\section{G\+RU$<$ Input\+Data\+Type, Output\+Data\+Type $>$ Class Template Reference} \label{classmlpack_1_1ann_1_1GRU}\index{G\+R\+U$<$ Input\+Data\+Type, Output\+Data\+Type $>$@{G\+R\+U$<$ Input\+Data\+Type, Output\+Data\+Type $>$}} An implementation of a gru network layer. \subsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \textbf{ G\+RU} () \begin{DoxyCompactList}\small\item\em Create the \doxyref{G\+RU}{p.}{classmlpack_1_1ann_1_1GRU} object. \end{DoxyCompactList}\item \textbf{ G\+RU} (const size\+\_\+t in\+Size, const size\+\_\+t out\+Size, const size\+\_\+t rho=std\+::numeric\+\_\+limits$<$ size\+\_\+t $>$\+::max()) \begin{DoxyCompactList}\small\item\em Create the \doxyref{G\+RU}{p.}{classmlpack_1_1ann_1_1GRU} layer object using the specified parameters. \end{DoxyCompactList}\item {\footnotesize template$<$typename eT $>$ }\\void \textbf{ Backward} (const arma\+::\+Mat$<$ eT $>$ \&, const arma\+::\+Mat$<$ eT $>$ \&gy, arma\+::\+Mat$<$ eT $>$ \&g) \begin{DoxyCompactList}\small\item\em Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards trough f. \end{DoxyCompactList}\item Output\+Data\+Type const \& \textbf{ Delta} () const \begin{DoxyCompactList}\small\item\em Get the delta. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Delta} () \begin{DoxyCompactList}\small\item\em Modify the delta. \end{DoxyCompactList}\item bool \textbf{ Deterministic} () const \begin{DoxyCompactList}\small\item\em The value of the deterministic parameter. \end{DoxyCompactList}\item bool \& \textbf{ Deterministic} () \begin{DoxyCompactList}\small\item\em Modify the value of the deterministic parameter. \end{DoxyCompactList}\item {\footnotesize template$<$typename eT $>$ }\\void \textbf{ Forward} (const arma\+::\+Mat$<$ eT $>$ \&input, arma\+::\+Mat$<$ eT $>$ \&output) \begin{DoxyCompactList}\small\item\em Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. \end{DoxyCompactList}\item {\footnotesize template$<$typename eT $>$ }\\void \textbf{ Gradient} (const arma\+::\+Mat$<$ eT $>$ \&input, const arma\+::\+Mat$<$ eT $>$ \&, arma\+::\+Mat$<$ eT $>$ \&) \item Output\+Data\+Type const \& \textbf{ Gradient} () const \begin{DoxyCompactList}\small\item\em Get the gradient. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Gradient} () \begin{DoxyCompactList}\small\item\em Modify the gradient. \end{DoxyCompactList}\item std\+::vector$<$ \textbf{ Layer\+Types}$<$$>$ $>$ \& \textbf{ Model} () \begin{DoxyCompactList}\small\item\em Get the model modules. \end{DoxyCompactList}\item Output\+Data\+Type const \& \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 Output\+Data\+Type const \& \textbf{ Parameters} () const \begin{DoxyCompactList}\small\item\em Get the parameters. \end{DoxyCompactList}\item Output\+Data\+Type \& \textbf{ Parameters} () \begin{DoxyCompactList}\small\item\em Modify the parameters. \end{DoxyCompactList}\item void \textbf{ Reset\+Cell} (const size\+\_\+t size) \item size\+\_\+t \textbf{ Rho} () const \begin{DoxyCompactList}\small\item\em Get the maximum number of steps to backpropagate through time (B\+P\+TT). \end{DoxyCompactList}\item size\+\_\+t \& \textbf{ Rho} () \begin{DoxyCompactList}\small\item\em Modify the maximum number of steps to backpropagate through time (B\+P\+TT). \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}\end{DoxyCompactItemize} \subsection{Detailed Description} \subsubsection*{template$<$typename Input\+Data\+Type = arma\+::mat, typename Output\+Data\+Type = arma\+::mat$>$\newline class mlpack\+::ann\+::\+G\+R\+U$<$ Input\+Data\+Type, Output\+Data\+Type $>$} An implementation of a gru network layer. This cell can be used in \doxyref{R\+NN}{p.}{classmlpack_1_1ann_1_1RNN} networks. \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 58 of file gru.\+hpp. \subsection{Constructor \& Destructor Documentation} \mbox{\label{classmlpack_1_1ann_1_1GRU_a375d9aa6e1d5554befe4173d70ca3e34}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!G\+RU@{G\+RU}} \index{G\+RU@{G\+RU}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{G\+R\+U()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily \textbf{ G\+RU} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})} Create the \doxyref{G\+RU}{p.}{classmlpack_1_1ann_1_1GRU} object. \mbox{\label{classmlpack_1_1ann_1_1GRU_a95db7ecef7c74dfd78bf58ea47667ab0}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!G\+RU@{G\+RU}} \index{G\+RU@{G\+RU}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{G\+R\+U()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily \textbf{ G\+RU} (\begin{DoxyParamCaption}\item[{const size\+\_\+t}]{in\+Size, }\item[{const size\+\_\+t}]{out\+Size, }\item[{const size\+\_\+t}]{rho = {\ttfamily std\+:\+:numeric\+\_\+limits$<$~size\+\_\+t~$>$\+:\+:max()} }\end{DoxyParamCaption})} Create the \doxyref{G\+RU}{p.