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 binary_op."""
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import tensorflow 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
  
  
  def make_binary_op_tests(options,
                           binary_operator,
                           allow_fully_quantize=False,
                           expected_tf_failures=0):
    """Make a set of tests to do binary ops with and without broadcast."""
  
    test_parameters = [
        # Avoid creating all combinations to keep the test size small.
        {
            "dtype": [tf.float32, tf.int32],
            "input_shape_1": [[1, 3, 4, 3]],
            "input_shape_2": [[1, 3, 4, 3]],
            "activation": [True],
            "fully_quantize": [False],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[5]],
            "input_shape_2": [[5]],
            "activation": [False, True],
            "fully_quantize": [False],
        },
        {
            "dtype": [tf.float32, tf.int32, tf.int64],
            "input_shape_1": [[1, 3, 4, 3]],
            "input_shape_2": [[3]],
            "activation": [True, False],
            "fully_quantize": [False],
        },
        {
            "dtype": [tf.float32, tf.int32],
            "input_shape_1": [[3]],
            "input_shape_2": [[1, 3, 4, 3]],
            "activation": [True, False],
            "fully_quantize": [False],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[]],
            "input_shape_2": [[]],
            "activation": [False],
            "fully_quantize": [False],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[0]],
            "input_shape_2": [[1]],
            "activation": [False],
            "fully_quantize": [False],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[1, 3, 4, 3]],
            "input_shape_2": [[1, 3, 4, 3]],
            "activation": [False],
            "fully_quantize": [True],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[5]],
            "input_shape_2": [[5]],
            "activation": [False],
            "fully_quantize": [True],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[1, 3, 4, 3]],
            "input_shape_2": [[3]],
            "activation": [False],
            "fully_quantize": [True],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[3]],
            "input_shape_2": [[1, 3, 4, 3]],
            "activation": [False],
            "fully_quantize": [True],
        },
        {
            "dtype": [tf.float32],
            "input_shape_1": [[]],
            "input_shape_2": [[]],
            "activation": [False],
            "fully_quantize": [True],
        },
    ]
  
    # test_parameters include fully_quantize option only when
    # allow_fully_quantize is True.
    if not allow_fully_quantize:
      test_parameters = [
          test_parameter for test_parameter in test_parameters
          if True not in test_parameter["fully_quantize"]
      ]
  
    def build_graph(parameters):
      """Builds the graph given the current parameters."""
      input1 = tf.compat.v1.placeholder(
          dtype=parameters["dtype"],
          name="input1",
          shape=parameters["input_shape_1"])
      input2 = tf.compat.v1.placeholder(
          dtype=parameters["dtype"],
          name="input2",
          shape=parameters["input_shape_2"])
      out = binary_operator(input1, input2)
      if parameters["activation"]:
        out = tf.nn.relu(out)
      return [input1, input2], [out]
  
    def build_inputs(parameters, sess, inputs, outputs):
      """Builds operand inputs for op."""
      if allow_fully_quantize:
        input1 = create_tensor_data(
            parameters["dtype"],
            parameters["input_shape_1"],
            min_value=-1,
            max_value=1)
        input2 = create_tensor_data(
            parameters["dtype"],
            parameters["input_shape_2"],
            min_value=-1,
            max_value=1)
      else:
        input1 = create_tensor_data(parameters["dtype"],
                                    parameters["input_shape_1"])
        input2 = create_tensor_data(parameters["dtype"],
                                    parameters["input_shape_2"])
      return [input1, input2], sess.run(
          outputs, feed_dict={
              inputs[0]: input1,
              inputs[1]: input2
          })
  
    make_zip_of_tests(
        options,
        test_parameters,
        build_graph,
        build_inputs,
        expected_tf_failures=expected_tf_failures)
  
  
  def make_binary_op_tests_func(binary_operator):
    """Return a function that does a test on a binary operator."""
    return lambda options: make_binary_op_tests(options, binary_operator)
  
  
  @register_make_test_function()
  def make_add_tests(options):
    make_binary_op_tests(options, tf.add, allow_fully_quantize=True)
  
  
  @register_make_test_function()
  def make_div_tests(options):
    make_binary_op_tests(options, tf.compat.v1.div)
  
  
  @register_make_test_function()
  def make_sub_tests(options):
    make_binary_op_tests(options, tf.subtract, allow_fully_quantize=True)
  
  
  @register_make_test_function()
  def make_mul_tests(options):
    make_binary_op_tests(options, tf.multiply, allow_fully_quantize=True)
  
  
  @register_make_test_function()
  def make_pow_tests(options):
    make_binary_op_tests(options, tf.pow, expected_tf_failures=7)
  
  
  @register_make_test_function()
  def make_floor_div_tests(options):
    make_binary_op_tests(options, tf.floor_div)
  
  
  @register_make_test_function()
  def make_floor_mod_tests(options):
    make_binary_op_tests(options, tf.math.floormod)
  
  
  @register_make_test_function()
  def make_squared_difference_tests(options):
    make_binary_op_tests(options, tf.math.squared_difference)
  