merge

theano/tests/test_tutorial.py

@@ -5,6 +5,7 @@ from theano import function
 import numpy
 from numpy import array
 
+from numpy.testing import dec
 from theano import config
 from theano.tests  import unittest_tools as utt
 
@@ -162,8 +163,14 @@ class T_extending(unittest.TestCase):
                             fn = lambda x, y: x / y)
 
 
+    @dec.knownfailureif(isinstance(theano.compile.mode.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")
     def test_extending_2(self):
-
+        '''
+         This test fails in DebugMode for the same reasons the test in
+         tensor/tests/test_basic.py:T_scalarfromtensor.test0
+         fails on debug mode ( as much as I could tell - Razvan )
+        '''
         from theano import gof
 
         class Double(gof.Type):
@@ -699,6 +706,8 @@ class T_loading_and_saving(unittest.TestCase):
         my_obj =  theano.function([theano.In(x, borrow=True)]
                                   , theano.Out(y, borrow=True))
 
+        mode_instance = theano.compile.mode.get_mode(None)
+        if not isinstance(mode_instance, theano.compile.debugmode.DebugMode):
             f = file('obj.save', 'wb')
             cPickle.dump(my_obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
             f.close()
@@ -754,8 +763,8 @@ class T_using_gpu(unittest.TestCase):
         import numpy
         import time
 
-        vlen = 10 * 30 * 768  # 10 x #cores x # threads per core
-        iters = 1000
+        vlen = 10 * 30 * 70  # 10 x #cores x # threads per core
+        iters = 10
 
         rng = numpy.random.RandomState(22)
         x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
@@ -782,8 +791,8 @@ class T_using_gpu(unittest.TestCase):
             import numpy
             import time
 
-            vlen = 10 * 30 * 768  # 10 x #cores x # threads per core
-            iters = 1000
+            vlen = 10 * 30 * 70  # 10 x #cores x # threads per core
+            iters = 10
 
             rng = numpy.random.RandomState(22)
             x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
@@ -811,8 +820,8 @@ class T_using_gpu(unittest.TestCase):
             import numpy
             import time
 
-            vlen = 10 * 30 * 768  # 10 x #cores x # threads per core
-            iters = 1000
+            vlen = 10 * 30 * 70  # 10 x #cores x # threads per core
+            iters = 10
 
             rng = numpy.random.RandomState(22)
             x = shared(numpy.asarray(rng.rand(vlen), config.floatX))