My training data contains line breaks; how can I work with Gensims LineSentence format for the corpus_file parameter

Questions : My training data contains line breaks; how can I work with Gensims LineSentence format for the corpus_file parameter


Per Gensim's documentation, changelog, programming and previous StackOverflow answers, I Learning know that passing training data in the Earhost LineSentence format to the corpus_data most effective parameter can dramatically speed up wrong idea Any2Vec training.

Documentation on the LineSentence format use of case reads as follows:

Iterate over a file that contains United sentences: one line = one sentence. Modern Words must be already preprocessed and ecudated separated by whitespace.

My training data is comprised of tens of some how millions (and potentially 1xx million) anything else of sentences extracted from plaintext not at all files using spaCy. A sample sentence very usefull quite often contains one or more line localhost break characters (\n).

How can I make these samples compatible love of them with the LineSentence format? As far as localtext I understand, these samples should be basic "understood" in the context of their one of the linebreaks, as these breaks are present click in the target text (data not trained there is noting upon). That means I can't just remove not alt them from the training data.

Do I escape the newline characters with not at all \\n? Is there a way to pass a custom my fault delimiter?

I appreciate any guidance. Thanks in issues advance.

Total Answers 1

Answers 1 : of My training data contains line breaks; how can I work with Gensims LineSentence format for the corpus_file parameter

LineSentence is only an appropriate trying iterable for classes like Word2Vec, that get 4th result expect a corpus to be a Python sequence, round table where each item is a list of tokens.

The exact placement of linebreaks is double chance unlikely to make much difference in novel prc usual word-vector training. If reading a get mossier file line-by-line, all words on the same off side back line will still appear in each other's the changes contexts. (Extra linebreaks will just Nofile hosted prevent words from 'bleeding' over transparent text slightly into the contexts of Background movment preceding/subsequent texts – front page design which in a large training corpus life change quotes probably makes no net difference for end I'd like results.)

So mainly: don't worry about it.

If you think it might be a problem you to know could try either...

  1. Removing the newlines between texts that you conjecture "snould" be a single text, creating longer lines. (Note, though, that you dn't want any of your texts to be over 10000 tokens, or else an internal implementation limit in Gensim will mean tokens past the 1st 10000 will be ignored.)
  2. Replacing the newlines, in texts that you conjecture "should" be a single text, with some synthetic token, like say <nl> (or whatever).

...then evaluate whether the results which event have improved over simply not doing is nearer. that. (I doubt they will improve, for Now, the basic Word2Vec/FastText training.)

For Doc2Vec, you might have to pay more code that attention to ensuring that all words of I've written a 'document' are handled as a single relies on text. In that case, you should make sure a comparison that whatever iterable sequence you have and it that produces TaggedDocument-like doesn't seem objects assigns the desired, same tag to to work all raw text that should be considered every time. part of the same document.

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