Disable compute_test_value for test that expect errors.

theano/tensor/nnet/tests/test_neighbours.py

@@ -8,6 +8,7 @@ import theano.tensor as T
 from theano.tensor.nnet.neighbours import images2neibs, neibs2images, Images2Neibs
 
 from theano.tests import unittest_tools
+from theano.configparser import change_flags
 
 mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpu')
 
@@ -140,6 +141,7 @@ class T_Images2Neibs(unittest_tools.InferShapeTester):
                 # print g()
                 # assert numpy.allclose(images.get_value(borrow=True), g())
 
+    @change_flags(compute_test_value='off')
     def test_neibs_bad_shape(self):
         shape = (2, 3, 10, 10)
         for dtype in self.dtypes:
@@ -287,6 +289,7 @@ class T_Images2Neibs(unittest_tools.InferShapeTester):
                     f_full = theano.function([], x_using_full, mode=self.mode)
                     unittest_tools.assert_allclose(f_valid(), f_full())
 
+    @change_flags(compute_test_value='off')
     def test_neibs_bad_shape_wrap_centered(self):
         shape = (2, 3, 10, 10)
 

theano/tensor/tests/test_basic.py

@@ -57,7 +57,7 @@ from theano.tensor import (
 
 from theano.tests import unittest_tools as utt
 from theano.tests.unittest_tools import attr
-
+from theano.configparser import change_flags
 
 imported_scipy_special = False
 mode_no_scipy = get_default_mode()
@@ -443,6 +443,7 @@ def makeTester(name, op, expected, checks=None, good=None, bad_build=None,
                 # instantiated on the following bad inputs: %s"
                 # % (self.op, testname, node, inputs))
 
+        @change_flags(compute_test_value='off')
         def test_bad_runtime(self):
             if skip:
                 raise SkipTest(skip)
@@ -4383,14 +4384,15 @@ class T_Join_and_Split(unittest.TestCase):
             for node in topo:
                 assert not isinstance(node.op, type(self.join_op))
 
-        # Test hide error
-        x1.set_value(get_mat(3, 4))
-        x2.set_value(get_mat(3, 4))
-        x3.set_value(get_mat(2, 5))
-        if not self.hide_error:
-            self.assertRaises(ValueError, f)
-        else:
-            f()
+        with change_flags(compute_test_value='off'):
+            # Test hide error
+            x1.set_value(get_mat(3, 4))
+            x2.set_value(get_mat(3, 4))
+            x3.set_value(get_mat(2, 5))
+            if not self.hide_error:
+                self.assertRaises(ValueError, f)
+            else:
+                f()
 
     def test_rebroadcast(self):
         # Regression test for a crash that used to happen when rebroadcasting.
@@ -4432,6 +4434,7 @@ class T_Join_and_Split(unittest.TestCase):
         assert np.allclose(o1, m.get_value(borrow=True))
         assert np.allclose(o2, m.get_value(borrow=True)[4:])
 
+    @change_flags(compute_test_value='off')
     def test_split_neg(self):
         rng = np.random.RandomState(seed=utt.fetch_seed())
         m = self.shared(rng.rand(4, 6).astype(self.floatX))
@@ -7321,11 +7324,12 @@ class T_get_scalar_constant_value(unittest.TestCase):
         a = opt.Assert()(c, c > 1)
         assert get_scalar_constant_value(a) == 2
 
-        # condition is always False
-        a = opt.Assert()(c, c > 2)
-        self.assertRaises(
-            tensor.NotScalarConstantError,
-            get_scalar_constant_value, a)
+        with change_flags(compute_test_value='off'):
+            # condition is always False
+            a = opt.Assert()(c, c > 2)
+            self.assertRaises(
+                tensor.NotScalarConstantError,
+                get_scalar_constant_value, a)
 
         # condition is not constant
         a = opt.Assert()(c, c > x)

theano/tensor/tests/test_mpi.py

@@ -6,11 +6,14 @@ import subprocess
 import os
 from theano.gof.sched import sort_schedule_fn
 
+from theano.configparser import change_flags
+
 mpi_scheduler = sort_schedule_fn(*mpi_cmps)
 mpi_linker = theano.OpWiseCLinker(schedule=mpi_scheduler)
 mpi_mode = theano.Mode(linker=mpi_linker)
 
 
+@change_flags(compute_test_value='off')
 def test_recv():
     x = recv((10, 10), 'float64', 0, 11)
     assert x.dtype == 'float64'
@@ -29,6 +32,7 @@ def test_send():
     assert sendnode.op.tag  == 11
 
