Merge pull request #238 from nouiz/fix_test

theano/sandbox/linalg/tests/test_linalg.py

@@ -281,29 +281,30 @@ def test_trace():
         ok = True
     assert ok
 
+
 def test_spectral_radius_bound():
-    tol = 10**(-6)
+    tol = 10 ** (-6)
     rng = numpy.random.RandomState(utt.fetch_seed())
     x = theano.tensor.matrix()
     radius_bound = spectral_radius_bound(x, 5)
     f = theano.function([x], radius_bound)
-    
-    shp = (3, 3)
+
+    shp = (3, 4)
     m = rng.rand(*shp).astype(config.floatX)
-    m = numpy.cov(m)
+    m = numpy.cov(m).astype(config.floatX)
     radius_bound_theano = f(m)
-    
+
     # test the approximation
     mm = m
     for i in range(5):
         mm = numpy.dot(mm, mm)
-    radius_bound_numpy = numpy.trace(mm)**(2**(-5))
+    radius_bound_numpy = numpy.trace(mm) ** (2 ** (-5))
     assert abs(radius_bound_numpy - radius_bound_theano) < tol
-    
-    # test the bound 
+
+    # test the bound
     eigen_val = numpy.linalg.eig(m)
     assert (eigen_val[0].max() - radius_bound_theano) < tol
-    
+
     # test type errors
     xx = theano.tensor.vector()
     ok = False
@@ -318,7 +319,7 @@ def test_spectral_radius_bound():
     except TypeError:
         ok = True
     assert ok
-    
+
     # test value error
     ok = False
     try:

theano/tensor/tests/test_basic.py

@@ -2816,7 +2816,7 @@ class T_Join_and_Split(unittest.TestCase):
     def test_roll(self):
 
         # Test simple 1D example
-        a = self.shared(numpy.array([1, 2, 3, 4, 5, 6]))
+        a = self.shared(numpy.array([1, 2, 3, 4, 5, 6], dtype=self.floatX))
         b = roll(a, 2)
         want = numpy.array([5, 6, 1, 2, 3, 4])
         out = theano.function([], b)()
@@ -2831,7 +2831,7 @@ class T_Join_and_Split(unittest.TestCase):
         assert (out == want).all()
 
         # Test 2D example - ensure that behavior matches numpy.roll behavior
-        a = self.shared(numpy.arange(21).reshape((3, 7)))
+        a = self.shared(numpy.arange(21).reshape((3, 7)).astype(self.floatX))
         b = roll(a, -2, 1)
 
         want = numpy.roll(a.get_value(borrow=True), -2, 1)