Caffe代码解读(二):base_data_layer.hpp

#ifndef CAFFE_DATA_LAYERS_HPP_#define CAFFE_DATA_LAYERS_HPP_#include <vector>#include "caffe/blob.hpp"#include "caffe/data_transformer.hpp"#include "caffe/internal_thread.hpp"#include "caffe/layer.hpp"#include "caffe/proto/caffe.pb.h"#include "caffe/util/blocking_queue.hpp"namespace caffe {/** * @brief Provides base for data layers that feed blobs to the Net. * * TODO(dox): thorough documentation for Forward and proto params. */template <typename Dtype>//BaseDataLayer类 继承自Layerclass BaseDataLayer : public Layer<Dtype> { public://显示构造函数  explicit BaseDataLayer(const LayerParameter& param);// LayerSetUp: 实现常见的数据层设置功能,并且调用函数DataLayerSetUp实现个人特定的数据层设置// 除了BasePrefetchingDataLayer都不能重写该方法  virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,      const vector<Blob<Dtype>*>& top);// Data layers应该被多个solver同步共享  virtual inline bool ShareInParallel() const { return true; }//数据层的参数设置  virtual void DataLayerSetUp(const vector<Blob<Dtype>*>& bottom,      const vector<Blob<Dtype>*>& top) {}// 数据层没有Bottom,所以reshape不重要  virtual void Reshape(const vector<Blob<Dtype>*>& bottom,      const vector<Blob<Dtype>*>& top) {}//前向传播cpu函数  virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {}//反向传播cpu函数  virtual void Backward_gpu(const vector<Blob<Dtype>*>& top,      const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {} protected://声明变量  TransformationParameter transform_param_;  shared_ptr<DataTransformer<Dtype> > data_transformer_;  bool output_labels_;};template <typename Dtype>//Batch类,存放的就是数据和标签class Batch { public:  Blob<Dtype> data_, label_;};template <typename Dtype>class BasePrefetchingDataLayer :    public BaseDataLayer<Dtype>, public InternalThread { public://显示构造函数  explicit BasePrefetchingDataLayer(const LayerParameter& param);//LayerSetUp: 实现常见的数据层设置功能,并且调用函数DataLayerSetUp实现个人特定的数据层设置//不能重写该方法  void LayerSetUp(const vector<Blob<Dtype>*>& bottom,      const vector<Blob<Dtype>*>& top);//前向传播  virtual void Forward_cpu(const vector<Blob<Dtype>*>& bottom,      const vector<Blob<Dtype>*>& top);//反向传播  virtual void Forward_gpu(const vector<Blob<Dtype>*>& bottom,      const vector<Blob<Dtype>*>& top);//把需要的batches提前取出,这样可以提高速度,这里是设定提前去多少数量的batches// Prefetches batches (asynchronously if to GPU memory)  static const int PREFETCH_COUNT = 3; protected://声明变量  virtual void InternalThreadEntry();  virtual void load_batch(Batch<Dtype>* batch) = 0;  Batch<Dtype> prefetch_[PREFETCH_COUNT];  BlockingQueue<Batch<Dtype>*> prefetch_free_;  BlockingQueue<Batch<Dtype>*> prefetch_full_;  Blob<Dtype> transformed_data_;};}  // namespace caffe#endif  // CAFFE_DATA_LAYERS_HPP_