def test_v1_summary_tb_summary(self):
tf_summary = summary_v1.scalar_pb("foo", 5.0)
tb_summary = summary_pb2.Summary.FromString(
tf_summary.SerializeToString())
event = event_pb2.Event(step=1, wall_time=123.456, summary=tb_summary)
run_proto = write_service_pb2.WriteScalarRequest.Run()
self._populate_run_from_events(run_proto, [event])
expected_run_proto = write_service_pb2.WriteScalarRequest.Run()
foo_tag = expected_run_proto.tags.add()
foo_tag.name = "foo/scalar_summary"
foo_tag.metadata.display_name = "foo"
foo_tag.metadata.plugin_data.plugin_name = "scalars"
foo_tag.points.add(step=1,
wall_time=test_util.timestamp_pb(123456000000),
value=5.0)
self.assertProtoEquals(run_proto, expected_run_proto)
import tensorflow as tf
from tensorboard.backend.event_processing import directory_watcher
from tensorboard.backend.event_processing import event_file_loader
from tensorboard.backend.event_processing import io_wrapper
from tensorboard.summary import v1 as summary_lib
from tensorboard.util import tensor_util
flags.DEFINE_string('benchmark_output_dir',
default=None,
help='Benchmark output directory.')
FLAGS = flags.FLAGS
_SCALAR_PLUGIN_NAME = summary_lib.scalar_pb(
'', 0).value[0].metadata.plugin_data.plugin_name
def _make_events_generator(path):
"""Makes a generator yielding TensorBoard events from files in `path`."""
return directory_watcher.DirectoryWatcher(
path, event_file_loader.EventFileLoader,
io_wrapper.IsSummaryEventsFile).Load()
def _is_scalar_value(value):
if value.HasField('metadata') and value.metadata.HasField('plugin_data'):
plugin_data = value.metadata.plugin_data
return plugin_data.plugin_name == _SCALAR_PLUGIN_NAME
return False