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