text: #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, typename MItype, typename MOtype>
  class MVNLayer : public Layer<Dtype, MItype, MOtype> {
   public:
    explicit MVNLayer(const LayerParameter& param)
        : Layer<Dtype, MItype, MOtype>(param) {}
    virtual void Reshape(const vector<Blob<MItype>*>& bottom,
        const vector<Blob<MOtype>*>& top);
  
    virtual inline const char* type() const { return "MVN"; }
    virtual inline int_tp ExactNumBottomBlobs() const { return 1; }
    virtual inline int_tp ExactNumTopBlobs() const { return 1; }
  
   protected:
    virtual void Forward_cpu(const vector<Blob<MItype>*>& bottom,
        const vector<Blob<MOtype>*>& top);
    virtual void Forward_gpu(const vector<Blob<MItype>*>& bottom,
        const vector<Blob<MOtype>*>& top);
    virtual void Backward_cpu(const vector<Blob<MOtype>*>& top,
        const vector<bool>& propagate_down,
        const vector<Blob<MItype>*>& bottom);
    virtual void Backward_gpu(const vector<Blob<MOtype>*>& top,
       const vector<bool>& propagate_down,
       const vector<Blob<MItype>*>& 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_
  