Reference Trac tickets in KnownFailureTests error messages

theano/tensor/tests/test_basic.py

@@ -2323,8 +2323,10 @@ class T_tensorfromscalar(unittest.TestCase):
         self.failUnless(isinstance(v, numpy.ndarray))
         self.failUnless(v.shape == (), v.shape)
 
-    @dec.knownfailureif(isinstance(get_default_mode(),theano.compile.debugmode.DebugMode),
-                        "This test fail in DEBUG_MODE but this don't make theano generate some bad code. It is a trouble with DEBUG_MODE")
+    @dec.knownfailureif(
+            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 #624."))
     def test1(self):
         s = scal.constant(56)
         t = as_tensor_variable(s)
@@ -2343,8 +2345,10 @@ class T_tensorfromscalar(unittest.TestCase):
         self.failUnless(eval_outputs([g])==1)
 
 class T_scalarfromtensor(unittest.TestCase):
-    @dec.knownfailureif(isinstance(get_default_mode(),theano.compile.debugmode.DebugMode),
-                        "This test fail in DEBUG_MODE but this don't make theano generate some bad code. It is a trouble with DEBUG_MODE")
+    @dec.knownfailureif(
+        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 #625."))
     def test0(self):
         tt = constant(56)#scal.constant(56)
         ss = scalar_from_tensor(tt)
@@ -3309,8 +3313,10 @@ def test_sum_overflow():
     f = function([a], sum(a))
     assert f([1]*300) == 300
 
-@dec.knownfailureif(isinstance(get_default_mode(),theano.compile.debugmode.DebugMode),
-                    "This test fail in DEBUG_MODE but this don't make theano generate some bad code. It is a trouble in DEBUG_MODE")
+@dec.knownfailureif(
+        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."))
 def test_default():
     x, y = scalars('xy')
     z = default(x, y)
@@ -3319,8 +3325,10 @@ def test_default():
     assert f(None, 2) == 2
     assert f(1, None) == 1
 
-@dec.knownfailureif(isinstance(get_default_mode(),theano.compile.debugmode.DebugMode),
-                    "This test fail in DEBUG_MODE but this don't make theano generate some bad code. It is a trouble in DEBUG_MODE")
+@dec.knownfailureif(
+        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."))
 def test_default_state():
     x, y = scalars('xy')
     print config.floatX

theano/tensor/tests/test_blas.py

@@ -549,13 +549,13 @@ def test_inplace0():
         raise Failure('gemm_inplace in graph')
     assert _dot22 in [n.op for n in f.maker.env.nodes]
 
-    raise KnownFailureTest("gemm not always inserted")
     f = inplace_func([X,Y,Z,a,b, R, S, c],
             [Z * (c*Z + a * T.dot(X,Y) + b * T.dot(R,S).T)], mode='FAST_RUN')
     # gemm_inplace should be inserted here, to work in-place on Z*c
     if (not gemm_inplace in [n.op for n in f.maker.env.nodes]):
         print pp(f.maker.env.outputs[0])
-        raise Failure('no gemm_inplace in graph')
+        #raise Failure('no gemm_inplace in graph')
+        raise KnownFailureTest("gemm not always inserted, see #415")
 
 def test_inplace1():
     X,Y,Z,a,b = XYZab()

theano/tensor/tests/test_complex.py

@@ -55,7 +55,7 @@ class TestRealImag(unittest.TestCase):
         mval = numpy.asarray(rng.randn(2,5))
         utt.verify_grad(f, [mval])
 
-    @dec.knownfailureif(True,"Complex grads not enabled")
+    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
     def test_mul_mixed0(self):
 
         def f(a):
@@ -71,7 +71,7 @@ class TestRealImag(unittest.TestCase):
             print e.analytic_grad
             raise
 
-    @dec.knownfailureif(True,"Complex grads not enabled")
+    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
     def test_mul_mixed1(self):
 
         def f(a):
@@ -86,7 +86,7 @@ class TestRealImag(unittest.TestCase):
             print e.num_grad.gf
             print e.analytic_grad
             raise
-    @dec.knownfailureif(True,"Complex grads not enabled")
+    @dec.knownfailureif(True,"Complex grads not enabled, see #178")
     def test_mul_mixed(self):
 
         def f(a,b):

theano/tensor/tests/test_opt.py

@@ -1136,7 +1136,8 @@ def test_log_add():
         print f([10000], [10000])  # causes overflow if handled incorrectly
         assert numpy.allclose(f([10000], [10000]), 20000)
     except AssertionError:
-        raise KnownFailureTest
+        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.
 
@@ -1710,19 +1711,25 @@ def test_constant_get_stabilized():
     x2 = T.scalar()
     y2 = T.log(1+T.exp(x2))
     f2 = theano.function([x2],y2)
-    raise KnownFailureTest("Theano optimize constant before stabilization! This break stabilization optimization is some case!")
-    assert len(f2.maker.env.toposort())==1
-    assert f2.maker.env.toposort()[0].op==theano.tensor.nnet.sigm.softplus
-    assert f2(800)==800
-
-    x = T.as_tensor_variable(800)
-    y = T.log(1+T.exp(x))
-    f = theano.function([],y)
-    assert len(f.maker.env.toposort())==0
-    assert numpy.isinf(f())
-
-    #When this error is fixed, the following line should be ok.
-    assert f()==800,f()
+    try:
+        assert len(f2.maker.env.toposort())==1
+        assert f2.maker.env.toposort()[0].op==theano.tensor.nnet.sigm.softplus
+        assert f2(800)==800
+
+        x = T.as_tensor_variable(800)
+        y = T.log(1+T.exp(x))
+        f = theano.function([],y)
+        assert len(f.maker.env.toposort())==0
+        assert numpy.isinf(f())
+
+        #When this error is fixed, the following line should be ok.
+        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."))
+
 
 class T_local_switch_sink(unittest.TestCase):
     def setUp(self):