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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 pad."""
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_pad_tests(options):
29  """Make a set of tests to do pad."""
30
31  # TODO(nupurgarg): Add test for tf.uint8.
32  test_parameters = [
33      # 5D:
34      {
35          "dtype": [tf.int32, tf.int64, tf.float32],
36          "input_shape": [[1, 1, 2, 1, 1], [2, 1, 1, 1, 1]],
37          "paddings": [[[0, 0], [0, 1], [2, 3], [0, 0], [1, 0]],
38                       [[0, 1], [0, 0], [0, 0], [2, 3], [1, 0]]],
39          "constant_paddings": [True, False],
40          "fully_quantize": [False],
41          "quant_16x8": [False]
42      },
43      # 4D:
44      {
45          "dtype": [tf.int32, tf.int64, tf.float32],
46          "input_shape": [[1, 1, 2, 1], [2, 1, 1, 1]],
47          "paddings": [[[0, 0], [0, 1], [2, 3], [0, 0]],
48                       [[0, 1], [0, 0], [0, 0], [2, 3]]],
49          "constant_paddings": [True, False],
50          "fully_quantize": [False],
51          "quant_16x8": [False]
52      },
53      # 2D:
54      {
55          "dtype": [tf.int32, tf.int64, tf.float32],
56          "input_shape": [[1, 2]],
57          "paddings": [[[0, 1], [2, 3]]],
58          "constant_paddings": [True, False],
59          "fully_quantize": [False],
60          "quant_16x8": [False]
61      },
62      # 1D:
63      {
64          "dtype": [tf.int32],
65          "input_shape": [[1]],
66          "paddings": [[[1, 2]]],
67          "constant_paddings": [False],
68          "fully_quantize": [False],
69          "quant_16x8": [False]
70      },
71      # 4D:
72      {
73          "dtype": [tf.float32],
74          "input_shape": [[1, 1, 2, 1], [2, 1, 1, 1]],
75          "paddings": [[[0, 0], [0, 1], [2, 3], [0, 0]],
76                       [[0, 1], [0, 0], [0, 0], [2, 3]],
77                       [[0, 0], [0, 0], [0, 0], [0, 0]]],
78          "constant_paddings": [True],
79          "fully_quantize": [True],
80          "quant_16x8": [False, True]
81      },
82      # 2D:
83      {
84          "dtype": [tf.float32],
85          "input_shape": [[1, 2]],
86          "paddings": [[[0, 1], [2, 3]]],
87          "constant_paddings": [True],
88          "fully_quantize": [True],
89          "quant_16x8": [False, True],
90      },
91      # 1D:
92      {
93          "dtype": [tf.float32],
94          "input_shape": [[1]],
95          "paddings": [[[1, 2]]],
96          "constant_paddings": [True],
97          "fully_quantize": [True],
98          "quant_16x8": [False, True],
99      },
100  ]
101
102  def build_graph(parameters):
103    """Build a pad graph given `parameters`."""
104    input_tensor = tf.compat.v1.placeholder(
105        dtype=parameters["dtype"],
106        name="input",
107        shape=parameters["input_shape"])
108
109    # Get paddings as either a placeholder or constants.
110    if parameters["constant_paddings"]:
111      paddings = parameters["paddings"]
112      input_tensors = [input_tensor]
113    else:
114      shape = [len(parameters["paddings"]), 2]
115      paddings = tf.compat.v1.placeholder(
116          dtype=tf.int32, name="padding", shape=shape)
117      input_tensors = [input_tensor, paddings]
118
119    out = tf.pad(input_tensor, paddings=paddings)
120    return input_tensors, [out]
121
122  def build_inputs(parameters, sess, inputs, outputs):
123    """Build inputs for pad op."""
124
125    values = [
126        create_tensor_data(
127            parameters["dtype"],
128            parameters["input_shape"],
129            min_value=-1,
130            max_value=1)
131    ]
132    if not parameters["constant_paddings"]:
133      values.append(np.array(parameters["paddings"]))
134    return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
135
136  make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
137