def testScalarSummaryNameScope(self):
"""Test record_summaries_every_n_global_steps and all_summaries()."""
with ops.Graph().as_default(), self.cached_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()
with ops.name_scope('scope'):
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,
'scope/my_scalar')
def testScalarSummaryNameScope(self):
"""Test record_summaries_every_n_global_steps and all_summaries()."""
with ops.Graph().as_default(), self.cached_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()
with ops.name_scope('scope'):
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, 'scope/my_scalar')
def testGraphSummary(self):
training_util.get_or_create_global_step()
name = 'hi'
graph = graph_pb2.GraphDef(node=(node_def_pb2.NodeDef(name=name), ))
with self.cached_session():
with self.create_db_writer().as_default():
summary_ops.initialize(graph=graph)
six.assertCountEqual(self, [name],
get_all(self.db, 'SELECT node_name FROM Nodes'))
def testGraphSummary(self):
training_util.get_or_create_global_step()
name = 'hi'
graph = graph_pb2.GraphDef(node=(node_def_pb2.NodeDef(name=name),))
with self.cached_session():
with self.create_db_writer().as_default():
summary_ops.initialize(graph=graph)
six.assertCountEqual(self, [name],
get_all(self.db, 'SELECT node_name FROM Nodes'))
def testSummaryGraphModeCond(self):
with ops.Graph().as_default(), self.cached_session():
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.initialize()
training_util.get_or_create_global_step().initializer.run()
def f():
summary_ops.scalar('scalar', 2.0)
return constant_op.constant(True)
pred = array_ops.placeholder(dtypes.bool)
x = control_flow_ops.cond(pred, f,
lambda: constant_op.constant(False))
x.eval(feed_dict={pred: True})
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 2)
self.assertEqual(events[1].summary.value[0].tag, 'cond/scalar')
def testSummaryGraphModeCond(self):
with ops.Graph().as_default(), self.cached_session():
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.initialize()
training_util.get_or_create_global_step().initializer.run()
def f():
summary_ops.scalar('scalar', 2.0)
return constant_op.constant(True)
pred = array_ops.placeholder(dtypes.bool)
x = control_flow_ops.cond(pred, f,
lambda: constant_op.constant(False))
x.eval(feed_dict={pred: True})
events = summary_test_util.events_from_logdir(logdir)
self.assertEqual(len(events), 2)
self.assertEqual(events[1].summary.value[0].tag, 'cond/scalar')
