Point WordEmbeddingSimilarityIndex documentation to gensim.similarities

piskvorky · Nov 21, 2020 · d4aa31c · d4aa31c
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Showing 4 changed files with 8 additions and 7 deletions.
diff --git a/docs/notebooks/soft_cosine_benchmark.ipynb b/docs/notebooks/soft_cosine_benchmark.ipynb
@@ -58,7 +58,7 @@
     "from gensim.similarities import SparseTermSimilarityMatrix\n",
     "from gensim.similarities import UniformTermSimilarityIndex\n",
     "from gensim.similarities import LevenshteinSimilarityIndex\n",
-    "from gensim.models import WordEmbeddingSimilarityIndex\n",
+    "from gensim.similarities import WordEmbeddingSimilarityIndex\n",
     "from gensim.utils import simple_preprocess\n",
     "\n",
     "RANDOM_SEED = 12345\n",

diff --git a/docs/notebooks/soft_cosine_tutorial.ipynb b/docs/notebooks/soft_cosine_tutorial.ipynb
@@ -143,8 +143,8 @@
     "%%time\n",
     "import gensim.downloader as api\n",
     "\n",
-    "from gensim.models import WordEmbeddingSimilarityIndex\n",
     "from gensim.similarities import SparseTermSimilarityMatrix\n",
+    "from gensim.similarities import WordEmbeddingSimilarityIndex\n",
     "\n",
     "w2v_model = api.load(\"glove-wiki-gigaword-50\")\n",
     "similarity_index = WordEmbeddingSimilarityIndex(w2v_model)\n",
@@ -296,7 +296,7 @@
     "from gensim.corpora import Dictionary\n",
     "from gensim.models import TfidfModel\n",
     "from gensim.models import Word2Vec\n",
-    "from gensim.models import WordEmbeddingSimilarityIndex\n",
+    "from gensim.similarities import WordEmbeddingSimilarityIndex\n",
     "from gensim.similarities import SparseTermSimilarityMatrix\n",
     "\n",
     "dictionary = Dictionary(corpus)\n",

diff --git a/gensim/similarities/docsim.py b/gensim/similarities/docsim.py
@@ -887,8 +887,9 @@ class SoftCosineSimilarity(interfaces.SimilarityABC):
 
         >>> from gensim.test.utils import common_texts
         >>> from gensim.corpora import Dictionary
-        >>> from gensim.models import Word2Vec, WordEmbeddingSimilarityIndex
+        >>> from gensim.models import Word2Vec
         >>> from gensim.similarities import SoftCosineSimilarity, SparseTermSimilarityMatrix
+        >>> from gensim.similarities import WordEmbeddingSimilarityIndex
         >>>
         >>> model = Word2Vec(common_texts, vector_size=20, min_count=1)  # train word-vectors
         >>> termsim_index = WordEmbeddingSimilarityIndex(model.wv)
@@ -925,7 +926,7 @@ def __init__(self, corpus, similarity_matrix, num_best=None, chunksize=256):
             A sparse term similarity matrix build using a term similarity index.
         :class:`gensim.similarities.LevenshteinSimilarityIndex`
             A term similarity index that computes Levenshtein similarities between terms.
-        :class:`gensim.models.WordEmbeddingSimilarityIndex`
+        :class:`gensim.similarities.WordEmbeddingSimilarityIndex`
             A term similarity index that computes cosine similarities between word embeddings.
 
         """

diff --git a/gensim/similarities/termsim.py b/gensim/similarities/termsim.py
@@ -405,8 +405,8 @@ class SparseTermSimilarityMatrix(SaveLoad):
     --------
     >>> from gensim.test.utils import common_texts
     >>> from gensim.corpora import Dictionary
-    >>> from gensim.models import Word2Vec, WordEmbeddingSimilarityIndex
-    >>> from gensim.similarities import SoftCosineSimilarity, SparseTermSimilarityMatrix
+    >>> from gensim.models import Word2Vec
+    >>> from gensim.similarities import SoftCosineSimilarity, SparseTermSimilarityMatrix, WordEmbeddingSimilarityIndex
     >>> from gensim.similarities.index import AnnoyIndexer
     >>> from scikits.sparse.cholmod import cholesky
     >>>