Fix pep8 error.

theano/sandbox/cuda/tests/test_rng_curand.py

@@ -3,18 +3,17 @@ import theano
 from theano.sandbox.cuda.rng_curand import CURAND_RandomStreams
 from theano.sandbox.rng_mrg import MRG_RandomStreams
 
-if theano.config.mode=='FAST_COMPILE':
+if theano.config.mode == 'FAST_COMPILE':
     mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpu')
-    mode_without_gpu = theano.compile.mode.get_mode('FAST_RUN').excluding('gpu')
 else:
     mode_with_gpu = theano.compile.mode.get_default_mode().including('gpu')
-    mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpu')
+
 
 def test_uniform_basic():
     rng = CURAND_RandomStreams(234)
 
-    u0 = rng.uniform((10,10))
-    u1 = rng.uniform((10,10))
+    u0 = rng.uniform((10, 10))
+    u1 = rng.uniform((10, 10))
 
     f0 = theano.function([], u0, mode=mode_with_gpu)
     f1 = theano.function([], u1, mode=mode_with_gpu)
@@ -30,7 +29,7 @@ def test_uniform_basic():
     assert numpy.all(v0list[0] != v1list[0])
 
     for v in v0list:
-        assert v.shape == (10,10)
+        assert v.shape == (10, 10)
         assert v.min() >= 0
         assert v.max() <= 1
         assert v.min() < v.max()
@@ -40,8 +39,8 @@ def test_uniform_basic():
 def test_normal_basic():
     rng = CURAND_RandomStreams(234)
 
-    u0 = rng.normal((10,10))
-    u1 = rng.normal((10,10))
+    u0 = rng.normal((10, 10))
+    u1 = rng.normal((10, 10))
 
     f0 = theano.function([], u0, mode=mode_with_gpu)
     f1 = theano.function([], u1, mode=mode_with_gpu)
@@ -57,7 +56,7 @@ def test_normal_basic():
     assert numpy.all(v0list[0] != v1list[0])
 
     for v in v0list:
-        assert v.shape == (10,10)
+        assert v.shape == (10, 10)
         assert v.min() < v.max()
         assert -.5 <= v.mean() <= .5
 
@@ -71,17 +70,17 @@ def compare_speed():
     mrg = MRG_RandomStreams()
     crn = CURAND_RandomStreams(234)
 
-    N=1000*100
+    N = 1000 * 100
 
-    dest = theano.shared(numpy.zeros(N,dtype=theano.config.floatX))
+    dest = theano.shared(numpy.zeros(N, dtype=theano.config.floatX))
 
-    mrg_u = theano.function([], [], updates={dest:mrg.uniform((N,))},
+    mrg_u = theano.function([], [], updates={dest: mrg.uniform((N,))},
             profile='mrg uniform')
-    crn_u = theano.function([], [], updates={dest:crn.uniform((N,))},
+    crn_u = theano.function([], [], updates={dest: crn.uniform((N,))},
             profile='crn uniform')
-    mrg_n = theano.function([], [], updates={dest:mrg.normal((N,))},
+    mrg_n = theano.function([], [], updates={dest: mrg.normal((N,))},
             profile='mrg normal')
-    crn_n = theano.function([], [], updates={dest:crn.normal((N,))},
+    crn_n = theano.function([], [], updates={dest: crn.normal((N,))},
             profile='crn normal')
 
     for f in mrg_u, crn_u, mrg_n, crn_n:
@@ -93,5 +92,5 @@ def compare_speed():
     for i in range(100):
         for f in mrg_u, crn_u, mrg_n, crn_n:
             # don't time the first call, it has some startup cost
-            f.fn.time_thunks = (i>0)
+            f.fn.time_thunks = (i > 0)
             f()