def extract_word2vec_vector(self, token):
        if self.model.vocab in token:
            return self.model[token]
        #elif token == '_START_' or token == '_END_':
        elif token == '<s>' or token == '</s>':
            return self.zero_vector
        else:
            return self.default_vector

    # extract the word2vec features for a window of tokens around the target token
dataset/ETHPy150Open qe-team/marmot/marmot/features/word2vec_feature_extractor.py/Word2VecFeatureExtractor.extract_word2vec_vector/swapped operands of `in`