/usr/include/caffe/layers/mvn_layer.hpp is in libcaffe-cpu-dev 1.0.0~rc4-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | #ifndef CAFFE_MVN_LAYER_HPP_
#define CAFFE_MVN_LAYER_HPP_
#include <vector>
#include "caffe/blob.hpp"
#include "caffe/layer.hpp"
#include "caffe/proto/caffe.pb.h"
namespace caffe {
/**
* @brief Normalizes the input to have 0-mean and/or unit (1) variance.
*
* TODO(dox): thorough documentation for Forward, Backward, and proto params.
*/
template <typename Dtype>
class MVNLayer : public Layer<Dtype> {
public:
explicit MVNLayer(const LayerParameter& param)
: Layer<Dtype>(param) {}
virtual void Reshape(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual inline const char* type() const { return "MVN"; }
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);
Blob<Dtype> mean_, variance_, temp_;
/// sum_multiplier is used to carry out sum using BLAS
Blob<Dtype> sum_multiplier_;
Dtype eps_;
};
} // namespace caffe
#endif // CAFFE_MVN_LAYER_HPP_
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