Gensim 3.8.0 to Gensim 4.0.0

We Are Going To Discuss About Gensim 3.8.0 to Gensim 4.0.0. So lets Start this Python Article.

Gensim 3.8.0 to Gensim 4.0.0

  1. How to solve Gensim 3.8.0 to Gensim 4.0.0

    The changes caused by the migration from Gensim 3.x to 4 are all present in the github link:
    https://github.com/RaRe-Technologies/gensim/wiki/Migrating-from-Gensim-3.x-to-4
    For the above problem, the solution that worked for me:
    words = list(model.wv.index_to_key)

  2. Gensim 3.8.0 to Gensim 4.0.0

    The changes caused by the migration from Gensim 3.x to 4 are all present in the github link:
    https://github.com/RaRe-Technologies/gensim/wiki/Migrating-from-Gensim-3.x-to-4
    For the above problem, the solution that worked for me:
    words = list(model.wv.index_to_key)

Solution 1

The changes caused by the migration from Gensim 3.x to 4 are all present in the github link:

https://github.com/RaRe-Technologies/gensim/wiki/Migrating-from-Gensim-3.x-to-4

For the above problem, the solution that worked for me:

    words = list(model.wv.index_to_key)

Original Author Debangan Mandal Of This Content

Solution 2

The migration notes explain major changes & how to adapt your code:

https://github.com/RaRe-Technologies/gensim/wiki/Migrating-from-Gensim-3.x-to-4

Per the guidance there, to just get a list of the words, since your model variable is already an instance of KeyedVectors, you can use:

model.index_to_key

Your code doesn’t show a need for a dict, but there is a slightly-different word-to-index-position dict in model.key_to_index. However, you can just use model[key] like before to get individual vectors.

(Separately: I can’t imagine your %EMBEDDING_DIM is doing anything useful. Why would you want to perform an elementwise % modulus operation, using the integer count of dimensions, against individual dimensions that are often small floating-point numbers? It’ll often be harmless, as the EMBEDDING_DIM will usually be far larger than the individual values, but it doesn’t serve any good purpose.)

Original Author gojomo Of This Content

Solution 3

On gensim 4.0.0 you will need to use the key_to_index method from the KeyedVector of your model, that will return you a dict_keys object with all the words -keys- on the model so you can still iterate through all your vocabulary :).

Your code should be now like this:

model = KeyedVectors.load_word2vec_format(wv_path, binary= False)
words = list(model.wv.key_to_index.keys())
self.word2vec = {word:model.wv[word]%EMBEDDING_DIM for word in words}

Original Author Liliana Of This Content

Conclusion

So This is all About This Tutorial. Hope This Tutorial Helped You. Thank You.

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I am an Information Technology Engineer. I have Completed my MCA And I have 4 Year Plus Experience, I am a web developer with knowledge of multiple back-end platforms Like PHP, Node.js, Python and frontend JavaScript frameworks Like Angular, React, and Vue.

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