scikit-learn
diff --git a/‎sklearn/utils/validation.py‎
Lines changed: 1 addition & 15 deletions b/‎sklearn/utils/validation.py‎
Lines changed: 1 addition & 15 deletions
@@ -151,20 +151,6 @@ def check_consistent_length(*arrays):
                          % str(uniques))
 
 
-def _get_sparse_type_string(sparse_matrix):
-    """Return string representation of sparse matrix format of input"""
-    formats = ['csr', 'csc', 'coo', 'dok', 'lil', 'dia', 'bsr']
-    type_checkers = [sp.isspmatrix_csr, sp.isspmatrix_csc, sp.isspmatrix_coo,
-                     sp.isspmatrix_dok, sp.isspmatrix_lil, sp.isspmatrix_dia,
-                     sp.isspmatrix_bsr]
-    for type_checker, s in zip(type_checkers, formats):
-        if type_checker(sparse_matrix):
-            return s
-    else:
-        raise ValueError("Unknown sparse matrix format passed: %s"
-                         % type(sparse_matrix))
-
-
 def _sparse_matrix_constructor(string_format):
     """Get constructor from a sparse matrix string format."""
     if string_format == "csr":
@@ -218,7 +204,7 @@ def _ensure_sparse_format(spmatrix, allowed_sparse, dtype, order, copy,
         raise TypeError('A sparse matrix was passed, but dense '
                         'data is required. Use X.toarray() to '
                         'convert to a dense numpy array.')
-    sparse_type = _get_sparse_type_string(spmatrix)
+    sparse_type = spmatrix.format
     if sparse_type in allowed_sparse:
         # correct type
         if dtype == spmatrix.dtype or dtype is None: