Modify style (#12465)

paddle/fluid/inference/analysis/argument.h

@@ -23,6 +23,7 @@
 
 #pragma once
 
+#include <string>
 #include "paddle/fluid/framework/program_desc.h"
 #include "paddle/fluid/inference/analysis/data_flow_graph.h"
 

paddle/fluid/inference/analysis/data_flow_graph.h

@@ -176,7 +176,7 @@ struct GraphTraits<DataFlowGraph> {
 // sub-graph is the inputs nodes and output nodes that doesn't inside the
 // sub-graph.
 std::pair<std::vector<Node *>, std::vector<Node *>>
-ExtractInputAndOutputOfSubGraph(std::vector<Node *> &graph);
+ExtractInputAndOutputOfSubGraph(std::vector<Node *> &graph);  // NOLINT
 
 }  // namespace analysis
 }  // namespace inference

paddle/fluid/inference/analysis/model_store_pass.cc

@@ -12,11 +12,13 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/fluid/inference/analysis/model_store_pass.h"
 #include <stdio.h>
 #include <stdlib.h>
+#include <string>
+
 #include "paddle/fluid/inference/analysis/analyzer.h"
 #include "paddle/fluid/inference/analysis/argument.h"
+#include "paddle/fluid/inference/analysis/model_store_pass.h"
 
 namespace paddle {
 namespace inference {

paddle/fluid/inference/analysis/model_store_pass.h

@@ -17,6 +17,8 @@
  * model in the disk, and that model can be reloaded for prediction.
  */
 
+#pragma once
+#include <string>
 #include "paddle/fluid/inference/analysis/pass.h"
 
 namespace paddle {

paddle/fluid/inference/api/demo_ci/vis_demo.cc

@@ -20,8 +20,8 @@ limitations under the License. */
 #include <glog/logging.h>  // use glog instead of PADDLE_ENFORCE to avoid importing other paddle header files.
 #include <fstream>
 #include <iostream>
+#include "paddle/fluid/inference/demo_ci/utils.h"
 #include "paddle/fluid/platform/enforce.h"
-#include "utils.h"
 
 #ifdef PADDLE_WITH_CUDA
 DECLARE_double(fraction_of_gpu_memory_to_use);

paddle/fluid/inference/api/paddle_inference_api.h

@@ -44,7 +44,7 @@ class PaddleBuf {
   PaddleBuf(void* data, size_t length)
       : data_(data), length_(length), memory_owned_{false} {}
   // Own memory.
-  PaddleBuf(size_t length)
+  explicit PaddleBuf(size_t length)
       : data_(new char[length]), length_(length), memory_owned_(true) {}
   // Resize to `length` bytes.
   void Resize(size_t length);

paddle/fluid/inference/tensorrt/convert/fc_op.cc

@@ -38,7 +38,7 @@ void Reorder2(nvinfer1::DimsHW shape, const T* idata, nvinfer1::DimsHW istrides,
 }
 // indata c * k
 // Reorder the data layout from CK to KC.
-void ReorderCKtoKC(TensorRTEngine::Weight& iweights,
+void ReorderCKtoKC(TensorRTEngine::Weight& iweights,  // NOLINT
                    TensorRTEngine::Weight* oweights) {
   int c = iweights.dims[0];
   int k = iweights.dims[1];

