make test pass on computer with nvcc but not cuda enabled card.

theano/sandbox/test_rng_mrg.py

@@ -345,7 +345,7 @@ def test_uniform():
         #print 'random?[-1,-10:]\n', out[-1,-10:]
         basictest(f, steps, sample_size, prefix='mrg  cpu', inputs=input)
 
-        if mode!='FAST_COMPILE':
+        if mode!='FAST_COMPILE' and cuda_available:
             print ''
             print 'ON GPU with size=(%s):'%str(size)
             R = MRG_RandomStreams(234, use_cuda=True)
@@ -403,7 +403,7 @@ def test_binomial():
             print 'random?[-1,-10:]\n', out[-1,-10:]
             basictest(f, steps, sample_size, prefix='mrg  cpu', inputs=input, allow_01=True, target_avg = mean)
 
-            if mode!='FAST_COMPILE':
+            if mode!='FAST_COMPILE' and cuda_available:
                 print ''
                 print 'ON GPU with size=(%s) and mean(%d):'%(str(size),mean)
                 R = MRG_RandomStreams(234, use_cuda=True)
@@ -450,7 +450,7 @@ def test_normal0():
     # now with odd number of samples
     sample_size = (sample_size[0],sample_size[1]-1)
 
-    if mode!='FAST_COMPILE':
+    if mode!='FAST_COMPILE' and cuda_available:
         print ''
         print 'ON GPU:'
         R = MRG_RandomStreams(234, use_cuda=True)
@@ -465,7 +465,7 @@ def test_normal0():
         print 'random?[:10]\n', numpy.asarray(f())[0,0:10]
         print '----'
         sys.stdout.flush()
-        basictest(f, steps, sample_size_odd, target_avg=-5.0, target_std=2.0, prefix='gpu mrg ', allow_01=True)
+        basictest(f, steps, sample_size, target_avg=-5.0, target_std=2.0, prefix='gpu mrg ', allow_01=True)
         
 
     print ''