tag some tests as slow

theano/sparse/sandbox/test_sp.py

@@ -24,6 +24,7 @@ from theano.sparse.tests.test_basic import sparse_random_inputs
 
 
 class TestSP(unittest.TestCase):
+    @attr('slow')
     def test_convolution(self):
 #        print '\n\n*************************************************'
 #        print '           TEST CONVOLUTION'
@@ -218,6 +219,7 @@ class TestSP(unittest.TestCase):
 #            print 'Theano processing time: ', ttot
         # profmode.print_summary()
 
+    @attr('slow')
     def test_multilayer_sparse(self):
         # fixed parameters
         bsize = 10     # batch size

theano/sparse/tests/test_basic.py

 import time
 import unittest
 
+from nose.plugins.attrib import attr
 from nose.plugins.skip import SkipTest
 import numpy
 try:
@@ -2347,6 +2348,7 @@ class CastTester(utt.InferShapeTester):
                     utt.assert_allclose(expected, t_cls)
                     utt.assert_allclose(expected, t_prop)
 
+    @attr('slow')
     def test_infer_shape(self):
         for format in sparse.sparse_formats:
             for i_dtype in sparse.all_dtypes:

theano/tensor/tests/test_elemwise.py

@@ -521,6 +521,7 @@ class test_CAReduce(unittest_tools.InferShapeTester):
             self.with_linker(gof.CLinker(), scalar.and_, dtype=dtype)
             self.with_linker(gof.CLinker(), scalar.xor, dtype=dtype)
 
+    @attr('slow')
     def test_c_nan(self):
         if not theano.config.cxx:
             raise SkipTest("G++ not available, so we need to skip this test.")

theano/tensor/tests/test_extra_ops.py

+from nose.plugins.attrib import attr
 import numpy as np
 import numpy
 import unittest
@@ -191,6 +192,7 @@ class TestBinCountOp(utt.InferShapeTester):
                 assert (np.bincount(a, minlength=23) == f3(a)).all()
                 assert (np.bincount(a, minlength=5) == f4(a)).all()
 
+    @attr('slow')
     def test_infer_shape(self):
         for dtype in tensor.discrete_dtypes:
             # uint64 always fails
@@ -432,6 +434,7 @@ class TestRepeatOp(utt.InferShapeTester):
                         assert np.allclose(np.repeat(a, r, axis=axis),
                                            f(a, r))
 
+    @attr('slow')
     def test_infer_shape(self):
         for ndim in range(4):
             x = T.TensorType(config.floatX, [False] * ndim)()