Fix pep8 and simplify the code as we don't support one option.

theano/gof/opt.py

@@ -1385,8 +1385,14 @@ class LocalOptGroup(LocalOptimizer):
 
 
 class GraphToGPULocalOptGroup(LocalOptGroup):
-    """
-    This is the equivalent of LocalOptGroup for GraphToGPU
+    """This is the equivalent of LocalOptGroup for GraphToGPU.
+
+    The main different is the function signature of the local
+    optimizer that use the GraphToGPU signature and not the normal
+    LocalOptimizer signature.
+
+    apply_all_opts=True is not supported
+
     """
     def __init__(self, *optimizers, **kwargs):
         super(GraphToGPULocalOptGroup, self).__init__(*optimizers, **kwargs)
@@ -1396,34 +1402,21 @@ class GraphToGPULocalOptGroup(LocalOptGroup):
         if len(self.opts) == 0:
             return
         fgraph = outputs[0].fgraph
-        repl = None
-        while True:
-            opts = self.track_map[type(op)] + self.track_map[op] + self.track_map[None]
-            new_repl = None
-            for opt in opts:
-                opt_start = time.time()
-                new_repl = opt.transform(op, context_name, inputs, outputs)
-                opt_finish = time.time()
-                if self.profile:
-                    self.time_opts[opt] += opt_start - opt_finish
-                    self.process_count[opt] += 1
-                if not new_repl:
-                    continue
-                else:
-                    if self.profile:
-                        self.node_created[opt] += len(graph.ops(fgraph.variables, new_repl))
-                        self.applied_true[opt] += 1
-                    break  # break from the for loop over optimization.
-            if not new_repl:  # No optimization applied in the last iteration
-                return repl
-            # only 1 iteration or we are at the start of the graph.
-            if not self.apply_all_opts or not new_repl[0].owner:
-                return new_repl
-            if len(new_repl) > 1:
-                s = set([v.owner for v in new_repl])
-                assert len(s) == 1
-            repl = new_repl
-            node = repl[0].owner
+        opts = self.track_map[type(op)] + self.track_map[op] + self.track_map[None]
+        for opt in opts:
+            opt_start = time.time()
+            new_repl = opt.transform(op, context_name, inputs, outputs)
+            opt_finish = time.time()
+            if self.profile:
+                self.time_opts[opt] += opt_start - opt_finish
+                self.process_count[opt] += 1
+            if not new_repl:
+                continue
+            if self.profile:
+                self.node_created[opt] += len(graph.ops(fgraph.variables, new_repl))
+                self.applied_true[opt] += 1
+
+            return new_repl
 
 
 class OpSub(LocalOptimizer):