Use the new verify_grad_sparse (if only to make sure it works).

theano/sparse/tests/test_basic.py

@@ -19,6 +19,7 @@ if enable_sparse == False:
 
 from theano.sparse.basic import _is_dense, _is_sparse, _mtypes
 from theano.sparse.basic import _is_dense_variable, _is_sparse_variable
+from theano.sparse.basic import verify_grad_sparse
 from theano.sparse import as_sparse_variable, CSC, CSR, CSM, CSMProperties
 from theano.sparse import SparseType, StructuredDotCSC, CSMGrad
 from theano.sparse import AddSS, AddSD, MulSS, MulSD, Transpose, Neg
@@ -462,16 +463,8 @@ class test_structureddot(unittest.TestCase):
 
         mat = numpy.asarray(numpy.random.randn(3, 2), 'float32')
 
-        def buildgraphCSC(spdata, sym_mat):
-            csc = CSC(spdata, spmat.indices[:spmat.size],
-                    spmat.indptr, spmat.shape)
-            assert csc.type.dtype == 'float32'
-            rval = structured_dot(csc, sym_mat)
-            assert rval.type.dtype == 'float32'
-            return rval
+        verify_grad_sparse(structured_dot, [spmat, mat])
 
-        utt.verify_grad(buildgraphCSC,
-                    [spmat.data, mat])
 
         def buildgraphCSC_T(spdata, sym_mat):
             csc = CSC(spdata, spmat.indices[:spmat.size],
@@ -493,16 +486,7 @@ class test_structureddot(unittest.TestCase):
 
         mat = numpy.asarray(numpy.random.randn(3, 2), 'float64')
 
-        def buildgraph(spdata, sym_mat):
-            csr = CSR(spdata, spmat.indices[:spmat.size],
-                    spmat.indptr, spmat.shape)
-            assert csr.type.dtype == 'float64'
-            rval = structured_dot(csr, sym_mat)
-            assert rval.type.dtype == 'float64'
-            return rval
-
-        utt.verify_grad(buildgraph,
-                    [spmat.data, mat])
+        verify_grad_sparse(structured_dot, [spmat, mat])
 
         def buildgraph_T(spdata, sym_mat):
             csr = CSR(spdata, spmat.indices[:spmat.size],