Tag a bunch of slow tests according to the linux timings.

theano/sandbox/test_rng_mrg.py

@@ -16,6 +16,7 @@ if cuda_available:
 import unittest
 from theano.tests import unittest_tools as utt
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 
 #TODO: test gpu
 # Done in test_consistency_GPU_{serial,parallel}
@@ -445,6 +446,7 @@ def test_uniform():
                   allow_01=True, inputs=input)
 
 
+@attr('slow')
 def test_binomial():
 #TODO: test size=None, ndim=X
 #TODO: test size=X, ndim!=X.ndim
@@ -532,6 +534,7 @@ def test_binomial():
                       inputs=input, target_avg=mean, mean_rtol=rtol)
 
 
+@attr('slow')
 def test_normal0():
 
     steps = 50

theano/scan_module/tests/test_scan.py

@@ -1620,6 +1620,7 @@ class T_Scan(unittest.TestCase):
                              analytic_grad[max_err_pos],
                              num_grad.gx[max_err_pos]))
 
+    @attr('slow')
     def test_grad_multiple_outs_taps_backwards(self):
         l = 5
         rng = numpy.random.RandomState(utt.fetch_seed())
@@ -2601,6 +2602,7 @@ class T_Scan(unittest.TestCase):
         f2 = theano.function([], gx)
         utt.assert_allclose(f2(), numpy.ones((10,)))
 
+    @attr('slow')
     def test_rop2(self):
         seed = utt.fetch_seed()
         rng = numpy.random.RandomState(seed)

theano/sparse/sandbox/test_sp.py

 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 import sys
 import time
 import unittest
@@ -128,6 +129,7 @@ class TestSP(unittest.TestCase):
         #profmode.print_summary()
 
 
+    @attr('slow')
     def test_sparse(self):
 
 #        print '\n\n*************************************************'

theano/tensor/nnet/tests/test_conv.py

 import time
 
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 import numpy
 
 import theano
@@ -246,6 +247,7 @@ class TestConv2D(utt.InferShapeTester):
                       N_image_shape=(2, 3, 3, 3),  N_filter_shape=(5, 3, 2, 2),
                       should_raise=True)
 
+    @attr('slow')
     def test_subsample(self):
         """
         Tests convolution where subsampling != (1,1)
@@ -282,6 +284,7 @@ class TestConv2D(utt.InferShapeTester):
                           (3, 2, 8, 8), (4, 3, 5, 5),
                           'valid')
 
+    @attr('slow')
     def test_invalid_input_shape(self):
         """
         Tests that when the shape gived at build time is not the same as

theano/tensor/nnet/tests/test_conv3d.py

@@ -12,6 +12,7 @@ import theano.sparse
 if theano.sparse.enable_sparse:
     from scipy import sparse
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 
 floatX = theano.config.floatX
 
@@ -222,6 +223,7 @@ class TestConv3D(utt.InferShapeTester):
         self.randomize()
         self.check_c_against_python(self.V.get_value(borrow=True).shape[1:4])
 
+    @attr('slow')
     def test_c_against_mat_mul(self):
         # Use a filter of the same size as the image, so the convolution is
         # just a dense matrix multiply.

theano/tensor/tests/test_blas.py

@@ -864,6 +864,7 @@ def test_dot22():
             cmp((0, 0), (0, 0))
 
 
+@attr('slow')
 def test_dot22scalar():
     ## including does not seem to work for 'local_dot_to_dot22' and
     ## 'local_dot22_to_dot22scalar'

theano/tensor/tests/test_elemwise.py

@@ -5,6 +5,7 @@ import unittest
 
 import numpy
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 
 import theano
 from theano.gof.python25 import all, any
@@ -454,6 +455,7 @@ class test_CAReduce(unittest_tools.InferShapeTester):
             self.with_linker(gof.PerformLinker(), scalar.and_, dtype=dtype,
                              test_nan=True, tensor_op=tensor.all)
 
+    @attr('slow')
     def test_c(self):
         if not theano.config.cxx:
             raise SkipTest("G++ not available, so we need to skip this test.")
@@ -624,6 +626,7 @@ class test_Prod(unittest.TestCase):
         fn_a0 = theano.function([x], pwz_a0, mode=self.mode)
         assert numpy.allclose(fn_a0(x_val), [1, 10, 162])
 
+    @attr('slow')
     def test_other_grad_tests(self):
         x = theano.tensor.dmatrix()
         x_val1 = numpy.array([[1, 2, 3], [0, 5, 6], [0, 0, 9]],
@@ -753,6 +756,7 @@ class T_sum_dtype(unittest.TestCase):
             data = data.astype(dtype)
             f(data)
 
+    @attr('slow')
     def test_sum_custom_dtype(self):
         """
         Test the ability to provide your own output dtype for a sum.
@@ -853,6 +857,7 @@ class T_mean_dtype(unittest.TestCase):
             data = data.astype(dtype)
             f(data)
 
+    @attr('slow')
     def test_mean_custom_dtype(self):
         """
         Test the ability to provide your own output dtype for a mean.
@@ -960,6 +965,7 @@ class T_prod_dtype(unittest.TestCase):
             data = data.astype(dtype)
             f(data)
 
