def testMultipleDatasetWithPrefixes(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator, prefix="dataset1")
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset2 = dataset_transformation(dataset2, aggregator, prefix="dataset2")
iterator_0 = dataset_ops.make_initializable_iterator(dataset)
iterator_1 = dataset_ops.make_initializable_iterator(dataset2)
next_element = iterator_0.get_next() + iterator_1.get_next()
summary_t = aggregator.get_summary()
with self.test_session() as sess:
self.evaluate([iterator_0.initializer, iterator_1.initializer])
for i in range(100):
self.assertEqual(i * 2, self.evaluate(next_element))
self._assertSummaryHasCount(
self.evaluate(summary_t), "dataset1_record_latency", float(i + 1))
self._assertSummaryHasCount(
self.evaluate(summary_t), "dataset2_record_latency", float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
self._assertSummaryHasCount(
self.evaluate(summary_t), "dataset1_record_latency", 100.0)
self._assertSummaryHasCount(
self.evaluate(summary_t), "dataset2_record_latency", 100.0)
def testMultipleDatasetWithPrefixes(self):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = self.datasetExperimentalStats(
dataset, aggregator, prefix="dataset1")
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset2 = self.datasetExperimentalStats(
dataset2, aggregator, prefix="dataset2")
next_element1 = self.getNext(dataset, requires_initialization=True)
next_element2 = self.getNext(dataset2, requires_initialization=True)
for i in range(100):
self.assertEqual(i * 2, self.evaluate(next_element1() + next_element2()))
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(
handle, "dataset1::record_latency", float(i + 1), 2 * i + 3, offset=1)
self.assertStatisticsHasCount(handle, "dataset2::record_latency",
float(i + 1), 2 * i + 3)
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element1())
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element2())
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(
handle, "dataset1::record_latency", 100.0, 201, offset=1)
self.assertStatisticsHasCount(handle, "dataset2::record_latency", 100.0,
201)
def testMultipleDatasetWithPrefixes(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator, prefix="dataset1")
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset2 = dataset_transformation(dataset2, aggregator, prefix="dataset2")
next_element1 = self.getNext(dataset, requires_initialization=True)
next_element2 = self.getNext(dataset2, requires_initialization=True)
for i in range(100):
self.assertEqual(i * 2, self.evaluate(next_element1() + next_element2()))
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset1_record_latency",
float(i + 1))
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset2_record_latency",
float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element1())
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element2())
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset1_record_latency",
100.0)
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset2_record_latency",
100.0)
def testMultipleDatasetWithPrefixes(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator, prefix="dataset1")
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset2 = dataset_transformation(dataset2, aggregator, prefix="dataset2")
next_element1 = self.getNext(dataset, requires_initialization=True)
next_element2 = self.getNext(dataset2, requires_initialization=True)
for i in range(100):
self.assertEqual(i * 2, self.evaluate(next_element1() + next_element2()))
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset1_record_latency",
float(i + 1))
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset2_record_latency",
float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element1())
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element2())
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset1_record_latency",
100.0)
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "dataset2_record_latency",
100.0)
def testMultipleTags(self):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency_2"))
dataset = self.datasetExperimentalStats(dataset, aggregator)
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle,
"record_latency",
float(i + 1),
2 * i + 3,
offset=1)
self.assertStatisticsHasCount(handle, "record_latency_2",
float(i + 1), 2 * i + 3)
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle,
"record_latency",
100.0,
201,
offset=1)
self.assertStatisticsHasCount(handle, "record_latency_2", 100.0, 201)
def testMultipleDatasetWithTags(self):
stats_aggregator = stats_ops.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.set_stats_aggregator(stats_aggregator, "dataset1"))
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.set_stats_aggregator(stats_aggregator, "dataset2"))
iterator_0 = dataset.make_initializable_iterator()
iterator_1 = dataset2.make_initializable_iterator()
next_element = iterator_0.get_next() + iterator_1.get_next()
summary_t = stats_aggregator.get_summary()
