[TF FE] Supported Complex tensor for AddN op (openvinotoolkit#23614)

### Details:
- extended addN.cpp file to support complex tensor
- extended test_tf_addN.py with test for complex input

### Tickets:
 - openvinotoolkit#22944

---------

Co-authored-by: Roman Kazantsev <[email protected]>

src/frontends/tensorflow_common/src/op/addN.cpp

@@ -3,6 +3,7 @@
 //
 
 #include "common_op_table.hpp"
+#include "helper_ops/complex_type_mark.hpp"
 #include "openvino/op/add.hpp"
 
 using namespace std;
@@ -15,10 +16,24 @@ namespace tensorflow {
 namespace op {
 
 OutputVector translate_add_n_op(const NodeContext& node) {
-    default_op_checks(node, 1, {"AddN", "ADD_N"});
+    default_op_checks(node, 1, {"AddN", "ADD_N"}, true);
     int num_size = static_cast<int>(node.get_input_size());
+    auto result = node.get_input(0);
+    auto complex_type_mark = as_type_ptr<ComplexTypeMark>(result.get_node_shared_ptr());
+    if (complex_type_mark) {
+        element::Type complex_part_type = complex_type_mark->get_complex_part_type();
+        result = complex_type_mark->input_value(0);
+
+        // converting all the inputs to complex type (simulating complex type) and adding them
+        for (int ind = 1; ind < num_size; ++ind) {
+            auto complex_type_mark_ind = as_type_ptr<ComplexTypeMark>(node.get_input(ind).get_node_shared_ptr());
+            result = make_shared<v1::Add>(result, complex_type_mark_ind->input_value(0));
+        }
+        auto complex_add_n = make_shared<ComplexTypeMark>(result, complex_part_type);
+        set_node_name(node.get_name(), result.get_node_shared_ptr());
+        return {complex_add_n->output(0)};
+    }
 
-    Output<Node> result = node.get_input(0);
     for (int ind = 1; ind < num_size; ++ind) {
         result = make_shared<v1::Add>(result, node.get_input(ind));
     }

tests/layer_tests/tensorflow_tests/test_tf_AddN.py

@@ -3,10 +3,9 @@
 
 import numpy as np
 import pytest
-
+import tensorflow as tf
 from common.tf_layer_test_class import CommonTFLayerTest
 
-import logging
 
 # Testing operation AddN
 # Documentation: https://www.tensorflow.org/api_docs/python/tf/raw_ops/AddN
@@ -30,7 +29,6 @@ def create_addn_placeholder_const_net(self, input_shapes, ir_version, use_legacy
 
         if len(input_shapes) == 1 and not use_legacy_frontend:
             pytest.xfail(reason="96687")
-        import tensorflow as tf
 
         tf.compat.v1.reset_default_graph()
 
@@ -66,3 +64,42 @@ def test_addn_placeholder_const(self, params, ie_device, precision, ir_version,
                                                           use_legacy_frontend=use_legacy_frontend),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
                    use_legacy_frontend=use_legacy_frontend)
+
+class TestComplexAddN(CommonTFLayerTest):
+    def _prepare_input(self, inputs_info):
+        rng = np.random.default_rng()
+        inputs_data = {}
+        for idx, key in enumerate(inputs_info):
+            assert key in inputs_info
+            inputs_data[key] = 4 * rng.random(inputs_info[key]).astype(np.float32) - 2
+        return inputs_data
+
+    def create_complex_addn_net(self, input_shapes):
+        tf.compat.v1.reset_default_graph()
+        with tf.compat.v1.Session() as sess:
+            complex_tensors = []
+            for idx, input_shape in enumerate(input_shapes):
+                real = tf.compat.v1.placeholder(np.float32, input_shape, f'param_real_{idx+1}')
+                imag = tf.compat.v1.placeholder(np.float32, input_shape, f'param_imag_{idx+1}')
+                complex_tensors.append(tf.raw_ops.Complex(real=real, imag=imag))
+            addn = tf.raw_ops.AddN(inputs=complex_tensors, name='complex_AddN')
+            real = tf.raw_ops.Real(input=addn)
+            imag = tf.raw_ops.Imag(input=addn)
+            tf.compat.v1.global_variables_initializer()
+            tf_net = sess.graph_def
+        return tf_net, None
+
+    test_data = [
+        dict(input_shapes=[[1], [1]]),
+        dict(input_shapes=[[2, 3], [2, 3], [2, 3], [2, 3]]),
+        dict(input_shapes=[[3, 4, 5], [3, 4, 5], [3, 4, 5], [3, 4, 5], [3, 4, 5], [3, 4, 5]]),
+    ]
+
+    @pytest.mark.parametrize("params", test_data)
+    @pytest.mark.precommit
+    @pytest.mark.nightly
+    def test_complex_addn(self, params, ie_device, precision, ir_version, temp_dir,
+                          use_legacy_frontend):
+        self._test(*self.create_complex_addn_net(**params),
+                   ie_device, precision, ir_version, temp_dir=temp_dir,
+                   use_legacy_frontend=use_legacy_frontend)