def testTFSummaryImage(self):
"""Verify processing of tf.summary.image."""
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = SummaryToEventTransformer(event_sink)
with self.test_session() as sess:
ipt = array_ops.ones([10, 4, 4, 3], dtypes.uint8)
# This is an interesting example, because the old tf.image_summary op
# would throw an error here, because it would be tag reuse.
# Using the tf node name instead allows argument re-use to the image
# summary.
with ops.name_scope('1'):
summary_lib.image('images', ipt, max_outputs=1)
with ops.name_scope('2'):
summary_lib.image('images', ipt, max_outputs=2)
with ops.name_scope('3'):
summary_lib.image('images', ipt, max_outputs=3)
merged = summary_lib.merge_all()
writer.add_graph(sess.graph)
for i in xrange(10):
summ = sess.run(merged)
writer.add_summary(summ, global_step=i)
accumulator = ea.EventAccumulator(event_sink)
accumulator.Reload()
tags = [
u'1/images/image', u'2/images/image/0', u'2/images/image/1',
u'3/images/image/0', u'3/images/image/1', u'3/images/image/2'
]
self.assertTagsEqual(accumulator.Tags(), {
ea.IMAGES: tags,
ea.GRAPH: True,
ea.META_GRAPH: False,
})
def testExpiredDataDiscardedAfterRestartForFileVersionLessThan2(self):
"""Tests that events are discarded after a restart is detected.
If a step value is observed to be lower than what was previously seen,
this should force a discard of all previous items with the same tag
that are outdated.
Only file versions < 2 use this out-of-order discard logic. Later versions
discard events based on the step value of SessionLog.START.
"""
warnings = []
self.stubs.Set(tf.logging, 'warn', warnings.append)
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddEvent(
tf.Event(wall_time=0, step=0, file_version='brain.Event:1'))
gen.AddScalar('s1', wall_time=1, step=100, value=20)
gen.AddScalar('s1', wall_time=1, step=200, value=20)
gen.AddScalar('s1', wall_time=1, step=300, value=20)
acc.Reload()
## Check that number of items are what they should be
self.assertEqual([x.step for x in acc.Scalars('s1')], [100, 200, 300])
gen.AddScalar('s1', wall_time=1, step=101, value=20)
gen.AddScalar('s1', wall_time=1, step=201, value=20)
gen.AddScalar('s1', wall_time=1, step=301, value=20)
acc.Reload()
## Check that we have discarded 200 and 300 from s1
self.assertEqual([x.step for x in acc.Scalars('s1')],
[100, 101, 201, 301])
def testTFSummaryTensor(self):
"""Verify processing of tf.summary.tensor."""
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = tf.summary.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
tf.summary.tensor_summary('scalar', tf.constant(1.0))
tf.summary.tensor_summary('vector', tf.constant([1.0, 2.0, 3.0]))
tf.summary.tensor_summary('string', tf.constant(six.b('foobar')))
merged = tf.summary.merge_all()
summ = sess.run(merged)
writer.add_summary(summ, 0)
accumulator = ea.EventAccumulator(event_sink)
accumulator.Reload()
self.assertTagsEqual(accumulator.Tags(), {
ea.TENSORS: ['scalar', 'vector', 'string'],
})
scalar_proto = accumulator.Tensors('scalar')[0].tensor_proto
scalar = tf.make_ndarray(scalar_proto)
vector_proto = accumulator.Tensors('vector')[0].tensor_proto
vector = tf.make_ndarray(vector_proto)
string_proto = accumulator.Tensors('string')[0].tensor_proto
string = tf.make_ndarray(string_proto)
self.assertTrue(np.array_equal(scalar, 1.0))
self.assertTrue(np.array_equal(vector, [1.0, 2.0, 3.0]))
self.assertTrue(np.array_equal(string, six.b('foobar')))
def testSessionLogStartMessageDiscardsExpiredEvents(self):
"""Test that SessionLog.START message discards expired events.
This discard logic is preferred over the out-of-order step discard logic,
but this logic can only be used for event protos which have the SessionLog
enum, which was introduced to event.proto for file_version >= brain.Event:2.
