CODEWITHSUNDEEP
similaritygensimdoc2vec
Abhishek Kaushik
Abhishek Kaushik

Reputation: 93

NameError: name 'gensim' is not defined (doc2vec similarity)

I have gensim installed in my system. I did the summarization with gensim. NOw I want to find the similarity between the sentence and it showing an error. sample code is given below. I have downloaded the Google news vectors.

from gensim.models import KeyedVectors

#two sample sentences
s1 = 'the first sentence'
s2 = 'the second text'
#model = gensim.models.KeyedVectors.load_word2vec_format('../GoogleNews-vectors-negative300.bin', binary=True)
model = gensim.models.KeyedVectors.load_word2vec_format('./data/GoogleNews-vectors-negative300.bin.gz', binary=True)
#calculate distance between two sentences using WMD algorithm
distance = model.wmdistance(s1, s2)

print ('distance = %.3f' % distance)

Error#################################################

****Traceback (most recent call last): File "/home/abhi/Desktop/CHiir/CLustering & summarization/.idea/FInal_version/sentence_embedding.py", line 7, in model = gensim.models.KeyedVectors.load_word2vec_format('./data/GoogleNews-vectors-negative300.bin.gz', binary=True) NameError: name 'gensim' is not defined****

Upvotes: 1

Views: 4239

Answers (1)

WolfgangK
WolfgangK

Reputation: 993

Importing with from x import y only lets you use y, but not x.

You can either do import gensim instead of from gensim.models import KeyedVectors, or you can directly use the imported KeyedVectors:

model = KeyedVectors.load_word2vec_format('./data/GoogleNews-vectors-negative300.bin.gz', binary=True)

Upvotes: 1

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