further maxint-related corrections

theano/tensor/raw_random.py

@@ -212,7 +212,7 @@ class RandomKit(SymbolicInputKit):
         return out
 
     def distribute(self, value, indices, containers):
-        rg = partial(numpy.random.RandomState(value).randint, 2**32)
+        rg = partial(numpy.random.RandomState(value).randint, 2**30)
         elems = deque(zip(indices, containers))
         i = 0
         while elems:
@@ -270,7 +270,7 @@ class RModule(compile.Module):
                     # and a list of corresponding gof.Container instances. In this
                     # situation it will reseed all the rngs using the containers
                     # associated to them.
-                    c._rkit.kit.distribute(seedgen.random_integers(2**31),
+                    c._rkit.kit.distribute(seedgen.random_integers(2**30),
                                            xrange(len(inst2._rkit)), inst2._rkit)
         else:
-            self._rkit.kit.distribute(seedgen.random_integers(2**31), xrange(len(inst._rkit)), inst._rkit)
+            self._rkit.kit.distribute(seedgen.random_integers(2**30), xrange(len(inst._rkit)), inst._rkit)

theano/tensor/tests/test_naacl09.py

@@ -484,7 +484,7 @@ def test_naacl_model(optimizer='fast_run'):
             m.pretraining_update(*inputs)
         s0, s1 = [str(i) for i in m.pretraining_update(*inputs)]
         print s0, s1
-    if s0 + ' ' + s1 != '0.315775007436 0.132479386981':
+    if s0 + ' ' + s1 != '0.402187608584 0.0744508017774':
         raise ValueError('pretraining update values do not match')
     print 'FINETUNING GRAPH'
     print 'SUPERVISED PHASE COSTS (%s)'%optimizer
@@ -493,7 +493,7 @@ def test_naacl_model(optimizer='fast_run'):
             m.finetuning_update(*(inputs + [targets]))
         s0 = str(m.finetuning_update(*(inputs + [targets])))
         print s0
-    if s0 != '15.8609933666':
+    if s0 != '15.6512776369':
         raise ValueError('finetuning values do not match')
 
 if __name__ == '__main__':

theano/tensor/tests/test_raw_random.py

@@ -50,15 +50,15 @@ def test_B():
     #print m.f(N.ones(5))
     #print m.f(N.ones(5))
     #print m.f(N.ones(5))
-    rvals = ["0.0655889727823 0.566937256035 0.486897708861 0.939594224804 0.731948448071",
-        "0.407174827663 0.450046718267 0.454825370073 0.874814293401 0.828759935744",
-        "0.573194634066 0.746015418896 0.864696705461 0.8405810785 0.540268740918",
-        "0.924477905238 0.96687901023 0.306490321744 0.654349923901 0.789402591813",
-        "0.513182053208 0.0426565286449 0.0723651478047 0.454308519009 0.86151064181"]
-
+    rvals = ["0.74802375876 0.872308123517 0.294830748897 0.803123780003 0.6321109955",
+        "0.00168744844365 0.278638315678 0.725436793755 0.7788480779 0.629885140994",
+        "0.545561221664 0.0992011009108 0.847112593242 0.188015424144 0.158046201298",
+        "0.054382248842 0.563459168529 0.192757276954 0.360455221883 0.174805216702",
+        "0.961942907777 0.49657319422 0.0316111492826 0.0915054717012 0.195877184515"]
 
     for i in xrange(5):
         s = " ".join([str(n) for n in m.f(N.ones(5))])
+        print s
         assert s == rvals[i]