mlpack 3.4.2
dice_loss.hpp
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1
12#ifndef MLPACK_METHODS_ANN_LOSS_FUNCTIONS_DICE_LOSS_HPP
13#define MLPACK_METHODS_ANN_LOSS_FUNCTIONS_DICE_LOSS_HPP
14
15#include <mlpack/prereqs.hpp>
16
17namespace mlpack {
18namespace ann {
19
46template <
47 typename InputDataType = arma::mat,
48 typename OutputDataType = arma::mat
49>
51{
52 public:
58 DiceLoss(const double smooth = 1);
59
66 template<typename InputType, typename TargetType>
67 typename InputType::elem_type Forward(const InputType& input,
68 const TargetType& target);
69
77 template<typename InputType, typename TargetType, typename OutputType>
78 void Backward(const InputType& input,
79 const TargetType& target,
80 OutputType& output);
81
83 OutputDataType& OutputParameter() const { return outputParameter; }
85 OutputDataType& OutputParameter() { return outputParameter; }
86
88 double Smooth() const { return smooth; }
90 double& Smooth() { return smooth; }
91
95 template<typename Archive>
96 void serialize(Archive& ar, const unsigned int /* version */);
97
98 private:
100 OutputDataType outputParameter;
101
103 double smooth;
104}; // class DiceLoss
105
106} // namespace ann
107} // namespace mlpack
108
109// Include implementation.
110#include "dice_loss_impl.hpp"
111
112#endif
The dice loss performance function measures the network's performance according to the dice coefficie...
Definition: dice_loss.hpp:51
DiceLoss(const double smooth=1)
Create the DiceLoss object.
OutputDataType & OutputParameter() const
Get the output parameter.
Definition: dice_loss.hpp:83
void Backward(const InputType &input, const TargetType &target, OutputType &output)
Ordinary feed backward pass of a neural network.
double & Smooth()
Modify the smooth.
Definition: dice_loss.hpp:90
InputType::elem_type Forward(const InputType &input, const TargetType &target)
Computes the dice loss function.
double Smooth() const
Get the smooth.
Definition: dice_loss.hpp:88
OutputDataType & OutputParameter()
Modify the output parameter.
Definition: dice_loss.hpp:85
void serialize(Archive &ar, const unsigned int)
Serialize the layer.
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: cv.hpp:1
The core includes that mlpack expects; standard C++ includes and Armadillo.