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#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_
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