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Caffe Commons

misc code @

// Convert macro to string
#define STRINGIFY(m) #m
#define AS_STRING(m) STRINGIFY(m)

commons, D:\tzx\git\caffe-rc3\src\caffe\common.cpp @

class caffe {

  ...

  static Caffe& Get(); //   Thread local context for Caffe.
  enum Brew { CPU, GPU };
  inline static Brew mode() { return Get().mode_; }

  ...

  // This random number generator facade hides boost and CUDA rng
  // implementation from one another (for cross-platform compatibility).
  class RNG {
   public:
    RNG();
    explicit RNG(unsigned int seed);
    explicit RNG(const RNG&);
    RNG& operator=(const RNG&);
    void* generator();
   private:
    class Generator;
    shared_ptr<Generator> generator_;
  };

  ...

  // Prints the current GPU status.
  static void DeviceQuery();
  // Parallel training info
  inline static int solver_count() { return Get().solver_count_; }
  inline static void set_solver_count(int val) { Get().solver_count_ = val; }
  inline static bool root_solver() { return Get().root_solver_; }
  inline static void set_root_solver(bool val) { Get().root_solver_ = val; }

 protected:
#ifndef CPU_ONLY
  cublasHandle_t cublas_handle_;
  curandGenerator_t curand_generator_;
#endif
  shared_ptr<RNG> random_generator_;

  Brew mode_;
  int solver_count_;
  bool root_solver_;

 private:
  // The private constructor to avoid duplicate instantiation.
  Caffe();

  DISABLE_COPY_AND_ASSIGN(Caffe);
};

Caffe Utils

math_functions.cpp, D:\tzx\git\caffe-rc3\src\caffe\util\math_functions.cpp @

todo

io.cpp, D:\tzx\git\caffe-rc3\src\caffe\util\io.cpp @

bool ReadProtoFromTextFile(const char* filename, Message* proto) {
  int fd = open(filename, O_RDONLY);
  CHECK_NE(fd, -1) << "File not found: " << filename;
  FileInputStream* input = new FileInputStream(fd);
  bool success = google::protobuf::TextFormat::Parse(input, proto);
  delete input;
  close(fd);
  return success;
}

#ifdef USE_OPENCV
cv::Mat ReadImageToCVMat(const string& filename,
    const int height, const int width, const bool is_color) {
  cv::Mat cv_img;
  int cv_read_flag = (is_color ? CV_LOAD_IMAGE_COLOR :
    CV_LOAD_IMAGE_GRAYSCALE);
  cv::Mat cv_img_origin = cv::imread(filename, cv_read_flag);
  if (!cv_img_origin.data) {
    LOG(ERROR) << "Could not open or find file " << filename;
    return cv_img_origin;
  }
  if (height > 0 && width > 0) {
    cv::resize(cv_img_origin, cv_img, cv::Size(width, height));
  } else {
    cv_img = cv_img_origin;
  }
  return cv_img;
}

// Do the file extension and encoding match?
static bool matchExt(const std::string & fn,
                     std::string en) {
  size_t p = fn.rfind('.');
  std::string ext = p != fn.npos ? fn.substr(p) : fn;
  std::transform(ext.begin(), ext.end(), ext.begin(), ::tolower);
  std::transform(en.begin(), en.end(), en.begin(), ::tolower);
  if ( ext == en )
    return true;
  if ( en == "jpg" && ext == "jpeg" )
    return true;
  return false;
}

bool ReadImageToDatum(const string& filename, const int label,
    const int height, const int width, const bool is_color,
    const std::string & encoding, Datum* datum) {
  cv::Mat cv_img = ReadImageToCVMat(filename, height, width, is_color);
  if (cv_img.data) {
    if (encoding.size()) {
      if ( (cv_img.channels() == 3) == is_color && !height && !width &&
          matchExt(filename, encoding) )
        return ReadFileToDatum(filename, label, datum);
      std::vector<uchar> buf;
      cv::imencode("."+encoding, cv_img, buf);
      datum->set_data(std::string(reinterpret_cast<char*>(&buf[0]),
                      buf.size()));
      datum->set_label(label);
      datum->set_encoded(true);
      return true;
    }
    CVMatToDatum(cv_img, datum);
    datum->set_label(label);
    return true;
  } else {
    return false;
  }
}

bool ReadFileToDatum(const string& filename, const int label,
    Datum* datum) {
  std::streampos size;

  fstream file(filename.c_str(), ios::in|ios::binary|ios::ate);
  if (file.is_open()) {
    size = file.tellg();
    std::string buffer(size, ' ');
    file.seekg(0, ios::beg);
    file.read(&buffer[0], size);
    file.close();
    datum->set_data(buffer);
    datum->set_label(label);
    datum->set_encoded(true);
    return true;
  } else {
    return false;
  }
}

Caffe Layers

absval_layer.cpp @

文档：Caffe: caffe::AbsValLayer Class Template Reference。

Caffe: include/caffe/layers/absval_layer.hpp Source File

header file: include/caffe/layers/absval_layer.hpp @

Caffe: include/caffe/layers/absval_layer.hpp Source File

#ifndef CAFFE_ABSVAL_LAYER_HPP_
#define CAFFE_ABSVAL_LAYER_HPP_

#include <vector>

#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"

#include "caffe/layers/neuron_layer.hpp"

namespace caffe {

template <typename Dtype>
class AbsValLayer : public NeuronLayer<Dtype> {
 public:
  explicit AbsValLayer(const LayerParameter& param)
      : NeuronLayer<Dtype>(param) {}
  virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);

  virtual inline const char* type() const { return "AbsVal"; }
  virtual inline int ExactNumBottomBlobs() const { return 1; }
  virtual inline int ExactNumTopBlobs() const { return 1; }

 protected:
  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);
  virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top);

  virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
  virtual void Backward_gpu(const vector<Blob<Dtype>*>& top,
      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
};

}  // namespace caffe

#endif  // CAFFE_ABSVAL_LAYER_HPP_

source code: src/caffe/layers/absval_layer.cpp @

#include <vector>

#include "caffe/layers/absval_layer.hpp"
#include "caffe/util/math_functions.hpp"

namespace caffe {

template <typename Dtype>
void AbsValLayer<Dtype>::LayerSetUp(const vector<Blob<Dtype>*>& bottom,
      const vector<Blob<Dtype>*>& top) {
  NeuronLayer<Dtype>::LayerSetUp(bottom, top);
  CHECK_NE(top[0], bottom[0]) << this->type() << " Layer does not "
    "allow in-place computation.";
}

template <typename Dtype>
void AbsValLayer<Dtype>::Forward_cpu(
    const vector<Blob<Dtype>*>& bottom, const vector<Blob<Dtype>*>& top) {
  const int count = top[0]->count();
  Dtype* top_data = top[0]->mutable_cpu_data();
  caffe_abs(count, bottom[0]->cpu_data(), top_data);
}

template <typename Dtype>
void AbsValLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,
    const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {
  const int count = top[0]->count();
  const Dtype* top_diff = top[0]->cpu_diff();
  if (propagate_down[0]) {
    const Dtype* bottom_data = bottom[0]->cpu_data();
    Dtype* bottom_diff = bottom[0]->mutable_cpu_diff();
    caffe_cpu_sign(count, bottom_data, bottom_diff);
    caffe_mul(count, bottom_diff, top_diff, bottom_diff);
  }
}

#ifdef CPU_ONLY
STUB_GPU(AbsValLayer);
#endif

INSTANTIATE_CLASS(AbsValLayer);
REGISTER_LAYER_CLASS(AbsVal);

}  // namespace caffe