}{classmlpack_1_1ann_1_1GRU} layer object using the specified parameters. \begin{DoxyParams}{Parameters} {\em in\+Size} & The number of input units. \\ \hline {\em out\+Size} & The number of output units. \\ \hline {\em rho} & Maximum number of steps to backpropagate through time (B\+P\+TT). \\ \hline \end{DoxyParams} \subsection{Member Function Documentation} \mbox{\label{classmlpack_1_1ann_1_1GRU_ad9ad1a3bdb0f3fff5c839ed155e4bbf8}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Backward@{Backward}} \index{Backward@{Backward}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Backward()} {\footnotesize\ttfamily void Backward (\begin{DoxyParamCaption}\item[{const arma\+::\+Mat$<$ eT $>$ \&}]{, }\item[{const arma\+::\+Mat$<$ eT $>$ \&}]{gy, }\item[{arma\+::\+Mat$<$ eT $>$ \&}]{g }\end{DoxyParamCaption})} Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards trough f. Using the results from the feed forward pass. \begin{DoxyParams}{Parameters} {\em input} & The propagated input activation. \\ \hline {\em gy} & The backpropagated error. \\ \hline {\em g} & The calculated gradient. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1GRU_a797f7edb44dd081e5e2b3cc316eef6bd}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Delta@{Delta}} \index{Delta@{Delta}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Delta()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily Output\+Data\+Type const\& Delta (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the delta. Definition at line 140 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_ad6601342d560219ce951d554e69e5e87}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Delta@{Delta}} \index{Delta@{Delta}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Delta()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily Output\+Data\+Type\& Delta (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the delta. Definition at line 142 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a9f4103707f4d199ce5594d239b60443e}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Deterministic@{Deterministic}} \index{Deterministic@{Deterministic}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Deterministic()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily bool Deterministic (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} The value of the deterministic parameter. Definition at line 120 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a42d4ee3da432cff20d3a41b8b1ec801c}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Deterministic@{Deterministic}} \index{Deterministic@{Deterministic}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Deterministic()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily bool\& Deterministic (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the value of the deterministic parameter. Definition at line 122 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a461f849bc638c15bec262dc9c3a58abe}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Forward@{Forward}} \index{Forward@{Forward}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Forward()} {\footnotesize\ttfamily void Forward (\begin{DoxyParamCaption}\item[{const arma\+::\+Mat$<$ eT $>$ \&}]{input, }\item[{arma\+::\+Mat$<$ eT $>$ \&}]{output }\end{DoxyParamCaption})} Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. \begin{DoxyParams}{Parameters} {\em input} & Input data used for evaluating the specified function. \\ \hline {\em output} & Resulting output activation. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1GRU_ae3face09d68158413cc32cefe69f060d}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Gradient@{Gradient}} \index{Gradient@{Gradient}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Gradient()\hspace{0.1cm}{\footnotesize\ttfamily [1/3]}} {\footnotesize\ttfamily void Gradient (\begin{DoxyParamCaption}\item[{const arma\+::\+Mat$<$ eT $>$ \&}]{input, }\item[{const arma\+::\+Mat$<$ eT $>$ \&}]{, }\item[{arma\+::\+Mat$<$ eT $>$ \&}]{ }\end{DoxyParamCaption})} \mbox{\label{classmlpack_1_1ann_1_1GRU_a0f1f4e6d93472d83852731a96c8c3f59}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Gradient@{Gradient}} \index{Gradient@{Gradient}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Gradient()\hspace{0.1cm}{\footnotesize\ttfamily [2/3]}} {\footnotesize\ttfamily Output\+Data\+Type const\& Gradient (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the gradient. Definition at line 145 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a19abce4739c3b0b658b612537e21956a}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Gradient@{Gradient}} \index{Gradient@{Gradient}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Gradient()\hspace{0.1cm}{\footnotesize\ttfamily [3/3]}} {\footnotesize\ttfamily Output\+Data\+Type\& Gradient (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the gradient. Definition at line 147 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a50c707b4f7c009339d8d661539baf38f}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Model@{Model}} \index{Model@{Model}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Model()} {\footnotesize\ttfamily std\+::vector$<$\textbf{ Layer\+Types}$<$$>$ $>$\& Model (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Get the model modules. Definition at line 150 of file gru.\+hpp. References G\+R\+U$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::serialize(). \mbox{\label{classmlpack_1_1ann_1_1GRU_a0ee21c2a36e5abad1e7a9d5dd00849f9}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily Output\+Data\+Type const\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the output parameter. Definition at line 135 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a21d5f745f02c709625a4ee0907f004a5}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \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 137 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_aa530552c7ef915c952fbacc77b965c90}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Parameters@{Parameters}} \index{Parameters@{Parameters}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Parameters()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily Output\+Data\+Type const\& Parameters (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the parameters. Definition at line 130 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_a9c5c5900772a689d5a6b59778ec67120}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Parameters@{Parameters}} \index{Parameters@{Parameters}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Parameters()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily Output\+Data\+Type\& Parameters (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the parameters. Definition at line 132 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_ab92846e8253dc597239574d87d969ffb}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Reset\+Cell@{Reset\+Cell}} \index{Reset\+Cell@{Reset\+Cell}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Reset\+Cell()} {\footnotesize\ttfamily void Reset\+Cell (\begin{DoxyParamCaption}\item[{const size\+\_\+t}]{size }\end{DoxyParamCaption})} \mbox{\label{classmlpack_1_1ann_1_1GRU_a45280505858e9bda815a48c96e930f8d}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Rho@{Rho}} \index{Rho@{Rho}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Rho()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily size\+\_\+t Rho (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the maximum number of steps to backpropagate through time (B\+P\+TT). Definition at line 125 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_aeb617af2894a3e4bbabcd7ebc30a35af}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!Rho@{Rho}} \index{Rho@{Rho}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{Rho()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily size\+\_\+t\& Rho (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the maximum number of steps to backpropagate through time (B\+P\+TT). Definition at line 127 of file gru.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1GRU_af0dd9205158ccf7bcfcd8ff81f79c927}} \index{mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}!serialize@{serialize}} \index{serialize@{serialize}!mlpack\+::ann\+::\+G\+RU@{mlpack\+::ann\+::\+G\+RU}} \subsubsection{serialize()} {\footnotesize\ttfamily void serialize (\begin{DoxyParamCaption}\item[{Archive \&}]{ar, }\item[{const unsigned}]{int }\end{DoxyParamCaption})} Serialize the layer. Referenced by G\+R\+U$<$ Input\+Data\+Type, Output\+Data\+Type $>$\+::\+Model(). 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.\+0/src/mlpack/methods/ann/layer/\textbf{ gru.\+hpp}\end{DoxyCompactItemize}