with self.test_session() as sess:
sess.run([iterator_0.initializer, iterator_1.initializer])
for i in range(100):
self.assertEqual(i * 2, sess.run(next_element))
self._assertSummaryHasCount(
sess.run(summary_t), "dataset1_record_latency", float(i + 1))
self._assertSummaryHasCount(
sess.run(summary_t), "dataset2_record_latency", float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
self._assertSummaryHasCount(
sess.run(summary_t), "dataset1_record_latency", 100.0)
self._assertSummaryHasCount(
sess.run(summary_t), "dataset2_record_latency", 100.0)
def testMultipleDatasetWithPrefixes(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset,
aggregator,
prefix="dataset1")
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset2 = dataset_transformation(dataset2,
aggregator,
prefix="dataset2")
iterator_0 = dataset.make_initializable_iterator()
iterator_1 = dataset2.make_initializable_iterator()
next_element = iterator_0.get_next() + iterator_1.get_next()
summary_t = aggregator.get_summary()
with self.test_session() as sess:
sess.run([iterator_0.initializer, iterator_1.initializer])
for i in range(100):
self.assertEqual(i * 2, self.evaluate(next_element))
self._assertSummaryHasCount(sess.run(summary_t),
"dataset1_record_latency",
float(i + 1))
self._assertSummaryHasCount(sess.run(summary_t),
"dataset2_record_latency",
float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
self._assertSummaryHasCount(sess.run(summary_t),
"dataset1_record_latency", 100.0)
self._assertSummaryHasCount(sess.run(summary_t),
"dataset2_record_latency", 100.0)
def testRepeatedTags(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator)
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "record_latency",
float(2 * (i + 1)))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "record_latency", 200.0)
def testRepeatedTags(self):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency"))
dataset = self.datasetExperimentalStats(dataset, aggregator)
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle, "record_latency",
float(2 * (i + 1)), 2 * i + 3)
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle, "record_latency", 200.0, 201)
def testRepeatedTags(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator)
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "record_latency",
float(2 * (i + 1)))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
self._assertSummaryHasCount(
self.evaluate(aggregator.get_summary()), "record_latency", 200.0)
def test_latency_stats_invalid_tag_shape(self):
with self.assertRaisesRegexp(
ValueError, "Shape must be rank 0 but is rank 1"):
# pylint: disable=g-long-lambda
self.run_core_tests(
lambda: dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats(["record_latency", "record_latency_2"])),
100)
def test_latency_stats_invalid_tag_shape(self):
with self.assertRaisesRegexp(
ValueError, "Shape must be rank 0 but is rank 1"):
# pylint: disable=g-long-lambda
self.run_core_tests(
lambda: dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats(["record_latency", "record_latency_2"])),
None, 100)
def testNoAggregatorRegistered(self):
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
def testNoAggregatorRegistered(self, dataset_transformation):
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
def testRepeatedTags(self):
stats_aggregator = stats_ops.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.set_stats_aggregator(stats_aggregator))
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
summary_t = stats_aggregator.get_summary()
with self.cached_session() as sess:
sess.run(iterator.initializer)
for i in range(100):
self.assertEqual(i, sess.run(next_element))
self._assertSummaryHasCount(
sess.run(summary_t), "record_latency", float(2 * (i + 1)))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
self._assertSummaryHasCount(sess.run(summary_t), "record_latency", 200.0)
def testNoAggregatorRegistered(self, dataset_transformation):
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
with self.cached_session() as sess:
self.evaluate(iterator.initializer)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
def testNoAggregatorRegistered(self, dataset_transformation):
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
iterator = dataset_ops.make_initializable_iterator(dataset)
next_element = iterator.get_next()
with self.cached_session() as sess:
self.evaluate(iterator.initializer)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
def DISABLED_testMultipleDatasetWithPrefixes(self):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = self.datasetExperimentalStats(dataset,
aggregator,
prefix="dataset1")
dataset2 = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset2 = self.datasetExperimentalStats(dataset2,
aggregator,
prefix="dataset2")
next_element1 = self.getNext(dataset, requires_initialization=True)
next_element2 = self.getNext(dataset2, requires_initialization=True)
for i in range(100):
self.assertEqual(i * 2,
self.evaluate(next_element1() + next_element2()))
