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Allows training if model is not modified by "_minimize_model". Adds deprecation warning. #1207

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merged 4 commits into from
Mar 12, 2017
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Allows training if model is not modified by "_minimize_model". Adds deprecation warning. #1207

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11ad64d
checks if model changed before setting model_trimmed_post_training
chinmayapancholi13 Mar 12, 2017
2a3c192
shows deprecation warning for _minimize_model
chinmayapancholi13 Mar 12, 2017
4091d3e
using warnings.warn to show deprecation message
chinmayapancholi13 Mar 12, 2017
0be6395
updated warning message and logic to check parameters
chinmayapancholi13 Mar 12, 2017
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5 changes: 4 additions & 1 deletion gensim/models/word2vec.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1251,7 +1251,10 @@ def _minimize_model(self, save_syn1 = False, save_syn1neg = False, save_syn0_loc
del self.syn1neg
if hasattr(self, 'syn0_lockf') and not save_syn0_lockf:
del self.syn0_lockf
self.model_trimmed_post_training = True
if not save_syn1 or not save_syn1neg or not save_syn0_lockf:
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Do you mean when all 3 are true? Then use if (save_syn1 and save_syn1neg and save_syn0_lockf) and just return. Please move this check to the top of the function.

self.model_trimmed_post_training = True
import warnings
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Please move imports to the file header

warnings.warn("This method would be deprecated in the future. Use KeyedVectors to retain the previously trained word vectors instead.")
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Please move to the top of the function. Better text is "This method would be deprecated in the future. Keep just_word_vectors = model.wv to retain just the KeyedVectors instance for read-only querying of word vectors."


def delete_temporary_training_data(self, replace_word_vectors_with_normalized=False):
"""
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