"""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddEvent(
tf.Event(wall_time=0, step=1, file_version='brain.Event:2'))
gen.AddScalar('s1', wall_time=1, step=100, value=20)
gen.AddScalar('s1', wall_time=1, step=200, value=20)
gen.AddScalar('s1', wall_time=1, step=300, value=20)
gen.AddScalar('s1', wall_time=1, step=400, value=20)
gen.AddScalar('s2', wall_time=1, step=202, value=20)
gen.AddScalar('s2', wall_time=1, step=203, value=20)
slog = tf.SessionLog(status=tf.SessionLog.START)
gen.AddEvent(tf.Event(wall_time=2, step=201, session_log=slog))
acc.Reload()
self.assertEqual([x.step for x in acc.Scalars('s1')], [100, 200])
self.assertEqual([x.step for x in acc.Scalars('s2')], [])
def testImages(self):
"""Tests 2 images inserted/accessed in EventAccumulator."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
im1 = ea.ImageEvent(wall_time=1,
step=10,
encoded_image_string=b'big',
width=400,
height=300)
im2 = ea.ImageEvent(wall_time=2,
step=12,
encoded_image_string=b'small',
width=40,
height=30)
gen.AddImage('im1',
wall_time=1,
step=10,
encoded_image_string=b'big',
width=400,
height=300)
gen.AddImage('im2',
wall_time=2,
step=12,
encoded_image_string=b'small',
width=40,
height=30)
acc.Reload()
self.assertEqual(acc.Images('im1'), [im1])
self.assertEqual(acc.Images('im2'), [im2])
def testAudio(self):
"""Tests 2 audio events inserted/accessed in EventAccumulator."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
snd1 = ea.AudioEvent(wall_time=1,
step=10,
encoded_audio_string=b'big',
content_type='audio/wav',
sample_rate=44100,
length_frames=441000)
snd2 = ea.AudioEvent(wall_time=2,
step=12,
encoded_audio_string=b'small',
content_type='audio/wav',
sample_rate=44100,
length_frames=44100)
gen.AddAudio('snd1',
wall_time=1,
step=10,
encoded_audio_string=b'big',
content_type='audio/wav',
sample_rate=44100,
length_frames=441000)
gen.AddAudio('snd2',
wall_time=2,
step=12,
encoded_audio_string=b'small',
content_type='audio/wav',
sample_rate=44100,
length_frames=44100)
acc.Reload()
self.assertEqual(acc.Audio('snd1'), [snd1])
self.assertEqual(acc.Audio('snd2'), [snd2])
def testCompressedHistogramsWithEmptyHistogram(self):
"""Tests that empty histograms compressed properly in EventAccumulator."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen,
compression_bps=(0, 2500, 5000, 7500, 10000))
gen.AddHistogram('hst1',
wall_time=1,
step=10,
hmin=None,
hmax=None,
hnum=0,
hsum=0,
hsum_squares=0,
hbucket_limit=[1, 2, 3],
hbucket=[0, 0, 0])
acc.Reload()
# Create the expected values after compressing hst1
expected_vals1 = [
ea.CompressedHistogramValue(bp, val)
for bp, val in [(0, 0.0), (2500, 0), (5000, 0), (7500,
0), (10000, 0)]
]
expected_cmphst1 = ea.CompressedHistogramEvent(
wall_time=1, step=10, compressed_histogram_values=expected_vals1)
self.assertEqual(acc.CompressedHistograms('hst1'), [expected_cmphst1])
def testGraphFromMetaGraphBecomesAvailable(self):
"""Test accumulator by writing values and then reading them."""
directory = os.path.join(self.get_temp_dir(),
'metagraph_test_values_dir')
if gfile.IsDirectory(directory):
gfile.DeleteRecursively(directory)
gfile.MkDir(directory)
writer = writer_lib.FileWriter(directory, max_queue=100)
with ops.Graph().as_default() as graph:
_ = constant_op.constant([2.0, 1.0])
