\section{Empty\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$ Class Template Reference}
\label{classmlpack_1_1ann_1_1EmptyLoss}\index{Empty\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$@{Empty\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$}}


The empty loss does nothing, letting the user calculate the loss outside the model.  


\subsection*{Public Member Functions}
\begin{DoxyCompactItemize}
\item 
\textbf{ Empty\+Loss} ()
\begin{DoxyCompactList}\small\item\em Create the \doxyref{Empty\+Loss}{p.}{classmlpack_1_1ann_1_1EmptyLoss} object. \end{DoxyCompactList}\item 
{\footnotesize template$<$typename Input\+Type , typename Target\+Type , typename Output\+Type $>$ }\\void \textbf{ Backward} (const Input\+Type \&input, const Target\+Type \&target, Output\+Type \&output)
\begin{DoxyCompactList}\small\item\em Ordinary feed backward pass of a neural network. \end{DoxyCompactList}\item 
{\footnotesize template$<$typename Input\+Type , typename Target\+Type $>$ }\\double \textbf{ Forward} (const Input\+Type \&input, const Target\+Type \&target)
\begin{DoxyCompactList}\small\item\em Computes the Empty loss function. \end{DoxyCompactList}\end{DoxyCompactItemize}


\subsection{Detailed Description}
\subsubsection*{template$<$typename Input\+Data\+Type = arma\+::mat, typename Output\+Data\+Type = arma\+::mat$>$\newline
class mlpack\+::ann\+::\+Empty\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$}

The empty loss does nothing, letting the user calculate the loss outside the model. 


\begin{DoxyTemplParams}{Template Parameters}
{\em Input\+Data\+Type} & Type of the input data (arma\+::colvec, arma\+::mat, arma\+::sp\+\_\+mat or arma\+::cube). \\
\hline
{\em Output\+Data\+Type} & Type of the output data (arma\+::colvec, arma\+::mat, arma\+::sp\+\_\+mat or arma\+::cube). \\
\hline
\end{DoxyTemplParams}


Definition at line 35 of file empty\+\_\+loss.\+hpp.



\subsection{Constructor \& Destructor Documentation}
\mbox{\label{classmlpack_1_1ann_1_1EmptyLoss_a20a0237f5a0af56a78486e698c74a5e8}} 
\index{mlpack\+::ann\+::\+Empty\+Loss@{mlpack\+::ann\+::\+Empty\+Loss}!Empty\+Loss@{Empty\+Loss}}
\index{Empty\+Loss@{Empty\+Loss}!mlpack\+::ann\+::\+Empty\+Loss@{mlpack\+::ann\+::\+Empty\+Loss}}
\subsubsection{Empty\+Loss()}
{\footnotesize\ttfamily \textbf{ Empty\+Loss} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})}



Create the \doxyref{Empty\+Loss}{p.}{classmlpack_1_1ann_1_1EmptyLoss} object. 



\subsection{Member Function Documentation}
\mbox{\label{classmlpack_1_1ann_1_1EmptyLoss_a7a5e88245fe9cf5644f846902393e97a}} 
\index{mlpack\+::ann\+::\+Empty\+Loss@{mlpack\+::ann\+::\+Empty\+Loss}!Backward@{Backward}}
\index{Backward@{Backward}!mlpack\+::ann\+::\+Empty\+Loss@{mlpack\+::ann\+::\+Empty\+Loss}}
\subsubsection{Backward()}
{\footnotesize\ttfamily void Backward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input,  }\item[{const Target\+Type \&}]{target,  }\item[{Output\+Type \&}]{output }\end{DoxyParamCaption})}



Ordinary feed backward pass of a neural network. 


\begin{DoxyParams}{Parameters}
{\em input} & The propagated input activation. \\
\hline
{\em target} & The target vector. \\
\hline
{\em output} & The calculated error. \\
\hline
\end{DoxyParams}
\mbox{\label{classmlpack_1_1ann_1_1EmptyLoss_ab29558c4430cc17c1f76f92a470fb17a}} 
\index{mlpack\+::ann\+::\+Empty\+Loss@{mlpack\+::ann\+::\+Empty\+Loss}!Forward@{Forward}}
\index{Forward@{Forward}!mlpack\+::ann\+::\+Empty\+Loss@{mlpack\+::ann\+::\+Empty\+Loss}}
\subsubsection{Forward()}
{\footnotesize\ttfamily double Forward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input,  }\item[{const Target\+Type \&}]{target }\end{DoxyParamCaption})}



Computes the Empty loss function. 


\begin{DoxyParams}{Parameters}
{\em input} & Input data used for evaluating the specified function. \\
\hline
{\em target} & The target vector. \\
\hline
\end{DoxyParams}


The documentation for this class was generated from the following file\+:\begin{DoxyCompactItemize}
\item 
/var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+2/src/mlpack/methods/ann/loss\+\_\+functions/\textbf{ empty\+\_\+loss.\+hpp}\end{DoxyCompactItemize}