fix coding style

yolov5/calibrator.cpp

@@ -7,32 +7,28 @@
 #include "utils.h"
 
 Int8EntropyCalibrator2::Int8EntropyCalibrator2(int batchsize, int input_w, int input_h, const char* img_dir, const char* calib_table_name, const char* input_blob_name, bool read_cache)
-    : batchsize_(batchsize)
-    , input_w_(input_w)
-    , input_h_(input_h)
-    , img_idx_(0)
-    , img_dir_(img_dir)
-    , calib_table_name_(calib_table_name)
-    , input_blob_name_(input_blob_name)
-    , read_cache_(read_cache)
-{
+    : batchsize_(batchsize),
+      input_w_(input_w),
+      input_h_(input_h),
+      img_idx_(0),
+      img_dir_(img_dir),
+      calib_table_name_(calib_table_name),
+      input_blob_name_(input_blob_name),
+      read_cache_(read_cache) {
     input_count_ = 3 * input_w * input_h * batchsize;
     CUDA_CHECK(cudaMalloc(&device_input_, input_count_ * sizeof(float)));
     read_files_in_dir(img_dir, img_files_);
 }
 
-Int8EntropyCalibrator2::~Int8EntropyCalibrator2()
-{
+Int8EntropyCalibrator2::~Int8EntropyCalibrator2() {
     CUDA_CHECK(cudaFree(device_input_));
 }
 
-int Int8EntropyCalibrator2::getBatchSize() const TRT_NOEXCEPT
-{
+int Int8EntropyCalibrator2::getBatchSize() const TRT_NOEXCEPT {
     return batchsize_;
 }
 
-bool Int8EntropyCalibrator2::getBatch(void* bindings[], const char* names[], int nbBindings) TRT_NOEXCEPT
-{
+bool Int8EntropyCalibrator2::getBatch(void* bindings[], const char* names[], int nbBindings) TRT_NOEXCEPT {
     if (img_idx_ + batchsize_ > (int)img_files_.size()) {
         return false;
     }
@@ -41,7 +37,7 @@ bool Int8EntropyCalibrator2::getBatch(void* bindings[], const char* names[], int
     for (int i = img_idx_; i < img_idx_ + batchsize_; i++) {
         std::cout << img_files_[i] << "  " << i << std::endl;
         cv::Mat temp = cv::imread(img_dir_ + img_files_[i]);
-        if (temp.empty()){
+        if (temp.empty()) {
             std::cerr << "Fatal error: image cannot open!" << std::endl;
             return false;
         }
@@ -57,22 +53,19 @@ bool Int8EntropyCalibrator2::getBatch(void* bindings[], const char* names[], int
     return true;
 }
 
-const void* Int8EntropyCalibrator2::readCalibrationCache(size_t& length) TRT_NOEXCEPT
-{
+const void* Int8EntropyCalibrator2::readCalibrationCache(size_t& length) TRT_NOEXCEPT {
     std::cout << "reading calib cache: " << calib_table_name_ << std::endl;
     calib_cache_.clear();
     std::ifstream input(calib_table_name_, std::ios::binary);
     input >> std::noskipws;
-    if (read_cache_ && input.good())
-    {
+    if (read_cache_ && input.good()) {
         std::copy(std::istream_iterator<char>(input), std::istream_iterator<char>(), std::back_inserter(calib_cache_));
     }
     length = calib_cache_.size();
     return length ? calib_cache_.data() : nullptr;
 }
 
-void Int8EntropyCalibrator2::writeCalibrationCache(const void* cache, size_t length) TRT_NOEXCEPT
-{
+void Int8EntropyCalibrator2::writeCalibrationCache(const void* cache, size_t length) TRT_NOEXCEPT {
     std::cout << "writing calib cache: " << calib_table_name_ << " size: " << length << std::endl;
     std::ofstream output(calib_table_name_, std::ios::binary);
     output.write(reinterpret_cast<const char*>(cache), length);

yolov5/calibrator.h

@@ -11,8 +11,7 @@
 //! \brief Implements Entropy calibrator 2.
 //!  CalibrationAlgoType is kENTROPY_CALIBRATION_2.
 //!
-class Int8EntropyCalibrator2 : public nvinfer1::IInt8EntropyCalibrator2
-{
+class Int8EntropyCalibrator2 : public nvinfer1::IInt8EntropyCalibrator2 {
 public:
     Int8EntropyCalibrator2(int batchsize, int input_w, int input_h, const char* img_dir, const char* calib_table_name, const char* input_blob_name, bool read_cache = true);
 
@@ -37,4 +36,4 @@ private:
     std::vector<char> calib_cache_;
 };
 
-#endif // ENTROPY_CALIBRATOR_H
+#endif  // ENTROPY_CALIBRATOR_H

yolov5/common.hpp

@@ -98,8 +98,7 @@ std::map<std::string, Weights> loadWeights(const std::string file) {
     input >> count;
     assert(count > 0 && "Invalid weight map file.");
 
-    while (count--)
-    {
+    while (count--) {
         Weights wt{ DataType::kFLOAT, nullptr, 0 };
         uint32_t size;
 
@@ -110,8 +109,7 @@ std::map<std::string, Weights> loadWeights(const std::string file) {
 
         // Load blob
         uint32_t* val = reinterpret_cast<uint32_t*>(malloc(sizeof(val) * size));
-        for (uint32_t x = 0, y = size; x < y; ++x)
-        {
+        for (uint32_t x = 0, y = size; x < y; ++x) {
             input >> std::hex >> val[x];
         }
         wt.values = val;
@@ -156,8 +154,6 @@ IScaleLayer* addBatchNorm2d(INetworkDefinition *network, std::map<std::string, W
     return scale_1;
 }
 
-
-
 ILayer* convBlock(INetworkDefinition *network, std::map<std::string, Weights>& weightMap, ITensor& input, int outch, int ksize, int s, int g, std::string lname) {
     Weights emptywts{ DataType::kFLOAT, nullptr, 0 };
     int p = ksize / 3;
@@ -323,5 +319,5 @@ IPluginV2Layer* addYoLoLayer(INetworkDefinition *network, std::map<std::string,
     auto yolo = network->addPluginV2(&input_tensors[0], input_tensors.size(), *plugin_obj);
     return yolo;
 }
-#endif
+#endif  // YOLOV5_COMMON_H_