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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 unique."""
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
25
26@register_make_test_function()
27def make_unique_tests(options):
28  """Make a set of tests for Unique op."""
29
30  test_parameters = [{
31      "input_shape": [[1]],
32      "index_type": [tf.int32, tf.int64, None],
33      "input_values": [3]
34  }, {
35      "input_shape": [[5]],
36      "index_type": [tf.int32, tf.int64],
37      "input_values": [[3, 2, 1, 2, 3]]
38  }, {
39      "input_shape": [[7]],
40      "index_type": [tf.int32, tf.int64],
41      "input_values": [[1, 1, 1, 1, 1, 1, 1]]
42  }, {
43      "input_shape": [[5]],
44      "index_type": [tf.int32, tf.int64],
45      "input_values": [[3, 2, 1, 0, -1]]
46  }]
47
48  def build_graph(parameters):
49    """Build the graph for the test case."""
50
51    input_tensor = tf.compat.v1.placeholder(
52        dtype=tf.int32, name="input", shape=parameters["input_shape"])
53    if parameters["index_type"] is None:
54      output = tf.unique(input_tensor)
55    else:
56      output = tf.unique(input_tensor, parameters["index_type"])
57
58    return [input_tensor], output
59
60  def build_inputs(parameters, sess, inputs, outputs):
61    input_values = [create_tensor_data(tf.int32, parameters["input_shape"])]
62    return input_values, sess.run(
63        outputs, feed_dict=dict(zip(inputs, input_values)))
64
65  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
66