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Make plugin_event_accumulator_test TF 2.x–compatible #2558

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wchargin merged 3 commits into from
Aug 16, 2019
Merged

Make plugin_event_accumulator_test TF 2.x–compatible #2558

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44bbf04
Make audio-related functionality and tests TF 2.x–compatible
wchargin Aug 16, 2019
b2da803
Make `plugin_event_accumulator_test` TF 2.x–compatible
wchargin Aug 16, 2019
2bbc0ff
[update diffbase]
wchargin Aug 16, 2019
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139 changes: 71 additions & 68 deletions tensorboard/backend/event_processing/plugin_event_accumulator_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -121,7 +121,6 @@ def assertTagsEqual(self, actual, expected):
self.assertEqual(actual[key], expected_value)


@test_util.run_v1_only('Uses v1 SummaryWriter and v1 audio summary')
class MockingEventAccumulatorTest(EventAccumulatorTest):

def setUp(self):
Expand Down Expand Up @@ -358,15 +357,16 @@ def testNewStyleScalarSummary(self):
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = test_util.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
step = tf.compat.v1.placeholder(tf.float32, shape=[])
scalar_summary.op('accuracy', 1.0 - 1.0 / (step + tf.constant(1.0)))
scalar_summary.op('xent', 1.0 / (step + tf.constant(1.0)))
merged = tf.compat.v1.summary.merge_all()
writer.add_graph(sess.graph)
for i in xrange(10):
summ = sess.run(merged, feed_dict={step: float(i)})
writer.add_summary(summ, global_step=i)
with tf.compat.v1.Graph().as_default():
with self.test_session() as sess:
step = tf.compat.v1.placeholder(tf.float32, shape=[])
scalar_summary.op('accuracy', 1.0 - 1.0 / (step + tf.constant(1.0)))
scalar_summary.op('xent', 1.0 / (step + tf.constant(1.0)))
merged = tf.compat.v1.summary.merge_all()
writer.add_graph(sess.graph)
for i in xrange(10):
summ = sess.run(merged, feed_dict={step: float(i)})
writer.add_summary(summ, global_step=i)

accumulator = ea.EventAccumulator(event_sink)
accumulator.Reload()
Expand All @@ -387,19 +387,20 @@ def testNewStyleAudioSummary(self):
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = test_util.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
ipt = tf.random.normal(shape=[5, 441, 2])
with tf.name_scope('1'):
audio_summary.op('one', ipt, sample_rate=44100, max_outputs=1)
with tf.name_scope('2'):
audio_summary.op('two', ipt, sample_rate=44100, max_outputs=2)
with tf.name_scope('3'):
audio_summary.op('three', ipt, sample_rate=44100, max_outputs=3)
merged = tf.compat.v1.summary.merge_all()
writer.add_graph(sess.graph)
for i in xrange(10):
summ = sess.run(merged)
writer.add_summary(summ, global_step=i)
with tf.compat.v1.Graph().as_default():
with self.test_session() as sess:
ipt = tf.random.normal(shape=[5, 441, 2])
with tf.name_scope('1'):
audio_summary.op('one', ipt, sample_rate=44100, max_outputs=1)
with tf.name_scope('2'):
audio_summary.op('two', ipt, sample_rate=44100, max_outputs=2)
with tf.name_scope('3'):
audio_summary.op('three', ipt, sample_rate=44100, max_outputs=3)
merged = tf.compat.v1.summary.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()
Expand All @@ -421,23 +422,24 @@ def testNewStyleImageSummary(self):
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = test_util.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
ipt = tf.ones([10, 4, 4, 3], tf.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 tf.name_scope('1'):
image_summary.op('images', ipt, max_outputs=1)
with tf.name_scope('2'):
image_summary.op('images', ipt, max_outputs=2)
with tf.name_scope('3'):
image_summary.op('images', ipt, max_outputs=3)
merged = tf.compat.v1.summary.merge_all()
writer.add_graph(sess.graph)
for i in xrange(10):
summ = sess.run(merged)
writer.add_summary(summ, global_step=i)
with tf.compat.v1.Graph().as_default():
with self.test_session() as sess:
ipt = tf.ones([10, 4, 4, 3], tf.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 tf.name_scope('1'):
image_summary.op('images', ipt, max_outputs=1)
with tf.name_scope('2'):
image_summary.op('images', ipt, max_outputs=2)
with tf.name_scope('3'):
image_summary.op('images', ipt, max_outputs=3)
merged = tf.compat.v1.summary.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()
Expand All @@ -459,13 +461,15 @@ def testTFSummaryTensor(self):
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = test_util.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
tf.compat.v1.summary.tensor_summary('scalar', tf.constant(1.0))
tf.compat.v1.summary.tensor_summary('vector', tf.constant([1.0, 2.0, 3.0]))
tf.compat.v1.summary.tensor_summary('string', tf.constant(six.b('foobar')))
merged = tf.compat.v1.summary.merge_all()
summ = sess.run(merged)
writer.add_summary(summ, 0)
with tf.compat.v1.Graph().as_default():
with self.test_session() as sess:
tensor_summary = tf.compat.v1.summary.tensor_summary
tensor_summary('scalar', tf.constant(1.0))
tensor_summary('vector', tf.constant([1.0, 2.0, 3.0]))
tensor_summary('string', tf.constant(six.b('foobar')))
merged = tf.compat.v1.summary.merge_all()
summ = sess.run(merged)
writer.add_summary(summ, 0)

