Fix sklearn_api bug with documents_columns parameter. Fix piskvorky#1676

(piskvorky#1704) * updated param passed to 'Sparse2Corpus' * updated unit test * updated 'partial_fit' and passed named params
VaiyeBe · Nov 26, 2017 · 76983da · 76983da
1 parent fb05df2
commit 76983da
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Showing 4 changed files with 7 additions and 7 deletions.
diff --git a/gensim/sklearn_api/hdp.py b/gensim/sklearn_api/hdp.py
@@ -51,7 +51,7 @@ def fit(self, X, y=None):
         Calls gensim.models.HdpModel
         """
         if sparse.issparse(X):
-            corpus = matutils.Sparse2Corpus(X)
+            corpus = matutils.Sparse2Corpus(sparse=X, documents_columns=False)
         else:
             corpus = X
 
@@ -95,7 +95,7 @@ def partial_fit(self, X):
         Train model over X.
         """
         if sparse.issparse(X):
-            X = matutils.Sparse2Corpus(X)
+            X = matutils.Sparse2Corpus(sparse=X, documents_columns=False)
 
         if self.gensim_model is None:
             self.gensim_model = models.HdpModel(

diff --git a/gensim/sklearn_api/ldamodel.py b/gensim/sklearn_api/ldamodel.py
@@ -58,7 +58,7 @@ def fit(self, X, y=None):
         Calls gensim.models.LdaModel
         """
         if sparse.issparse(X):
-            corpus = matutils.Sparse2Corpus(X)
+            corpus = matutils.Sparse2Corpus(sparse=X, documents_columns=False)
         else:
             corpus = X
 
@@ -102,7 +102,7 @@ def partial_fit(self, X):
 
         """
         if sparse.issparse(X):
-            X = matutils.Sparse2Corpus(X)
+            X = matutils.Sparse2Corpus(sparse=X, documents_columns=False)
 
         if self.gensim_model is None:
             self.gensim_model = models.LdaModel(

diff --git a/gensim/sklearn_api/lsimodel.py b/gensim/sklearn_api/lsimodel.py
@@ -43,7 +43,7 @@ def fit(self, X, y=None):
         Calls gensim.models.LsiModel
         """
         if sparse.issparse(X):
-            corpus = matutils.Sparse2Corpus(X)
+            corpus = matutils.Sparse2Corpus(sparse=X, documents_columns=False)
         else:
             corpus = X
 
@@ -78,7 +78,7 @@ def partial_fit(self, X):
         Train model over X.
         """
         if sparse.issparse(X):
-            X = matutils.Sparse2Corpus(X)
+            X = matutils.Sparse2Corpus(sparse=X, documents_columns=False)
 
         if self.gensim_model is None:
             self.gensim_model = models.LsiModel(

diff --git a/gensim/test/test_sklearn_api.py b/gensim/test/test_sklearn_api.py
@@ -177,7 +177,7 @@ def testCSRMatrixConversion(self):
         newmodel.fit(sarr)
         bow = [(0, 1), (1, 2), (2, 0)]
         transformed_vec = newmodel.transform(bow)
-        expected_vec = numpy.array([0.35367903, 0.64632097])
+        expected_vec = numpy.array([0.12843782, 0.87156218])
         passed = numpy.allclose(transformed_vec, expected_vec, atol=1e-1)
         self.assertTrue(passed)