def test_sparse_tensor_error(self):
import theano.sparse
if not theano.sparse.enable_sparse:
raise SkipTest("Optimization temporarily disabled")
rng = numpy.random.RandomState(utt.fetch_seed())
data = rng.rand(2, 3).astype(self.dtype)
x = self.shared(data)
y = theano.sparse.matrix('csc', dtype=self.dtype, name='y')
z = theano.sparse.matrix('csr', dtype=self.dtype, name='z')
cond = theano.tensor.iscalar('cond')
self.assertRaises(TypeError, ifelse, cond, x, y)
self.assertRaises(TypeError, ifelse, cond, y, x)
self.assertRaises(TypeError, ifelse, cond, x, z)
self.assertRaises(TypeError, ifelse, cond, z, x)
self.assertRaises(TypeError, ifelse, cond, y, z)
self.assertRaises(TypeError, ifelse, cond, z, y)
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