def test_skips_non_scalar_events_in_scalar_time_series(self):
events = [
event_pb2.Event(file_version="brain.Event:2"),
event_pb2.Event(summary=scalar_v2.scalar_pb("scalar1", 5.0)),
event_pb2.Event(summary=scalar_v2.scalar_pb("scalar2", 5.0)),
event_pb2.Event(
summary=histogram_v2.histogram_pb("scalar2", [5.0])),
]
run_proto = write_service_pb2.WriteScalarRequest.Run()
self._populate_run_from_events(run_proto, events)
tag_counts = {tag.name: len(tag.points) for tag in run_proto.tags}
self.assertEqual(tag_counts, {"scalar1": 1, "scalar2": 1})
def test_remembers_first_metadata_in_scalar_time_series(self):
scalar_1 = event_pb2.Event(summary=scalar_v2.scalar_pb("loss", 4.0))
scalar_2 = event_pb2.Event(summary=scalar_v2.scalar_pb("loss", 3.0))
scalar_2.summary.value[0].ClearField("metadata")
events = [
event_pb2.Event(file_version="brain.Event:2"),
scalar_1,
scalar_2,
]
run_proto = write_service_pb2.WriteScalarRequest.Run()
self._populate_run_from_events(run_proto, events)
tag_counts = {tag.name: len(tag.points) for tag in run_proto.tags}
self.assertEqual(tag_counts, {"loss": 2})
def test_upload_preserves_wall_time(self):
logdir = self.get_temp_dir()
with tb_test_util.FileWriter(logdir) as writer:
# Add a raw event so we can specify the wall_time value deterministically.
writer.add_event(
event_pb2.Event(
step=1,
wall_time=123.123123123,
summary=scalar_v2.scalar_pb("foo", 5.0),
)
)
mock_client = _create_mock_client()
mock_rate_limiter = mock.create_autospec(util.RateLimiter)
uploader = uploader_lib.TensorBoardUploader(
mock_client, logdir, mock_rate_limiter
)
uploader.create_experiment()
uploader._upload_once()
mock_client.WriteScalar.assert_called_once()
request = mock_client.WriteScalar.call_args[0][0]
# Just check the wall_time value; everything else is covered in the full
# logdir test below.
self.assertEqual(
123123123123,
request.runs[0].tags[0].points[0].wall_time.ToNanoseconds(),
)
def test_break_at_scalar_point_boundary(self):
mock_client = _create_mock_client()
point_count = 2000 # comfortably saturates a single 1024-byte request
events = []
for step in range(point_count):
summary = scalar_v2.scalar_pb("loss", -2.0 * step)
if step > 0:
summary.value[0].ClearField("metadata")
events.append(event_pb2.Event(summary=summary, step=step))
run_to_events = {"train": events}
builder = _create_request_sender("123", mock_client)
builder.send_requests(run_to_events)
requests = [c[0][0] for c in mock_client.WriteScalar.call_args_list]
for request in requests:
_clear_wall_times(request)
self.assertGreater(len(requests), 1)
self.assertLess(len(requests), point_count)
total_points_in_result = 0
for request in requests:
self.assertLen(request.runs, 1)
run = request.runs[0]
self.assertEqual(run.name, "train")
self.assertLen(run.tags, 1)
tag = run.tags[0]
self.assertEqual(tag.name, "loss")
for point in tag.points:
self.assertEqual(point.step, total_points_in_result)
self.assertEqual(point.value, -2.0 * point.step)
total_points_in_result += 1
self.assertLessEqual(request.ByteSize(),
uploader_lib._MAX_REQUEST_LENGTH_BYTES)
self.assertEqual(total_points_in_result, point_count)
def test_skips_events_from_disallowed_plugins(self):
event = event_pb2.Event(step=1,
wall_time=123.456,
summary=scalar_v2.scalar_pb("foo", 5.0))
run_proto = write_service_pb2.WriteScalarRequest.Run()
self._populate_run_from_events(
run_proto, [event], allowed_plugins=frozenset("not-scalars"))
expected_run_proto = write_service_pb2.WriteScalarRequest.Run()
self.assertProtoEquals(run_proto, expected_run_proto)
def test_v2_summary(self):
event = event_pb2.Event(
step=1, wall_time=123.456, summary=scalar_v2.scalar_pb("foo", 5.0)
)
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"
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)
def scalar_event(tag, value):
return event_pb2.Event(summary=scalar_v2.scalar_pb(tag, value))
def make_event(step, wall_time, tag, value):
return event_pb2.Event(
step=step,
wall_time=wall_time,
summary=scalar_v2.scalar_pb(tag, value),
)
