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Fix memory consumption in AuthorTopicModel #2122

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merged 3 commits into from
Jul 13, 2018
Merged

Fix memory consumption in AuthorTopicModel #2122

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656d9b4
Fix quadratic iteration
philipphager Jul 7, 2018
0d0c69e
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philipphager Jul 7, 2018
9ba25e7
Move from list to set
philipphager Jul 8, 2018
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6 changes: 3 additions & 3 deletions gensim/models/atmodel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -767,9 +767,9 @@ def update(self, corpus=None, author2doc=None, doc2author=None, chunksize=None,

# Train on all documents of authors in input_corpus.
train_corpus_idx = []
for _ in author2doc.keys(): # For all authors in input corpus.
for doc_ids in self.author2doc.values(): # For all documents in total corpus.
train_corpus_idx.extend(doc_ids)
# Collect all documents of authors.
for doc_ids in self.author2doc.values():
train_corpus_idx.extend(doc_ids)
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Why keep train_corpus_idx as list in the first place? It looks like it's converted to a set right below, so maybe better to make it a set from the start?

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That is true, indeed. I would propose something like this:

# Train on all documents of authors in input_corpus.
train_corpus_idx = set()
# Collect all documents of authors.
for doc_ids in self.author2doc.values():
    train_corpus_idx.update(doc_ids)

train_corpus_idx = list(train_corpus_idx)

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I'm not familiar with the algo, but for the sake of reproducibility, I'd replace list(train_corpus_idx) with sorted(train_corpus_idx). That will remove randomness from the ordering of values, while still producing a list.


# Make the list of training documents unique.
train_corpus_idx = list(set(train_corpus_idx))
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