mlpack
empty_loss.hpp
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1 
14 #ifndef MLPACK_METHODS_ANN_LOSS_FUNCTION_EMPTY_LOSS_HPP
15 #define MLPACK_METHODS_ANN_LOSS_FUNCTION_EMPTY_LOSS_HPP
16 
17 #include <mlpack/prereqs.hpp>
18 
19 namespace mlpack {
20 namespace ann {
21 
31 template <
32  typename InputDataType = arma::mat,
33  typename OutputDataType = arma::mat
34 >
35 class EmptyLoss
36 {
37  public:
41  EmptyLoss();
42 
49  template<typename InputType, typename TargetType>
50  double Forward(const InputType& input, const TargetType& target);
51 
59  template<typename InputType, typename TargetType, typename OutputType>
60  void Backward(const InputType& input,
61  const TargetType& target,
62  OutputType& output);
63 }; // class EmptyLoss
64 
65 } // namespace ann
66 } // namespace mlpack
67 
68 // Include implementation.
69 #include "empty_loss_impl.hpp"
70 
71 #endif
mlpack
Linear algebra utility functions, generally performed on matrices or vectors.
Definition: add_to_po.hpp:21
mlpack::ann::EmptyLoss::Backward
void Backward(const InputType &input, const TargetType &target, OutputType &output)
Ordinary feed backward pass of a neural network.
prereqs.hpp
The core includes that mlpack expects; standard C++ includes and Armadillo.
mlpack::ann::EmptyLoss
The empty loss does nothing, letting the user calculate the loss outside the model.
Definition: empty_loss.hpp:35
mlpack::ann::EmptyLoss::EmptyLoss
EmptyLoss()
Create the EmptyLoss object.
mlpack::ann::EmptyLoss::Forward
double Forward(const InputType &input, const TargetType &target)
Computes the Empty loss function.