• 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 range."""
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_scalar_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_range_tests(options):
28  """Make a set of tests to do range."""
29
30  test_parameters = [{
31      "dtype": [tf.int32, tf.float32],
32      "offset": [10, 100, 1000, 0],
33      "delta": [1, 2, 3, 4, -1, -2, -3, -4],
34  }]
35
36  def build_graph(parameters):
37    """Build the range op testing graph."""
38    input_tensor = tf.compat.v1.placeholder(
39        dtype=parameters["dtype"], name=("start"), shape=[])
40    if parameters["delta"] < 0:
41      offset = parameters["offset"] * -1
42    else:
43      offset = parameters["offset"]
44    delta = parameters["delta"]
45    limit_tensor = input_tensor + offset
46    delta_tensor = tf.constant(delta, dtype=parameters["dtype"])
47    out = tf.range(input_tensor, limit_tensor, delta_tensor)
48    return [input_tensor], [out]
49
50  def build_inputs(parameters, sess, inputs, outputs):
51    input_value = create_scalar_data(parameters["dtype"])
52    return [input_value], sess.run(
53        outputs, feed_dict=dict(zip(inputs, [input_value])))
54
55  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
56