text: #ifndef CAFFE_BNLL_LAYER_HPP_
  #define CAFFE_BNLL_LAYER_HPP_
  
  #include <vector>
  
  #include "caffe/blob.hpp"
  #include "caffe/layer.hpp"
  #include "caffe/proto/caffe.pb.h"
  
  #include "caffe/layers/neuron_layer.hpp"
  
  namespace caffe {
  
  /**
   * @brief Computes @f$ y = x + \log(1 + \exp(-x)) @f$ if @f$ x > 0 @f$;
   *        @f$ y = \log(1 + \exp(x)) @f$ otherwise.
   *
   * @param bottom input Blob vector (length 1)
   *   -# @f$ (N \times C \times H \times W) @f$
   *      the inputs @f$ x @f$
   * @param top output Blob vector (length 1)
   *   -# @f$ (N \times C \times H \times W) @f$
   *      the computed outputs @f$
   *      y = \left\{
   *         \begin{array}{ll}
   *            x + \log(1 + \exp(-x)) & \mbox{if } x > 0 \\
   *            \log(1 + \exp(x)) & \mbox{otherwise}
   *         \end{array} \right.
   *      @f$
   */
  template <typename Dtype>
  class BNLLLayer : public NeuronLayer<Dtype> {
   public:
    explicit BNLLLayer(const LayerParameter& param)
        : NeuronLayer<Dtype>(param) {}
  
    virtual inline const char* type() const { return "BNLL"; }
  
   protected:
    /// @copydoc BNLLLayer
    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);
  
    /**
     * @brief Computes the error gradient w.r.t. the BNLL inputs.
     *
     * @param top output Blob vector (length 1), providing the error gradient with
     *      respect to the outputs
     *   -# @f$ (N \times C \times H \times W) @f$
     *      containing error gradients @f$ \frac{\partial E}{\partial y} @f$
     *      with respect to computed outputs @f$ y @f$
     * @param propagate_down see Layer::Backward.
     * @param bottom input Blob vector (length 2)
     *   -# @f$ (N \times C \times H \times W) @f$
     *      the inputs @f$ x @f$; Backward fills their diff with
     *      gradients @f$
     *        \frac{\partial E}{\partial x}
     *      @f$ if propagate_down[0]
     */
    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);
  };
  
  }  // namespace caffe
  
  #endif  // CAFFE_BNLL_LAYER_HPP_
  