minor doc + pep8 updates

piskvorky · Jan 11, 2017 · b2ff794 · b2ff794
1 parent 2f37b04
commit b2ff794
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Showing 3 changed files with 6 additions and 6 deletions.
diff --git 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
@@ -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
@@ -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):