walltime.py has been modified in order to respect the flake8 style.

theano/sandbox/cuda/tests/walltime.py

 from __future__ import absolute_import, print_function, division
 from __future__ import print_function
-import sys, time
+import sys
+import time
 from six import iteritems
 from theano.compile.pfunc import pfunc
 from theano import tensor
@@ -35,35 +36,47 @@ def showtimes(times):
 
 def cmp_sigmoids(shape):
     def numpy_sigmoid(input):
-        rval = 1.0 / (1.0 + numpy.exp(-input))
-    sinput = tensor.Tensor(dtype='float32', broadcastable=(0,)*len(shape))()
-    shared_input = tcn.shared_constructor(numpy.random.rand(*shape), 'shared_input')
-    times = compare_fns(
-            dict( numpy=numpy_sigmoid
-                , theano_cpu=pfunc([sinput], 1.0 / (1.0 + tensor.exp(-sinput)))
-                , theano_gpu_onboard=pfunc([sinput], [], updates=[(shared_input, 1.0 / (1.0 + tensor.exp(-shared_input)))])
-                ),
-            input=shared_input.value)
+        1.0 / (1.0 + numpy.exp(-input))
+    sinput = tensor.Tensor(
+        dtype='float32', broadcastable=(0,) * len(shape))()
+    shared_input = tcn.shared_constructor(
+        numpy.random.rand(*shape),
+        'shared_input')
+    times = compare_fns(dict(
+        numpy=numpy_sigmoid,
+        theano_cpu=pfunc([sinput], 1.0 / (1.0 + tensor.exp(-sinput))),
+        theano_gpu_onboard=pfunc(
+            [sinput],
+            [],
+            updates=[(
+                shared_input,
+                1.0 / (1.0 + tensor.exp(-shared_input)))])),
+        input=shared_input.value)
     showtimes(times)
 
 
 def cmp_sigmoids_T(shape):
     def numpy_sigmoid(input):
-        rval = 1.0 / (1.0 + numpy.exp(-input.T))
-    sinput = tensor.Tensor(dtype='float32', broadcastable=(0,)*len(shape))()
-    shared_input = tcn.shared_constructor(numpy.random.rand(*shape), 'shared_input')
-    times = compare_fns(
-            dict( numpy=numpy_sigmoid
-                , theano_cpu=pfunc([sinput], 1.0 / (1.0 + tensor.exp(-sinput.T)))
-                , theano_gpu_onboard=pfunc([sinput], [], updates=[(shared_input, 1.0 / (1.0 +
-                    tensor.exp(-shared_input.T)))])
-                ),
-            input=shared_input.value)
+        1.0 / (1.0 + numpy.exp(-input.T))
+    sinput = tensor.Tensor(
+        dtype='float32', broadcastable=(0,) * len(shape))()
+    shared_input = tcn.shared_constructor(
+        numpy.random.rand(*shape),
+        'shared_input')
+    times = compare_fns(dict(
+        numpy=numpy_sigmoid,
+        theano_cpu=pfunc([sinput], 1.0 / (1.0 + tensor.exp(-sinput.T))),
+        theano_gpu_onboard=pfunc(
+            [sinput],
+            [],
+            updates=[(
+                shared_input,
+                1.0 / (1.0 + tensor.exp(-shared_input.T)))])),
+        input=shared_input.value)
     showtimes(times)
 
 if __name__ == '__main__':
     eval(sys.argv[1])
     # cmp_sigmoids((640, 64*64)) # looks great in profiler
-    #cmp_sigmoids((173, 74*49))
-    #cmp_sigmoids_T((173, 74*49))
-
+    # cmp_sigmoids((173, 74*49))
+    # cmp_sigmoids_T((173, 74*49))