# Add a graph to the summary writer.
meta_graph_def = saver.export_meta_graph(graph_def=graph.as_graph_def(
add_shapes=True))
writer.add_meta_graph(meta_graph_def)
writer.flush()
# Verify that we can load those events properly
acc = ea.EventAccumulator(directory)
acc.Reload()
self.assertTagsEqual(acc.Tags(), {
ea.GRAPH: True,
ea.META_GRAPH: True,
})
self.assertProtoEquals(graph.as_graph_def(add_shapes=True),
acc.Graph())
self.assertProtoEquals(meta_graph_def, acc.MetaGraph())
def testGetOpsWithHealthPills(self):
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddHealthPill(13371337, 41, 'Add', 0, range(1, 13))
gen.AddHealthPill(13381338, 42, 'MatMul', 1, range(42, 54))
acc.Reload()
self.assertItemsEqual(['Add', 'MatMul'], acc.GetOpsWithHealthPills())
def testFirstEventTimestamp(self):
"""Test that FirstEventTimestamp() returns wall_time of the first event."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddEvent(
tf.Event(wall_time=10, step=20, file_version='brain.Event:2'))
gen.AddScalar('s1', wall_time=30, step=40, value=20)
self.assertEqual(acc.FirstEventTimestamp(), 10)
def get_data_from_log(log_path, tag_name='val_acc'):
#加载日志数据
ea=event_accumulator.EventAccumulator(log_path)
ea.Reload()
val_acc = ea.Scalars('val_acc')
items = []
for item in val_acc:
items.append(item.value)
return items
def testFirstEventTimestampLoadsEvent(self):
"""Test that FirstEventTimestamp() doesn't discard the loaded event."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddEvent(tf.Event(wall_time=1, step=2, file_version='brain.Event:2'))
self.assertEqual(acc.FirstEventTimestamp(), 1)
acc.Reload()
self.assertEqual(acc.file_version, 2.0)
def testScalars(self):
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
s1 = ea.ScalarEvent(wall_time=1, step=10, value=32)
s2 = ea.ScalarEvent(wall_time=2, step=12, value=64)
gen.AddScalar('s1', wall_time=1, step=10, value=32)
gen.AddScalar('s2', wall_time=2, step=12, value=64)
acc.Reload()
self.assertEqual(acc.Scalars('s1'), [s1])
self.assertEqual(acc.Scalars('s2'), [s2])
def testScalars(self):
"""Tests whether EventAccumulator contains scalars after adding them."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
s1 = ea.ScalarEvent(wall_time=1, step=10, value=32)
s2 = ea.ScalarEvent(wall_time=2, step=12, value=64)
gen.AddScalar('s1', wall_time=1, step=10, value=32)
gen.AddScalar('s2', wall_time=2, step=12, value=64)
acc.Reload()
self.assertEqual(acc.Scalars('s1'), [s1])
self.assertEqual(acc.Scalars('s2'), [s2])
def testOnlySummaryEventsTriggerDiscards(self):
"""Test that file version event does not trigger data purge."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddScalar('s1', wall_time=1, step=100, value=20)
ev1 = tf.Event(wall_time=2, step=0, file_version='brain.Event:1')
graph_bytes = tf.GraphDef().SerializeToString()
ev2 = tf.Event(wall_time=3, step=0, graph_def=graph_bytes)
gen.AddEvent(ev1)
gen.AddEvent(ev2)
acc.Reload()
self.assertEqual([x.step for x in acc.Scalars('s1')], [100])
def testGetOpsWithHealthPills(self):
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
health_pill_elements_1 = list(range(1, 13)) + [
float(1), 2.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0]
gen.AddHealthPill(13371337, 41, '/job:localhost/replica:0/task:0/cpu:0',
'Add', 0, health_pill_elements_1)
health_pill_elements_2 = list(range(42, 54)) + [
float(2), 2.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0]
gen.AddHealthPill(13381338, 42, '/job:localhost/replica:0/task:0/cpu:0',
'MatMul', 1, health_pill_elements_2)
acc.Reload()
self.assertItemsEqual(['Add', 'MatMul'], acc.GetOpsWithHealthPills())
def testReloadPopulatesFirstEventTimestamp(self):
"""Test that Reload() means FirstEventTimestamp() won't load events."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddEvent(tf.Event(wall_time=1, step=2, file_version='brain.Event:2'))
acc.Reload()
def _Die(*args, **kwargs): # pylint: disable=unused-argument
raise RuntimeError('Load() should not be called')
self.stubs.Set(gen, 'Load', _Die)
self.assertEqual(acc.FirstEventTimestamp(), 1)
def testCompressedHistograms(self):
"""Tests compressed histograms inserted into EventAccumulator."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen,
