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)