text: # Copyright 2019 The TensorFlow Authors. All Rights Reserved.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  # ==============================================================================
  """Test configs for unique."""
  import tensorflow.compat.v1 as tf
  from tensorflow.lite.testing.zip_test_utils import create_tensor_data
  from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
  from tensorflow.lite.testing.zip_test_utils import register_make_test_function
  
  
  @register_make_test_function()
  def make_unique_tests(options):
    """Make a set of tests for Unique op."""
  
    test_parameters = [{
        "input_shape": [[1]],
        "index_type": [tf.int32, tf.int64, None],
        "input_values": [3]
    }, {
        "input_shape": [[5]],
        "index_type": [tf.int32, tf.int64],
        "input_values": [[3, 2, 1, 2, 3]]
    }, {
        "input_shape": [[7]],
        "index_type": [tf.int32, tf.int64],
        "input_values": [[1, 1, 1, 1, 1, 1, 1]]
    }, {
        "input_shape": [[5]],
        "index_type": [tf.int32, tf.int64],
        "input_values": [[3, 2, 1, 0, -1]]
    }]
  
    def build_graph(parameters):
      """Build the graph for the test case."""
  
      input_tensor = tf.compat.v1.placeholder(
          dtype=tf.int32, name="input", shape=parameters["input_shape"])
      if parameters["index_type"] is None:
        output = tf.unique(input_tensor)
      else:
        output = tf.unique(input_tensor, parameters["index_type"])
  
      return [input_tensor], output
  
    def build_inputs(parameters, sess, inputs, outputs):
      input_values = [create_tensor_data(tf.int32, parameters["input_shape"])]
      return input_values, sess.run(
          outputs, feed_dict=dict(zip(inputs, input_values)))
  
    make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
  