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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 reduce operators."""
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
27def make_reduce_tests(reduce_op,
28                      min_value=-10,
29                      max_value=10,
30                      boolean_tensor_only=False,
31                      allow_fully_quantize=False):
32  """Make a set of tests to do reduce operation.
33
34  Args:
35    reduce_op: TensorFlow reduce operation to test, i.e. `tf.reduce_mean`.
36    min_value: min value for created tensor data.
37    max_value: max value for created tensor data.
38    boolean_tensor_only: If true, will only generate tensor with boolean value.
39    allow_fully_quantize: bool, whether fully_quantize is allowed.
40
41  Returns:
42    a function representing the true generator with `reduce_op_in` curried.
43  """
44
45  def f(options):
46    """Actual function that generates examples."""
47
48    test_parameters = [
49        {
50            "input_dtype": [tf.float32, tf.int32, tf.int64],
51            "input_shape": [[3, 3, 2, 4]],
52            "axis": [
53                0,
54                1,
55                2,
56                [0, 1],
57                [0, 2],
58                [1, 2],
59                [0, 1, 2],
60                [1, 0],
61                [2, 0],
62                [2, 1],
63                [2, 1, 0],
64                [2, 0, 1],
65                -1,
66                -2,
67                -3,
68                [1, -1],
69                [0, -1],
70                [-1, 0],
71                [-1, -2, -3],
72            ],
73            "const_axis": [True, False],
74            "keepdims": [True, False],
75            "fully_quantize": [False],
76        },
77        {
78            "input_dtype": [tf.float32],
79            "input_shape": [[1, 8, 8, 3]],
80            "axis": [
81                0,
82                1,
83                2,
84                3,
85                [1, 2],
86                [0, 3],
87                [1, 2, 3],
88                [0, 1, 2, 3],
89                [3, 2, 1, 0],
90                [3, 1, 0, 2],
91                [2, 0],
92                [3, 0],
93                [3, 1],
94                [1, 0],
95                -1,
96                -2,
97                -3,
98                -4,
99                [0, -2],
100                [2, 3, 1, 0],
101                [3, 1, 2],
102                [3, -4],
103            ],
104            "const_axis": [True, False],
105            "keepdims": [True, False],
106            "fully_quantize": [False],
107        },
108        {
109            "input_dtype": [tf.float32],
110            "input_shape": [[], [1, 8, 8, 3], [3, 2, 4]],
111            "axis": [[]],  # shape is: [0]
112            "const_axis": [False],
113            "keepdims": [True, False],
114            "fully_quantize": [False],
115        },
116        {
117            "input_dtype": [tf.float32],
118            "input_shape": [[], [1, 8, 8, 3], [3, 2, 4]],
119            "axis": [None],  # shape is: []
120            "const_axis": [True],
121            "keepdims": [True, False],
122            "fully_quantize": [False],
123        },
124        {
125            "input_dtype": [tf.float32],
126            "input_shape": [[3, 3, 2, 4]],
127            "axis": [
128                0,
129                1,
130                2,
131                [0, 1],
132                [0, 2],
133                [1, 2],
134                [0, 1, 2],
135                [1, 0],
136                [2, 0],
137                [2, 1],
138                [2, 1, 0],
139                [2, 0, 1],
140                -1,
141                -2,
142                -3,
143                [1, -1],
144                [0, -1],
145                [-1, 0],
146                [-1, -2, -3],
147            ],
148            "const_axis": [True],
149            "keepdims": [True, False],
150            "fully_quantize": [True],
151        },
152        {
153            "input_dtype": [tf.float32],
154            "input_shape": [[1, 8, 8, 4], [1, 8, 8, 3]],
155            "axis": [
156                0, 1, 2, 3, [0], [1], [2], [3], [-1], [-2], [-3], [1, 2],
157                [0, 3], [1, 2, 3], [1, 3], [2, 3]
158            ],
159            "const_axis": [True],
160            "keepdims": [True, False],
161            "fully_quantize": [True],
162        },
163        {
164            "input_dtype": [tf.float32, tf.int32],
165            "input_shape": [[2, 0, 2], [0]],
166            "axis": [0],
167            "const_axis": [True],
168            "keepdims": [True, False],
169            "fully_quantize": [False],
170        },
171    ]
172    # test_parameters include fully_quantize option only when
173    # allow_fully_quantize is True.
