def __createModelCheckpoint(self):
if self._model is None or self._modelCheckpointGUID is None:<EOL><INDENT>return<EOL><DEDENT>if self._predictionLogger is None:<EOL><INDENT>self._createPredictionLogger()<EOL><DEDENT>predictions = io.StringIO()<EOL>self._predictionLogger.checkpoint(<EOL>checkpointSink=predictions,<EOL>maxRows=int(Configuration.get('<STR_LIT>')))<EOL>self._model.save(os.path.join(self._experimentDir, str(self._modelCheckpointGUID)))<EOL>self._jobsDAO.modelSetFields(modelID,<EOL>{'<STR_LIT>':str(self._modelCheckpointGUID)},<EOL>ignoreUnchanged=True)<EOL>self._logger.info("<STR_LIT>"<EOL>"<STR_LIT>", self._modelID, checkpointID)<EOL>return<EOL>
Create a checkpoint from the current model, and store it in a dir named
        after checkpoint GUID, and finally store the GUID in the Models DB