset12::Add>(add2, const3);
+
+    auto model = std::make_shared<Model>(NodeVector{add3}, ParameterVector{input});
+    ov::pass::Manager m;
+    m.register_pass<ov::pass::MOCTransformations>(false);
+    m.run_passes(model);
+
+    std::unordered_set<std::string> new_tensors = {"new_name"};
+    model->outputs()[0].set_names(new_tensors);
+    EXPECT_TRUE(model->outputs()[0].get_names() == new_tensors);
+
+    model->validate_nodes_and_infer_types();
+    EXPECT_TRUE(model->outputs()[0].get_names() == new_tensors);
+}

tests/layer_tests/mo_python_api_tests/test_mo_convert_tf.py

@@ -903,6 +903,38 @@ class TestMoConvertTF(CommonMOConvertTest):
         assert CommonLayerTest().compare_ie_results_with_framework(ov_infer2, {"add:0": fw_infer2}, eps)
         assert CommonLayerTest().compare_ie_results_with_framework(ov_infer1, {"add:0": [2.6, 9.6, 12.4]}, eps)
 
+    def test_tensor_names(self, ie_device, precision, ir_version, temp_dir):
+        import tensorflow as tf
+        class LayerModel(tf.Module):
+            def __init__(self):
+                super(LayerModel, self).__init__()
+                self.var1 = tf.Variable([7., 5., 6.], name='var1')
+                self.var2 = tf.Variable([5., 7., 3.], name='var2')
+                self.var3 = tf.Variable([5., 7., 3.], name='var2')
+
+
+            @tf.function
+            def sub_function(self, input):
+                return input + self.var1 + self.var2 + self.var3
+
+            @tf.function()
+            def __call__(self, input):
+                return self.sub_function(input)
+
+        from openvino.tools.ovc import convert_model
+        model = LayerModel()
+        ov_model = convert_model(model)
+
+        ov_model.outputs[0].get_tensor().set_names({"name1"})
+        assert ov_model.outputs[0].names == {"name1"}
+
+        ov_model.validate_nodes_and_infer_types()
+        assert ov_model.outputs[0].names == {"name1"}
+
+        ov_model.outputs[0].get_tensor().set_names({"name2"})
+        assert ov_model.outputs[0].names == {"name2"}
+
+
 
 class TFConvertTest(unittest.TestCase):
     @pytest.mark.nightly