[TF FE]: Support complex tensors for SegmentSum operations (#23676)

### Details:
 - *Edited Tests for Segment Sum*



Resolves #23241

---------

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

src/frontends/tensorflow_common/src/op/segment_sum.cpp

@@ -3,6 +3,7 @@
 //
 
 #include "common_op_table.hpp"
+#include "helper_ops/complex_type_mark.hpp"
 #include "openvino/op/add.hpp"
 #include "openvino/op/constant.hpp"
 #include "openvino/op/embedding_segments_sum.hpp"
@@ -21,7 +22,7 @@ namespace frontend {
 namespace tensorflow {
 namespace op {
 OutputVector translate_segment_sum_op(const NodeContext& node) {
-    default_op_checks(node, 2, {"SegmentSum"});
+    default_op_checks(node, 2, {"SegmentSum"}, true);
     auto data = node.get_input(0);
     auto segment_ids = node.get_input(1);
 
@@ -45,6 +46,17 @@ OutputVector translate_segment_sum_op(const NodeContext& node) {
     auto num_indices = make_shared<v0::Squeeze>(segment_ids_shape, squeeze_axis);
     auto indices = make_shared<v4::Range>(const_zero, num_indices, const_one, indices_type);
 
+    auto complex_type_mark = as_type_ptr<ComplexTypeMark>(data.get_node_shared_ptr());
+    if (complex_type_mark) {
+        element::Type complex_part_type = complex_type_mark->get_complex_part_type();
+        data = complex_type_mark->input_value(0);
+        auto emb_segment_sum_complex = make_shared<v3::EmbeddingSegmentsSum>(data, indices, segment_ids, num_segments);
+        auto emb_segment_sum_complex_output =
+            make_shared<ComplexTypeMark>(emb_segment_sum_complex->output(0), complex_part_type);
+        set_node_name(node.get_name(), emb_segment_sum_complex);
+        return {emb_segment_sum_complex_output};
+    }
+
     auto emb_segment_sum = make_shared<v3::EmbeddingSegmentsSum>(data, indices, segment_ids, num_segments);
     set_node_name(node.get_name(), emb_segment_sum);
     return {emb_segment_sum};

tests/layer_tests/tensorflow_tests/test_tf_SegmentSum.py

@@ -69,3 +69,57 @@ class TestSegmentSum(CommonTFLayerTest):
         self._test(*self.create_segment_sum_net(**params),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
                    use_legacy_frontend=use_legacy_frontend)
+
+
+class TestSegmentSumComplex(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        rng = np.random.default_rng()
+        assert "data_real:0" in inputs_info
+        assert "data_imag:0" in inputs_info
+        assert "segment_ids:0" in inputs_info
+        data_real_shape = inputs_info["data_real:0"]
+        data_imag_shape = inputs_info["data_imag:0"]
+        segment_ids_shape = inputs_info["segment_ids:0"]
+        inputs_data = {}
+        inputs_data["data_real:0"] = rng.random(data_real_shape).astype(np.float32)
+        inputs_data["data_imag:0"] = rng.random(data_imag_shape).astype(np.float32)
+        inputs_data["segment_ids:0"] = np.sort(rng.integers(
+            low=0, high=data_real_shape[0], size=segment_ids_shape
+        ).astype(np.int32))
+        return inputs_data
+
+    def create_segment_sum_net(self, data_shape, segment_ids_shape):
+        tf.compat.v1.reset_default_graph()
+        # Create the graph and model
+        with tf.compat.v1.Session() as sess:
+            data_real = tf.compat.v1.placeholder(tf.float32,data_shape,'data_real')
+            data_imag = tf.compat.v1.placeholder(tf.float32,data_shape,'data_imag')
+            data = tf.raw_ops.Complex(real=data_real,imag=data_imag)
+            segment_ids = tf.compat.v1.placeholder(tf.int32, segment_ids_shape, "segment_ids")
+            segment_sum_output = tf.raw_ops.SegmentSum(data=data, segment_ids=segment_ids)
+            tf.raw_ops.Real(input=segment_sum_output)
+            tf.raw_ops.Imag(input=segment_sum_output)
+            tf.compat.v1.global_variables_initializer().run()
+            tf_net = sess.graph_def
+
+        return tf_net, None 
+
+    test_data_basic = [
+        dict(data_shape=[2, 3], segment_ids_shape=[2]),
+        dict(data_shape=[3, 2], segment_ids_shape=[3]),
+        dict(data_shape=[3, 1, 2], segment_ids_shape=[3]),
+        dict(data_shape=[4, 2, 1], segment_ids_shape=[4]),
+    ]
+
+    @pytest.mark.parametrize("params", test_data_basic)
+    @pytest.mark.precommit
+    @pytest.mark.nightly
+    def test_complex_segment_sum(self, params, ie_device, precision, ir_version, temp_dir,
+                                         use_legacy_frontend):
+        if use_legacy_frontend:
+            pytest.skip("SegmentSum operation is not supported via legacy frontend.")
+        if ie_device == 'GPU':
+            pytest.skip("GPU error: to_shape was called on a dynamic shape")
+        self._test(*self.create_segment_sum_net(**params),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_legacy_frontend=use_legacy_frontend)