def _deSerializeExtraData(self, extraDataDir):
assert self.__restoringFromState<EOL>assert (self._netInfo.net is None), "<STR_LIT>"<EOL>stateDir = self.__getNetworkStateDirectory(extraDataDir=extraDataDir)<EOL>self.__logger.debug(<EOL>"<STR_LIT>", self)<EOL>self._netInfo.net = Network(stateDir)<EOL>self.__logger.debug(<EOL>"<STR_LIT>", self)<EOL>self._netInfo.net.initialize()<EOL>if self.getInferenceType() == InferenceType.TemporalAnomaly:<EOL><INDENT>classifierType = self._getAnomalyClassifier().getSelf().__class__.__name__<EOL>if classifierType is '<STR_LIT>':<EOL><INDENT>anomalyClParams = dict(<EOL>trainRecords=self._classifier_helper._autoDetectWaitRecords,<EOL>cacheSize=self._classifier_helper._history_length,<EOL>)<EOL>spEnable = (self._getSPRegion() is not None)<EOL>tmEnable = True<EOL>knnRegion = self._getAnomalyClassifier().getSelf()<EOL>self._addAnomalyClassifierRegion(self._netInfo.net, anomalyClParams,<EOL>spEnable, tmEnable)<EOL>self._getAnomalyClassifier().getSelf()._iteration = self.__numRunCalls<EOL>self._getAnomalyClassifier().getSelf()._recordsCache = (<EOL>self._classifier_helper.saved_states)<EOL>self._getAnomalyClassifier().getSelf().saved_categories = (<EOL>self._classifier_helper.saved_categories)<EOL>self._getAnomalyClassifier().getSelf()._knnclassifier = knnRegion<EOL>self._getTPRegion().setParameter('<STR_LIT>', True)<EOL>del self._classifier_helper<EOL>self._netInfo.net.initialize()<EOL><DEDENT><DEDENT>self.__restoringFromState = False<EOL>self.__logger.debug("<STR_LIT>", self)<EOL>return<EOL>
[virtual method override] This method is called during deserialization
        (after __setstate__) with an external directory path that can be used to
        bypass pickle for loading large binary states.

        extraDataDir:
                      Model's extra data directory path