doxygen/lrn__layer_8hpp_source.html

 #ifndef CAFFE_LRN_LAYER_HPP_
 #define CAFFE_LRN_LAYER_HPP_

 #include <vector>

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

 #include "caffe/layers/eltwise_layer.hpp"
 #include "caffe/layers/pooling_layer.hpp"
 #include "caffe/layers/power_layer.hpp"
 #include "caffe/layers/split_layer.hpp"

 namespace caffe {

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

   virtual inline const char* type() const { return "LRN"; }
   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);

   virtual void CrossChannelForward_cpu(const vector<Blob<Dtype>*>& bottom,
       const vector<Blob<Dtype>*>& top);
   virtual void CrossChannelForward_gpu(const vector<Blob<Dtype>*>& bottom,
       const vector<Blob<Dtype>*>& top);
   virtual void WithinChannelForward(const vector<Blob<Dtype>*>& bottom,
       const vector<Blob<Dtype>*>& top);
   virtual void CrossChannelBackward_cpu(const vector<Blob<Dtype>*>& top,
       const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
   virtual void CrossChannelBackward_gpu(const vector<Blob<Dtype>*>& top,
       const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);
   virtual void WithinChannelBackward(const vector<Blob<Dtype>*>& top,
       const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom);

   int size_;
   int pre_pad_;
   Dtype alpha_;
   Dtype beta_;
   Dtype k_;
   int num_;
   int channels_;
   int height_;
   int width_;

   // Fields used for normalization ACROSS_CHANNELS
   // scale_ stores the intermediate summing results
   Blob<Dtype> scale_;

   // Fields used for normalization WITHIN_CHANNEL
   shared_ptr<SplitLayer<Dtype> > split_layer_;
   vector<Blob<Dtype>*> split_top_vec_;
   shared_ptr<PowerLayer<Dtype> > square_layer_;
   Blob<Dtype> square_input_;
   Blob<Dtype> square_output_;
   vector<Blob<Dtype>*> square_bottom_vec_;
   vector<Blob<Dtype>*> square_top_vec_;
   shared_ptr<PoolingLayer<Dtype> > pool_layer_;
   Blob<Dtype> pool_output_;
   vector<Blob<Dtype>*> pool_top_vec_;
   shared_ptr<PowerLayer<Dtype> > power_layer_;
   Blob<Dtype> power_output_;
   vector<Blob<Dtype>*> power_top_vec_;
   shared_ptr<EltwiseLayer<Dtype> > product_layer_;
   Blob<Dtype> product_input_;
   vector<Blob<Dtype>*> product_bottom_vec_;
 };

 }  // namespace caffe

 #endif  // CAFFE_LRN_LAYER_HPP_
caffe::Layer
An interface for the units of computation which can be composed into a Net.
Definition: layer.hpp:33

caffe
A layer factory that allows one to register layers. During runtime, registered layers can be called b...
Definition: blob.hpp:14

caffe::LRNLayer::ExactNumTopBlobs
virtual int ExactNumTopBlobs() const
Returns the exact number of top blobs required by the layer, or -1 if no exact number is required...
Definition: lrn_layer.hpp:34

caffe::LRNLayer::Backward_gpu
virtual void Backward_gpu(const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_...

caffe::LRNLayer::LayerSetUp
virtual void LayerSetUp(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Does layer-specific setup: your layer should implement this function as well as Reshape.
Definition: lrn_layer.cpp:9

caffe::LRNLayer::Reshape
virtual void Reshape(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs...
Definition: lrn_layer.cpp:69

caffe::LRNLayer::Backward_cpu
virtual void Backward_cpu(const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
Using the CPU device, compute the gradients for any parameters and for the bottom blobs if propagate_...
Definition: lrn_layer.cpp:165

caffe::LRNLayer::ExactNumBottomBlobs
virtual int ExactNumBottomBlobs() const
Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required...
Definition: lrn_layer.hpp:33

caffe::LRNLayer::Forward_cpu
virtual void Forward_cpu(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Using the CPU device, compute the layer output.
Definition: lrn_layer.cpp:93

caffe::LRNLayer::type
virtual const char * type() const
Returns the layer type.
Definition: lrn_layer.hpp:32

caffe::LRNLayer::Forward_gpu
virtual void Forward_gpu(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Using the GPU device, compute the layer output. Fall back to Forward_cpu() if unavailable.

caffe::LRNLayer
Normalize the input in a local region across or within feature maps.
Definition: lrn_layer.hpp:23

caffe::Blob
A wrapper around SyncedMemory holders serving as the basic computational unit through which Layers...
Definition: blob.hpp:24