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#ifndef CAFFE_THRESHOLD_LAYER_HPP_
#define CAFFE_THRESHOLD_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 Tests whether the input exceeds a threshold: outputs 1 for inputs
* above threshold; 0 otherwise.
*/
template <typename Dtype>
class ThresholdLayer : public NeuronLayer<Dtype> {
public:
/**
* @param param provides ThresholdParameter threshold_param,
* with ThresholdLayer options:
* - threshold (\b optional, default 0).
* the threshold value @f$ t @f$ to which the input values are compared.
*/
explicit ThresholdLayer(const LayerParameter& param)
: NeuronLayer<Dtype>(param) {}
virtual void LayerSetUp(const vector<Blob<Dtype>*>& bottom,
const vector<Blob<Dtype>*>& top);
virtual inline const char* type() const { return "Threshold"; }
protected:
/**
* @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}{lr}
* 0 & \mathrm{if} \; x \le t \\
* 1 & \mathrm{if} \; x > t
* \end{array} \right.
* @f$
*/
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 Not implemented (non-differentiable function)
virtual void Backward_cpu(const vector<Blob<Dtype>*>& top,
const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {
NOT_IMPLEMENTED;
}
Dtype threshold_;
};
} // namespace caffe
#endif // CAFFE_THRESHOLD_LAYER_HPP_
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