Errors due to Word2Vec being deprecated

[saxenapriyansh]

The vocab dictionary mapping words to slots/counts/etc has been moved to a KeyedVectors object used by the model, and held in the wv property.

So model.vocab should be replaced by model.wv.vocab.
So in In[19] it should be : print("Word2Vec vocabulary length:", len(thrones2vec.wv.vocab))

[saxenapriyansh]

Since, the syntax for word2vec training is:
train(sentences=None, corpus_file=None, total_examples=None, total_words=None, epochs=None, start_alpha=None, end_alpha=None, word_count=0, queue_factor=2, report_delay=1.0, compute_loss=False, callbacks=())

Therefore, to avoid common mistakes around the model’s ability to do multiple training passes itself, an explicit epochs argument MUST be provided. In the common and recommended case where train() is only called once, you can set epochs=self.iter.

So instead of
In [20]:thrones2vec.train(sentences)
it should be
thrones2vec.train(sentences, total_words=token_count, epochs=self.iter)

[saxenapriyansh]

In [25]:all_word_vectors_matrix = thrones2vec.syn0
Throes an error : AttributeError: 'Word2Vec' object has no attribute 'syn0'

Solution:
Use : model.wv.syn0 instead of model.syn0

The error was due to,
Two methods and several attributes in word2vec class have been deprecated. The methods are load_word2vec_format and save_word2vec_format. The attributes are syn0norm, syn0, vocab, index2word . They have been moved to KeyedVectors class.

[bgloger3489]

Since, the syntax for word2vec training is:
train(sentences=None, corpus_file=None, total_examples=None, total_words=None, epochs=None, start_alpha=None, end_alpha=None, word_count=0, queue_factor=2, report_delay=1.0, compute_loss=False, callbacks=())

Therefore, to avoid common mistakes around the model’s ability to do multiple training passes itself, an explicit epochs argument MUST be provided. In the common and recommended case where train() is only called once, you can set epochs=self.iter.

So instead of
In [20]:thrones2vec.train(sentences)
it should be
thrones2vec.train(sentences, total_words=token_count, epochs=self.iter)

It should actually be thrones2vec.train(sentences,total_words=thrones2vec.corpus_count,epochs=thrones2vec.epochs)