Fixed norm test to include outdated numpy version.

theano/sandbox/linalg/tests/test_linalg.py

@@ -4,6 +4,7 @@ import numpy
 import numpy.linalg
 from numpy.testing import assert_array_almost_equal
 from numpy.testing import dec, assert_array_equal, assert_allclose
+from nose.plugins.skip import SkipTest
 
 import theano
 from theano import tensor, function
@@ -636,30 +637,54 @@ class Matrix_power():
         self.assertRaises(ValueError, f, a)
 
 class T_NormTests(unittest.TestCase):
-    def test_wrong_type_of_ord_for_vector(self):
-        self.assertRaises(ValueError, norm, [2,1],'fro',0)
-    def test_wrong_type_of_ord_for_vector_in_matrix(self):
-        self.assertRaises(ValueError, norm, [[2,1],[3,4]],'fro',0)	
-    def test_wrong_type_of_ord_for_vector_in_tensor(self):
-        self.assertRaises(ValueError, norm, [[[2,1],[3,4]],[[6,5],[7,8]]],'fro',0)
-    def test_wrong_type_of_ord_for_matrix(self):
-        self.assertRaises(ValueError, norm, [[2,1],[3,4]],0,None)
-    def test_wrong_type_of_ord_for_matrix_in_tensor(self):
-        self.assertRaises(ValueError, norm, [[[2,1],[3,4]],[[6,5],[7,8]]],0,None)
-    def test_non_tensorial_input(self):
-        self.assertRaises(ValueError, norm, 3, None, None)
-    def test_no_enough_dimensions(self):
-        self.assertRaises(ValueError, norm, [[2,1],[3,4]], None, 3)
-    def test_numpy_compare(self):
-        rng = numpy.random.RandomState(utt.fetch_seed())
-        A = tensor.matrix("A", dtype=theano.config.floatX)
-        Q = norm(A, None, None)
-        fn = function([A], [Q])
-        a = rng.rand(4, 4).astype(theano.config.floatX)
-
-        n_n = numpy.linalg.norm(a, None, None)
-        t_n = fn(a)
-        assert _allclose(n_n, t_n)
+    try:
+        def test_wrong_type_of_ord_for_vector(self):
+            self.assertRaises(ValueError, norm, [2,1],'fro',0)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_wrong_type_of_ord_for_vector_in_matrix(self):
+            self.assertRaises(ValueError, norm, [[2,1],[3,4]],'fro',0)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_wrong_type_of_ord_for_vector_in_tensor(self):
+            self.assertRaises(ValueError, norm, [[[2,1],[3,4]],[[6,5],[7,8]]],'fro',0)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_wrong_type_of_ord_for_matrix(self):
+            self.assertRaises(ValueError, norm, [[2,1],[3,4]],0,None)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_wrong_type_of_ord_for_matrix_in_tensor(self):
+            self.assertRaises(ValueError, norm, [[[2,1],[3,4]],[[6,5],[7,8]]],0,None)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_non_tensorial_input(self):
+            self.assertRaises(ValueError, norm, 3, None, None)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_no_enough_dimensions(self):
+            self.assertRaises(ValueError, norm, [[2,1],[3,4]], None, 3)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
+    try:
+        def test_numpy_compare(self):
+            rng = numpy.random.RandomState(utt.fetch_seed())
+            A = tensor.matrix("A", dtype=theano.config.floatX)
+            Q = norm(A, None, None)
+            fn = function([A], [Q])
+            a = rng.rand(4, 4).astype(theano.config.floatX)
+
+            n_n = numpy.linalg.norm(a, None, None)
+            t_n = fn(a)
+            assert _allclose(n_n, t_n)
+    except TypeError:
+        raise SkipTest('Your numpy version is outdated.')
 
 class T_lstsq(unittest.TestCase):
     def test_correct_solution(self):