Don't use test_values when checking for errors.

theano/tensor/tests/test_subtensor.py

@@ -421,6 +421,7 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         assert_array_equal(numpy_inc_subtensor(numpy_n4, [numpy_n > 2, Ellipsis, 0, 1], 1),
                            inc_subtensor(n4[n > 2, ..., 0, 1], 1).eval())
 
+        with change_flags(compute_test_value='off'):
             # the boolean mask should have the correct shape
             # - too large, padded with True
             mask = np.array([True, False, True])

theano/tests/test_gradient.py

@@ -9,7 +9,7 @@ import numpy as np
 from six.moves import xrange
 
 import theano
-from theano import gof
+from theano import gof, change_flags
 from theano.compat import izip
 from theano.tests import unittest_tools as utt
 
@@ -803,6 +803,7 @@ def test_grad_scale():
     assert np.allclose(out, (8, 4))
 
 
+@change_flags(compute_test_value='off')
 def test_undefined_grad_opt():
     # Make sure that undefined grad get removed in optimized graph.
     random = RandomStreams(np.random.randint(1, 2147462579))