Merge pull request #2789 from thomasmesnard/knownfailuretest

theano/compile/tests/test_function_module.py

@@ -11,13 +11,13 @@ from theano.compile import function
 from theano.compile import UnusedInputError
 from theano.gof import MissingInputError
 from theano.compat import exc_message
+from theano.tests.unittest_tools import SkipTest
 
 from theano import tensor
 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)
 
@@ -41,7 +41,8 @@ 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("See #254: Using None as function output leads "
+                           "to [] return value")
         else:
             assert rval is None
 

theano/sandbox/gpuarray/tests/test_basic_ops.py

@@ -14,7 +14,6 @@ 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
 
@@ -73,7 +72,7 @@ def may_fail(msg, EClass):
                 f()
             except Exception as e:
                 if isinstance(e, EClass):
-                    raise KnownFailureTest(msg, e)
+                    raise SkipTest(msg, e)
                 raise
         wrapper.__name__ = f.__name__
         return wrapper

theano/sandbox/scan_module/tests/test_scan.py

@@ -16,7 +16,7 @@ import theano.sandbox.rng_mrg
 from theano import tensor
 from theano.compile.pfunc import rebuild_collect_shared
 from theano.tests  import unittest_tools as utt
-from numpy.testing.noseclasses import KnownFailureTest
+from theano.tests.unittest_tools import SkipTest
 
 from .test_utils import *
 import theano.sandbox.scan_module as scan_module
@@ -471,8 +471,9 @@ 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("Work-in-progress sandbox ScanOp is "
+                       "not fully functional yet")
 
         def f_pow2(x_tm1):
             return 2 * x_tm1
@@ -508,9 +509,8 @@ 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("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

@@ -25,8 +25,6 @@ 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 :
@@ -218,7 +216,7 @@ 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."))
@@ -3055,9 +3053,8 @@ 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("This tests depends on an optimization for "
+                       "scan that has not been implemented yet.")
         W1 = tensor.matrix()
         W2 = tensor.matrix()
         h0 = tensor.vector()
@@ -3135,7 +3132,7 @@ 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."))
@@ -3284,8 +3281,9 @@ 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("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

@@ -18,7 +18,6 @@ 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
@@ -5911,7 +5910,7 @@ 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."))
@@ -5924,7 +5923,7 @@ 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."))
@@ -6209,17 +6208,12 @@ 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. 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_complex.py

@@ -49,7 +49,7 @@ 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])
@@ -59,7 +59,7 @@ 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):
@@ -75,7 +75,7 @@ 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):
@@ -91,7 +91,7 @@ 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):
@@ -108,7 +108,7 @@ 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])
@@ -118,7 +118,7 @@ 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)

theano/tensor/tests/test_opt.py

@@ -1581,8 +1581,8 @@ 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("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.
 
@@ -4048,9 +4048,9 @@ 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('Theano optimizes constant before stabilization. '
+                       'This breaks stabilization optimization in some '
+                       'cases. See #504.')
 
 
 class T_local_switch_sink(unittest.TestCase):
@@ -4307,8 +4307,11 @@ 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('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):
@@ -4376,8 +4379,13 @@ class T_local_erfc(unittest.TestCase):
 
         # TODO: fix this problem
         if theano.config.floatX == "float32" and theano.config.mode in ["DebugMode", "DEBUG_MODE"]:
+            # 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 do not generate the same value. You can ignore
+            # this error. This happen in an intermediate step that don't show
+            # in the final result.
+
             # Showing this test error is a duplicate of the one in test_local_log_erfc. We hide it.
-            #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. This happen in an intermediate step that don't show in the final result.")
             pass
         else:
             assert all(numpy.isfinite(f(val)))

theano/tests/test_rop.py

@@ -20,7 +20,7 @@ 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
 
@@ -190,9 +190,8 @@ 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('Rop does not handle non-differentiable inputs '
+                           'correctly. Bug exposed by fixing Add.grad method.')
 
 
 class test_RopLop(RopLop_checker):