paddle/fluid/operators/conv_mkldnn_op.cc

@@ -55,7 +55,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   std::shared_ptr<mkldnn::memory> AcquireSrcMemoryFromWeightsPrimitive(
       const std::shared_ptr<mkldnn::memory> user_memory_p,
-      std::vector<mkldnn::primitive>& pipeline) {
+      std::vector<mkldnn::primitive>& pipeline) {  // NOLINT
     auto src_pd = conv_bwd_weights_pd_->src_primitive_desc();
     auto user_pd = user_memory_p->get_primitive_desc();
     return this->AcquireMemory(src_pd, user_pd, user_memory_p,
@@ -64,7 +64,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   std::shared_ptr<mkldnn::memory> AcquireDiffDstMemoryFromWeightsPrimitive(
       const std::shared_ptr<mkldnn::memory> user_memory_p,
-      std::vector<mkldnn::primitive>& pipeline) {
+      std::vector<mkldnn::primitive>& pipeline) {  // NOLINT
     auto diff_dst_pd = conv_bwd_weights_pd_->diff_dst_primitive_desc();
     auto user_pd = user_memory_p->get_primitive_desc();
     return this->AcquireMemory(diff_dst_pd, user_pd, user_memory_p,
@@ -80,7 +80,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   std::shared_ptr<mkldnn::memory> AcquireDiffDstMemoryFromDataPrimitive(
       const std::shared_ptr<mkldnn::memory> user_memory_p,
-      std::vector<mkldnn::primitive>& pipeline) {
+      std::vector<mkldnn::primitive>& pipeline) {  // NOLINT
     auto diff_dst_pd = conv_bwd_data_pd_->diff_dst_primitive_desc();
     auto user_pd = user_memory_p->get_primitive_desc();
     return this->AcquireMemory(diff_dst_pd, user_pd, user_memory_p,
@@ -89,7 +89,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   std::shared_ptr<mkldnn::memory> AcquireWeightsMemoryFromDataPrimitive(
       const std::shared_ptr<mkldnn::memory> user_weights_memory_p,
-      std::vector<mkldnn::primitive>& pipeline) {
+      std::vector<mkldnn::primitive>& pipeline) {  // NOLINT
     auto weights_pd = conv_bwd_data_pd_->weights_primitive_desc();
     auto user_pd = user_weights_memory_p->get_primitive_desc();
     return this->AcquireMemory(weights_pd, user_pd, user_weights_memory_p,
@@ -109,7 +109,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   std::shared_ptr<mkldnn::memory> AcquireSrcMemoryFromPrimitive(
       const std::shared_ptr<mkldnn::memory> user_memory_p,
-      std::vector<mkldnn::primitive>& pipeline) {
+      std::vector<mkldnn::primitive>& pipeline) {  // NOLINT
     auto src_pd = conv_pd_->src_primitive_desc();
     auto user_pd = user_memory_p->get_primitive_desc();
     return this->AcquireMemory(src_pd, user_pd, user_memory_p, "@src_mem_p",
@@ -118,7 +118,7 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   std::shared_ptr<mkldnn::memory> AcquireWeightsMemoryFromPrimitive(
       const std::shared_ptr<mkldnn::memory> user_weights_memory_p,
-      std::vector<mkldnn::primitive>& pipeline) {
+      std::vector<mkldnn::primitive>& pipeline) {  // NOLINT
     auto user_weights_pd = user_weights_memory_p->get_primitive_desc();
     auto weights_pd = conv_pd_->weights_primitive_desc();
     return this->AcquireMemory(weights_pd, user_weights_pd,
@@ -197,12 +197,12 @@ class ConvMKLDNNHandler : public platform::MKLDNNHandler {
 
   // Generate keys for storing/retriving primitives for this operator
   // TODO(jczaja): Make hashing function more optimial
-  static std::string GetHash(memory::dims& input_dims,
-                             memory::dims& weights_dims,
-                             std::vector<int>& strides,
-                             std::vector<int>& paddings,
-                             std::vector<int>& dilations, int groups,
-                             const std::string& suffix) {
+  static std::string GetHash(memory::dims& input_dims,     // NOLINT
+                             memory::dims& weights_dims,   // NOLINT
+                             std::vector<int>& strides,    // NOLINT
+                             std::vector<int>& paddings,   // NOLINT
+                             std::vector<int>& dilations,  // NOLINT
+                             int groups, const std::string& suffix) {
     return dims2str(input_dims) + dims2str(weights_dims) + dims2str(strides) +
            dims2str(paddings) + dims2str(dilations) + std::to_string(groups) +
            suffix;