 
+@change_flags(compute_test_value='off')
 def test_can_make_function():
     x = recv((5, 5), 'float32', 0, 11)
     y = x+1
@@ -61,6 +65,7 @@ def test_mpi_send_wait_cmp():
     assert mpi_send_wait_cmp(waitnode, addnode) > 0  # wait happens last
 
 
+@change_flags(compute_test_value='off')
 def test_mpi_tag_ordering():
     x = recv((2, 2), 'float32', 1, 12)
     y = recv((2, 2), 'float32', 1, 11)

theano/tensor/tests/test_opt.py

@@ -63,6 +63,7 @@ from theano.tensor.elemwise import DimShuffle
 from theano.tensor.type import values_eq_approx_remove_nan
 from theano.tests import unittest_tools as utt
 from theano.gof.opt import check_stack_trace, out2in
+from theano.configparser import change_flags
 from nose.plugins.attrib import attr
 
 mode_opt = theano.config.mode
@@ -3685,6 +3686,7 @@ class Test_local_canonicalize_alloc(unittest.TestCase):
     def setUp(self):
         self.rng = np.random.RandomState(utt.fetch_seed())
 
+    @change_flags(compute_test_value='off')
     def test0(self):
         x = shared(self.rng.randn(3, 7))
         a = tensor.alloc(x, 6, 7)
@@ -5602,7 +5604,7 @@ class T_local_opt_alloc(unittest.TestCase):
         finally:
             theano.config.warn_float64 = orig
 
-    @theano.configparser.change_flags(on_opt_error='raise')
+    @change_flags(on_opt_error='raise')
     def test_sum_bool_upcast(self):
         s = theano.tensor.lscalar()
         a = theano.tensor.alloc(np.asarray(True, dtype='bool'), s, s)

theano/tensor/tests/test_subtensor.py

@@ -34,6 +34,7 @@ from theano.tensor.subtensor import (AdvancedIncSubtensor,
 from theano.tensor.tests.test_basic import inplace_func, rand, randint_ranged
 from theano.tests import unittest_tools as utt
 from theano.tests.unittest_tools import attr
+from theano.configparser import change_flags
 
 if PY3:
     def L(i):
@@ -126,14 +127,10 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
             return
         self.fail()
 
+    @change_flags(compute_test_value='off')
     def test1_err_bounds(self):
         n = self.shared(np.ones(3, dtype=self.dtype))
-        ctv_backup = config.compute_test_value
-        config.compute_test_value = 'off'
-        try:
-            t = n[7]
-        finally:
-            config.compute_test_value = ctv_backup
+        t = n[7]
         self.assertTrue(isinstance(t.owner.op, Subtensor))
         # Silence expected error messages
         _logger = logging.getLogger('theano.gof.opt')
@@ -223,26 +220,23 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         self.assertTrue(tval.shape == (2,))
         self.assertTrue((tval == [0.0, 2.0]).all())
 
+    @change_flags(compute_test_value='off')
     def test2_err_bounds0(self):
         n = self.shared(np.ones((2, 3), dtype=self.dtype) * 5)
-        ctv_backup = config.compute_test_value
-        config.compute_test_value = 'off'
-        try:
-            for idx in [(0, 4), (0, -4)]:
-                t = n[idx]
-                self.assertTrue(isinstance(t.owner.op, Subtensor))
-                # Silence expected warnings
-                _logger = logging.getLogger('theano.gof.opt')
-                oldlevel = _logger.level
-                _logger.setLevel(logging.CRITICAL)
-                try:
-                    self.assertRaises(IndexError,
-                                      self.eval_output_and_check, [t])
-                finally:
-                    _logger.setLevel(oldlevel)
-        finally:
-            config.compute_test_value = ctv_backup
+        for idx in [(0, 4), (0, -4)]:
+            t = n[idx]
+            self.assertTrue(isinstance(t.owner.op, Subtensor))
+            # Silence expected warnings
+            _logger = logging.getLogger('theano.gof.opt')
+            oldlevel = _logger.level
+            _logger.setLevel(logging.CRITICAL)
+            try:
+                self.assertRaises(IndexError,
+                                  self.eval_output_and_check, [t])
+            finally:
+                _logger.setLevel(oldlevel)
 
+    @change_flags(compute_test_value='off')
     def test2_err_bounds1(self):
         n = self.shared((np.ones((2, 3), dtype=self.dtype) * 5))
         t = n[4:5, 3]