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# Copyright 2016 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.
# ==============================================================================
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import six
import tensorflow as tf
from tensorflow.core.framework import types_pb2
class ScalarSummaryTest(tf.test.TestCase):
def testDtypeErrors(self):
def _TryMakingScalarSummary(dtype):
base = dtype.base_dtype
if base == tf.bool:
v = False
elif base == tf.string:
v = ''
elif base.is_complex:
v = complex(0, 0)
else:
v = base.min
c = tf.constant(v, dtype)
return tf.summary.scalar('name', c)
for datatype_enum in types_pb2.DataType.values():
if datatype_enum == types_pb2.DT_INVALID:
continue
dtype = tf.as_dtype(datatype_enum)
if dtype.is_quantized:
# Quantized ops are funky, and not expected to work.
continue
if dtype.is_integer or dtype.is_floating:
_TryMakingScalarSummary(dtype)
# No exception should be thrown
else:
with self.assertRaises(ValueError):
_TryMakingScalarSummary(dtype)
def testShapeErrors(self):
c1 = tf.constant(0)
c2 = tf.zeros(5)
c3 = tf.zeros(5, 5)
tf.summary.scalar('1', c1)
with self.assertRaises(ValueError):
tf.summary.scalar('2', c2)
with self.assertRaises(ValueError):
tf.summary.scalar('3', c3)
def testLabelsAdded(self):
c = tf.constant(0)
no_labels = tf.summary.scalar('2', c)
labels = tf.summary.scalar('1', c, labels=['foo'])
def _GetLabels(n):
return n.op.get_attr('labels')
expected_label = six.b(tf.summary.SCALAR_SUMMARY_LABEL)
self.assertEquals(_GetLabels(no_labels), [expected_label])
self.assertEquals(_GetLabels(labels), [six.b('foo'), expected_label])
def testTensorSummaryOpCreated(self):
c = tf.constant(0)
s = tf.summary.scalar('', c)
self.assertEquals(s.op.type, 'TensorSummary')
self.assertEquals(s.op.inputs[0], c)
if __name__ == '__main__':
tf.test.main()