@classmethod
    def buildRuleFeats(cls, probs, term_count):
    
        ## All feature values must be represented as log-probs in base 'e' ##
        ## Any log-prob in base '10' must be converted to base 'e' by dividing it by math.log10(math.exp(1)) ##
        # add the TM features
        tmFeatVec = [float(x) for x in probs.split()]        # Already in base-e log-prob
        tmFeatVec.append(cls.pp_val)                         # Add phrase penalty

        return StatelessFeatures(tmFeatVec, -term_count)
Create the stateless feature object for a regular rule
dataset/ETHPy150Open sfu-natlang/Kriya/src/Kriya-Decoder/featureManager.py/FeatureManager.buildRuleFeats