List boundary discards one token in the context window

[jonnybluesman]

word2vec-pytorch/word2vec/data_reader.py

Line 102 in 36b93a5

enumerate(word_ids[max(i - boundary, 0):i + boundary]) if u != v]

I think i + boundary should include a + 1 to make it inclusive, otherwise the right context takes 1 token less in the resulting skipgrams.

[francesco-mollica]

Why creating a boundary like this:
boundary = np.random.randint(1, self.window_size)

and not use simply the window_size value instead of boundary?

[jonnybluesman]

Why creating a boundary like this: boundary = np.random.randint(1, self.window_size)

and not use simply the window_size value instead of boundary?

Because with the random function you are implicitly giving "more importance" to the closest words in the neighbourhood, by creating more data with those "close" tokens.

[francesco-mollica]

You wanna say explicitly? So why not reduce the window size and fix it instead of using a boundary? This use of boundary is in other implementations?
Just to be clear, this implementation uses a random window size that is in the range (1, window_size)? Is it correct that the boundary changes with each new sentence?
thanks for the quick response!

[francesco-mollica]

Does the concept of boundary can be apply to cbow-style? I implemented it and i'm in stuck because the size of the context varies from phrase to phrase as boundary changes as well and put it all in a unique tensor create me big problems!