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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 shape."""
16from __future__ import absolute_import
17from __future__ import division
18from __future__ import print_function
19
20import numpy as np
21import tensorflow 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_shape_tests(options):
29  """Make a set of tests to do shape."""
30
31  test_parameters = [{
32      "input_dtype": [tf.float32, tf.int32],
33      "input_shape": [[1, 4]],
34      "new_shape": [[1, 4], [4, 1], [2, 2]],
35      "out_type": [tf.int32, tf.int64],
36  }]
37
38  def build_graph(parameters):
39    """Build the shape op testing graph."""
40    # Note that we intentionally leave out the shape from the input placeholder
41    # to prevent the Shape operation from being optimized out during conversion.
42    # TODO(haoliang): Test shape op directly after we have better support for
43    # dynamic input. Currently we need to introduce a Reshape op to prevent
44    # shape being constant-folded.
45    input_value = tf.compat.v1.placeholder(
46        dtype=parameters["input_dtype"],
47        shape=parameters["input_shape"],
48        name="input")
49    shape_of_new_shape = [len(parameters["new_shape"])]
50    new_shape = tf.compat.v1.placeholder(
51        dtype=tf.int32, shape=shape_of_new_shape, name="new_shape")
52    reshaped = tf.reshape(input_value, shape=new_shape)
53    out = tf.shape(reshaped, out_type=parameters["out_type"])
54    return [input_value, new_shape], [out]
55
56  def build_inputs(parameters, sess, inputs, outputs):
57    input_value = create_tensor_data(parameters["input_dtype"],
58                                     parameters["input_shape"])
59    new_shape = np.array(parameters["new_shape"])
60    return [input_value, new_shape], sess.run(
61        outputs, feed_dict=dict(zip(inputs, [input_value, new_shape])))
62
63  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
64