pep8 for scan_op

theano/scan_module/scan_op.py

@@ -433,7 +433,7 @@ class Scan(PureOp):
                     aux_txt += str(k) + ','
                 aux_txt += '},%s,%s}'
         else:
-            aux_txt +='{%s,%s}'
+            aux_txt += '{%s,%s}'
         aux_txt = aux_txt % (name, gpu_str, str(self.name))
         return aux_txt
 
@@ -1164,16 +1164,15 @@ class Scan(PureOp):
     ### GRAD FUNCTION
     def grad(self, args, g_outs):
 
-
         # This discards information about whether incoming gradients are 0
         # or disconnected from the cost
         # TODO: upgrade scan op to report disconnection correctly
-        def strip_disconnected( g ):
+        def strip_disconnected(g):
             if isinstance(g.type, DisconnectedType):
                 return None
             return g
 
-        g_outs = [ strip_disconnected(g) for g in g_outs ]
+        g_outs = [strip_disconnected(g) for g in g_outs]
 
         # 1. forward pass - get the outputs after applying scan
         scan_outputs = self(*args)
@@ -1538,12 +1537,12 @@ class Scan(PureOp):
         gradients += [x[::-1] for x in outputs[:end]]
         start = len(gradients)
         gradients += [
-                grad_undefined(self, x + start, args[x+start],
+                grad_undefined(self, x + start, args[x + start],
                     'Shared Variable with update')
                 for x in xrange(self.n_shared_outs)]
         start = len(gradients)
         gradients += [
-                grad_undefined(self, x + start, args[x+start],
+                grad_undefined(self, x + start, args[x + start],
                     'Dimension of memory buffer for output')
                 for x in xrange(self.n_nit_sot)]
         begin = end
@@ -1569,7 +1568,8 @@ class Scan(PureOp):
             rop_self_outputs = self_outputs
         if self.info['n_shared_outs'] > 0:
             rop_self_outputs = rop_self_outputs[:-self.info['n_shared_outs']]
-        rop_outs = tensor.Rop(rop_self_outputs, rop_of_inputs, inner_eval_points)
+        rop_outs = tensor.Rop(rop_self_outputs, rop_of_inputs,
+             inner_eval_points)
         if type(rop_outs) not in (list, tuple):
             rop_outs = [rop_outs]
         # Step 2. Figure out what corresponds to what in the scan
@@ -1760,7 +1760,7 @@ class Scan(PureOp):
         b = e + self.n_nit_sot
         e = e + self.n_nit_sot * 2
         final_outs += outputs[b:e]
-        final_outs += [None]*self.n_shared_outs
+        final_outs += [None] * self.n_shared_outs
 
         return final_outs