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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 control_dep."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20import tensorflow.compat.v1 as tf
21from tensorflow.lite.testing.zip_test_utils import create_tensor_data
22from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
23from tensorflow.lite.testing.zip_test_utils import register_make_test_function
24
25TEST_INPUT_DEPTH = 3
26
27
28@register_make_test_function()
29def make_control_dep_tests(options):
30  """Make a set of tests that use control dependencies."""
31
32  test_parameters = [{
33      "input_shape": [[], [1, 1, 1, 1], [1, 15, 14, 1], [3, 15, 14, 3]],
34  }]
35
36  def build_graph(parameters):
37    input_tensor = tf.compat.v1.placeholder(
38        dtype=tf.float32, name="input", shape=parameters["input_shape"])
39    filter_value = tf.zeros((3, 3, TEST_INPUT_DEPTH, 8), tf.float32)
40    assert_op = tf.compat.v1.assert_greater_equal(input_tensor,
41                                                  input_tensor - 1)
42    with tf.control_dependencies([assert_op]):
43      out = tf.nn.conv2d(
44          input_tensor, filter_value, strides=(1, 1, 1, 1), padding="SAME")
45      return [input_tensor], [out]
46
47  def build_inputs(parameters, sess, inputs, outputs):
48    input_values = create_tensor_data(tf.float32, parameters["input_shape"])
49    return [input_values], sess.run(
50        outputs, feed_dict=dict(zip(inputs, [input_values])))
51
52  make_zip_of_tests(
53      options,
54      test_parameters,
55      build_graph,
56      build_inputs,
57      expected_tf_failures=3)
58