Why computing similarity with gensim needs the size of the dictionary?
Note that you don't need to use gensim.similarities.docsim.Similarity to calculate word-to-word similarities.
There are individual methods on the word-vector supporting objects for doing things like calculating similarity between 2 words (model.similarity(wordA, wordB)) or getting the list of most-similar 'neighbor' words (model.most_similar(target_word)).
In order to use the gensim.similarities.docsim.Similarity class to compute similarities between words, one need to provide the corpus and the size of the dictionary.
In my case, the corpus are the word vectors computed using a word2vec model.
I wonder why gensim needs the size of the dictionary? And also, if it needs here the size of the dictionary used to create the word2vec model, or the size of the dictionary of the corpus, for which I want to compute the similarities.