• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
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 squeeze_transpose."""
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_squeeze_transpose_tests(options):
28  """Make a set of tests to do squeeze followed by transpose."""
29
30  test_parameters = [{
31      "dtype": [tf.int32, tf.float32, tf.int64],
32      "input_shape": [[1, 4, 10, 1]],
33      "axis": [[-1], [3]],
34  }]
35
36  def build_graph(parameters):
37    input_tensor = tf.compat.v1.placeholder(
38        dtype=parameters["dtype"],
39        name="input",
40        shape=parameters["input_shape"])
41    out = tf.squeeze(input_tensor, axis=parameters["axis"])
42    out = tf.transpose(out, perm=[1, 2])
43    return [input_tensor], [out]
44
45  def build_inputs(parameters, sess, inputs, outputs):
46    input_values = create_tensor_data(parameters["dtype"],
47                                      parameters["input_shape"])
48    return [input_values], sess.run(
49        outputs, feed_dict=dict(zip(inputs, [input_values])))
50
51  make_zip_of_tests(
52      options,
53      test_parameters,
54      build_graph,
55      build_inputs,
56      expected_tf_failures=0)
57