accumulator = ea.EventAccumulator(event_sink)
accumulator.Reload()
Expand Down Expand Up @@ -493,15 +497,16 @@ def _testTFSummaryTensor_SizeGuidance(self,
event_sink = _EventGenerator(self, zero_out_timestamps=True)
writer = test_util.FileWriter(self.get_temp_dir())
writer.event_writer = event_sink
with self.test_session() as sess:
summary_metadata = summary_pb2.SummaryMetadata(
plugin_data=summary_pb2.SummaryMetadata.PluginData(
plugin_name=plugin_name, content=b'{}'))
tf.compat.v1.summary.tensor_summary('scalar', tf.constant(1.0),
summary_metadata=summary_metadata)
merged = tf.compat.v1.summary.merge_all()
for step in xrange(steps):
writer.add_summary(sess.run(merged), global_step=step)
with tf.compat.v1.Graph().as_default():
with self.test_session() as sess:
summary_metadata = summary_pb2.SummaryMetadata(
plugin_data=summary_pb2.SummaryMetadata.PluginData(
plugin_name=plugin_name, content=b'{}'))
tf.compat.v1.summary.tensor_summary('scalar', tf.constant(1.0),
summary_metadata=summary_metadata)
merged = tf.compat.v1.summary.merge_all()
for step in xrange(steps):
writer.add_summary(sess.run(merged), global_step=step)


accumulator = ea.EventAccumulator(
Expand Down Expand Up @@ -548,7 +553,6 @@ def testTFSummaryTensor_SizeGuidance_IgnoreIrrelevantGuidances(self):
expected_count=size_small)


@test_util.run_v1_only('Uses contrib and v1 SummaryWriter')
class RealisticEventAccumulatorTest(EventAccumulatorTest):

def testTensorsRealistically(self):
Expand All @@ -568,11 +572,11 @@ def FakeScalarSummary(tag, value):

with tf.Graph().as_default() as graph:
_ = tf.constant([2.0, 1.0])
# Add a graph to the summary writer.
writer.add_graph(graph)
meta_graph_def = tf.compat.v1.train.export_meta_graph(graph_def=graph.as_graph_def(
add_shapes=True))
writer.add_meta_graph(meta_graph_def)
# Add a graph to the summary writer.
writer.add_graph(graph)
graph_def = graph.as_graph_def(add_shapes=True)
meta_graph_def = tf.compat.v1.train.export_meta_graph(graph_def=graph_def)
writer.add_meta_graph(meta_graph_def)

run_metadata = config_pb2.RunMetadata()
device_stats = run_metadata.step_stats.dev_stats.add()
Expand Down Expand Up @@ -646,12 +650,11 @@ def testGraphFromMetaGraphBecomesAvailable(self):

with tf.Graph().as_default() as graph:
_ = tf.constant([2.0, 1.0])
# Add a graph to the summary writer.
meta_graph_def = tf.compat.v1.train.export_meta_graph(graph_def=graph.as_graph_def(
add_shapes=True))
writer.add_meta_graph(meta_graph_def)

writer.flush()
# Add a graph to the summary writer.
graph_def = graph.as_graph_def(add_shapes=True)
meta_graph_def = tf.compat.v1.train.export_meta_graph(graph_def=graph_def)
writer.add_meta_graph(meta_graph_def)
writer.flush()

# Verify that we can load those events properly
acc = ea.EventAccumulator(directory)
Expand Down