# 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
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# ==============================================================================
"""Test configs for relu6."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import numpy as np
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_relu6_tests(options):
  """Make a set of tests to do relu6."""

  # Chose a set of parameters
  test_parameters = [{
      "input_shape": [[], [1, 1, 1, 1], [1, 3, 4, 3], [3, 15, 14, 3],
                      [3, 1, 2, 4, 6], [2, 2, 3, 4, 5, 6]],
      "fully_quantize": [True, False],
      "input_range": [(-2, 8)]
  }]

  def build_graph(parameters):
    input_tensor = tf.compat.v1.placeholder(
        dtype=tf.float32, name="input", shape=parameters["input_shape"])
    out = tf.nn.relu6(input_tensor)
    return [input_tensor], [out]

  def build_inputs(parameters, sess, inputs, outputs):
    min_value, max_value = parameters["input_range"]
    input_values = create_tensor_data(np.float32, parameters["input_shape"],
                                      min_value, max_value)
    return [input_values], sess.run(
        outputs, feed_dict=dict(zip(inputs, [input_values])))

  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
