def session_end_pb(status, end_time_secs=None):
"""Constructs a SessionEndInfo protobuffer.
Creates a summary that contains status information for a completed
training session. Should be exported after the training session is completed.
One such summary per training session should be created. Each should have
a different run.
Args:
status: A tensorboard.hparams.Status enumeration value denoting the
status of the session.
end_time_secs: float. The time to use as the session end time. Represented
as seconds since the unix epoch. If None uses the current time.
Returns:
The summary protobuffer mentioned above.
"""
if end_time_secs is None:
end_time_secs = time.time()
session_end_info = plugin_data_pb2.SessionEndInfo(
status=status, end_time_secs=end_time_secs)
return _summary(
metadata.SESSION_END_INFO_TAG,
plugin_data_pb2.HParamsPluginData(session_end_info=session_end_info),
)
def test_session_end_pb(self):
end_time_secs = 1234.0
self.assertEqual(
summary.session_end_pb(api_pb2.STATUS_SUCCESS, end_time_secs),
tf.compat.v1.Summary(
value=[
tf.compat.v1.Summary.Value(
tag="_hparams_/session_end_info",
tensor=summary._TF_NULL_TENSOR,
metadata=tf.compat.v1.SummaryMetadata(
plugin_data=tf.compat.v1.SummaryMetadata.PluginData(
plugin_name="hparams",
content=(
plugin_data_pb2.HParamsPluginData(
version=0,
session_end_info=(
plugin_data_pb2.SessionEndInfo(
status=api_pb2.STATUS_SUCCESS,
end_time_secs=end_time_secs,
)
),
).SerializeToString()
),
)
),
)
]
),
)
def session_end_pb(status):
"""Creates a summary that contains status information for a completed
training session. Should be exported after the training session is completed.
One such summary per training session should be created. Each should have
a different run.
Arguments:
status: A tensorboard.hparams.Status enumeration value denoting the
status of the session.
Returns:
Returns the summary protobuffer mentioned above.
"""
session_end_info = plugin_data_pb2.SessionEndInfo(status=status)
return _summary(metadata.SESSION_END_INFO_TAG,
plugin_data_pb2.HParamsPluginData(
session_end_info=session_end_info))
def test_eager(self):
def mock_time():
mock_time.time += 1
return mock_time.time
mock_time.time = 1556227801.875
initial_time = mock_time.time
with mock.patch("time.time", mock_time):
self._initialize_model(writer=self.logdir)
self.model.fit(x=[(1,)], y=[(2,)], callbacks=[self.callback])
final_time = mock_time.time
files = os.listdir(self.logdir)
self.assertEqual(len(files), 1, files)
events_file = os.path.join(self.logdir, files[0])
plugin_data = []
for event in tf.compat.v1.train.summary_iterator(events_file):
if event.WhichOneof("what") != "summary":
continue
self.assertEqual(len(event.summary.value), 1, event.summary.value)
value = event.summary.value[0]
self.assertEqual(
value.metadata.plugin_data.plugin_name,
metadata.PLUGIN_NAME,
)
plugin_data.append(value.metadata.plugin_data.content)
self.assertEqual(len(plugin_data), 2, plugin_data)
(start_plugin_data, end_plugin_data) = plugin_data
start_pb = metadata.parse_session_start_info_plugin_data(start_plugin_data)
end_pb = metadata.parse_session_end_info_plugin_data(end_plugin_data)
# We're not the only callers of `time.time`; Keras calls it
# internally an unspecified number of times, so we're not guaranteed
# to know the exact values. Instead, we perform relative checks...
self.assertGreater(start_pb.start_time_secs, initial_time)
self.assertLess(start_pb.start_time_secs, end_pb.end_time_secs)
self.assertLessEqual(start_pb.start_time_secs, final_time)
# ...and then stub out the times for proto equality checks below.
start_pb.start_time_secs = 1234.5
end_pb.end_time_secs = 6789.0
expected_start_pb = plugin_data_pb2.SessionStartInfo()
text_format.Merge(
"""
start_time_secs: 1234.5
group_name: "my_trial"
hparams {
key: "optimizer"
value {
string_value: "adam"
}
}
hparams {
key: "dense_neurons"
value {
number_value: 8.0
}
}
""",
expected_start_pb,
)
self.assertEqual(start_pb, expected_start_pb)
expected_end_pb = plugin_data_pb2.SessionEndInfo()
text_format.Merge(
"""
end_time_secs: 6789.0
status: STATUS_SUCCESS
""",
expected_end_pb,
)
self.assertEqual(end_pb, expected_end_pb)
