forked from tensorflow/tensorflow
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathtest_util_test.py
More file actions
329 lines (276 loc) · 10.9 KB
/
test_util_test.py
File metadata and controls
329 lines (276 loc) · 10.9 KB
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
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
# Copyright 2015 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 tensorflow.ops.test_util."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import random
import threading
import numpy as np
from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tensorflow.core.protobuf import meta_graph_pb2
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
from tensorflow.python.framework import test_util
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.platform import googletest
class TestUtilTest(test_util.TensorFlowTestCase):
def test_assert_ops_in_graph(self):
with self.test_session():
constant_op.constant(["hello", "taffy"], name="hello")
test_util.assert_ops_in_graph({"hello": "Const"}, ops.get_default_graph())
self.assertRaises(ValueError, test_util.assert_ops_in_graph,
{"bye": "Const"}, ops.get_default_graph())
self.assertRaises(ValueError, test_util.assert_ops_in_graph,
{"hello": "Variable"}, ops.get_default_graph())
def test_assert_equal_graph_def(self):
with ops.Graph().as_default() as g:
def_empty = g.as_graph_def()
constant_op.constant(5, name="five")
constant_op.constant(7, name="seven")
def_57 = g.as_graph_def()
with ops.Graph().as_default() as g:
constant_op.constant(7, name="seven")
constant_op.constant(5, name="five")
def_75 = g.as_graph_def()
# Comparing strings is order dependent
self.assertNotEqual(str(def_57), str(def_75))
# assert_equal_graph_def doesn't care about order
test_util.assert_equal_graph_def(def_57, def_75)
# Compare two unequal graphs
with self.assertRaisesRegexp(AssertionError,
r"^Found unexpected node 'seven"):
test_util.assert_equal_graph_def(def_57, def_empty)
def testIsGoogleCudaEnabled(self):
# The test doesn't assert anything. It ensures the py wrapper
# function is generated correctly.
if test_util.IsGoogleCudaEnabled():
print("GoogleCuda is enabled")
else:
print("GoogleCuda is disabled")
def testAssertProtoEqualsStr(self):
graph_str = "node { name: 'w1' op: 'params' }"
graph_def = graph_pb2.GraphDef()
text_format.Merge(graph_str, graph_def)
# test string based comparison
self.assertProtoEquals(graph_str, graph_def)
# test original comparison
self.assertProtoEquals(graph_def, graph_def)
def testAssertProtoEqualsAny(self):
# Test assertProtoEquals with a protobuf.Any field.
meta_graph_def_str = """
meta_info_def {
meta_graph_version: "outer"
any_info {
[type.googleapis.com/tensorflow.MetaGraphDef] {
meta_info_def {
meta_graph_version: "inner"
}
}
}
}
"""
meta_graph_def_outer = meta_graph_pb2.MetaGraphDef()
meta_graph_def_outer.meta_info_def.meta_graph_version = "outer"
meta_graph_def_inner = meta_graph_pb2.MetaGraphDef()
meta_graph_def_inner.meta_info_def.meta_graph_version = "inner"
meta_graph_def_outer.meta_info_def.any_info.Pack(meta_graph_def_inner)
self.assertProtoEquals(meta_graph_def_str, meta_graph_def_outer)
self.assertProtoEquals(meta_graph_def_outer, meta_graph_def_outer)
# Check if the assertion failure message contains the content of
# the inner proto.
with self.assertRaisesRegexp(AssertionError,
r'meta_graph_version: "inner"'):
self.assertProtoEquals("", meta_graph_def_outer)
def testNDArrayNear(self):
a1 = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
a2 = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
a3 = np.array([[10.0, 20.0, 30.0], [40.0, 50.0, 60.0]])
self.assertTrue(self._NDArrayNear(a1, a2, 1e-5))
self.assertFalse(self._NDArrayNear(a1, a3, 1e-5))
def testCheckedThreadSucceeds(self):
def noop(ev):
ev.set()
event_arg = threading.Event()
self.assertFalse(event_arg.is_set())
t = self.checkedThread(target=noop, args=(event_arg,))
t.start()
t.join()
self.assertTrue(event_arg.is_set())
def testCheckedThreadFails(self):
def err_func():
return 1 // 0
t = self.checkedThread(target=err_func)
t.start()
with self.assertRaises(self.failureException) as fe:
t.join()
self.assertTrue("integer division or modulo by zero" in str(fe.exception))
def testCheckedThreadWithWrongAssertionFails(self):
x = 37
def err_func():
self.assertTrue(x < 10)
t = self.checkedThread(target=err_func)
t.start()
with self.assertRaises(self.failureException) as fe:
t.join()
self.assertTrue("False is not true" in str(fe.exception))
def testMultipleThreadsWithOneFailure(self):
def err_func(i):
self.assertTrue(i != 7)
threads = [
self.checkedThread(
target=err_func, args=(i,)) for i in range(10)
]
for t in threads:
t.start()
for i, t in enumerate(threads):
if i == 7:
with self.assertRaises(self.failureException):
t.join()
else:
t.join()
def _WeMustGoDeeper(self, msg):
with self.assertRaisesOpError(msg):
node_def = ops._NodeDef("op_type", "name")
node_def_orig = ops._NodeDef("op_type_orig", "orig")
op_orig = ops.Operation(node_def_orig, ops.get_default_graph())
op = ops.Operation(node_def, ops.get_default_graph(), original_op=op_orig)
raise errors.UnauthenticatedError(node_def, op, "true_err")
def testAssertRaisesOpErrorDoesNotPassMessageDueToLeakedStack(self):
with self.assertRaises(AssertionError):
self._WeMustGoDeeper("this_is_not_the_error_you_are_looking_for")
self._WeMustGoDeeper("true_err")
self._WeMustGoDeeper("name")
self._WeMustGoDeeper("orig")
def testAllCloseScalars(self):
self.assertAllClose(7, 7 + 1e-8)
with self.assertRaisesRegexp(AssertionError, r"Not equal to tolerance"):
self.assertAllClose(7, 7 + 1e-5)
def testAllCloseDictToNonDict(self):
with self.assertRaisesRegexp(ValueError, r"Can't compare dict to non-dict"):
self.assertAllClose(1, {"a": 1})
with self.assertRaisesRegexp(ValueError, r"Can't compare dict to non-dict"):
self.assertAllClose({"a": 1}, 1)
def testAllCloseDicts(self):
a = 7
b = (2., 3.)