compression_bps=(0, 2500, 5000, 7500, 10000))
gen.AddHistogram('hst1',
wall_time=1,
step=10,
hmin=1,
hmax=2,
hnum=3,
hsum=4,
hsum_squares=5,
hbucket_limit=[1, 2, 3],
hbucket=[0, 3, 0])
gen.AddHistogram('hst2',
wall_time=2,
step=12,
hmin=-2,
hmax=3,
hnum=4,
hsum=5,
hsum_squares=6,
hbucket_limit=[2, 3, 4],
hbucket=[1, 3, 0])
acc.Reload()
# Create the expected values after compressing hst1
expected_vals1 = [
ea.CompressedHistogramValue(bp, val)
for bp, val in [(0, 1.0), (2500, 1.25), (5000,
1.5), (7500,
1.75), (10000,
2.0)]
]
expected_cmphst1 = ea.CompressedHistogramEvent(
wall_time=1, step=10, compressed_histogram_values=expected_vals1)
self.assertEqual(acc.CompressedHistograms('hst1'), [expected_cmphst1])
# Create the expected values after compressing hst2
expected_vals2 = [
ea.CompressedHistogramValue(bp, val)
for bp, val in [(0, -2), (2500,
2), (5000,
2 + 1 / 3), (7500,
2 + 2 / 3), (10000, 3)]
]
expected_cmphst2 = ea.CompressedHistogramEvent(
wall_time=2, step=12, compressed_histogram_values=expected_vals2)
self.assertEqual(acc.CompressedHistograms('hst2'), [expected_cmphst2])
def testHistograms(self):
"""Tests whether histograms are inserted into EventAccumulator."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
val1 = ea.HistogramValue(
min=1,
max=2,
num=3,
sum=4,
sum_squares=5,
bucket_limit=[1, 2, 3],
bucket=[0, 3, 0])
val2 = ea.HistogramValue(
min=-2,
max=3,
num=4,
sum=5,
sum_squares=6,
bucket_limit=[2, 3, 4],
bucket=[1, 3, 0])
hst1 = ea.HistogramEvent(wall_time=1, step=10, histogram_value=val1)
hst2 = ea.HistogramEvent(wall_time=2, step=12, histogram_value=val2)
gen.AddHistogram(
'hst1',
wall_time=1,
step=10,
hmin=1,
hmax=2,
hnum=3,
hsum=4,
hsum_squares=5,
hbucket_limit=[1, 2, 3],
hbucket=[0, 3, 0])
gen.AddHistogram(
'hst2',
wall_time=2,
step=12,
hmin=-2,
hmax=3,
hnum=4,
hsum=5,
hsum_squares=6,
hbucket_limit=[2, 3, 4],
hbucket=[1, 3, 0])
acc.Reload()
self.assertEqual(acc.Histograms('hst1'), [hst1])
self.assertEqual(acc.Histograms('hst2'), [hst2])
def testHealthPills(self):
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddHealthPill(13371337, 41, 'Add', 0, range(1, 13))
gen.AddHealthPill(13381338, 42, 'Add', 1, range(42, 54))
acc = ea.EventAccumulator(gen)
acc.Reload()
# Retrieve the health pills for each node name.
gotten_events = acc.HealthPills('Add')
self.assertEquals(2, len(gotten_events))
self._compareHealthPills(
ea.HealthPillEvent(wall_time=13371337,
step=41,
node_name='Add',
output_slot=0,
value=range(1, 13)), gotten_events[0])
self._compareHealthPills(
ea.HealthPillEvent(wall_time=13381338,
step=42,
node_name='Add',
output_slot=1,
value=range(42, 54)), gotten_events[1])
def load_event_scalars(path, *scalar_names):
"""
Loads scalar values from eventfiles.
Keyword arguments:
path -- path to the event file
*event_names -- scalar names
"""
accumulator = event_accumulator.EventAccumulator(path)
accumulator.Reload()
scalar_values = []
for scalar_name in scalar_names:
scalar_values.append(accumulator.Scalars(scalar_name))
return scalar_values
def testNonValueEvents(self):
"""Non-value events in the generator don't cause early exits."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddScalar('s1', wall_time=1, step=10, value=20)
gen.AddEvent(tf.Event(wall_time=2, step=20, file_version='nots2'))
gen.AddScalar('s3', wall_time=3, step=100, value=1)
gen.AddHistogram('hst1')
gen.AddImage('im1')
gen.AddAudio('snd1')
acc.Reload()
self.assertTagsEqual(acc.Tags(), {
ea.IMAGES: ['im1'],
ea.AUDIO: ['snd1'],
ea.SCALARS: ['s1', 's3'],
ea.HISTOGRAMS: ['hst1'],
ea.COMPRESSED_HISTOGRAMS: ['hst1'],
})
def testTags(self):
gen = _EventGenerator(self)
gen.AddScalar('s1')
gen.AddScalar('s2')
gen.AddHistogram('hst1')
gen.AddHistogram('hst2')
gen.AddImage('im1')
gen.AddImage('im2')
gen.AddAudio('snd1')
gen.AddAudio('snd2')
acc = ea.EventAccumulator(gen)
acc.Reload()
self.assertTagsEqual(
acc.Tags(), {
ea.IMAGES: ['im1', 'im2'],
ea.AUDIO: ['snd1', 'snd2'],
ea.SCALARS: ['s1', 's2'],
ea.HISTOGRAMS: ['hst1', 'hst2'],
ea.COMPRESSED_HISTOGRAMS: ['hst1', 'hst2'],
})
def AddRun(self, path, name=None):
"""Add a run to the multiplexer.
