common.hpp
#ifndef CAFFE_COMMON_HPP_
#define CAFFE_COMMON_HPP_
#include <boost/shared_ptr.hpp>
#include <gflags/gflags.h>
#include <glog/logging.h>
#include <climits>
#include <cmath>
#include <fstream> // NOLINT(readability/streams)
#include <iostream> // NOLINT(readability/streams)
#include <map>
#include <set>
#include <sstream>
#include <string>
#include <utility> // pair
#include <vector>
#include "caffe/util/device_alternate.hpp"
// Convert macro to string
#define STRINGIFY(m) #m
#define AS_STRING(m) STRINGIFY(m)
// gflags 2.1 issue: namespace google was changed to gflags without warning.
// Luckily we will be able to use GFLAGS_GFLAGS_H_ to detect if it is version
// 2.1. If yes, we will add a temporary solution to redirect the namespace.
// TODO(Yangqing): Once gflags solves the problem in a more elegant way, let's
// remove the following hack.
#ifndef GFLAGS_GFLAGS_H_
namespace gflags = google;
#endif // GFLAGS_GFLAGS_H_
// Disable the copy and assignment operator for a class.
#define DISABLE_COPY_AND_ASSIGN(classname) \
private:\
classname(const classname&);\
classname& operator=(const classname&)
// Instantiate a class with float and double specifications.
#define INSTANTIATE_CLASS(classname) \
char gInstantiationGuard##classname; \
template class classname<float>; \
template class classname<double>
#define INSTANTIATE_LAYER_GPU_FORWARD(classname) \
template void classname<float>::Forward_gpu( \
const std::vector<Blob<float>*>& bottom, \
const std::vector<Blob<float>*>& top); \
template void classname<double>::Forward_gpu( \
const std::vector<Blob<double>*>& bottom, \
const std::vector<Blob<double>*>& top);
#define INSTANTIATE_LAYER_GPU_BACKWARD(classname) \
template void classname<float>::Backward_gpu( \
const std::vector<Blob<float>*>& top, \
const std::vector<bool>& propagate_down, \
const std::vector<Blob<float>*>& bottom); \
template void classname<double>::Backward_gpu( \
const std::vector<Blob<double>*>& top, \
const std::vector<bool>& propagate_down, \
const std::vector<Blob<double>*>& bottom)
#define INSTANTIATE_LAYER_GPU_FUNCS(classname) \
INSTANTIATE_LAYER_GPU_FORWARD(classname); \
INSTANTIATE_LAYER_GPU_BACKWARD(classname)
// A simple macro to mark codes that are not implemented, so that when the code
// is executed we will see a fatal log.
#define NOT_IMPLEMENTED LOG(FATAL) << "Not Implemented Yet"
// See PR #1236
namespace cv { class Mat; }
namespace caffe {
// We will use the boost shared_ptr instead of the new C++11 one mainly
// because cuda does not work (at least now) well with C++11 features.
using boost::shared_ptr;
// Common functions and classes from std that caffe often uses.
using std::fstream;
using std::ios;
using std::isnan;
using std::isinf;
using std::iterator;
using std::make_pair;
using std::map;
using std::ostringstream;
using std::pair;
using std::set;
using std::string;
using std::stringstream;
using std::vector;
// A global initialization function that you should call in your main function.
// Currently it initializes google flags and google logging.
void GlobalInit(int* pargc, char*** pargv);
// A singleton class to hold common caffe stuff, such as the handler that
// caffe is going to use for cublas, curand, etc.
class Caffe {
public:
~Caffe();
// Thread local context for Caffe. Moved to common.cpp instead of
// including boost/thread.hpp to avoid a boost/NVCC issues (#1009, #1010)
// on OSX. Also fails on Linux with CUDA 7.0.18.
static Caffe& Get();
enum Brew { CPU, GPU };
// 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_;
};
// Getters for boost rng, curand, and cublas handles
inline static RNG& rng_stream() {
if (!Get().random_generator_) {
Get().random_generator_.reset(new RNG());
}
return *(Get().random_generator_);
}
#ifndef CPU_ONLY
inline static cublasHandle_t cublas_handle() { return Get().cublas_handle_; }
inline static curandGenerator_t curand_generator() {
return Get().curand_generator_;
}
#endif
// Returns the mode: running on CPU or GPU.
inline static Brew mode() { return Get().mode_; }
// The setters for the variables
// Sets the mode. It is recommended that you don't change the mode halfway
// into the program since that may cause allocation of pinned memory being
// freed in a non-pinned way, which may cause problems - I haven't verified
// it personally but better to note it here in the header file.
inline static void set_mode(Brew mode) { Get().mode_ = mode; }
// Sets the random seed of both boost and curand
static void set_random_seed(const unsigned int seed);
// Sets the device. Since we have cublas and curand stuff, set device also
// requires us to reset those values.
static void SetDevice(const int device_id);
// Prints the current GPU status.
static void DeviceQuery();
// Check if specified device is available
static bool CheckDevice(const int device_id);
// Search from start_id to the highest possible device ordinal,
// return the ordinal of the first available device.
static int FindDevice(const int start_id = 0);
// Parallel training
inline static int solver_count() { return Get().solver_count_; }
inline static void set_solver_count(int val) { Get().solver_count_ = val; }
inline static int solver_rank() { return Get().solver_rank_; }
inline static void set_solver_rank(int val) { Get().solver_rank_ = val; }
inline static bool multiprocess() { return Get().multiprocess_; }
inline static void set_multiprocess(bool val) { Get().multiprocess_ = val; }
inline static bool root_solver() { return Get().solver_rank_ == 0; }
protected:
#ifndef CPU_ONLY
cublasHandle_t cublas_handle_;
curandGenerator_t curand_generator_;
#endif
shared_ptr<RNG> random_generator_;
Brew mode_;
// Parallel training
int solver_count_;
int solver_rank_;
bool multiprocess_;
private:
// The private constructor to avoid duplicate instantiation.
Caffe();
DISABLE_COPY_AND_ASSIGN(Caffe);
};
} // namespace caffe
#endif // CAFFE_COMMON_HPP_
caffe::Caffe
Definition: common.hpp:102
caffe::Caffe::RNG
Definition: common.hpp:115
caffe::Caffe::RNG::Generator
Definition: common.cpp:239
caffe
A layer factory that allows one to register layers. During runtime, registered layers can be called b...
Definition: blob.hpp:14