Merge pull request #1723 from abergeron/tag_slow

theano/compile/profiling.py

@@ -885,9 +885,9 @@ if 0: # old code still to be ported from ProfileMode
         print 'Theano fct call %.3fs %.1f%%' % (total_fct_time,
                                                 total_fct_time / total_time *
                                                 100)
-        print '   Theano Op time (included in fct call, Time spent running thunks) %.3fs %.1f%%(of total) %.1f%%(of fct call)' % (local_time,
-                                                                                                                                  local_time / total_time * 100,
-                                                                                                                                  time_pr_in_fct)
+        print ('   Theano Op time (included in fct call, Time spent '
+               'running thunks) %.3fs %.1f%%(of total) %.1f%%(of fct call)' %
+               (local_time, local_time / total_time * 100, time_pr_in_fct))
         print 'Other time since import %.3fs %.1f%%'%(other_time,other_time/total_time*100)
         print '%i Theano fct call, %.3fs per call'%(total_fct_call, time_per_call)
 

theano/gof/tests/test_cc.py

@@ -2,6 +2,7 @@
 import unittest
 
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 
 import theano
 from theano.gof.link import PerformLinker
@@ -191,6 +192,7 @@ def test_clinker_straightforward():
     assert fn(2.0, 2.0, 2.0) == 2.0
 
 
+@attr('slow')
 def test_clinker_literal_inlining():
     if not theano.config.cxx:
         raise SkipTest("G++ not available, so we need to skip this test.")
@@ -206,6 +208,7 @@ def test_clinker_literal_inlining():
     assert "4.12345678" in code  # we expect the number to be inlined
 
 
+@attr('slow')
 def test_clinker_single_node():
     if not theano.config.cxx:
         raise SkipTest("G++ not available, so we need to skip this test.")
@@ -216,6 +219,7 @@ def test_clinker_single_node():
     assert fn(2.0, 7.0) == 9
 
 
+@attr('slow')
 def test_clinker_dups():
     if not theano.config.cxx:
         raise SkipTest("G++ not available, so we need to skip this test.")
@@ -228,18 +232,19 @@ def test_clinker_dups():
     # note: for now the behavior of fn(2.0, 7.0) is undefined
 
 
+@attr('slow')
 def test_clinker_not_used_inputs():
     if not theano.config.cxx:
         raise SkipTest("G++ not available, so we need to skip this test.")
-    # Testing that duplicate inputs are allowed.
+    # Testing that unused inputs are allowed.
     x, y, z = inputs()
     e = add(x, y)
     lnk = CLinker().accept(Env([x, y, z], [e]))
     fn = lnk.make_function()
     assert fn(2.0, 1.5, 1.0) == 3.5
-    # note: for now the behavior of fn(2.0, 7.0) is undefined
 
 
+@attr('slow')
 def test_clinker_dups_inner():
     if not theano.config.cxx:
         raise SkipTest("G++ not available, so we need to skip this test.")
@@ -255,6 +260,7 @@ def test_clinker_dups_inner():
 # Test OpWiseCLinker #
 ######################
 
+# slow on linux, but near sole test and very central
 def test_opwiseclinker_straightforward():
     x, y, z = inputs()
     e = add(mul(add(x, y), div(x, y)), bad_sub(bad_sub(x, y), z))
@@ -267,6 +273,7 @@ def test_opwiseclinker_straightforward():
         assert fn(2.0, 2.0, 2.0) == -6
 
 
+@attr('slow')
 def test_opwiseclinker_constant():
     x, y, z = inputs()
     x = Constant(tdouble, 7.2, name='x')
@@ -300,6 +307,7 @@ def test_duallinker_straightforward():
     assert res == 15.3
 
 
+@attr('slow')
 def test_duallinker_mismatch():
     if not theano.config.cxx:
         raise SkipTest("G++ not available, so we need to skip this test.")

theano/sandbox/linalg/tests/test_linalg.py

@@ -34,6 +34,7 @@ from theano.sandbox.linalg.ops import (cholesky,
                                        )
 from theano.sandbox.linalg import eig, eigh
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 
 
 def check_lower_triangular(pd, ch_f):
@@ -93,6 +94,7 @@ def test_cholesky_grad():
                                    rng, eps=eps))
 
 
+@attr('slow')
 def test_cholesky_and_cholesky_grad_shape():
     if not imported_scipy:
         raise SkipTest("Scipy needed for the Cholesky op.")
@@ -395,6 +397,7 @@ class test_diag(unittest.TestCase):
         x = rng.rand(5, 4).astype(self.floatX)
         tensor.verify_grad(extract_diag, [x], rng=rng)
 
+    @attr('slow')
     def test_extract_diag_empty(self):
         c = self.shared(numpy.array([[], []], self.floatX))
         f = theano.function([], extract_diag(c), mode=self.mode)

