From b2ff794544e59b6fcd35fd3980ba9f5f86ec1950 Mon Sep 17 00:00:00 2001 From: Jayant Jain Date: Wed, 11 Jan 2017 18:49:11 +0530 Subject: [PATCH] minor doc + pep8 updates --- gensim/models/keyedvectors.py | 4 ++-- gensim/models/word2vec.py | 2 +- gensim/models/wrappers/fasttext.py | 6 +++--- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/gensim/models/keyedvectors.py b/gensim/models/keyedvectors.py index d9321f3842..73969a8591 100644 --- a/gensim/models/keyedvectors.py +++ b/gensim/models/keyedvectors.py @@ -53,7 +53,7 @@ def word_vec(self, word, use_norm=False): Example:: - >>> trained_model['office'] + >>> trained_model.word_vec('office', use_norm=True) array([ -1.40128313e-02, ...]) """ @@ -323,7 +323,7 @@ def doesnt_match(self, words): if not words: raise ValueError("cannot select a word from an empty list") - logger.debug("using words %s" % words) + logger.debug("using words %s", words) vectors = [] for word in words: try: diff --git a/gensim/models/word2vec.py b/gensim/models/word2vec.py index ec5b9faa43..3a2d239802 100644 --- a/gensim/models/word2vec.py +++ b/gensim/models/word2vec.py @@ -470,7 +470,7 @@ def __init__( self.train(sentences) def initialize_word_vectors(self): - self.wv = KeyedVectors() # wv --> word vectors + self.wv = KeyedVectors() def make_cum_table(self, power=0.75, domain=2**31 - 1): """ diff --git a/gensim/models/wrappers/fasttext.py b/gensim/models/wrappers/fasttext.py index 7983efc1e7..81bb6ccce4 100644 --- a/gensim/models/wrappers/fasttext.py +++ b/gensim/models/wrappers/fasttext.py @@ -139,7 +139,7 @@ class FastText(Word2Vec): """ def initialize_word_vectors(self): - self.wv = FastTextKeyedVectors() # wv --> word vectors + self.wv = FastTextKeyedVectors() @classmethod def train(cls, ft_path, corpus_file, output_file=None, model='cbow', size=100, alpha=0.025, window=5, min_count=5, @@ -245,7 +245,7 @@ def delete_training_files(cls, model_file): def load_binary_data(self, model_binary_file): """Loads data from the output binary file created by FastText training""" - with open(model_binary_file, 'rb') as f: + with utils.smart_open(model_binary_file, 'rb') as f: self.load_model_params(f) self.load_dict(f) self.load_vectors(f) @@ -329,7 +329,7 @@ def init_ngrams(self): @staticmethod def compute_ngrams(word, min_n, max_n): ngram_indices = [] - BOW, EOW = ('<','>') # Used by FastText to attach to all words as prefix and suffix + BOW, EOW = ('<', '>') # Used by FastText to attach to all words as prefix and suffix extended_word = BOW + word + EOW ngrams = set() for i in range(len(extended_word) - min_n + 1):