merge

theano/tensor/tests/test_randomstreams.py

@@ -150,18 +150,18 @@ class T_RandomStreams(unittest.TestCase):
     def test_ndim(self):
         """Test that the behaviour of 'ndim' optional parameter"""
         # 'ndim' is an optional integer parameter, specifying the length
-        # of the 'shape', placed as first argument.
+        # of the 'shape', passed as a keyword argument.
 
         # ndim not specified, OK
         m1 = Module()
-        m1.random = RandomStreams(234)
+        m1.random = RandomStreams(utt.fetch_seed())
         m1.fn = Method([], m1.random.uniform((2,2)))
         made1 = m1.make()
         made1.random.initialize()
 
         # ndim specified, consistent with shape, OK
         m2 = Module()
-        m2.random = RandomStreams(234)
+        m2.random = RandomStreams(utt.fetch_seed())
         m2.fn = Method([], m2.random.uniform((2,2), ndim=2))
         made2 = m2.make()
         made2.random.initialize()
@@ -172,7 +172,7 @@ class T_RandomStreams(unittest.TestCase):
 
         # ndim specified, inconsistent with shape, should raise ValueError
         m3 = Module()
-        m3.random = RandomStreams(234)
+        m3.random = RandomStreams(utt.fetch_seed())
         self.assertRaises(ValueError, m3.random.uniform, (2,2), ndim=1)
 
     def test_uniform(self):
@@ -283,7 +283,7 @@ class T_RandomStreams(unittest.TestCase):
         assert numpy.all(fn_val1 == numpy_val1)
 
     def test_shuffle_row_elements(self):
-        """Ensure RandomStreams.shuffle_row_elements generates right results"""
+        """Test that RandomStreams.shuffle_row_elements generates the right results"""
         # Check over two calls to see if the random state is correctly updated.
         # On matrices, for each row, the elements of that row should be
         # shuffled.
@@ -475,7 +475,6 @@ class T_RandomStreams(unittest.TestCase):
 
         low_val = [.1, .2, .3]
         high_val = [1.1, 2.2, 3.3]
-
         seed_gen = numpy.random.RandomState(utt.fetch_seed())
         numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))
 
@@ -512,7 +511,6 @@ class T_RandomStreams(unittest.TestCase):
 
         n_val = [1, 2, 3]
         prob_val = [.1, .2, .3]
-
         seed_gen = numpy.random.RandomState(utt.fetch_seed())
         numpy_rng = numpy.random.RandomState(int(seed_gen.randint(2**30)))