c = np.ones((3, 2, 4)) * 7.
expected = {"a": a, "b": b, "c": c}
# Identity.
self.assertAllClose(expected, expected)
self.assertAllClose(expected, dict(expected))
# With each item removed.
for k in expected:
actual = dict(expected)
del actual[k]
with self.assertRaisesRegexp(AssertionError, r"mismatched keys"):
self.assertAllClose(expected, actual)
# With each item changed.
with self.assertRaisesRegexp(AssertionError, r"Not equal to tolerance"):
self.assertAllClose(expected, {"a": a + 1e-5, "b": b, "c": c})
with self.assertRaisesRegexp(AssertionError, r"Shape mismatch"):
self.assertAllClose(expected, {"a": a, "b": b + (4.,), "c": c})
c_copy = np.array(c)
c_copy[1, 1, 1] += 1e-5
with self.assertRaisesRegexp(AssertionError, r"Not equal to tolerance"):
self.assertAllClose(expected, {"a": a, "b": b, "c": c_copy})
def testAllCloseNestedDicts(self):
a = {"a": 1, "b": 2, "nested": {"d": 3, "e": 4}}
with self.assertRaisesRegexp(
TypeError,
r"inputs could not be safely coerced to any supported types"):
self.assertAllClose(a, a)
def testArrayNear(self):
a = [1, 2]
b = [1, 2, 5]
with self.assertRaises(AssertionError):
self.assertArrayNear(a, b, 0.001)
a = [1, 2]
b = [[1, 2], [3, 4]]
with self.assertRaises(TypeError):
self.assertArrayNear(a, b, 0.001)
a = [1, 2]
b = [1, 2]
self.assertArrayNear(a, b, 0.001)
def testForceGPU(self):
with self.assertRaises(errors.InvalidArgumentError):
with self.test_session(force_gpu=True):
# this relies on us not having a GPU implementation for assert, which
# seems sensible
x = constant_op.constant(True)
y = [15]
control_flow_ops.Assert(x, y).run()
def testAssertAllCloseAccordingToType(self):
# test float64
self.assertAllCloseAccordingToType(
np.asarray([1e-8], dtype=np.float64),
np.asarray([2e-8], dtype=np.float64),
rtol=1e-8, atol=1e-8
)
with (self.assertRaises(AssertionError)):
self.assertAllCloseAccordingToType(
np.asarray([1e-7], dtype=np.float64),
np.asarray([2e-7], dtype=np.float64),
rtol=1e-8, atol=1e-8
)
# test float32
self.assertAllCloseAccordingToType(
np.asarray([1e-7], dtype=np.float32),
np.asarray([2e-7], dtype=np.float32),
rtol=1e-8, atol=1e-8,
float_rtol=1e-7, float_atol=1e-7
)
with (self.assertRaises(AssertionError)):
self.assertAllCloseAccordingToType(
np.asarray([1e-6], dtype=np.float32),
np.asarray([2e-6], dtype=np.float32),
rtol=1e-8, atol=1e-8,
float_rtol=1e-7, float_atol=1e-7
)
# test float16
self.assertAllCloseAccordingToType(
np.asarray([1e-4], dtype=np.float16),
np.asarray([2e-4], dtype=np.float16),
rtol=1e-8, atol=1e-8,
float_rtol=1e-7, float_atol=1e-7,
half_rtol=1e-4, half_atol=1e-4
)
with (self.assertRaises(AssertionError)):
self.assertAllCloseAccordingToType(
np.asarray([1e-3], dtype=np.float16),
np.asarray([2e-3], dtype=np.float16),
rtol=1e-8, atol=1e-8,
float_rtol=1e-7, float_atol=1e-7,
half_rtol=1e-4, half_atol=1e-4
)
def testRandomSeed(self):
a = random.randint(1, 1000)
a_np_rand = np.random.rand(1)
with self.test_session():
a_rand = random_ops.random_normal([1]).eval()
# ensure that randomness in multiple testCases is deterministic.
self.setUp()
b = random.randint(1, 1000)
b_np_rand = np.random.rand(1)
with self.test_session():
b_rand = random_ops.random_normal([1]).eval()
self.assertEqual(a, b)
self.assertEqual(a_np_rand, b_np_rand)
self.assertEqual(a_rand, b_rand)
if __name__ == "__main__":
googletest.main()