Merge pull request #6178 from abergeron/fix_buildbot2

theano/compile/tests/test_ops.py

@@ -39,7 +39,7 @@ class OpDecoratorTests(utt.InferShapeTester):
         x = dmatrix('x')
         x.tag.test_value = np.zeros((2, 2))
         y = dvector('y')
-        y.tag.test_value = [0, 0]
+        y.tag.test_value = [0, 0, 0, 0]
 
         @as_op([dmatrix, dvector], dvector)
         def cumprod_plus(x, y):
@@ -55,7 +55,7 @@ class OpDecoratorTests(utt.InferShapeTester):
         x = dmatrix('x')
         x.tag.test_value = np.zeros((2, 2))
         y = dvector('y')
-        y.tag.test_value = [0, 0]
+        y.tag.test_value = [0, 0, 0, 0]
 
         def infer_shape(node, shapes):
             x, y = shapes

theano/gof/tests/test_destroyhandler.py

@@ -12,6 +12,8 @@ from theano.gof import destroyhandler
 from theano.gof.fg import FunctionGraph, InconsistencyError
 from theano.gof.toolbox import ReplaceValidate
 
+from theano.configparser import change_flags
+
 from copy import copy
 
 
@@ -429,6 +431,7 @@ def test_value_repl():
     consistent(g)
 
 
+@change_flags(compute_test_value='off')
 def test_value_repl_2():
     x, y, z = inputs()
     sy = sigmoid(y)

theano/sandbox/tests/test_rng_mrg.py

@@ -15,6 +15,8 @@ from theano.sandbox.rng_mrg import MRG_RandomStreams
 from theano.tests import unittest_tools as utt
 from theano.tests.unittest_tools import attr
 
+from theano.configparser import change_flags
+
 # TODO: test MRG_RandomStreams
 # Partly done in test_consistency_randomstreams
 
@@ -666,9 +668,10 @@ def test_overflow_cpu():
     # run with THEANO_FLAGS=mode=FAST_RUN,device=cpu,floatX=float32
     rng = MRG_RandomStreams(np.random.randint(1234))
     fct = rng.uniform
-    # should raise error as the size overflows
-    sizes = [(2**31, ), (2**32, ), (2**15, 2**16,), (2, 2**15, 2**15)]
-    rng_mrg_overflow(sizes, fct, config.mode, should_raise_error=True)
+    with change_flags(compute_test_value='off'):
+        # should raise error as the size overflows
+        sizes = [(2**31, ), (2**32, ), (2**15, 2**16,), (2, 2**15, 2**15)]
+        rng_mrg_overflow(sizes, fct, config.mode, should_raise_error=True)
     # should not raise error
     sizes = [(2**5, ), (2**5, 2**5), (2**5, 2**5, 2**5)]
     rng_mrg_overflow(sizes, fct, config.mode, should_raise_error=False)

theano/tensor/basic.py

@@ -5862,53 +5862,6 @@ class Dot(Op):
         if eval_points[0] is None and eval_points[1] is None:
             return [None]
 
-        debugger_available = config.compute_test_value != 'off'
-
-        if debugger_available:
-            try:
-                iv0 = gof.op.get_test_value(inputs[0])
-            except AttributeError:
-                gof.op.missing_test_message(
-                    'first input passed to Dot.R_op has no test value')
-                debugger_available = False
-
-            try:
-                iv1 = gof.op.get_test_value(inputs[1])
-            except AttributeError:
-                gof.op.missing_test_message(
-                    'second input passed to Dot.R_op has no test value')
-                debugger_available = False
-
-            if eval_points[0]:
-                try:
-                    ev0 = gof.op.get_test_value(eval_points[0])
-                except AttributeError:
-                    gof.op.missing_test_message(
-                        'first eval point passed to Dot.R_op '
-                        'has no test value')
-                    debugger_available = False
-            if eval_points[1]:
-                try:
-                    ev1 = gof.op.get_test_value(eval_points[1])
-                except AttributeError:
-                    gof.op.missing_test_message(
-                        'second eval point passed to Dot.R_op '
-                        'has no test value')
-                    debugger_available = False
-
-        if debugger_available:
-            input_values = [iv0, iv1]
-            eval_point_values = [ev0, ev1]
-
-            for i in xrange(2):
-                if eval_point_values[i] is not None and \
-                   input_values[i].shape != eval_point_values[i].shape:
-                    raise ValueError(
-                        'input ' + str(i) + ' and eval_point ' + str(i) +
-                        ' to Dot.R_op should have the same shape, but '
-                        'their shapes are %s and %s, respectively' % (
-                            str(input_values[i].shape),
-                            str(eval_point_values[i].shape)))
         if eval_points[0]:
             t1 = self(eval_points[0], inputs[1])
         if eval_points[1]:

theano/tensor/nnet/abstract_conv.py

@@ -2300,8 +2300,8 @@ class AbstractConv_gradInputs(BaseAbstractConv):
             mshp0 = mat.shape[0] // self.num_groups
             mshp1 = mat.shape[1] * self.num_groups
             mat = mat.reshape((self.num_groups, mshp0) + mat.shape[1:])
-            mat = mat.transpose((1, 0, 2, 3, 4))
-            mat = mat.reshape((mshp0, mshp1) + mat.shape[-2:])
+            mat = mat.transpose((1, 0, 2) + tuple(range(3, 3 + self.convdim)))
+            mat = mat.reshape((mshp0, mshp1) + mat.shape[-self.convdim:])
             return mat
         kern = correct_for_groups(kern)
         kern = kern.transpose(axes_order)

theano/tensor/nnet/tests/test_conv3d.py

@@ -130,7 +130,7 @@ class TestConv3D(utt.InferShapeTester):
         self.rb.name = 'rb'
         self.V = shared(N.ndarray(shape=(1, 1, 1, 1, 1), dtype=floatX))
         self.V.name = 'V'
-        self.d = shared(N.ndarray(shape=(3, ), dtype=int))
+        self.d = shared(N.ones(shape=(3, ), dtype=int))
         self.d.name = 'd'
 
         self.H = conv3D(self.V, self.W, self.b, self.d)

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]