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我收到此错误,一切都很好,我搜索了很多但没有找到任何解决方案

def _synset_similarity(s1,s2):
    L1 =dict()
    L2 =defaultdict(list)
       
    for syn1 in s1:
        L1[syn1[0]] =list()
        for syn2 in s2:                                     
            
            subsumer = syn1[1].lowest_common_hypernyms(syn2[1], simulate_root=True)[0]
            h =subsumer.max_depth() + 1 # as done on NLTK wordnet        
            syn1_dist_subsumer = syn1[1].shortest_path_distance(subsumer,simulate_root =True)
            syn2_dist_subsumer = syn2[1].shortest_path_distance(subsumer,simulate_root =True)
            l  =syn1_dist_subsumer + syn2_dist_subsumer
            f1 = np.exp(-alpha*l)
            a  = np.exp(beta*h)
            b  = np.exp(-beta*h)
            f2 = (a-b) /(a+b)
            sim = f1*f2
            L1[syn1[0]].append(sim)          
            L2[syn2[0]].append(sim)
    return L1, L2       
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-5-2321cf4ecea6> in <module>()
     66     s2 ='hurricane striked my house severly'
     67 
---> 68     print('similarity between '+'\"'+s1+'\"'+' and ' +'\"'+ s2+'\"'+ 'is: '+str(getSimilarity(s1,s2)))

1 frames
<ipython-input-5-2321cf4ecea6> in _synset_similarity(s1, s2)
     23         for syn2 in s2:
     24 
---> 25             subsumer = syn1[1].lowest_common_hypernyms(syn2[1], simulate_root=True)[0]
     26             h =subsumer.max_depth() + 1 # as done on NLTK wordnet
     27             syn1_dist_subsumer = syn1[1].shortest_path_distance(subsumer,simulate_root =True)

AttributeError: 'Synset' object has no attribute 'lowest_common_hypernyms'
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