knownfailuretest

theano/compile/tests/test_function_module.py

@@ -40,7 +40,8 @@ class T_function(unittest.TestCase):
         fn = function([], None)  # ok
         rval = fn()
         if rval == []:
-            raise KnownFailureTest('See #254: Using None as function output leads to [] return value')
+            raise SkipTest("Not yet implemented")
+            #raise KnownFailureTest('See #254: Using None as function output leads to [] return value')
         else:
             assert rval is None
 

theano/sandbox/gpuarray/tests/test_basic_ops.py

@@ -70,7 +70,8 @@ def may_fail(msg, EClass):
                 f()
             except Exception as e:
                 if isinstance(e, EClass):
-                    raise KnownFailureTest(msg, e)
+                    raise SkipTest("Not yet implemented")
+                    # raise KnownFailureTest(msg, e)
                 raise
         wrapper.__name__ = f.__name__
         return wrapper

theano/sandbox/scan_module/tests/test_scan.py

@@ -471,8 +471,10 @@ 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 KnownFailureTest('Work-in-progress sandbox ScanOp is not fully '
-                               'functional yet')
+        
+        raise SkipTest("Not yet implemented")
+        #raise KnownFailureTest('Work-in-progress sandbox ScanOp is not fully '
+        #                       'functional yet')
 
         def f_pow2(x_tm1):
             return 2 * x_tm1

theano/scan_module/tests/test_scan.py

@@ -3273,9 +3273,10 @@ class T_Scan(unittest.TestCase):
                     if isinstance(x.op, theano.tensor.Elemwise)]) == 0
 
     def test_alloc_inputs2(self):
-        raise KnownFailureTest((
-            "This tests depends on an optimization for scan "
-            "that has not been implemented yet."))
+        raise SkipTest("Not yet implemented")
+        # raise KnownFailureTest((
+        #    "This tests depends on an optimization for scan "
+        #    "that has not been implemented yet."))
         W1 = tensor.matrix()
         W2 = tensor.matrix()
         h0 = tensor.vector()
@@ -3502,8 +3503,9 @@ class T_Scan(unittest.TestCase):
         assert out == 24
 
     def test_infershape_seq_shorter_nsteps(self):
-        raise KnownFailureTest('This is a generic problem with infershape'
-                               ' that has to be discussed and figured out')
+        raise SkipTest("Not yet implemented")
+        # raise KnownFailureTest('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

@@ -6117,16 +6117,14 @@ class test_arithmetic_cast(unittest.TestCase):
                                     bool(numpy_version >= [1, 6]) and
                                     theano_dtype == 'complex128' and
                                     numpy_dtype == 'complex64'):
-                                    # In numpy 1.6.x adding a
-                                    # complex128 with a float32 or
-                                    # float16 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 KnownFailureTest('Known issue with '
-                                            'numpy >= 1.6.x see #761')
+                                    # 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")
+                                    # raise KnownFailureTest('Known issue with '
+                                    #        'numpy >= 1.6.x see #761')
 
                                 # In any other situation: something wrong is
                                 # going on!

theano/tensor/tests/test_opt.py

@@ -1558,8 +1558,9 @@ def test_log_add():
         f([10000], [10000])  # causes overflow if handled incorrectly
         assert numpy.allclose(f([10000], [10000]), 20000)
     except AssertionError:
-        raise KnownFailureTest(('log(add(exp)) is not stabilized when adding '
-                'more than 2 elements, see #623'))
+        raise SkipTest("Not yet implemented")
+        # raise KnownFailureTest(('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.
 
@@ -4025,9 +4026,10 @@ def test_constant_get_stabilized():
         assert f() == 800, f()
 
     except (AssertionError, theano.compile.debugmode.InvalidValueError):
-        raise KnownFailureTest((
-            "Theano optimizes constant before stabilization. "
-            "This breaks stabilization optimization in some cases. See #504."))
+        raise SkipTest("Not yet implemented")
+        # raise KnownFailureTest((
+        #    "Theano optimizes constant before stabilization. "
+        #    "This breaks stabilization optimization in some cases. See #504."))
 
 
 class T_local_switch_sink(unittest.TestCase):
@@ -4284,8 +4286,9 @@ 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 KnownFailureTest(
-                "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("Not yet implemented")
+            # raise KnownFailureTest(
+            #    "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.")
         assert all(numpy.isfinite(f(val)))
 
     def test_local_grad_log_erfc_neg(self):

theano/tests/test_rop.py

@@ -190,9 +190,10 @@ class RopLop_checker(unittest.TestCase):
         assert numpy.allclose(v1, v2), ('LOP mismatch: %s %s' % (v1, v2))
 
         if known_fail:
-            raise KnownFailureTest("Rop doesn't handle non-differentiable "
-                    "inputs correctly. Bug exposed by fixing Add.grad"
-                    " method.")
+            raise SkipTest("Not yet implemented")
+            # raise KnownFailureTest("Rop doesn't handle non-differentiable "
+            #        "inputs correctly. Bug exposed by fixing Add.grad"
+            #        " method.")
 
 
 class test_RopLop(RopLop_checker):