Fix details for comments

theano/compile/tests/test_function_module.py

@@ -17,7 +17,6 @@ from theano import tensor as T
 import theano
 
 import numpy as N
-from numpy.testing.noseclasses import KnownFailureTest
 
 PatternOptimizer = lambda p1, p2, ign=True: gof.OpKeyOptimizer(gof.PatternSub(p1, p2), ignore_newtrees=ign)
 

theano/sandbox/gpuarray/tests/test_basic_ops.py

@@ -12,7 +12,6 @@ from theano.tensor.basic import alloc
 from theano.tensor.tests import test_basic
 from theano.tensor.tests.test_basic import rand, safe_make_node
 from theano.tests.unittest_tools import SkipTest
-from numpy.testing.noseclasses import KnownFailureTest
 
 import theano.sandbox.gpuarray
 
@@ -70,7 +69,7 @@ def may_fail(msg, EClass):
                 f()
             except Exception as e:
                 if isinstance(e, EClass):
-                    raise SkipTest("Not yet implemented")
+                    raise SkipTest(msg, e)
                 raise
         wrapper.__name__ = f.__name__
         return wrapper

theano/sandbox/scan_module/tests/test_scan.py

@@ -16,7 +16,6 @@ from theano import tensor
 from theano.compile.pfunc import rebuild_collect_shared
 from theano.tests  import unittest_tools as utt
 from theano.tests.unittest_tools import SkipTest
-from numpy.testing.noseclasses import KnownFailureTest
 
 from test_utils import *
 import theano.sandbox.scan_module as scan_module
@@ -473,9 +472,7 @@ class TestScan(unittest.TestCase):
         # soon, and it is in the sandbox and not for user consumption, the
         # error is marked as KnownFailure
         
-        raise SkipTest("Not yet implemented")
-        # Work-in-progress sandbox ScanOp is not fully 
-        # functional yet
+        raise SkipTest("Work-in-progress sandbox ScanOp is not fully functional yet")
 
         def f_pow2(x_tm1):
             return 2 * x_tm1
@@ -511,9 +508,7 @@ class TestScan(unittest.TestCase):
         # place (even when told not to by DebugMode). As this op will change
         # soon, and it is in the sandbox and not for user consumption, the
         # error is marked as KnownFailure
-        raise SkipTest("Not yet implemented")
-        # Work-in-progress sandbox ScanOp is not fully 
-        # functional yet
+        raise SkipTest("Work-in-progress sandbox ScanOp is not fully functional yet")
 
         def f_rnn(u_t, x_tm1, W_in, W):
             return u_t * W_in + x_tm1 * W

theano/scan_module/tests/test_scan.py

@@ -24,8 +24,6 @@ import theano.scalar.sharedvar
 from theano.scan_module.scan_op import Scan
 from theano.compat import PY3, OrderedDict
 
-from numpy.testing.noseclasses import KnownFailureTest
-
 
 '''
   Questions and notes about scan that should be answered :
@@ -3273,9 +3271,7 @@ class T_Scan(unittest.TestCase):
                     if isinstance(x.op, theano.tensor.Elemwise)]) == 0
 
     def test_alloc_inputs2(self):
-        raise SkipTest("Not yet implemented")
-        # This tests depends on an optimization for scan
-        # that has not been implemented yet.
+        raise SkipTest("This tests depends on an optimization for scan that has not been implemented yet.")
         W1 = tensor.matrix()
         W2 = tensor.matrix()
         h0 = tensor.vector()
@@ -3502,9 +3498,7 @@ class T_Scan(unittest.TestCase):
         assert out == 24
 
     def test_infershape_seq_shorter_nsteps(self):
-        raise SkipTest("Not yet implemented")
-        # This is a generic problem with infershape
-        # that has to be discussed and figured out
+        raise SkipTest("This is a generic problem with infershape that has to be discussed and figured out")
         x = tensor.vector('x')
         [o1, o2], _ = theano.scan(lambda x, y: (x + 1, y + x),
                          sequences=x,

