revert test_wikicorpus

gensim/models/doc2vec.py

@@ -529,7 +529,7 @@ def repeat(self, word_count):
 
 class Doc2Vec(Word2Vec):
     """Class for training, using and evaluating neural networks described in http://arxiv.org/pdf/1405.4053v2.pdf"""
-    def __init__(self, documents=None,dm_mean=None,
+    def __init__(self, documents=None, dm_mean=None,
                  dm=1, dbow_words=0, dm_concat=0, dm_tag_count=1,
                  docvecs=None, docvecs_mapfile=None, comment=None, trim_rule=None, **kwargs):
         """
@@ -601,9 +601,12 @@ def __init__(self, documents=None,dm_mean=None,
         """
 
         super(Doc2Vec, self).__init__(
-            sg=(1 + dm) % 2, dm_mean=dm_mean,
+            sg=(1 + dm) % 2,
             null_word=dm_concat, **kwargs)
 
+        if dm_mean is not None:
+            self.cbow_mean = dm_mean
+
         self.dbow_words = dbow_words
         self.dm_concat = dm_concat
         self.dm_tag_count = dm_tag_count

gensim/models/word2vec.py

@@ -361,7 +361,7 @@ def __init__(
             self, sentences=None, size=100, alpha=0.025, window=5, min_count=5,
             max_vocab_size=None, sample=1e-3, seed=1, workers=3, min_alpha=0.0001,
             sg=0, hs=0, negative=5, cbow_mean=1, hashfxn=hash, iter=5, null_word=0,
-            trim_rule=None, sorted_vocab=1, batch_words=MAX_WORDS_IN_BATCH,**kwargs):
+            trim_rule=None, sorted_vocab=1, batch_words=MAX_WORDS_IN_BATCH):
         """
         Initialize the model from an iterable of `sentences`. Each sentence is a
         list of words (unicode strings) that will be used for training.
@@ -451,6 +451,7 @@ def __init__(
         self.min_alpha = float(min_alpha)
         self.hs = hs
         self.negative = negative
+        self.cbow_mean = int(cbow_mean)
         self.hashfxn = hashfxn
         self.iter = iter
         self.null_word = null_word
@@ -459,11 +460,6 @@ def __init__(
         self.sorted_vocab = sorted_vocab
         self.batch_words = batch_words
 
-        if "dm_mean" in kwargs and kwargs["dm_mean"] is not None:
-            self.cbow_mean = int(kwargs["dm_mean"])
-        else:
-            self.cbow_mean = int(cbow_mean)
-
         if sentences is not None:
             if isinstance(sentences, GeneratorType):
                 raise TypeError("You can't pass a generator as the sentences argument. Try an iterator.")

gensim/test/test_doc2vec.py

@@ -84,11 +84,10 @@ def test_int_doctags(self):
         """Test doc2vec doctag alternatives"""
         corpus = DocsLeeCorpus()
 
-        size = 300
-        model = doc2vec.Doc2Vec(min_count=1, size=size)
+        model = doc2vec.Doc2Vec(min_count=1)
         model.build_vocab(corpus)
-        self.assertEqual(len(model.docvecs.doctag_syn0), size)
-        self.assertEqual(model.docvecs[0].shape, (size,))
+        self.assertEqual(len(model.docvecs.doctag_syn0), 300)
+        self.assertEqual(model.docvecs[0].shape, (100,))
         self.assertRaises(KeyError, model.__getitem__, '_*0')
 
     def test_missing_string_doctag(self):
@@ -107,13 +106,12 @@ def test_string_doctags(self):
         # force duplicated tags
         corpus = corpus[0:10] + corpus
 
-        size = 300
-        model = doc2vec.Doc2Vec(size=size, min_count=1)
+        model = doc2vec.Doc2Vec(min_count=1)
         model.build_vocab(corpus)
 
-        self.assertEqual(len(model.docvecs.doctag_syn0), size)
-        self.assertEqual(model.docvecs[0].shape, (size,))
-        self.assertEqual(model.docvecs['_*0'].shape, (size,))
+        self.assertEqual(len(model.docvecs.doctag_syn0), 300)
+        self.assertEqual(model.docvecs[0].shape, (100,))
+        self.assertEqual(model.docvecs['_*0'].shape, (100,))
         self.assertTrue(all(model.docvecs['_*0'] == model.docvecs[0]))
         self.assertTrue(max(d.offset for d in model.docvecs.doctags.values()) < len(model.docvecs.doctags))
         self.assertTrue(max(model.docvecs._int_index(str_key) for str_key in model.docvecs.doctags.keys()) < len(model.docvecs.doctag_syn0))

gensim/test/test_wikicorpus.py

@@ -30,11 +30,10 @@ def setUp(self):
         wc = WikiCorpus(datapath(FILENAME))
 
     def test_get_texts_returns_generator_of_lists(self):
-
         logger.debug("Current Python Version is "+str(sys.version_info))
         if sys.version_info < (2, 7, 0):
             return
-
+        
         wc = WikiCorpus(datapath(FILENAME))
         l = wc.get_texts()
         self.assertEqual(type(l), types.GeneratorType)
@@ -49,7 +48,6 @@ def test_first_element(self):
         2) autism
 
         """
-
         if sys.version_info < (2, 7, 0):
             return
         wc = WikiCorpus(datapath(FILENAME))