def testBytesProduced(self):
stats_aggregator = stats_ops.StatsAggregator()
dataset = dataset_ops.Dataset.range(100).map(
lambda x: array_ops.tile([x], ops.convert_to_tensor([x]))).apply(
stats_ops.bytes_produced_stats("bytes_produced")).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.test_session() as sess:
sess.run(iterator.initializer)
expected_sum = 0.0
for i in range(100):
self.assertAllEqual(
np.array([i] * i, dtype=np.int64), sess.run(next_element))
summary_str = sess.run(summary_t)
self._assertSummaryHasCount(summary_str, "bytes_produced", float(i + 1))
expected_sum += i * 8.0
self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum)
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
summary_str = sess.run(summary_t)
self._assertSummaryHasCount(summary_str, "bytes_produced", 100.0)
self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum)
def testBytesProduced(self):
dataset = dataset_ops.Dataset.range(100).map(
lambda x: array_ops.tile([x], ops.convert_to_tensor([x]))).apply(
stats_ops.bytes_produced_stats("bytes_produced"))
iterator = dataset.make_initializable_iterator()
stats_aggregator = stats_ops.StatsAggregator()
stats_aggregator_subscriber = stats_aggregator.subscribe(iterator)
next_element = iterator.get_next()
summary_t = stats_aggregator.get_summary()
with self.test_session() as sess:
sess.run([iterator.initializer, stats_aggregator_subscriber])
expected_sum = 0.0
for i in range(100):
self.assertAllEqual(
np.array([i] * i, dtype=np.int64), sess.run(next_element))
summary_str = sess.run(summary_t)
self._assertSummaryHasCount(summary_str, "bytes_produced", float(i + 1))
expected_sum += i * 8.0
self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum)
with self.assertRaises(errors.OutOfRangeError):
sess.run(next_element)
summary_str = sess.run(summary_t)
self._assertSummaryHasCount(summary_str, "bytes_produced", 100.0)
self._assertSummaryHasSum(summary_str, "bytes_produced", expected_sum)
def test_bytes_produced_stats_invalid_tag_shape(self):
with self.assertRaisesRegexp(ValueError,
'Shape must be rank 0 but is rank 1'):
self.run_core_tests(
lambda: dataset_ops.Dataset.range(100).apply(
stats_ops.bytes_produced_stats(["bytes_produced"])), None,
100)
def test_bytes_produced_stats_invalid_tag_shape(self):
with self.assertRaisesRegexp(
ValueError, 'Shape must be rank 0 but is rank 1'):
self.run_core_tests(
lambda: dataset_ops.Dataset.range(100).apply(
stats_ops.bytes_produced_stats(["bytes_produced"])),
None, 100)
def _build_dataset_bytes_stats(self, num_elements):
return dataset_ops.Dataset.range(num_elements).map(
lambda x: array_ops.tile([x], ops.convert_to_tensor([x]))).apply(
stats_ops.bytes_produced_stats("bytes_produced"))
def _build_dataset_bytes_stats(self, num_elements):
return dataset_ops.Dataset.range(num_elements).map(
lambda x: array_ops.tile([x], ops.convert_to_tensor([x]))).apply(
stats_ops.bytes_produced_stats("bytes_produced"))