174    if not allow_fully_quantize:
175      test_parameters = [
176          test_parameter for test_parameter in test_parameters
177          if True not in test_parameter["fully_quantize"]
178      ]
179
180    def build_graph(parameters):
181      """Build the mean op testing graph."""
182      dtype = parameters["input_dtype"]
183      if boolean_tensor_only:
184        dtype = tf.bool
185      input_tensor = tf.compat.v1.placeholder(
186          dtype=dtype, name="input", shape=parameters["input_shape"])
187
188      # Get axis as either a placeholder or constants.
189      if parameters["const_axis"]:
190        axis = parameters["axis"]
191        input_tensors = [input_tensor]
192      else:
193        if isinstance(parameters["axis"], list):
194          shape = [len(parameters["axis"])]
195        else:
196          shape = []  # shape for None or integers.
197        axis = tf.compat.v1.placeholder(
198            dtype=tf.int32, name="axis", shape=shape)
199        input_tensors = [input_tensor, axis]
200
201      out = reduce_op(input_tensor, axis=axis, keepdims=parameters["keepdims"])
202      return input_tensors, [out]
203
204    def build_inputs(parameters, sess, inputs, outputs):
205      """Build the inputs for reduced operators."""
206
207      dtype = parameters["input_dtype"]
208      if boolean_tensor_only:
209        dtype = tf.bool
210      values = [
211          create_tensor_data(
212              dtype,
213              parameters["input_shape"],
214              min_value=min_value,
215              max_value=max_value)
216      ]
217      if not parameters["const_axis"]:
218        values.append(np.array(parameters["axis"]))
219      return values, sess.run(outputs, feed_dict=dict(zip(inputs, values)))
220
221    make_zip_of_tests(options, test_parameters, build_graph, build_inputs)
222
223  return f
224
225
226@register_make_test_function()
227def make_mean_tests(options):
228  """Make a set of tests to do mean."""
229  return make_reduce_tests(
230      tf.reduce_mean,
231      min_value=-1,
232      max_value=1,
233      boolean_tensor_only=False,
234      allow_fully_quantize=True)(
235          options)
236
237
238@register_make_test_function()
239def make_sum_tests(options):
240  """Make a set of tests to do sum."""
241  return make_reduce_tests(
242      tf.reduce_sum,
243      min_value=-1,
244      max_value=1,
245      boolean_tensor_only=False,
246      allow_fully_quantize=True)(
247          options)
248
249
250@register_make_test_function()
251def make_reduce_prod_tests(options):
252  """Make a set of tests to do prod."""
253  # set min max value to be -2, 2 to avoid overflow.
254  return make_reduce_tests(tf.reduce_prod, -2, 2)(options)
255
256
257@register_make_test_function()
258def make_reduce_max_tests(options):
259  """Make a set of tests to do max."""
260  return make_reduce_tests(
261      tf.reduce_max, allow_fully_quantize=True, min_value=-1, max_value=1)(
262          options)
263
264
265@register_make_test_function()
266def make_reduce_min_tests(options):
267  """Make a set of tests to do min."""
268  return make_reduce_tests(
269      tf.reduce_min, allow_fully_quantize=True, min_value=-1, max_value=1)(
270          options)
271
272
273@register_make_test_function()
274def make_reduce_any_tests(options):
275  """Make a set of tests to do any."""
276  return make_reduce_tests(tf.reduce_any, boolean_tensor_only=True)(options)
277
278
279@register_make_test_function()
280def make_reduce_all_tests(options):
281  """Make a set of tests to do all."""
282  return make_reduce_tests(tf.reduce_all, boolean_tensor_only=True)(options)
283