\section{Dice\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$ Class Template Reference} \label{classmlpack_1_1ann_1_1DiceLoss}\index{Dice\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$@{Dice\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$}} The dice loss performance function measures the network\textquotesingle{}s performance according to the dice coefficient between the input and target distributions. \subsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \textbf{ Dice\+Loss} (const double smooth=1) \begin{DoxyCompactList}\small\item\em Create the \doxyref{Dice\+Loss}{p.}{classmlpack_1_1ann_1_1DiceLoss} 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 $>$ }\\Input\+Type\+::elem\+\_\+type \textbf{ Forward} (const Input\+Type \&input, const Target\+Type \&target) \begin{DoxyCompactList}\small\item\em Computes the dice loss function. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Output\+Parameter} () const \begin{DoxyCompactList}\small\item\em Get the output parameter. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Output\+Parameter} () \begin{DoxyCompactList}\small\item\em Modify the output parameter. \end{DoxyCompactList}\item {\footnotesize template$<$typename Archive $>$ }\\void \textbf{ serialize} (Archive \&ar, const unsigned int) \begin{DoxyCompactList}\small\item\em Serialize the layer. \end{DoxyCompactList}\item double \textbf{ Smooth} () const \begin{DoxyCompactList}\small\item\em Get the smooth. \end{DoxyCompactList}\item double \& \textbf{ Smooth} () \begin{DoxyCompactList}\small\item\em Modify the smooth. \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\+::\+Dice\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$} The dice loss performance function measures the network\textquotesingle{}s performance according to the dice coefficient between the input and target distributions. For more information see the following. \begin{DoxyCode} @article\{Milletari2016, author = \{Fausto Milletari and Nassir Navab and Seyed\{-\}Ahmad Ahmadi\}, title = \{V-Net: Fully Convolutional Neural Networks \textcolor{keywordflow}{for} Volumetric Medical Image Segmentation\}, journal = \{CoRR\}, volume = \{abs/1606.04797\}, year = \{2016\}, url = \{http:\textcolor{comment}{//arxiv.org/abs/1606.04797\},} archivePrefix = \{arXiv\}, eprint = \{1606.04797\}, \} \end{DoxyCode} \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 50 of file dice\+\_\+loss.\+hpp. \subsection{Constructor \& Destructor Documentation} \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_a4bfcd6e91e6a5f7133996d0800ca248f}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Dice\+Loss@{Dice\+Loss}} \index{Dice\+Loss@{Dice\+Loss}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{Dice\+Loss()} {\footnotesize\ttfamily \textbf{ Dice\+Loss} (\begin{DoxyParamCaption}\item[{const double}]{smooth = {\ttfamily 1} }\end{DoxyParamCaption})} Create the \doxyref{Dice\+Loss}{p.}{classmlpack_1_1ann_1_1DiceLoss} object. \begin{DoxyParams}{Parameters} {\em smooth} & The Laplace smoothing parameter. \\ \hline \end{DoxyParams} \subsection{Member Function Documentation} \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_a7a5e88245fe9cf5644f846902393e97a}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Backward@{Backward}} \index{Backward@{Backward}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+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_1DiceLoss_aad9536a75d4ecfe220d313adc47f38fa}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Forward@{Forward}} \index{Forward@{Forward}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{Forward()} {\footnotesize\ttfamily Input\+Type\+::elem\+\_\+type Forward (\begin{DoxyParamCaption}\item[{const Input\+Type \&}]{input, }\item[{const Target\+Type \&}]{target }\end{DoxyParamCaption})} Computes the dice loss function. \begin{DoxyParams}{Parameters} {\em input} & Input data used for evaluating the specified function. \\ \hline {\em target} & The target vector. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_a8bae962cc603d1cab8d80ec78f8d505d}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily Output\+Data\+Type\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the output parameter. Definition at line 83 of file dice\+\_\+loss.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_a21d5f745f02c709625a4ee0907f004a5}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily Output\+Data\+Type\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the output parameter. Definition at line 85 of file dice\+\_\+loss.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_af0dd9205158ccf7bcfcd8ff81f79c927}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!serialize@{serialize}} \index{serialize@{serialize}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{serialize()} {\footnotesize\ttfamily void serialize (\begin{DoxyParamCaption}\item[{Archive \&}]{ar, }\item[{const unsigned}]{int }\end{DoxyParamCaption})} Serialize the layer. Referenced by Dice\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::\+Smooth(). \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_ac72576e4dbe1a49364cb15d8843e4cad}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Smooth@{Smooth}} \index{Smooth@{Smooth}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{Smooth()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily double Smooth (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the smooth. Definition at line 88 of file dice\+\_\+loss.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1DiceLoss_a5bd134044985cc6d34d5d1cc2e2484e7}} \index{mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}!Smooth@{Smooth}} \index{Smooth@{Smooth}!mlpack\+::ann\+::\+Dice\+Loss@{mlpack\+::ann\+::\+Dice\+Loss}} \subsubsection{Smooth()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily double\& Smooth (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the smooth. Definition at line 90 of file dice\+\_\+loss.\+hpp. References Dice\+Loss$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::serialize(). 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{ dice\+\_\+loss.\+hpp}\end{DoxyCompactItemize}