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data_reader.hpp
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#ifndef CAFFE_DATA_READER_HPP_
#define CAFFE_DATA_READER_HPP_
#include <map>
#include <string>
#include <vector>
#include "caffe/common.hpp"
#include "caffe/internal_thread.hpp"
#include "caffe/util/blocking_queue.hpp"
#include "caffe/util/db.hpp"
namespace caffe {
/**
* @brief Reads data from a source to queues available to data layers.
* A single reading thread is created per source, even if multiple solvers
* are running in parallel, e.g. for multi-GPU training. This makes sure
* databases are read sequentially, and that each solver accesses a different
* subset of the database. Data is distributed to solvers in a round-robin
* way to keep parallel training deterministic.
*/
template <typename T>
class DataReader {
public:
explicit DataReader(const LayerParameter& param);
~DataReader();
inline BlockingQueue<T*>& free() const {
return queue_pair_->free_;
}
inline BlockingQueue<T*>& full() const {
return queue_pair_->full_;
}
protected:
// Queue pairs are shared between a body and its readers
class QueuePair {
public:
explicit QueuePair(int size);
~QueuePair();
BlockingQueue<T*> free_;
BlockingQueue<T*> full_;
DISABLE_COPY_AND_ASSIGN(QueuePair);
};
// A single body is created per source
class Body : public InternalThread {
public:
explicit Body(const LayerParameter& param);
virtual ~Body();
protected:
void InternalThreadEntry();
void read_one(db::Cursor* cursor, QueuePair* qp);
const LayerParameter param_;
BlockingQueue<shared_ptr<QueuePair> > new_queue_pairs_;
friend class DataReader;
DISABLE_COPY_AND_ASSIGN(Body);
};
// A source is uniquely identified by its layer name + path, in case
// the same database is read from two different locations in the net.
static inline string source_key(const LayerParameter& param) {
return param.name() + ":" + param.data_param().source();
}
const shared_ptr<QueuePair> queue_pair_;
shared_ptr<Body> body_;
static map<const string, boost::weak_ptr<Body> > bodies_;
DISABLE_COPY_AND_ASSIGN(DataReader);
};
} // namespace caffe
#endif // CAFFE_DATA_READER_HPP_