+    @attr('slow')
     def test_prod_custom_dtype(self):
         """
         Test the ability to provide your own output dtype for a prod.
@@ -991,6 +997,7 @@ class T_prod_dtype(unittest.TestCase):
                 tensor.grad(prod_var.sum(), x,
                             disconnected_inputs='ignore')
 
+    @attr('slow')
     def test_prod_custom_acc_dtype(self):
         """
         Test the ability to provide your own acc_dtype for a prod.
@@ -1079,6 +1086,7 @@ class T_prod_without_zeros_dtype(unittest.TestCase):
             data = data.astype(dtype)
             f(data)
 
+    @attr('slow')
     def test_prod_without_zeros_custom_dtype(self):
         """
         Test ability to provide your own output dtype for a ProdWithoutZeros().
@@ -1102,6 +1110,7 @@ class T_prod_without_zeros_dtype(unittest.TestCase):
                 data = data.astype(input_dtype)
                 f(data)
 
+    @attr('slow')
     def test_prod_without_zeros_custom_acc_dtype(self):
         """
         Test ability to provide your own acc_dtype for a ProdWithoutZeros().

theano/tensor/tests/test_keepdims.py

+from nose.plugins.attrib import attr
+
 import numpy
 from theano import tensor, function
 
+import unittest
 
-class TestKeepDims:
+# this tests other ops to ensure they keep the dimensions of their
+# inputs correctly
+@attr('slow')
+class TestKeepDims(unittest.TestCase):
 
     def makeKeepDims_local(self, x, y, axis):
         x = tensor.as_tensor_variable(x)
@@ -95,7 +101,3 @@ class TestKeepDims:
 
             assert numpy.allclose(keep_param(a), keep_synth(a))
             assert keep_param(a).shape == keep_synth(a).shape
-
-
-if __name__ == '__main__':
-    TestKeepDims().test_keepdims()

theano/tensor/tests/test_naacl09.py

@@ -12,6 +12,8 @@ import sys
 from theano.tests import unittest_tools
 from numpy.testing.noseclasses import KnownFailureTest
 
+from nose.plugins.attrib import attr
+
 
 def cross_entropy(target, output, axis=1):
     """
@@ -557,6 +559,7 @@ def create_realistic(window_size=3,  # 7,
     return model
 
 
+@attr('slow')
 def test_naacl_model(iters_per_unsup=3, iters_per_sup=3,
         optimizer=None, realistic=False):
     #print "BUILDING MODEL"
@@ -643,13 +646,7 @@ def jtest_main():
     test_naacl_model(optimizer, 10, 10, realistic=False)
 
 
-def real_main():
-    test_naacl_model()
-
-
 def profile_main():
-    # This is the main function for profiling
-    # We've renamed our original main() above to real_main()
     import cProfile
     import pstats
     from theano.compat.six import StringIO
@@ -664,5 +661,4 @@ def profile_main():
     # stats.print_callers()
 
 if __name__ == '__main__':
-    #real_main()
     profile_main()

theano/tensor/tests/test_opt.py

@@ -408,6 +408,7 @@ class test_canonize(unittest.TestCase):
             assert(len(f.maker.fgraph.toposort()) == nb_elemwise)
             assert(out_dtype == out.dtype)
 
+    @attr('slow')
     def test_multiple_case(self):
         """ test those case take from the comment in Canonizer
         x / x -> 1
@@ -1135,6 +1136,7 @@ class test_fusion(unittest.TestCase):
             'local_elemwise_fusion', 'canonicalize')
         self.do(mode, shared, shp)
 
+    @attr('slow')
     def test_elemwise_fusion_4d(self):
         shp = (3, 3, 3, 3)
         mode = copy.copy(compile.mode.get_default_mode())
@@ -1159,6 +1161,7 @@ class test_fusion(unittest.TestCase):
 
         self.do(mode, cuda.float32_shared_constructor, shp, gpu=True)
 
+    @attr('slow')
     def test_gpu_fusion_Xd(self):
         #we need the optimisation enabled, debug do this.
         if theano.config.mode == "FAST_COMPILE":
@@ -1859,6 +1862,7 @@ class test_local_subtensor_merge(unittest.TestCase):
                     self.assertRaises(IndexError, f, x_val, idx)
                     self.assertRaises(IndexError, g, x_val, idx)
 
+    @attr('slow')
     def test_const2(self):
         # var[::-1][const] -> var[-1]
         x = tensor.matrix('x')
@@ -3156,6 +3160,7 @@ class T_local_switch_sink(unittest.TestCase):
                         resm[idx])).sum() == self.resm[idx].size
                 idx += 1
 
+    @attr('slow')
     def test_local_div_switch_sink(self):
         c = T.dscalar()
         idx = 0

theano/tensor/tests/test_subtensor.py

@@ -4,6 +4,7 @@ import sys
 import unittest
 
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 import numpy
 
 import theano
@@ -499,6 +500,7 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         self.assertTrue(isinstance(topo_[0].op, self.adv_sub1))
         self.assertTrue(numpy.allclose(f([0]), ones[0] * 5))
 
+    @attr('slow')
     def test_shape_i_const(self):
         # Each axis is treated independently by shape_i/shape operators
 
@@ -756,6 +758,7 @@ class T_subtensor(unittest.TestCase, utt.TestOptimizationMixin):
         except TypeError:
             pass
 
+    @attr('slow')
     def test_grad_list(self):
         data = rand(4)
         data = numpy.asarray(data, dtype=self.dtype)