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle,
"dataset1::record_latency",
float(i + 1),
2 * i + 3,
offset=1)
self.assertStatisticsHasCount(handle, "dataset2::record_latency",
float(i + 1), 2 * i + 3)
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element1())
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element2())
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle,
"dataset1::record_latency",
100.0,
201,
offset=1)
self.assertStatisticsHasCount(handle, "dataset2::record_latency",
100.0, 201)
def testMultipleTags(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency_2"))
dataset = dataset_transformation(dataset, aggregator)
iterator = dataset.make_initializable_iterator()
next_element = iterator.get_next()
summary_t = aggregator.get_summary()
with self.cached_session() as sess:
self.evaluate(iterator.initializer)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element))
self._assertSummaryHasCount(sess.run(summary_t),
"record_latency", float(i + 1))
self._assertSummaryHasCount(sess.run(summary_t),
"record_latency_2", float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
self._assertSummaryHasCount(self.evaluate(summary_t),
"record_latency", 100.0)
self._assertSummaryHasCount(sess.run(summary_t),
"record_latency_2", 100.0)
def testMultipleTags(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency")).apply(
stats_ops.latency_stats("record_latency_2"))
dataset = dataset_transformation(dataset, aggregator)
iterator = dataset_ops.make_initializable_iterator(dataset)
next_element = iterator.get_next()
summary_t = aggregator.get_summary()
with self.cached_session() as sess:
self.evaluate(iterator.initializer)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element))
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency", float(i + 1))
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency_2", float(i + 1))
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element)
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency", 100.0)
self._assertSummaryHasCount(
self.evaluate(summary_t), "record_latency_2", 100.0)
def testMultipleIteratorsSameAggregator(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator)
iterator_0 = dataset.make_initializable_iterator()
iterator_1 = dataset.make_initializable_iterator()
next_element = iterator_0.get_next() + iterator_1.get_next()
summary_t = aggregator.get_summary()
with self.cached_session() as sess:
sess.run([iterator_0.initializer, iterator_1.initializer])
for i in range(100):
self.assertEqual(i * 2, sess.run(next_element))
self._assertSummaryHasCount(
sess.run(summary_t), "record_latency", float(2 * (i + 1)))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
self._assertSummaryHasCount(sess.run(summary_t), "record_latency", 200.0)
def testReinitialize(self):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = self.datasetExperimentalStats(dataset, aggregator)
for j in range(5):
next_element = self.getNext(dataset, requires_initialization=True)
for i in range(100):
self.assertEqual(i, self.evaluate(next_element()))
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle, "record_latency",
float((j * 100) + i + 1),
(j * 100) + i + 2)
with self.assertRaises(errors.OutOfRangeError):
self.evaluate(next_element())
handle = self.getHandle(aggregator)
self.assertStatisticsHasCount(handle, "record_latency",
(j + 1) * 100.0, (j * 100) + 101)
def testMultipleIteratorsSameAggregator(self, dataset_transformation):
aggregator = stats_aggregator.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).apply(
stats_ops.latency_stats("record_latency"))
dataset = dataset_transformation(dataset, aggregator)
iterator_0 = dataset.make_initializable_iterator()
iterator_1 = dataset.make_initializable_iterator()
next_element = iterator_0.get_next() + iterator_1.get_next()
summary_t = aggregator.get_summary()
with self.cached_session() as sess:
sess.run([iterator_0.initializer, iterator_1.initializer])
for i in range(100):
self.assertEqual(i * 2, sess.run(next_element))
self._assertSummaryHasCount(sess.run(summary_t),
"record_latency",
float(2 * (i + 1)))
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
self._assertSummaryHasCount(sess.run(summary_t), "record_latency",
200.0)
def _build_dataset_latency_stats(self, num_elements, tag="record_latency"):
return dataset_ops.Dataset.range(num_elements).apply(
stats_ops.latency_stats(tag))
def _build_dataset_latency_stats(self, num_elements, tag="record_latency"):
return dataset_ops.Dataset.range(num_elements).apply(
stats_ops.latency_stats(tag))
def _build_dataset_multiple_tags(self,
num_elements,
tag1="record_latency",
tag2="record_latency_2"):
return dataset_ops.Dataset.range(num_elements).apply(
stats_ops.latency_stats(tag1)).apply(stats_ops.latency_stats(tag2))
def _build_dataset_multiple_tags(self,
num_elements,
tag1="record_latency",
tag2="record_latency_2"):
return dataset_ops.Dataset.range(num_elements).apply(
stats_ops.latency_stats(tag1)).apply(stats_ops.latency_stats(tag2))
