text: #
  # Copyright (C) 2018 The Android Open Source Project
  #
  # 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.
  #
  def test(name, input0, input1, output0, input0_data, input1_data, output_data, do_variations=True):
    model = Model().Operation("NOT_EQUAL", input0, input1).To(output0)
    example = Example({
        input0: input0_data,
        input1: input1_data,
        output0: output_data,
    }, model=model, name=name)
    if do_variations:
        example.AddVariations("int32", "float16", "relaxed")
  
  test(
      name="simple",
      input0=Input("input0", "TENSOR_FLOAT32", "{3}"),
      input1=Input("input1", "TENSOR_FLOAT32", "{3}"),
      output0=Output("output0", "TENSOR_BOOL8", "{3}"),
      input0_data=[5, 7, 10],
      input1_data=[10, 7, 5],
      output_data=[True, False, True],
  )
  
  test(
      name="broadcast",
      input0=Input("input0", "TENSOR_FLOAT32", "{2, 1}"),
      input1=Input("input1", "TENSOR_FLOAT32", "{2}"),
      output0=Output("output0", "TENSOR_BOOL8", "{2, 2}"),
      input0_data=[5, 10],
      input1_data=[10, 5],
      output_data=[True, False, False, True],
  )
  
  test(
      name="quantized_different_scale",
      input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
      input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 2.0, 128)),
      output0=Output("output0", "TENSOR_BOOL8", "{3}"),
      input0_data=[129, 130, 131], # effectively 1, 2, 3
      input1_data=[129],           # effectively 2
      output_data=[True, False, True],
      do_variations=False,
  )
  
  test(
      name="quantized_different_zero_point",
      input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [3], 1.0, 128)),
      input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.0, 129)),
      output0=Output("output0", "TENSOR_BOOL8", "{3}"),
      input0_data=[129, 130, 131], # effectively 1, 2, 3
      input1_data=[131],           # effectively 2
      output_data=[True, False, True],
      do_variations=False,
  )
  
  test(
      name="quantized_overflow_second_input_if_requantized",
      input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
      input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
      output0=Output("output0", "TENSOR_BOOL8", "{1}"),
      input0_data=[0],
      input1_data=[200],
      output_data=[True],
      do_variations=False,
  )
  
  test(
      name="quantized_overflow_first_input_if_requantized",
      input0=Input("input0", ("TENSOR_QUANT8_ASYMM", [1], 1.49725, 240)),
      input1=Input("input1", ("TENSOR_QUANT8_ASYMM", [1], 1.64771, 31)),
      output0=Output("output0", "TENSOR_BOOL8", "{1}"),
      input0_data=[200],
      input1_data=[0],
      output_data=[True],
      do_variations=False,
  )
  
  test(
      name="boolean",
      input0=Input("input0", "TENSOR_BOOL8", "{4}"),
      input1=Input("input1", "TENSOR_BOOL8", "{4}"),
      output0=Output("output0", "TENSOR_BOOL8", "{4}"),
      input0_data=[False, True, False, True],
      input1_data=[False, False, True, True],
      output_data=[False, True, True, False],
      do_variations=False,
  )
  