[TF FE]: Support Rint operation for TensorFlow (#24059)

Closes https://github.com/openvinotoolkit/openvino/issues/24032
### Details:
 - Support Rint operation for TensorFlow.

---------

Co-authored-by: Roman Kazantsev <roman.kazantsev@intel.com>

src/frontends/tensorflow/docs/supported_ops.md

@@ -988,7 +988,7 @@ A "supported operation" is one that TensorFlow Frontend can convert to the OpenV
 | ReverseV2                                               | YES                           |                               |
 | RewriteDataset                                          | NO                            |                               |
 | RightShift                                              | NO                            |                               |
-| Rint                                                    | NO                            |                               |
+| Rint                                                    | YES                           |                               |
 | RngReadAndSkip                                          | NO                            |                               |
 | RngSkip                                                 | NO                            |                               |
 | Roll                                                    | YES                           |                               |

src/frontends/tensorflow/src/op_table.cpp

@@ -353,6 +353,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
         {"RFFT", CreatorFunction(translate_rfft_op)},
         {"RFFT2D", CreatorFunction(translate_rfft_op)},
         {"RFFT3D", CreatorFunction(translate_rfft_op)},
+        {"Rint", CreatorFunction(translate_rint_op)},
         {"Roll", CreatorFunction(translate_roll_op)},
         {"Round", CreatorFunction(translate_round_op)},
         {"Rsqrt", CreatorFunction(translate_rsqrt_op)},

src/frontends/tensorflow_common/include/common_op_table.hpp

@@ -135,6 +135,7 @@ OP_CONVERTER(translate_reverse_op);
 OP_CONVERTER(translate_reverse_v2_op);
 OP_CONVERTER(translate_reverse_sequence_op);
 OP_CONVERTER(translate_rfft_op);
+OP_CONVERTER(translate_rint_op);
 OP_CONVERTER(translate_roll_op);
 OP_CONVERTER(translate_round_op);
 OP_CONVERTER(translate_rsqrt_op);

src/frontends/tensorflow_common/src/op/rint.cpp

@@ -0,0 +1,30 @@
+// Copyright (C) 2018-2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "common_op_table.hpp"
+#include "openvino/op/round.hpp"
+
+using namespace std;
+using namespace ov::op;
+
+namespace ov {
+namespace frontend {
+namespace tensorflow {
+namespace op {
+
+OutputVector translate_rint_op(const NodeContext& node) {
+    default_op_checks(node, 1, {"Rint"});
+
+    auto input = node.get_input(0);
+    // using default round mode "half_to_even" in openvino,
+    // as TF has only that mode
+    auto round_mode = v5::Round::RoundMode::HALF_TO_EVEN;
+    auto res = make_shared<v5::Round>(input, round_mode);
+    set_node_name(node.get_name(), res);
+    return res->outputs();
+}
+}  // namespace op
+}  // namespace tensorflow
+}  // namespace frontend
+}  // namespace ov

tests/layer_tests/tensorflow_tests/test_tf_Rint.py

@@ -0,0 +1,39 @@
+# Copyright (C) 2018-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+import pytest
+import tensorflow as tf
+from common.tf_layer_test_class import CommonTFLayerTest
+
+class TestRint(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        assert 'input:0' in inputs_info
+        inputs_shape = inputs_info['input:0']
+        inputs_data = {}
+        rng = np.random.default_rng()
+        inputs_data['input:0'] = rng.uniform(-5.0, 5.0, inputs_shape).astype(self.input_type)
+        return inputs_data
+
+    def create_tf_rint_net(self, input_shape, input_type):
+        self.input_type = input_type
+        tf.compat.v1.reset_default_graph()
+        with tf.compat.v1.Session() as sess:
+            input = tf.compat.v1.placeholder(input_type, input_shape, 'input')
+            tf.raw_ops.Rint(x=input)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        ref_net = None
+
+        return tf_net, ref_net
+
+    @pytest.mark.parametrize("input_shape", [[], [6], [2, 5], [5, 4, 1]])
+    @pytest.mark.parametrize("input_type", [np.float32, np.float64])
+    @pytest.mark.precommit
+    @pytest.mark.nightly
+    def test_rint_basic(self, input_shape, input_type, ie_device, precision,
+                        ir_version, temp_dir, use_legacy_frontend):
+        self._test(*self.create_tf_rint_net(input_shape, input_type),
+                ie_device, precision, ir_version, temp_dir=temp_dir,
+                use_legacy_frontend=use_legacy_frontend)