Polish code style

paddle/fluid/framework/op_desc.cc

@@ -209,7 +209,7 @@ void OpDesc::SetAttr(const std::string &name, const Attribute &v) {
   if (attr_type == proto::AttrType::INTS &&
       boost::get<std::vector<int>>(v).size() == 0u) {
     // Find current attr via attr name and set the correct attribute value
-    const proto::OpProto::Attr& attr = GetProtoAttr(name);
+    const proto::OpProto::Attr &attr = GetProtoAttr(name);
     switch (attr.type()) {
       case proto::AttrType::BOOLEANS: {
         VLOG(11) << "SetAttr: " << Type() << ", " << name
@@ -275,8 +275,8 @@ Attribute OpDesc::GetAttr(const std::string &name) const {
   return it->second;
 }
 
-const proto::OpProto::Attr& OpDesc::GetProtoAttr(const std::string &name) {
-  proto::OpProto& proto = OpInfoMap::Instance().Get(Type()).Proto();
+const proto::OpProto::Attr &OpDesc::GetProtoAttr(const std::string &name) {
+  proto::OpProto &proto = OpInfoMap::Instance().Get(Type()).Proto();
   for (int i = 0; i != proto.attrs_size(); ++i) {
     const proto::OpProto::Attr &attr = proto.attrs(i);
     if (attr.name() == name) {

paddle/fluid/framework/op_desc.h

@@ -81,7 +81,7 @@ class OpDesc {
 
   Attribute GetAttr(const std::string &name) const;
 
-  const proto::OpProto::Attr& GetProtoAttr(const std::string &name) const;
+  const proto::OpProto::Attr &GetProtoAttr(const std::string &name) const;
 
   Attribute GetNullableAttr(const std::string &name) const;
 

python/paddle/fluid/backward.py

@@ -364,8 +364,7 @@ def _append_backward_ops_(block,
 
         # Getting op's corresponding grad_op
         grad_op_desc, op_grad_to_var = core.get_grad_op_desc(
-            op.desc,
-            cpt.to_text(no_grad_dict[block.idx]), grad_sub_block_list)
+            op.desc, cpt.to_text(no_grad_dict[block.idx]), grad_sub_block_list)
 
         grad_op_descs.extend(grad_op_desc)
         grad_to_var.update(op_grad_to_var)

python/paddle/fluid/parallel_executor.py

@@ -159,8 +159,7 @@ class ParallelExecutor(object):
                 for p in main.global_block().iter_parameters()
                 if not p.stop_gradient
             ]),
-            set(cpt.to_text(var)
-                for var in self.persistable_vars), main.desc,
+            set(cpt.to_text(var) for var in self.persistable_vars), main.desc,
             cpt.to_text(loss_name)
             if loss_name else six.u(''), scope, local_scopes, exec_strategy,
             build_strategy, num_trainers, trainer_id)
@@ -274,8 +273,7 @@ class ParallelExecutor(object):
             self.executor.feed_tensors_into_local_scopes(res)
 
         fetch_var_name = '@FETCHED_VAR_NAME@'
-        self.executor.run(
-            cpt.to_text(fetch_list), cpt.to_text(fetch_var_name))
+        self.executor.run(cpt.to_text(fetch_list), cpt.to_text(fetch_var_name))
         arr = self.scope.find_var(fetch_var_name).get_lod_tensor_array()
 
         if self.is_dist:

python/paddle/fluid/transpiler/memory_optimization_transpiler.py

@@ -259,9 +259,9 @@ class ControlFlowGraph(object):
                         # Rename the var to the cache var already with
                         # memory allocated in order to reuse the memory.
                         _rename_arg_(self._ops, x, cache_var, begin_idx=i)
-                        self._program.block(block_desc.id).var(
-                            cpt.to_text(x)).desc = self._find_var(
-                                block_desc, cache_var, is_forward)
+                        self._program.block(block_desc.id).var(cpt.to_text(
+                            x)).desc = self._find_var(block_desc, cache_var,
+                                                      is_forward)
                         self._update_graph(x, cache_var, begin_idx=i)
                         break