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 resize_nearest_neighbor."""
  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_resize_nearest_neighbor_tests(options):
    """Make a set of tests to do resize_nearest_neighbor."""
  
    test_parameters = [{
        "dtype": [tf.float32],
        "input_shape": [[1, 3, 4, 3], [1, 10, 2, 1]],
        "size": [[1, 1], [4, 3], [2, 2], [5, 6]],
        "align_corners": [False],
        "half_pixel_centers": [False],
        "fully_quantize": [True, False],
    }, {
        "dtype": [tf.float32],
        "input_shape": [[1, 16, 24, 3], [1, 12, 18, 3]],
        "size": [[8, 12], [12, 18]],
        "align_corners": [True],
        "half_pixel_centers": [False],
        "fully_quantize": [True, False]
    }, {
        "dtype": [tf.float32],
        "input_shape": [[1, 16, 24, 3], [1, 12, 18, 3]],
        "size": [[8, 12], [12, 18]],
        "align_corners": [False],
        "half_pixel_centers": [True],
        "fully_quantize": [True, False]
    }]
  
    def build_graph(parameters):
      input_tensor = tf.compat.v1.placeholder(
          dtype=parameters["dtype"],
          name="input",
          shape=parameters["input_shape"])
      out = tf.image.resize_nearest_neighbor(
          input_tensor,
          size=parameters["size"],
          align_corners=parameters["align_corners"],
          half_pixel_centers=parameters["half_pixel_centers"])
      return [input_tensor], [out]
  
    def build_inputs(parameters, sess, inputs, outputs):
      input_values = create_tensor_data(
          parameters["dtype"],
          parameters["input_shape"],
          min_value=-1,
          max_value=1)
      return [input_values], sess.run(
          outputs, feed_dict=dict(zip(inputs, [input_values])))
  
    make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
  