[TF FE] Add layer test for tf.keras.layers.TextVectorization and for …

…LookupTableFindV2 with string key (openvinotoolkit#23011)

**Details:** Add layer test for tf.keras.layers.TextVectorization and
for LookupTableFindV2 with string key

**Ticket:** 132910

---------

Signed-off-by: Kazantsev, Roman <[email protected]>

tests/layer_tests/tensorflow2_keras_tests/test_tf2_keras_text_vectorization.py

@@ -0,0 +1,53 @@
+# Copyright (C) 2022-2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import numpy as np
+
+import pytest
+import tensorflow as tf
+
+from common.tf2_layer_test_class import CommonTF2LayerTest
+from tensorflow.keras.layers import TextVectorization
+
+rng = np.random.default_rng()
+
+
+class TestTextVectorization(CommonTF2LayerTest):
+    def _prepare_input(self, inputs_info):
+        assert 'text_input' in inputs_info
+        input_shape = inputs_info['text_input']
+        inputs_data = {}
+        strings_dictionary = ['hi OpenVINO here  ', '  hello OpenVINO there', ' привет ОПЕНВИНО  \n',
+                              'hello PyTorch here  ', '  hi TensorFlow here', '  hi JAX here \t']
+        inputs_data['text_input'] = rng.choice(strings_dictionary, input_shape)
+        return inputs_data
+
+    def create_text_vectorization_net(self, input_shape, vocabulary, output_mode, output_sequence_length):
+        assert len(input_shape) > 0
+        tf.keras.backend.clear_session()
+        text_input = tf.keras.Input(shape=input_shape[1:], name='text_input',
+                                    dtype=tf.string)
+        vectorized_text = TextVectorization(vocabulary=vocabulary,
+                                            output_mode=output_mode,
+                                            output_sequence_length=output_sequence_length,
+                                            name='text_vectorizer')(text_input)
+        tf2_net = tf.keras.Model(inputs=[text_input], outputs=[vectorized_text])
+
+        return tf2_net, None
+
+    @pytest.mark.parametrize('input_shape', [[2, 1], [2, 3]])
+    @pytest.mark.parametrize('vocabulary', [['hello', 'there', 'OpenVINO', 'check', 'привет', 'ОПЕНВИНО']])
+    @pytest.mark.parametrize('output_mode', ['int'])
+    @pytest.mark.parametrize('output_sequence_length', [32, 64])
+    @pytest.mark.precommit_tf_fe
+    @pytest.mark.xfail(reason='132692 - Add support of TextVectorization')
+    @pytest.mark.nightly
+    def test_text_vectorization(self, input_shape, vocabulary, output_mode, output_sequence_length, ie_device,
+                                precision, ir_version, temp_dir, use_legacy_frontend):
+        params = {}
+        params['input_shape'] = input_shape
+        params['vocabulary'] = vocabulary
+        params['output_mode'] = output_mode
+        params['output_sequence_length'] = output_sequence_length
+        self._test(*self.create_text_vectorization_net(**params), ie_device, precision,
+                   temp_dir=temp_dir, ir_version=ir_version, use_legacy_frontend=use_legacy_frontend, **params)

tests/layer_tests/tensorflow_tests/test_tf_LookupTableFind.py

@@ -18,6 +18,9 @@ def _prepare_input(self, inputs_info):
         if np.issubdtype(self.keys_type, np.integer):
             data = rng.choice(self.all_keys, keys_shape)
             inputs_data['keys:0'] = mix_array_with_value(data, self.invalid_key)
+        elif self.keys_type == str:
+            data = rng.choice(self.all_keys + [self.invalid_key], keys_shape)
+            inputs_data['keys:0'] = data
         else:
             raise "Unsupported type {}".format(self.keys_type)
 
@@ -64,6 +67,11 @@ def create_lookup_table_find_net(self, hash_table_type, keys_shape, keys_type, v
         dict(keys_type=np.int32, values_type=tf.string, all_keys=[20, 10, 33, -22, 44, 11],
              all_values=['PyTorch', 'TensorFlow', 'JAX', 'Lightning', 'MindSpore', 'OpenVINO'],
              default_value='UNKNOWN', invalid_key=1000),
+        pytest.param(dict(keys_type=str, values_type=np.int64,
+                          all_keys=['PyTorch', 'TensorFlow', 'JAX', 'Lightning', 'MindSpore', 'OpenVINO'],
+                          all_values=[200, 100, 0, -3, 10, 1],
+                          default_value=0, invalid_key='AbraCadabra'),
+                     marks=pytest.mark.xfail(reason="132669 - Support LookupTableFindV2 with string key")),
     ]
 
     @pytest.mark.parametrize("hash_table_type", [0, 1])