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1# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#     http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15"""Test configs for placeholder_with_default."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20import numpy as np
21import tensorflow.compat.v1 as tf
22from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
23from tensorflow.lite.testing.zip_test_utils import register_make_test_function
24from tensorflow.lite.testing.zip_test_utils import TF_TYPE_INFO
25
26
27@register_make_test_function()
28def make_placeholder_with_default_tests(options):
29  """Make a set of tests to test placeholder_with_default."""
30
31  test_parameters = [{
32      "dtype": [tf.float32, tf.int32, tf.int64],
33  }]
34
35  def build_graph(parameters):
36    """Build the placeholder_with_default testing graph."""
37    const_node = tf.constant([1, 2, 2, 0],
38                             shape=[2, 2],
39                             dtype=parameters["dtype"])
40    input_tensor = tf.compat.v1.placeholder_with_default(
41        const_node, shape=[2, 2], name="input")
42    out = tf.equal(input_tensor, const_node, name="output")
43
44    return [input_tensor], [out]
45
46  def build_inputs(parameters, sess, inputs, outputs):
47    numpy_type = TF_TYPE_INFO[parameters["dtype"]][0]
48    input_value = np.array([[1, 0], [2, 1]], numpy_type)
49    return [input_value], sess.run(
50        outputs, feed_dict=dict(zip(inputs, [input_value])))
51
52  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
53