From 872c8edd12287f1dbe7ce213e22c7c0fd7b60255 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Radim=20=C5=98eh=C5=AF=C5=99ek?= <radimrehurek@seznam.cz>
Date: Thu, 30 Jul 2020 20:58:28 +0200
Subject: [PATCH] fix typo

---
 gensim/models/fasttext.py     | 6 +++---
 gensim/models/keyedvectors.py | 6 +++---
 gensim/test/test_word2vec.py  | 2 +-
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/gensim/models/fasttext.py b/gensim/models/fasttext.py
index 277909822d..f21854f3d3 100644
--- a/gensim/models/fasttext.py
+++ b/gensim/models/fasttext.py
@@ -1269,9 +1269,9 @@ def get_vector(self, word, norm=False):
         Parameters
         ----------
         word : str
-            Input word
+            Input word.
         norm : bool, optional
-            If True - resulting vector will be L2-normalized (unit euclidean length).
+            If True, resulting vector will be L2-normalized (unit Euclidean length).
 
         Returns
         -------
@@ -1281,7 +1281,7 @@ def get_vector(self, word, norm=False):
         Raises
         ------
         KeyError
-            If word and all ngrams not in vocabulary.
+            If word and all its ngrams not in vocabulary.
 
         """
         if word in self.key_to_index:
diff --git a/gensim/models/keyedvectors.py b/gensim/models/keyedvectors.py
index 84a7a923c4..cc6cb1197f 100644
--- a/gensim/models/keyedvectors.py
+++ b/gensim/models/keyedvectors.py
@@ -358,10 +358,10 @@ def get_vector(self, key, norm=False):
 
         Parameters
         ----------
-        key : str or int
-            Key for vector to return, or int slot
+        key : str
+            Key for vector to return.
         norm : bool, optional
-            If True - resulting vector will be L2-normalized (unit euclidean length).
+            If True, the resulting vector will be L2-normalized (unit Euclidean length).
 
         Returns
         -------
diff --git a/gensim/test/test_word2vec.py b/gensim/test/test_word2vec.py
index 20bf3555eb..f7a73ee375 100644
--- a/gensim/test/test_word2vec.py
+++ b/gensim/test/test_word2vec.py
@@ -712,7 +712,7 @@ def testTrainingSgNegative(self):
         # self.assertTrue(sims[0][0] == 'trees', sims)  # most similar
 
         # test querying for "most similar" by vector
-        graph_vector = model.wv.get_vectors('graph', norm=True)
+        graph_vector = model.wv.get_vector('graph', norm=True)
         sims2 = model.wv.most_similar(positive=[graph_vector], topn=11)
         sims2 = [(w, sim) for w, sim in sims2 if w != 'graph']  # ignore 'graph' itself
         self.assertEqual(sims, sims2)