def identifyBestHyps(wgtVec, featFile):

    global tune_set_size
    global sentFVecDict
    sent_indx = 0
    feat_offset = 0
    bestHypIndxLst = []
    for sent_indx in xrange( tune_set_size ):
        cands_4_sent = len(sentFVecDict[sent_indx])

        hyp_indx = 0
        best_score = None
        best_hyp = -1
        for hypFeatVec in sentFVecDict[sent_indx]:
            i = 0
            hyp_score = 0
            for f_val in hypFeatVec:
                hyp_score += wgtVec[i] * f_val
                i += 1
            if best_score is None or best_score < hyp_score:
                best_score = hyp_score
                best_hyp = hyp_indx
            hyp_indx += 1

        bestHypIndxLst.append(best_hyp)
        feat_offset += cands_4_sent - 2

    return bestHypIndxLst
dataset/ETHPy150Open sfu-natlang/Kriya/src/Kriya-Decoder/mert-scripts/PRO.py/identifyBestHyps/operator `+` -> `-`