aboutsummaryrefslogtreecommitdiffhomepage
path: root/tensorflow/python/autograph/converters/control_flow_test.py
blob: 03fdfc804e497680c205df1945ac7c6079c51a41 (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for control_flow module."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from tensorflow.python.autograph.converters import control_flow
from tensorflow.python.autograph.core import converter_testing
from tensorflow.python.autograph.pyct import transformer
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.platform import test


class ControlFlowTest(converter_testing.TestCase):

  def assertTransformedResult(self, test_fn, inputs, expected):
    if not isinstance(inputs, tuple):
      inputs = (inputs,)
    with self.converted(test_fn, control_flow, {},
                        constant_op.constant) as result:
      with self.cached_session() as sess:
        self.assertEqual(sess.run(result.test_fn(*inputs)), expected)

  def test_while_basic(self):

    def test_fn(n):
      i = 0
      s = 0
      while i < n:
        s += i
        i += 1
      return s, i, n

    self.assertTransformedResult(test_fn, constant_op.constant(5), (10, 5, 5))

  def test_while_nested(self):

    def test_fn(n):
      i = 0
      j = 0
      s = 0
      while i < n:
        while j < i:
          j += 3
        u = i + j  # 'u' is not defined within the inner loop
        s += u
        i += 1
        j = 0
      return s, i, j, n

    self.assertTransformedResult(test_fn, constant_op.constant(5),
                                 (25, 5, 0, 5))

  def test_while_single_output(self):

    def test_fn(n):
      while n > 0:
        n -= 1
      return n

    self.assertTransformedResult(test_fn, constant_op.constant(5), 0)

  def test_while_variable_defined_in_body(self):
    def bad_while_loop(n):
      while n > 0:
        n -= 1
        s = n
      return s

    node, ctx = self.prepare(bad_while_loop, {})
    with self.assertRaises(NameError):
      control_flow.transform(node, ctx)

  def test_if_basic(self):

    def test_fn(n):
      a = 0
      b = 0
      if n > 0:
        a = -n
      else:
        b = 2 * n
      return a, b

    self.assertTransformedResult(test_fn, constant_op.constant(1), (-1, 0))
    self.assertTransformedResult(test_fn, constant_op.constant(-1), (0, -2))

  def test_if_complex_outputs(self):

    class TestClass(object):

      def __init__(self, a, b):
        self.a = a
        self.b = b

    def test_fn(n, obj):
      obj.a = 0
      obj.b = 0
      if n > 0:
        obj.a = -n
      else:
        obj.b = 2 * n
      return obj

    with self.converted(test_fn, control_flow, {}) as result:
      with self.cached_session() as sess:
        res_obj = result.test_fn(constant_op.constant(1), TestClass(0, 0))
        self.assertEqual(sess.run((res_obj.a, res_obj.b)), (-1, 0))
        res_obj = result.test_fn(constant_op.constant(-1), TestClass(0, 0))
        self.assertEqual(sess.run((res_obj.a, res_obj.b)), (0, -2))

  def test_if_single_output(self):

    def test_fn(n):
      if n > 0:
        n = -n
      return n

    self.assertTransformedResult(test_fn, constant_op.constant(1), -1)

  def test_if_semi(self):

    def test_fn(n):
      if n > 0:
        n = 3
      return n

    self.assertTransformedResult(test_fn, constant_op.constant(2), 3)
    self.assertTransformedResult(test_fn, constant_op.constant(-3), -3)

  def test_if_local_var(self):

    def test_fn(n):
      if n > 0:
        b = 4
        n = b + 1
      return n

    self.assertTransformedResult(test_fn, constant_op.constant(1), 5)
    self.assertTransformedResult(test_fn, constant_op.constant(-1), -1)

  def test_if_no_outputs(self):

    def test_fn(n):
      if n > 0:
        b = 4  # pylint:disable=unused-variable
      return n

    # Without side effect guards, the if statement will stage a cond,
    # but that will be pruned at execution.
    self.assertTransformedResult(test_fn, constant_op.constant(1), 1)
    self.assertTransformedResult(test_fn, constant_op.constant(-1), -1)

  def test_if_imbalanced_outputs(self):

    def test_fn(n):
      if n > 0:
        b = 4
      return b

    node, ctx = self.prepare(test_fn, {})
    with self.assertRaises(transformer.AutographParseError):
      control_flow.transform(node, ctx)

  def test_simple_for(self):

    def test_fn(l):
      s1 = 0
      s2 = 0
      for e in l:
        s1 += e
        s2 += e * e
      return s1, s2

    self.assertTransformedResult(test_fn, constant_op.constant([1, 3]), (4, 10))
    empty_vector = constant_op.constant([], shape=(0,), dtype=dtypes.int32)
    self.assertTransformedResult(test_fn, empty_vector, (0, 0))

  def test_for_single_output(self):

    def test_fn(l):
      s = 0
      for e in l:
        s += e
      return s

    self.assertTransformedResult(test_fn, constant_op.constant([1, 3]), 4)
    empty_vector = constant_op.constant([], shape=(0,), dtype=dtypes.int32)
    self.assertTransformedResult(test_fn, empty_vector, 0)

  def test_for_iterated_expression(self):

    eval_count = [0]

    def count_evals(x):
      eval_count[0] += 1
      return x

    def test_fn(n):
      s = 0
      for e in count_evals(range(n)):
        s += e
      return s

    ns = {'count_evals': count_evals}
    node, ctx = self.prepare(test_fn, ns)
    node = control_flow.transform(node, ctx)

    with self.compiled(node, ns) as result:
      self.assertEqual(result.test_fn(5), 10)
      self.assertEqual(eval_count[0], 1)

  def test_for_variable_defined_in_body(self):
    def bad_for_loop(n):
      for i in range(n):
        s = i
      return s

    node, ctx = self.prepare(bad_for_loop, {})
    with self.assertRaises(NameError):
      control_flow.transform(node, ctx)

  def test_for_tuple_unpacking(self):
    def test_fn(x_list):
      z = tf.constant(0)  # pylint:disable=undefined-variable
      for i, x in enumerate(x_list):
        z = z + x + i
      return z

    self.assertTransformedResult(test_fn, [3, 3], 7)
if __name__ == '__main__':
  test.main()