@dec.skipif

theano/scan_module/tests/test_scan.py

@@ -214,7 +214,7 @@ class T_Scan(unittest.TestCase):
 
     # generator network, only one output , type scalar ; no sequence or
     # non sequence arguments
-    @dec.knownfailureif(
+    @dec.skipif(
         isinstance(theano.compile.mode.get_default_mode(),
                    theano.compile.debugmode.DebugMode),
         ("This test fails in DebugMode, because it is not yet picklable."))
@@ -3350,7 +3350,7 @@ class T_Scan(unittest.TestCase):
         # One scan node gets optimnized out
         assert len(lssc) == 1
 
-    @dec.knownfailureif(True,
+    @dec.skipif(True,
                         ("This test fails because not typed outputs_info "
                          "are always gived the smallest dtype. There is "
                          "no upcast of outputs_info in scan for now."))

theano/tensor/tests/test_basic.py

@@ -5827,7 +5827,7 @@ def test_sum_overflow():
     assert f([1] * 300) == 300
 
 
-@dec.knownfailureif(
+@dec.skipif(
         isinstance(get_default_mode(), theano.compile.debugmode.DebugMode),
         ("This test fails in DEBUG_MODE, but the generated code is OK. "
          "It is actually a problem of DEBUG_MODE, see #626."))
@@ -5840,7 +5840,7 @@ def test_default():
     assert f(1, None) == 1
 
 
-@dec.knownfailureif(
+@dec.skipif(
         isinstance(get_default_mode(), theano.compile.debugmode.DebugMode),
         ("This test fails in DEBUG_MODE, but the generated code is OK. "
          "It is actually a problem of DEBUG_MODE, see #626."))

theano/tensor/tests/test_complex.py

@@ -48,7 +48,7 @@ class TestRealImag(unittest.TestCase):
         assert numpy.all(rval == mval[0]), (rval, mval[0])
         assert numpy.all(ival == mval[1]), (ival, mval[1])
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_complex_grads(self):
         def f(m):
             c = complex(m[0], m[1])
@@ -58,7 +58,7 @@ class TestRealImag(unittest.TestCase):
         mval = numpy.asarray(rng.randn(2, 5))
         utt.verify_grad(f, [mval])
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_mul_mixed0(self):
 
         def f(a):
@@ -74,7 +74,7 @@ class TestRealImag(unittest.TestCase):
             print(e.analytic_grad)
             raise
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_mul_mixed1(self):
 
         def f(a):
@@ -90,7 +90,7 @@ class TestRealImag(unittest.TestCase):
             print(e.analytic_grad)
             raise
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_mul_mixed(self):
 
         def f(a, b):
@@ -107,7 +107,7 @@ class TestRealImag(unittest.TestCase):
             print(e.analytic_grad)
             raise
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_polar_grads(self):
         def f(m):
             c = complex_from_polar(abs(m[0]), m[1])
@@ -117,7 +117,7 @@ class TestRealImag(unittest.TestCase):
         mval = numpy.asarray(rng.randn(2, 5))
         utt.verify_grad(f, [mval])
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_abs_grad(self):
         def f(m):
             c = complex(m[0], m[1])

theano/tensor/tests/test_fourier.py

@@ -39,7 +39,7 @@ class TestFourier(utt.InferShapeTester):
                                     [numpy.random.rand(12, 4), 0],
                                     self.op_class)
 
-    @dec.knownfailureif(True, "Complex grads not enabled, see #178")
+    @dec.skipif(True, "Complex grads not enabled, see #178")
     def test_gradient(self):
         def fft_test1(a):
             return self.op(a, None, None)