If the name is not specified, it is the same as the path.
If a run by that name exists, and we are already watching the right path,
do nothing. If we are watching a different path, replace the event
accumulator.
If `Reload` has been called, it will `Reload` the newly created
accumulators.
Args:
path: Path to the event files (or event directory) for given run.
name: Name of the run to add. If not provided, is set to path.
Returns:
The `EventMultiplexer`.
"""
if name is None or name is '':
name = path
accumulator = None
with self._accumulators_mutex:
if name not in self._accumulators or self._paths[name] != path:
if name in self._paths and self._paths[name] != path:
# TODO(danmane) - Make it impossible to overwrite an old path with
# a new path (just give the new path a distinct name)
logging.warning(
'Conflict for name %s: old path %s, new path %s', name,
self._paths[name], path)
logging.info('Constructing EventAccumulator for %s', path)
accumulator = event_accumulator.EventAccumulator(
path,
size_guidance=self._size_guidance,
purge_orphaned_data=self.purge_orphaned_data)
self._accumulators[name] = accumulator
self._paths[name] = path
if accumulator:
if self._reload_called:
accumulator.Reload()
return self
def testHealthPills(self):
"""HealthPills should be properly inserted into EventAccumulator."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
health_pill_elements_1 = list(range(1, 13)) + [
float(types_pb2.DT_FLOAT), 2.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0
]
gen.AddHealthPill(13371337, 41,
'/job:localhost/replica:0/task:0/cpu:0', 'Add', 0,
health_pill_elements_1)
health_pill_elements_2 = list(range(42, 54)) + [
float(types_pb2.DT_DOUBLE), 2.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0
]
gen.AddHealthPill(13381338, 42,
'/job:localhost/replica:0/task:0/gpu:0', 'Add', 1,
health_pill_elements_2)
acc.Reload()
# Retrieve the health pills for each node name.
gotten_events = acc.HealthPills('Add')
self.assertEquals(2, len(gotten_events))
self._compareHealthPills(
ea.HealthPillEvent(
wall_time=13371337,
step=41,
device_name='/job:localhost/replica:0/task:0/cpu:0',
node_name='Add',
output_slot=0,
dtype='tf.float32',
shape=[1, 2],
value=health_pill_elements_1), gotten_events[0])
self._compareHealthPills(
ea.HealthPillEvent(
wall_time=13381338,
device_name='/job:localhost/replica:0/task:0/gpu:0',
step=42,
node_name='Add',
output_slot=1,
dtype='tf.float64',
shape=[3, 4],
value=health_pill_elements_2), gotten_events[1])
def testOrphanedDataNotDiscardedIfFlagUnset(self):
"""Tests that events are not discarded if purge_orphaned_data is false.
