make tests less verbose.

theano/gof/tests/test_lazy.py

@@ -117,17 +117,17 @@ def test_ifelse():
                          mode=Mode(linker=linker, optimizer='fast_run'))
 
             try:
-                print "case 1"
+                #print "case 1"
                 f(1, 'a', 'b')
                 assert False
             except NotImplementedOp.E:
                 pass
-            print "... passed"
+            #print "... passed"
 
-            print "case 2"
-            print f(0, 'a', 'b')
+            #print "case 2"
+            #print f(0, 'a', 'b')
             assert f(0, 'a', 'b') == 'b'
-            print "... passed"
+            #print "... passed"
 
 
 def more_complex_test():

theano/gof/tests/test_opt.py

@@ -360,7 +360,7 @@ class TestEquilibrium(object):
         x, y, z = map(MyVariable, 'xyz')
         e = op3(op4(x, y))
         g = Env([x, y, z], [e])
-        print g
+        #print g
         opt = EquilibriumOptimizer(
             [PatternSub((op1, 'x', 'y'), (op2, 'x', 'y')),
              PatternSub((op4, 'x', 'y'), (op1, 'x', 'y')),
@@ -368,14 +368,14 @@ class TestEquilibrium(object):
              ],
             max_use_ratio = 10)
         opt.optimize(g)
-        print g
+        #print g
         assert str(g) == '[Op2(x, y)]'
 
     def test_2(self):
         x, y, z = map(MyVariable, 'xyz')
         e = op1(op1(op3(x, y)))
         g = Env([x, y, z], [e])
-        print g
+        #print g
         opt = EquilibriumOptimizer(
             [PatternSub((op1, (op2, 'x', 'y')), (op4, 'x', 'y')),
              PatternSub((op3, 'x', 'y'), (op4, 'x', 'y')),
@@ -391,7 +391,7 @@ class TestEquilibrium(object):
         x, y, z = map(MyVariable, 'xyz')
         e = op3(op4(x, y))
         g = Env([x, y, z], [e])
-        print 'before', g
+        #print 'before', g
         # display pesky warnings along with stdout
         # also silence logger for 'theano.gof.opt'
         _logger = logging.getLogger('theano.gof.opt')
@@ -407,5 +407,5 @@ class TestEquilibrium(object):
             opt.optimize(g)
         finally:
             _logger.setLevel(oldlevel)
-        print 'after', g
+        #print 'after', g
         assert str(g) == '[Op1(x, y)]'

theano/sandbox/cuda/tests/test_conv_cuda_ndarray.py

@@ -726,7 +726,7 @@ class TestConv2DGPU(unittest.TestCase):
             featshp_logical = (featshp[0], featshp[1], featshp[2] * stride,
                                featshp[3] * stride)
             kshp_rotated = (kshp[1], kshp[0], kshp[2], kshp[3])
-            print featshp, kshp_rotated, featshp_logical[1:], kshp[2:]
+            #print featshp, kshp_rotated, featshp_logical[1:], kshp[2:]
             image_estimate = tensor.nnet.conv2d(a, kernel_rotated,
                                                 border_mode='full',
                                                 image_shape=featshp,
@@ -735,7 +735,7 @@ class TestConv2DGPU(unittest.TestCase):
                                                 kshp_logical=kshp[2:])
 
             func = theano.function([a, A], image_estimate, mode=theano_mode)
-            theano.printing.debugprint(func,)
+            #theano.printing.debugprint(func,)
             assert any([isinstance(node.op, theano.sandbox.cuda.blas.GpuConv)
                         for node in func.maker.fgraph.toposort()])