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1# Copyright 2021 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 broadcast_args."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20import numpy as np
21import tensorflow as tf
22
23from tensorflow.lite.testing.zip_test_utils import make_zip_of_tests
24from tensorflow.lite.testing.zip_test_utils import register_make_test_function
25
26
27@register_make_test_function("make_broadcast_args_tests")
28def make_broadcast_args_tests(options):
29  """Make a set of tests to do broadcast_args."""
30
31  # Chose a set of parameters
32  test_parameters = [{
33      "dtype": [tf.int64, tf.int32],
34      "input1_shape": [[1], [4], [3, 4], [1, 3, 4]],
35      "input2_shape": [[6, 4, 3, 4]],
36  }, {
37      "dtype": [tf.int64, tf.int32],
38      "input1_shape": [[1, 4, 0]],
39      "input2_shape": [[3, 1, 0], [3, 4, 1]],
40  }]
41
42  def build_graph(parameters):
43    """Build the graph for broadcast_args tests."""
44    shape1_tensor = tf.compat.v1.placeholder(
45        dtype=parameters["dtype"],
46        name="input1",
47        shape=[len(parameters["input1_shape"])])
48    shape2_tensor = tf.compat.v1.placeholder(
49        dtype=parameters["dtype"],
50        name="input2",
51        shape=[len(parameters["input2_shape"])])
52
53    out = tf.raw_ops.BroadcastArgs(s0=shape1_tensor, s1=shape2_tensor)
54    return [shape1_tensor, shape2_tensor], [out]
55
56  def build_inputs(parameters, sess, inputs, outputs):
57    input_values = [
58        np.array(parameters["input1_shape"]).astype(
59            parameters["dtype"].as_numpy_dtype),
60        np.array(parameters["input2_shape"]).astype(
61            parameters["dtype"].as_numpy_dtype),
62    ]
63    return input_values, sess.run(
64        outputs, feed_dict=dict(zip(inputs, input_values)))
65
66  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
67