Assert that the gpuop is used.

theano/sandbox/cuda/tests/test_extra_ops.py

@@ -48,11 +48,13 @@ class TestGpuCumsum(theano.tensor.tests.test_extra_ops.TestCumsumOp):
 
         # Stepped strides
         f = theano.function([x], cumsum(x[::2]), mode=self.mode)
+        assert [n for n in f.maker.fgraph.toposort() if isinstance(n.op, GpuCumsum)]
         a = np.random.randint(10, size=(42,)).astype("float32")
         assert np.allclose(np.cumsum(a[::2]), f(a))
 
         # Negative strides
         f = theano.function([x], cumsum(x[::-1]), mode=self.mode)
+        assert [n for n in f.maker.fgraph.toposort() if isinstance(n.op, GpuCumsum)]
         a = np.random.randint(10, size=(42,)).astype("float32")
         assert np.allclose(np.cumsum(a[::-1]), f(a))
 
@@ -61,6 +63,7 @@ class TestGpuCumsum(theano.tensor.tests.test_extra_ops.TestCumsumOp):
 
         x = T.fvector('x')
         f = theano.function([x], cumsum(x), mode=self.mode)
+        assert [n for n in f.maker.fgraph.toposort() if isinstance(n.op, GpuCumsum)]
 
         # Extensive testing for the first 1k sizes
         a = np.ones((int(1e3),), dtype="float32")
@@ -82,6 +85,7 @@ class TestGpuCumsum(theano.tensor.tests.test_extra_ops.TestCumsumOp):
         x = T.fmatrix('x')
         for axis in xrange(2):
             f = theano.function([x], cumsum(x, axis=axis), mode=self.mode)
+            assert [n for n in f.maker.fgraph.toposort() if isinstance(n.op, GpuCumsum)]
 
             # Extensive testing for the first 1k sizes
             a_shape = [11, 11]