Make tests less verbose

theano/compile/tests/test_monitormode.py

 from __future__ import absolute_import, print_function, division
+import sys
+
 import numpy as np
+from six.moves import StringIO
 
 import theano
 
@@ -23,7 +26,12 @@ def test_detect_nan():
     f = theano.function([x], [theano.tensor.log(x) * x],
                         mode=theano.compile.MonitorMode(
                             post_func=detect_nan))
-    f(0)  # log(0) * 0 = -inf * 0 = NaN
+    try:
+        old_stdout = sys.stdout
+        sys.stdout = StringIO()
+        f(0)  # log(0) * 0 = -inf * 0 = NaN
+    finally:
+        sys.stdout = old_stdout
     assert nan_detected[0]
 
 
@@ -49,7 +57,12 @@ def test_optimizer():
                         mode=mode)
     # Test that the fusion wasn't done
     assert len(f.maker.fgraph.apply_nodes) == 2
-    f(0)  # log(0) * 0 = -inf * 0 = NaN
+    try:
+        old_stdout = sys.stdout
+        sys.stdout = StringIO()
+        f(0)  # log(0) * 0 = -inf * 0 = NaN
+    finally:
+        sys.stdout = old_stdout
 
     # Test that we still detect the nan
     assert nan_detected[0]
@@ -83,7 +96,12 @@ def test_not_inplace():
     # Test that the fusion wasn't done
     assert len(f.maker.fgraph.apply_nodes) == 5
     assert not f.maker.fgraph.toposort()[-1].op.destroy_map
-    f([0, 0])  # log(0) * 0 = -inf * 0 = NaN
+    try:
+        old_stdout = sys.stdout
+        sys.stdout = StringIO()
+        f([0, 0])  # log(0) * 0 = -inf * 0 = NaN
+    finally:
+        sys.stdout = old_stdout
 
     # Test that we still detect the nan
     assert nan_detected[0]

theano/gpuarray/tests/test_elemwise.py

@@ -59,7 +59,6 @@ def test_elemwise_pow():
             assert exp.dtype == dtype_exp
             output = base ** exp
             f = theano.function([base], output, mode=mode_with_gpu)
-            theano.printing.debugprint(f)
             # We don't transfer to the GPU when the output dtype is int*
             n = len([n for n in f.maker.fgraph.apply_nodes
                      if isinstance(n.op, GpuElemwise)])

theano/tensor/tests/test_basic.py

@@ -820,7 +820,7 @@ def test_maximum_minimum_grad():
     for op in [tensor.maximum, tensor.minimum]:
         o = op(x, y)
         g = theano.grad(o.sum(), [x, y])
-        theano.printing.debugprint(g)
+
         f = theano.function([x, y], g)
         assert np.allclose(f([1], [1]), [[1], [0]])
 
@@ -7789,7 +7789,7 @@ class TestSpecifyShape(unittest.TestCase):
         f(xval)
         xval = np.random.rand(3).astype(floatX)
         self.assertRaises(AssertionError, f, xval)
-        theano.printing.debugprint(f)
+
         assert isinstance([n for n in f.maker.fgraph.toposort()
                            if isinstance(n.op, SpecifyShape)][0].inputs[0].type,
                           self.input_type)

theano/tensor/tests/test_opt.py

@@ -1116,7 +1116,6 @@ class test_fusion(unittest.TestCase):
                  nb_elemwise, answer, out_dtype] in enumerate(cases):
             if isinstance(out_dtype, dict):
                 out_dtype = out_dtype[config.cast_policy]
-            print("new cases", id)
 
             if shared_fn is None:
                 f = compile.function(list(sym_inputs), g, mode=mode)
@@ -1139,6 +1138,7 @@ class test_fusion(unittest.TestCase):
                 atol = 1e-6
             if not np.allclose(out, answer * nb_repeat, atol=atol):
                 fail1.append(id)
+                print("cases", id)
                 print(val_inputs)
                 print(out)
                 print(answer * nb_repeat)
@@ -1163,7 +1163,8 @@ class test_fusion(unittest.TestCase):
                 fail4.append((id, out_dtype, out.dtype))
 
         failed = len(fail1 + fail2 + fail3 + fail4)
-        print("Executed", len(cases), "cases", "failed", failed)
+        if failed > 0:
+            print("Executed", len(cases), "cases", "failed", failed)
         if failed > 0:
             raise Exception("Failed %d cases" % failed, fail1,
                             fail2, fail3, fail4)