def _save_timeseries_prediction(
config,
model,
prediction,
source,
datasink=None,
):
if datasink is None:
datasink = model.default_datasink
if datasink is None or datasink == source.name:
sink = source
else:
try:
sink_settings = config.get_datasource(datasink)
sink = loudml.datasource.load_datasource(sink_settings)
except errors.LoudMLException as exn:
logging.error("cannot load data sink: %s", str(exn))
return
sink.save_timeseries_prediction(prediction, model)
def get_datasource(config, src_name):
"""
Get and load data source by name
"""
settings = config.get_datasource(src_name)
return loudml.datasource.load_datasource(settings)