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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 TensorScatterAdd."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20import numpy as np
21import tensorflow.compat.v1 as tf
22from tensorflow.lite.testing.zip_test_utils import create_tensor_data
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()
28def make_tensor_scatter_add_tests(options):
29  """Make a set of tests to do tensor_scatter_add."""
30
31  test_parameters = [{
32      "input_dtype": [tf.float32, tf.int32, tf.int64],
33      "input_shape": [[14], [2, 4, 7]],
34      "adds_count": [1, 3, 5],
35  }]
36
37  def build_graph(parameters):
38    """Build the tensor_scatter_add op testing graph."""
39    input_tensor = tf.compat.v1.placeholder(
40        dtype=parameters["input_dtype"],
41        name="input",
42        shape=parameters["input_shape"])
43    # The indices will be a list of "input_shape".
44    indices_tensor = tf.compat.v1.placeholder(
45        dtype=tf.int32,
46        name="indices",
47        shape=([parameters["adds_count"],
48                len(parameters["input_shape"])]))
49    # The adds will be a list of scalar, shaped of "adds_count".
50    adds_tensors = tf.compat.v1.placeholder(
51        dtype=parameters["input_dtype"],
52        name="updates",
53        shape=[parameters["adds_count"]])
54
55    out = tf.tensor_scatter_nd_add(input_tensor, indices_tensor, adds_tensors)
56    return [input_tensor, indices_tensor, adds_tensors], [out]
57
58  def build_inputs(parameters, sess, inputs, outputs):
59    indices = set()
60    while len(indices) < parameters["adds_count"]:
61      loc = []
62      for d in parameters["input_shape"]:
63        loc.append(np.random.randint(0, d))
64      indices.add(tuple(loc))
65
66    values = [
67        create_tensor_data(parameters["input_dtype"],
68                           parameters["input_shape"]),
69        np.array(list(indices), dtype=np.int32),
70        create_tensor_data(
71            parameters["input_dtype"],
72            parameters["adds_count"],
73            min_value=-3,
74            max_value=3)
75    ]
76    return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
77
78  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
79