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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 topk."""
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_topk_tests(options):
29  """Make a set of tests to do topk."""
30
31  test_parameters = [{
32      "input_dtype": [tf.float32, tf.int32],
33      "input_shape": [[10], [5, 20]],
34      "input_k": [None, 1, 3],
35  }]
36
37  def build_graph(parameters):
38    """Build the topk op testing graph."""
39    input_value = tf.compat.v1.placeholder(
40        dtype=parameters["input_dtype"],
41        name="input",
42        shape=parameters["input_shape"])
43    if parameters["input_k"] is not None:
44      k = tf.compat.v1.placeholder(dtype=tf.int32, name="input_k", shape=[])
45      inputs = [input_value, k]
46    else:
47      k = tf.constant(3, name="k")
48      inputs = [input_value]
49    out = tf.nn.top_k(input_value, k)
50    return inputs, [out[1]]
51
52  def build_inputs(parameters, sess, inputs, outputs):
53    input_value = create_tensor_data(parameters["input_dtype"],
54                                     parameters["input_shape"])
55    if parameters["input_k"] is not None:
56      k = np.array(parameters["input_k"], dtype=np.int32)
57      return [input_value, k], sess.run(
58          outputs, feed_dict=dict(zip(inputs, [input_value, k])))
59    else:
60      return [input_value], sess.run(
61          outputs, feed_dict=dict(zip(inputs, [input_value])))
62
63  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
64