"""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen, purge_orphaned_data=False)
gen.AddEvent(tf.Event(wall_time=0, step=0, file_version='brain.Event:1'))
gen.AddScalar('s1', wall_time=1, step=100, value=20)
gen.AddScalar('s1', wall_time=1, step=200, value=20)
gen.AddScalar('s1', wall_time=1, step=300, value=20)
acc.Reload()
## Check that number of items are what they should be
self.assertEqual([x.step for x in acc.Scalars('s1')], [100, 200, 300])
gen.AddScalar('s1', wall_time=1, step=101, value=20)
gen.AddScalar('s1', wall_time=1, step=201, value=20)
gen.AddScalar('s1', wall_time=1, step=301, value=20)
acc.Reload()
## Check that we have discarded 200 and 300 from s1
self.assertEqual([x.step for x in acc.Scalars('s1')],
[100, 200, 300, 101, 201, 301])
def testKeyError(self):
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
acc.Reload()
with self.assertRaises(KeyError):
acc.Scalars('s1')
with self.assertRaises(KeyError):
acc.Scalars('hst1')
with self.assertRaises(KeyError):
acc.Scalars('im1')
with self.assertRaises(KeyError):
acc.Histograms('s1')
with self.assertRaises(KeyError):
acc.Histograms('im1')
with self.assertRaises(KeyError):
acc.Images('s1')
with self.assertRaises(KeyError):
acc.Images('hst1')
with self.assertRaises(KeyError):
acc.Audio('s1')
with self.assertRaises(KeyError):
acc.Audio('hst1')
def testKeyError(self):
"""KeyError should be raised when accessing non-existing keys."""
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
acc.Reload()
with self.assertRaises(KeyError):
acc.Scalars('s1')
with self.assertRaises(KeyError):
acc.Scalars('hst1')
with self.assertRaises(KeyError):
acc.Scalars('im1')
with self.assertRaises(KeyError):
acc.Histograms('s1')
with self.assertRaises(KeyError):
acc.Histograms('im1')
with self.assertRaises(KeyError):
acc.Images('s1')
with self.assertRaises(KeyError):
acc.Images('hst1')
with self.assertRaises(KeyError):
acc.Audio('s1')
with self.assertRaises(KeyError):
acc.Audio('hst1')
def testTFSummaryScalar(self):
"""Verify processing of tf.summary.scalar."""
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = tf.summary.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
ipt = tf.placeholder(tf.float32)
tf.summary.scalar('scalar1', ipt)
tf.summary.scalar('scalar2', ipt * ipt)
merged = tf.summary.merge_all()
writer.add_graph(sess.graph)
for i in xrange(10):
summ = sess.run(merged, feed_dict={ipt: i})
writer.add_summary(summ, global_step=i)
accumulator = ea.EventAccumulator(event_sink)
accumulator.Reload()
seq1 = [
ea.ScalarEvent(wall_time=0, step=i, value=i) for i in xrange(10)
]
seq2 = [
ea.ScalarEvent(wall_time=0, step=i, value=i * i)
for i in xrange(10)
]
self.assertTagsEqual(
accumulator.Tags(), {
ea.SCALARS: ['scalar1', 'scalar2'],
ea.GRAPH: True,
ea.META_GRAPH: False,
})
self.assertEqual(accumulator.Scalars('scalar1'), seq1)
self.assertEqual(accumulator.Scalars('scalar2'), seq2)
first_value = accumulator.Scalars('scalar1')[0].value
self.assertTrue(isinstance(first_value, float))
def testEventsDiscardedPerTagAfterRestartForFileVersionLessThan2(self):
"""Tests that event discards after restart, only affect the misordered tag.
If a step value is observed to be lower than what was previously seen,
this should force a discard of all previous items that are outdated, but
only for the out of order tag. Other tags should remain unaffected.
Only file versions < 2 use this out-of-order discard logic. Later versions
discard events based on the step value of SessionLog.START.
"""
warnings = []
self.stubs.Set(tf.logging, 'warn', warnings.append)
gen = _EventGenerator(self)
acc = ea.EventAccumulator(gen)
gen.AddEvent(
tf.Event(wall_time=0, step=0, file_version='brain.Event:1'))
gen.AddScalar('s1', wall_time=1, step=100, value=20)
gen.AddScalar('s1', wall_time=1, step=200, value=20)
gen.AddScalar('s1', wall_time=1, step=300, value=20)
gen.AddScalar('s1', wall_time=1, step=101, value=20)
gen.AddScalar('s1', wall_time=1, step=201, value=20)
gen.AddScalar('s1', wall_time=1, step=301, value=20)
gen.AddScalar('s2', wall_time=1, step=101, value=20)
gen.AddScalar('s2', wall_time=1, step=201, value=20)
gen.AddScalar('s2', wall_time=1, step=301, value=20)
acc.Reload()
## Check that we have discarded 200 and 300
self.assertEqual([x.step for x in acc.Scalars('s1')],
[100, 101, 201, 301])
## Check that s1 discards do not affect s2
## i.e. check that only events from the out of order tag are discarded
self.assertEqual([x.step for x in acc.Scalars('s2')], [101, 201, 301])
