pep8

theano/scan_module/tests/test_scan.py

@@ -683,14 +683,13 @@ class T_Scan(unittest.TestCase):
         ny1[4] = (ny1[3] + ny1[1]) * numpy.dot(ny0[3], vWout)
         ny2[4] = numpy.dot(v_u1[4], vW_in1)
 
-
     def test_using_taps_sequence(self):
         # this test refers to a bug reported by Nicolas
         # Boulanger-Lewandowski June 6th
         x = theano.tensor.dvector()
         y, updates = theano.scan(lambda x: [x],
                                  sequences=dict(input=x, taps=[-1]),
-                                 outputs_info = [None])
+                                 outputs_info=[None])
         inp = numpy.arange(5).astype('float64')
         rval = theano.function([x], y, updates=updates)(inp)
         assert numpy.all(rval == inp[:-1])
@@ -940,11 +939,11 @@ class T_Scan(unittest.TestCase):
         vx1 = asarrayX(rng.uniform())
         x0 = theano.shared(vx0)
         x1 = theano.shared(vx1)
-        outputs, updates = theano.scan(lambda x,y: (x + asarrayX(1),
-                                                    y + asarrayX(1)),
+        outputs, updates = theano.scan(lambda x, y: (x + asarrayX(1),
+                                                     y + asarrayX(1)),
                                        [],
-                                       [x0,x1],
-                                       n_steps = 3)
+                                       [x0, x1],
+                                       n_steps=3)
         x0 = asarrayX(numpy.zeros((3,)))
         x0[0] = vx0
         x0 = theano.tensor.constant(x0)
@@ -2447,7 +2446,6 @@ class T_Scan(unittest.TestCase):
         v_eW = numpy.array(rng.uniform(size=(5, 5)) - .5, dtype=floatX)
         v_eh0 = numpy.array(rng.uniform(size=(5,)) - .5, dtype=floatX)
 
-
         def rnn_fn(_u, _y, _W):
 
             srng = theano.tensor.shared_randomstreams.RandomStreams(seed)