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

@@ -8,6 +8,7 @@ import unittest
 import cPickle
 import numpy
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 from numpy.testing import dec
 
 import theano
@@ -1525,6 +1526,7 @@ class T_Scan(unittest.TestCase):
                              analytic_grad[max_err_pos],
                              num_grad.gx[max_err_pos]))
 
+    @attr('slow')
     def test_grad_multiple_outs_taps(self):
         l = 5
         rng = numpy.random.RandomState(utt.fetch_seed())
@@ -1618,6 +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())
@@ -2599,6 +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)
@@ -3659,6 +3663,7 @@ class T_Scan(unittest.TestCase):
             inp = scan_node.op.outer_non_seqs(scan_node)
             assert len(inp) == 1
 
+    @attr('slow')
     def test_hessian_bug_grad_grad_two_scans(self):
         #Bug reported by Bitton Tenessi
 

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/sparse/tests/test_basic.py

@@ -1226,6 +1226,7 @@ class UsmmTests(unittest.TestCase):
         self.z = numpy.asarray(self.rng.uniform(-1, 1, z_size),
                                dtype=theano.config.floatX)
 
+    # this is slow, but it's the only test for the op.
     def test(self):
         def mat(format, name, dtype):
             if format == 'dense':
@@ -2069,6 +2070,7 @@ class CastTester(utt.InferShapeTester):
     def setUp(self):
         super(CastTester, self).setUp()
 
+    # slow but only test
     def test_cast(self):
         for format in sparse.sparse_formats:
             for i_dtype in sparse.all_dtypes:

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_basic.py

@@ -13,6 +13,7 @@ import __builtin__
 builtin_min = __builtin__.min
 
 from nose.plugins.skip import SkipTest
+from nose.plugins.attrib import attr
 import numpy
 from numpy.testing import dec, assert_array_equal, assert_allclose
 from numpy.testing.noseclasses import KnownFailureTest
@@ -1996,6 +1997,7 @@ class TestAlloc(unittest.TestCase):
                                   numpy.zeros(shp))
 
 
+# This is slow for the ('int8', 3) version.
 def test_eye():
     def check(dtype, N, M_=None, k=0):
         # Theano does not accept None as a tensor.
@@ -4050,6 +4052,7 @@ class t_dot(unittest.TestCase):
         utt.verify_grad(dot, [rand(2, 3, 4), rand(4, 5)])
         utt.verify_grad(dot, [rand(2, 3, 4), rand(3, 4, 5)])
 
+    @attr('slow')
     def test_broadcastable_patterns(self):
 
         #

theano/tensor/tests/test_blas.py

@@ -6,6 +6,8 @@ from numpy import (arange, array, common_type, complex64, complex128, float32,
                   float64, newaxis, shape, transpose, zeros)
 from numpy.testing import assert_array_almost_equal
 
+from nose.plugins.attrib import attr
+
 import theano
 import theano.tensor as T
 from theano import tensor, Param, shared, config
@@ -855,6 +857,7 @@ 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'
@@ -1179,6 +1182,7 @@ class TestGemv(TestCase, unittest_tools.TestOptimizationMixin):
         assert numpy.allclose(v2.get_value(),
                 numpy.dot(m.get_value(), v1.get_value()) + v2_orig)
 
+    @attr('slow')
     def test_gemv1(self):
         self.t_gemv1((3, 2))
         self.t_gemv1((0, 2))

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
@@ -470,6 +471,7 @@ 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.")
@@ -629,6 +631,7 @@ 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]],
@@ -760,6 +763,7 @@ 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.
@@ -860,6 +864,7 @@ 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.
@@ -967,6 +972,7 @@ 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.
@@ -998,6 +1004,7 @@ 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.
@@ -1086,6 +1093,7 @@ 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().
@@ -1109,6 +1117,7 @@ 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_extra_ops.py

@@ -407,13 +407,6 @@ class TestBartlett(utt.InferShapeTester):
         self._compile_and_check([x], [self.op(x)], [1], self.op_class)
 
 
-if __name__ == "__main__":
-    t = TestBartlett('setUp')
-    t.setUp()
-    t.test_perform()
-    t.test_infer_shape()
-
-
 class TestFillDiagonal(utt.InferShapeTester):
 
     rng = numpy.random.RandomState(43)
@@ -470,11 +463,3 @@ class TestFillDiagonal(utt.InferShapeTester):
                                  numpy.random.rand()],
                                 self.op_class,
                                 warn=False)
-
-if __name__ == "__main__":
-    utt.unittest.main()
-    t = TestFillDiagonal('setUp')
-    t.setUp()
-    t.test_perform()
-    t.test_gradient()
-    t.test_infer_shape()

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
+class TestKeepDims(unittest.TestCase):
 
     def makeKeepDims_local(self, x, y, axis):
         x = tensor.as_tensor_variable(x)
@@ -28,6 +33,7 @@ class TestKeepDims:
 
         return tensor.DimShuffle(y.type.broadcastable, new_dims)(y)
 
+    @attr('slow')
     def test_keepdims(self):
 
         x = tensor.dtensor3()
@@ -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_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)