def testSummaryGlobalStep(self):
step = training_util.get_or_create_global_step()
logdir = tempfile.mkdtemp()
with summary_ops.create_file_writer(
logdir, max_queue=0,
name='t2').as_default(), summary_ops.always_record_summaries():
summary_ops.scalar('scalar', 2.0, step=step)
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 2)
self.assertEqual(events[1].summary.value[0].tag, 'scalar')
def testMaxQueue(self):
logs = tempfile.mkdtemp()
with summary_ops.create_file_writer(
logs, max_queue=2, flush_millis=999999,
name='lol').as_default(), summary_ops.always_record_summaries():
get_total = lambda: len(summary_test_util.events_from_logdir(logs))
# Note: First tf.Event is always file_version.
self.assertEqual(1, get_total())
summary_ops.scalar('scalar', 2.0, step=1)
self.assertEqual(1, get_total())
summary_ops.scalar('scalar', 2.0, step=2)
self.assertEqual(3, get_total())
def testSummaryGlobalStep(self):
step = training_util.get_or_create_global_step()
logdir = tempfile.mkdtemp()
with summary_ops.create_file_writer(
logdir, max_queue=0,
name='t2').as_default(), summary_ops.always_record_summaries():
summary_ops.scalar('scalar', 2.0, step=step)
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 2)
self.assertEqual(events[1].summary.value[0].tag, 'scalar')
def testMaxQueue(self):
logs = tempfile.mkdtemp()
with summary_ops.create_file_writer(
logs, max_queue=2, flush_millis=999999,
name='lol').as_default(), summary_ops.always_record_summaries():
get_total = lambda: len(summary_test_util.events_from_logdir(logs))
# Note: First tf.Event is always file_version.
self.assertEqual(1, get_total())
summary_ops.scalar('scalar', 2.0, step=1)
self.assertEqual(1, get_total())
summary_ops.scalar('scalar', 2.0, step=2)
self.assertEqual(3, get_total())
def testSummaryOps(self):
training_util.get_or_create_global_step()
logdir = tempfile.mkdtemp()
summary_ops.create_summary_file_writer(logdir, max_queue=0, name='t0')
summary_ops.always_record_summaries()
summary_ops.generic('tensor', 1, '')
summary_ops.scalar('scalar', 2.0)
summary_ops.histogram('histogram', [1.0])
summary_ops.image('image', [[[[1.0]]]])
summary_ops.audio('audio', [[1.0]], 1.0, 1)
# The working condition of the ops is tested in the C++ test so we just
# test here that we're calling them correctly.
self.assertTrue(gfile.Exists(logdir))
def testSummaryOps(self):
training_util.get_or_create_global_step()
logdir = tempfile.mkdtemp()
summary_ops.create_summary_file_writer(logdir, max_queue=0, name='t0')
summary_ops.always_record_summaries()
summary_ops.generic('tensor', 1, '')
summary_ops.scalar('scalar', 2.0)
summary_ops.histogram('histogram', [1.0])
summary_ops.image('image', [[[[1.0]]]])
summary_ops.audio('audio', [[1.0]], 1.0, 1)
# The working condition of the ops is tested in the C++ test so we just
# test here that we're calling them correctly.
self.assertTrue(gfile.Exists(logdir))
def testScalarSummary(self):
"""Test record_summaries_every_n_global_steps and all_summaries()."""
with ops.Graph().as_default(), self.test_session() as sess:
global_step = training_util.get_or_create_global_step()
global_step.initializer.run()
with ops.device('/cpu:0'):
step_increment = state_ops.assign_add(global_step, 1)
sess.run(step_increment) # Increment global step from 0 to 1
logdir = tempfile.mkdtemp()
with summary_ops.create_file_writer(logdir, max_queue=0,
name='t2').as_default():
with summary_ops.record_summaries_every_n_global_steps(2):
summary_ops.initialize()
summary_op = summary_ops.scalar('my_scalar', 2.0)
# Neither of these should produce a summary because
# global_step is 1 and "1 % 2 != 0"
sess.run(summary_ops.all_summary_ops())
sess.run(summary_op)
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 1)
# Increment global step from 1 to 2 and check that the summary
# is now written
sess.run(step_increment)
sess.run(summary_ops.all_summary_ops())
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 2)
self.assertEqual(events[1].summary.value[0].tag,
'my_scalar')
def testSummaryName(self):
training_util.get_or_create_global_step()
logdir = tempfile.mkdtemp()
summary_ops.create_summary_file_writer(logdir, max_queue=0, name='t2')
summary_ops.always_record_summaries()
summary_ops.scalar('scalar', 2.0)
self.assertTrue(gfile.Exists(logdir))
files = gfile.ListDirectory(logdir)
self.assertEqual(len(files), 1)
records = list(tf_record.tf_record_iterator(os.path.join(logdir, files[0])))
self.assertEqual(len(records), 2)
event = event_pb2.Event()
event.ParseFromString(records[1])
self.assertEqual(event.summary.value[0].tag, 'scalar')
def testSummaryName(self):
training_util.get_or_create_global_step()
logdir = tempfile.mkdtemp()
summary_ops.create_summary_file_writer(logdir, max_queue=0, name='t2')
summary_ops.always_record_summaries()
summary_ops.scalar('scalar', 2.0)
self.assertTrue(gfile.Exists(logdir))
files = gfile.ListDirectory(logdir)
self.assertEqual(len(files), 1)
records = list(tf_record.tf_record_iterator(os.path.join(logdir, files[0])))
self.assertEqual(len(records), 2)
event = event_pb2.Event()
event.ParseFromString(records[1])
self.assertEqual(event.summary.value[0].tag, 'scalar')
def testScalarSummary(self):
"""Test record_summaries_every_n_global_steps and all_summaries()."""
with ops.Graph().as_default(), self.test_session() as sess:
global_step = training_util.get_or_create_global_step()
global_step.initializer.run()
with ops.device('/cpu:0'):
step_increment = state_ops.assign_add(global_step, 1)
sess.run(step_increment) # Increment global step from 0 to 1
logdir = tempfile.mkdtemp()
with summary_ops.create_file_writer(logdir, max_queue=0,
name='t2').as_default():
with summary_ops.record_summaries_every_n_global_steps(2):
summary_ops.initialize()
summary_op = summary_ops.scalar('my_scalar', 2.0)
# Neither of these should produce a summary because
# global_step is 1 and "1 % 2 != 0"
sess.run(summary_ops.all_summary_ops())
sess.run(summary_op)
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 1)
# Increment global step from 1 to 2 and check that the summary
# is now written
sess.run(step_increment)
sess.run(summary_ops.all_summary_ops())
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 2)
self.assertEqual(events[1].summary.value[0].tag, 'my_scalar')
def write():
summary_ops.scalar('scalar', 2.0)
def body(unused_pred):
summary_ops.scalar('scalar', 2.0)
return constant_op.constant(False)
def f():
summary_ops.scalar('scalar', 2.0)
return constant_op.constant(True)
def f():
summary_ops.scalar('scalar', 2.0)
return constant_op.constant(True)
def body(unused_pred):
summary_ops.scalar('scalar', 2.0)
return constant_op.constant(False)
def result(self): t = self.numer / self.denom summary_ops.scalar(name=self.name, tensor=t) return t
def write():
summary_ops.scalar('scalar', 2.0)
def result(self):
t = self.numer / self.denom
summary_ops.scalar(name=self.name, tensor=t)
return t