[TF FE][TF Hub] Support TruncateMod operation (#20468)

* [TF FE][TF Hub] Support TruncateMod operation

* Update truncate_mod.cpp

* fix

src/frontends/tensorflow/src/op_table.cpp

@@ -281,6 +281,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops() {
         {"TopK", CreatorFunction(translate_top_k_op)},
         {"TopKV2", CreatorFunction(translate_top_k_v2_op)},
         {"Transpose", CreatorFunction(translate_transpose_op)},
+        {"TruncateMod", CreatorFunction(translate_truncate_mod_op)},
         {"Unpack", CreatorFunction(translate_unpack_op)},
         {"UnravelIndex", CreatorFunction(translate_unravel_index_op)},
         {"UnsortedSegmentSum", CreatorFunction(translate_unsorted_segment_sum_op)},

src/frontends/tensorflow_common/include/common_op_table.hpp

@@ -145,6 +145,7 @@ OP_CONVERTER(translate_tile_op);
 OP_CONVERTER_NAMED(translate_top_k_op);
 OP_CONVERTER_NAMED(translate_top_k_v2_op);
 OP_CONVERTER(translate_transpose_op);
+OP_CONVERTER(translate_truncate_mod_op);
 OP_CONVERTER(translate_unpack_op);
 OP_CONVERTER(translate_unravel_index_op);
 OP_CONVERTER(translate_unsorted_segment_sum_op);

src/frontends/tensorflow_common/src/op/truncate_mod.cpp

@@ -0,0 +1,48 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "common_op_table.hpp"
+#include "openvino/op/equal.hpp"
+#include "openvino/op/floor_mod.hpp"
+#include "openvino/op/less.hpp"
+#include "openvino/op/negative.hpp"
+#include "openvino/op/select.hpp"
+#include "openvino/op/subtract.hpp"
+
+using namespace std;
+using namespace ov::opset10;
+
+namespace ov {
+namespace frontend {
+namespace tensorflow {
+namespace op {
+OutputVector translate_truncate_mod_op(const NodeContext& node) {
+    default_op_checks(node, 2, {"TruncateMod"});
+    auto x = node.get_input(0);
+    auto y = node.get_input(1);
+
+    auto is_x_negative = make_shared<Less>(x, create_same_type_const_scalar(x, 0));
+    auto is_y_negative = make_shared<Less>(y, create_same_type_const_scalar(y, 0));
+
+    // if (y < 0) {y = -y}
+    auto negative_y = make_shared<Negative>(y);
+    y = make_shared<Select>(is_y_negative, negative_y, y);
+
+    // check if floor_mod == zero
+    auto floor_mod = make_shared<FloorMod>(x, y);
+    auto is_zero = make_shared<Equal>(floor_mod, create_same_type_const_scalar(floor_mod, 0));
+
+    // floor_mod - y
+    auto other_res = make_shared<Subtract>(floor_mod, y);
+
+    // select operation to handle the sign
+    auto result = make_shared<Select>(is_zero, floor_mod, make_shared<Select>(is_x_negative, other_res, floor_mod));
+
+    set_node_name(node.get_name(), result);
+    return result->outputs();
+}
+}  // namespace op
+}  // namespace tensorflow
+}  // namespace frontend
+}  // namespace ov

tests/layer_tests/tensorflow_tests/test_tf_TruncateMod.py

@@ -0,0 +1,49 @@
+# Copyright (C) 2018-2023 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 TestTruncateMod(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        assert 'x' in inputs_info
+        assert 'y' in inputs_info
+        x_shape = inputs_info['x']
+        y_shape = inputs_info['y']
+        inputs_data = {}
+        # generate x and y to ensure truncation
+        inputs_data['x'] = np.random.randint(-10, 10, x_shape).astype(self.input_type)
+        inputs_data['y'] = np.random.randint(1, 10, y_shape).astype(self.input_type)
+        return inputs_data
+
+    def create_truncate_mod_net(self, input_shape, input_type):
+        self.input_type = input_type
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            x = tf.compat.v1.placeholder(input_type, input_shape, 'x')
+            y = tf.compat.v1.placeholder(input_type, input_shape, 'y')
+            tf.raw_ops.TruncateMod(x=x, y=y)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+
+        return tf_net, None
+
+    test_data_basic = [
+        dict(input_shape=[10, 20], input_type=np.float32),
+        dict(input_shape=[8, 5], input_type=np.float32),
+        dict(input_shape=[5, 3], input_type=np.int32),
+        dict(input_shape=[6, 4], input_type=np.int32),
+    ]
+
+    @pytest.mark.parametrize("params", test_data_basic)
+    @pytest.mark.precommit_tf_fe
+    @pytest.mark.nightly
+    def test_truncate_mod_basic(self, params, ie_device, precision, ir_version, temp_dir,
+                               use_new_frontend, use_old_api):
+        self._test(*self.create_truncate_mod_net(**params),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_new_frontend=use_new_frontend, use_old_api=use_old_api)