change format

test/fpga/test_rfcn_api.cpp

@@ -12,8 +12,8 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License. */
 
-#include <iostream>
 #include <fstream>
+#include <iostream>
 #include "../../src/io/paddle_inference_api.h"
 
 using namespace paddle_mobile;
@@ -67,7 +67,7 @@ int main() {
   readStream(g_image, reinterpret_cast<char *>(img));
 
   std::cout << "after initializing data" << std::endl;
-/*
+  /*
     predictor->FeedData({img_info, img});
     predictor->Predict_From_To(0, -1);
     std::cout << " Finishing predicting " << std::endl;
@@ -89,18 +89,18 @@ int main() {
         std:: cout << ((float*)(v[2]))[num * 4 + i] << std::endl;
       }
     }
-*/
+  */
 
   struct PaddleTensor t_img_info, t_img;
   t_img_info.dtype = FLOAT32;
   t_img_info.layout = LAYOUT_HWC;
-  t_img_info.shape = std::vector<int>({1,3});
+  t_img_info.shape = std::vector<int>({1, 3});
   t_img_info.name = "Image information";
   t_img_info.data.Reset(img_info, 3 * sizeof(float));
 
   t_img.dtype = FLOAT32;
   t_img.layout = LAYOUT_HWC;
-  t_img.shape = std::vector<int>({1,768, 1536, 3});
+  t_img.shape = std::vector<int>({1, 768, 1536, 3});
   t_img.name = "Image information";
   t_img.data.Reset(img, img_length * sizeof(float));
   predictor->FeedPaddleTensors({t_img_info, t_img});
@@ -112,23 +112,23 @@ int main() {
 
   std::vector<PaddleTensor> v(3, PaddleTensor());
   predictor->FetchPaddleTensors(&v);
-	auto post_nms = v[0].data.length()/sizeof(float)/8;
-  for (int num = 0; num < post_nms; num ++){
-    for (int i = 0; i < 8; i ++){
-      auto p = reinterpret_cast<float*>(v[0].data.data());
-      std:: cout << p[num * 8 + i] << std::endl;
+  auto post_nms = v[0].data.length() / sizeof(float) / 8;
+  for (int num = 0; num < post_nms; num++) {
+    for (int i = 0; i < 8; i++) {
+      auto p = reinterpret_cast<float *>(v[0].data.data());
+      std::cout << p[num * 8 + i] << std::endl;
     }
   }
-  for (int num = 0; num < post_nms; num ++){
-    for (int i = 0; i < 8; i ++){
-      auto p = reinterpret_cast<float*>(v[1].data.data());
-      std:: cout << p[num * 8 + i] << std::endl;
+  for (int num = 0; num < post_nms; num++) {
+    for (int i = 0; i < 8; i++) {
+      auto p = reinterpret_cast<float *>(v[1].data.data());
+      std::cout << p[num * 8 + i] << std::endl;
     }
   }
-  for (int num = 0; num < post_nms; num ++){
-    for (int i = 0; i < 4; i ++){
-      auto p = reinterpret_cast<float*>(v[2].data.data());
-      std:: cout << p[num * 4 + i] << std::endl;
+  for (int num = 0; num < post_nms; num++) {
+    for (int i = 0; i < 4; i++) {
+      auto p = reinterpret_cast<float *>(v[2].data.data());
+      std::cout << p[num * 4 + i] << std::endl;
     }
   }
   return 0;