Flake8 fixes for new file.

theano/sandbox/gpuarray/dnn.py

@@ -2,7 +2,7 @@ import os
 import numpy
 
 import theano
-from theano import Apply, gof, tensor, config, Variable
+from theano import Apply, tensor, config, Variable
 from theano.scalar import as_scalar, constant
 from theano.gradient import DisconnectedType, grad_not_implemented
 from theano.gof import Optimizer, local_optimizer, COp
@@ -485,8 +485,8 @@ class GpuDnnConv(DnnBase, COp):
 
         return (
             b, nb,
-            (h + 2*padh - kh)//sh + 1,
-            (w + 2*padw - kw)//sw + 1
+            (h + 2 * padh - kh) // sh + 1,
+            (w + 2 * padw - kw) // sw + 1
         )
 
     def infer_shape(self, node, shape):
@@ -858,8 +858,8 @@ class GpuDnnPool(DnnBase):
         return [(
             shape[0][0],
             shape[0][1],
-            (shape[0][2] + 2*padh - kh)//sh + 1,
-            (shape[0][3] + 2*padw - kw)//sw + 1
+            (shape[0][2] + 2 * padh - kh) // sh + 1,
+            (shape[0][3] + 2 * padw - kw) // sw + 1
         )]
 
     def c_support_code_struct(self, node, name):
@@ -976,8 +976,8 @@ if (err%(name)s != CUDNN_STATUS_SUCCESS) {
 """ % dict(out=out, desc=desc, fail=sub['fail'],
            name=name, set_in=set_in,
            set_out=set_out, input=inputs[0],
-           input_desc="input"+name,
-           output_desc="output"+name)
+           input_desc="input" + name,
+           output_desc="output" + name)
 
     def grad(self, inp, grads):
         img, desc = inp
@@ -1184,10 +1184,10 @@ if (err%(name)s != CUDNN_STATUS_SUCCESS) {
            fail=sub['fail'],
            name=name, set_in=set_in,
            set_out=set_out, input=inp, input_grad=inp_grad, output=out,
-           input_desc="input"+name,
-           input_grad_desc="input_grad"+name,
-           output_desc="output"+name,
-           output_grad_desc="output_grad"+name)
+           input_desc="input" + name,
+           input_grad_desc="input_grad" + name,
+           output_desc="output" + name,
+           output_grad_desc="output_grad" + name)
 
     def c_code_cache_version(self):
         return (5, version())
@@ -1725,8 +1725,8 @@ if True:
     def local_softmax_dnn_grad(node):
         if (isinstance(node.op, SoftmaxGrad) and
             ((node.inputs[0].owner and
-              isinstance(node.inputs[0].owner.op, HostFromGpu))
-             or (node.inputs[1].owner and
+              isinstance(node.inputs[0].owner.op, HostFromGpu)) or
+             (node.inputs[1].owner and
               isinstance(node.inputs[1].owner.op, HostFromGpu)))):
             if not dnn_available():
                 return