theano/tensor/tests/test_basic.py

@@ -16,7 +16,6 @@ from nose.plugins.skip import SkipTest
 from nose.plugins.attrib import attr
 import numpy
 from numpy.testing import dec, assert_array_equal, assert_allclose
-from numpy.testing.noseclasses import KnownFailureTest
 from distutils.version import LooseVersion
 
 import theano
@@ -6118,12 +6117,10 @@ class test_arithmetic_cast(unittest.TestCase):
                                     theano_dtype == 'complex128' and
                                     numpy_dtype == 'complex64'):
                                     # In numpy 1.6.x adding a complex128 with
-                                    # a float32 may result in a complex64. This
-                                    # may be a bug (investigation is currently
-                                    # in progress), so in the meantime we just
-                                    # mark this test as a known failure.
-                                    raise SkipTest("Not yet implemented")
-                                    # Known issue with numpy >= 1.6.x see #761'
+                                    # a float32 may result in a complex64. As
+                                    # of 1.9.2. this is still the case so it is
+                                    # probably by design
+                                    raise SkipTest("Known issue with numpy >= 1.6.x see #761")
                                 # In any other situation: something wrong is
                                 # going on!
                                 assert False

theano/tensor/tests/test_opt.py

@@ -1558,9 +1558,7 @@ def test_log_add():
         f([10000], [10000])  # causes overflow if handled incorrectly
         assert numpy.allclose(f([10000], [10000]), 20000)
     except AssertionError:
-        raise SkipTest("Not yet implemented")
-        # log(add(exp)) is not stabilized when adding 
-        # more than 2 elements, see #623
+        raise SkipTest("log(add(exp)) is not stabilized when adding more than 2 elements, see #623")
 
     # TODO: test that the optimization works in the presence of broadcasting.
 
@@ -4026,9 +4024,8 @@ def test_constant_get_stabilized():
         assert f() == 800, f()
 
     except (AssertionError, theano.compile.debugmode.InvalidValueError):
-        raise SkipTest("Not yet implemented")
-        # Theano optimizes constant before stabilization.
-        # This breaks stabilization optimization in some cases. See #504.
+        raise SkipTest('Theano optimizes constant before stabilization.'
+            'This breaks stabilization optimization in some cases. See #504.')
 
 
 class T_local_switch_sink(unittest.TestCase):
@@ -4285,8 +4282,8 @@ class T_local_erfc(unittest.TestCase):
             0].op.scalar_op.fgraph.apply_nodes) == 22, len(f.maker.fgraph.toposort()[0].fgraph.toposort()[0].op.scalar_op.fgraph.apply_nodes)
         # TODO: fix this problem
         if theano.config.floatX == "float32" and theano.config.mode in ["DebugMode", "DEBUG_MODE"]:
-            raise SkipTest("Not yet implemented")
-            # The python code upcast somewhere internally some value of float32 to python float for part of its computation. That make that the c and python code don't generate the same value. You can ignore this error.
+            raise SkipTest('The python code upcast somewhere internally some value of float32 to python float for part of its computation.'
+                'That make that the c and python code dont generate the same value. You can ignore this error.')
         assert all(numpy.isfinite(f(val)))
 
     def test_local_grad_log_erfc_neg(self):

theano/tests/test_rop.py

@@ -20,7 +20,6 @@ from theano import tensor
 import numpy
 from theano.gof import Op, Apply
 from theano.gradient import grad_undefined
-from numpy.testing.noseclasses import KnownFailureTest
 from theano.tests.unittest_tools import SkipTest
 from theano.tensor.signal.downsample import DownsampleFactorMax
 from theano.tensor.nnet import conv
@@ -191,11 +190,8 @@ class RopLop_checker(unittest.TestCase):
         assert numpy.allclose(v1, v2), ('LOP mismatch: %s %s' % (v1, v2))
 
         if known_fail:
-            raise SkipTest("Not yet implemented")
-            # Rop doesn't handle non-differentiable
-            # inputs correctly. Bug exposed by fixing Add.grad
-            # method.
-
+            raise SkipTest('Rop doesn t handle non-differentiable inputs correctly.' 
+                'Bug exposed by fixing Add.grad method.')
 
 class test_RopLop(RopLop_checker):
     def test_shape(self):