Fix CPPLint issues in framework/data_transform framework/prune.cc (#10178)

* Fic CPPLint issues with data_transform

* Fic CPPLint issues with prune.cc

paddle/fluid/framework/data_transform.cc

@@ -63,16 +63,16 @@ void DataTransform(const OpKernelType& expected_kernel_type,
 }
 
 void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,
-                            Variable& out_var) {
+                            Variable* out_var) {
   if (in_var.IsType<LoDTensor>()) {
     auto& in_lod_tensor = in_var.Get<LoDTensor>();
-    auto* tran_lod_tensor = out_var.GetMutable<LoDTensor>();
+    auto* tran_lod_tensor = out_var->GetMutable<LoDTensor>();
     tran_lod_tensor->set_lod(in_lod_tensor.lod());
     tran_lod_tensor->set_layout(in_lod_tensor.layout());
     tran_lod_tensor->ShareDataWith(tensor);
   } else if (in_var.IsType<SelectedRows>()) {
     auto& in_selected_rows = in_var.Get<SelectedRows>();
-    auto* trans_selected_rows = out_var.GetMutable<SelectedRows>();
+    auto* trans_selected_rows = out_var->GetMutable<SelectedRows>();
     trans_selected_rows->set_height(in_selected_rows.height());
     trans_selected_rows->set_rows(in_selected_rows.rows());
     trans_selected_rows->mutable_value()->ShareDataWith(tensor);

paddle/fluid/framework/data_transform.h

@@ -35,7 +35,7 @@ void DataTransform(const OpKernelType& expected_kernel_type,
                    const Tensor& input_tensor, Tensor* out);
 
 void CopyVariableWithTensor(const Variable& in_var, const Tensor& tensor,
-                            Variable& out_var);
+                            Variable* out_var);
 
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/operator.cc

@@ -554,7 +554,7 @@ void OperatorWithKernel::RunImpl(const Scope& scope,
             std::shared_ptr<Tensor> out(new Tensor);
             DataTransform(expected_kernel_key, kernel_type_for_var, *tensor_in,
                           out.get());
-            CopyVariableWithTensor(*var, *(out.get()), *trans_var);
+            CopyVariableWithTensor(*var, *(out.get()), trans_var);
           }
         }
       }

paddle/fluid/framework/prune.cc

@@ -14,19 +14,19 @@ limitations under the License. */
 
 #include "paddle/fluid/framework/prune.h"
 
+#include <glog/logging.h>
+
 #include <algorithm>
 #include <set>
 #include <string>
 #include <unordered_map>
 #include <vector>
 
-#include <glog/logging.h>
-
 namespace paddle {
 namespace framework {
 
-const std::string kFeedOpType = "feed";
-const std::string kFetchOpType = "fetch";
+const char kFeedOpType[] = "feed";
+const char kFetchOpType[] = "fetch";
 
 bool HasDependentVar(const proto::OpDesc& op_desc,
                      const std::set<std::string>& dependent_vars) {
@@ -68,7 +68,7 @@ bool HasSubBlock(const proto::OpDesc& op_desc) {
 // the child block to help pruning
 void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
                 int block_id, int parent_block_id,
-                std::set<std::string>& dependent_vars) {
+                std::set<std::string>* dependent_vars) {
   auto& block = input.blocks(block_id);
   auto& ops = block.ops();
 
@@ -90,11 +90,11 @@ void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
   std::vector<bool> should_run;
   for (auto op_iter = ops.rbegin(); op_iter != ops.rend(); ++op_iter) {
     auto& op_desc = *op_iter;
-    if (IsTarget(op_desc) || HasDependentVar(op_desc, dependent_vars)) {
+    if (IsTarget(op_desc) || HasDependentVar(op_desc, *dependent_vars)) {
       // insert its input to the dependency graph
       for (auto& var : op_desc.inputs()) {
         for (auto& argu : var.arguments()) {
-          dependent_vars.insert(argu);
+          dependent_vars->insert(argu);
         }
       }
       should_run.push_back(true);
@@ -138,7 +138,7 @@ void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
         // GetSubBlockIndex(*op) is the idx of the sub_block in the input desc
         // output_block_id is the idx of the current block in the output desc
         prune_impl(input, output, GetSubBlockIndex(*op), output_block_id,
-                   sub_block_dependent_vars);
+                   &sub_block_dependent_vars);
       }
     }
   }
@@ -181,7 +181,7 @@ void prune_impl(const proto::ProgramDesc& input, proto::ProgramDesc* output,
 void Prune(const proto::ProgramDesc& input, proto::ProgramDesc* output) {
   std::set<std::string> dependent_vars;
   output->clear_blocks();
-  prune_impl(input, output, 0, -1, dependent_vars);
+  prune_impl(input, output, 0, -1, &dependent_vars);
 }
 
 void inference_optimize_impl(proto::ProgramDesc* input, int block_id) {