\section{Sequential$<$ Input\+Data\+Type, Output\+Data\+Type, Residual, Custom\+Layers $>$ Class Template Reference} \label{classmlpack_1_1ann_1_1Sequential}\index{Sequential$<$ Input\+Data\+Type, Output\+Data\+Type, Residual, Custom\+Layers $>$@{Sequential$<$ Input\+Data\+Type, Output\+Data\+Type, Residual, Custom\+Layers $>$}} Implementation of the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} class. \subsection*{Public Member Functions} \begin{DoxyCompactItemize} \item \textbf{ Sequential} (const bool model=true) \begin{DoxyCompactList}\small\item\em Create the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} object using the specified parameters. \end{DoxyCompactList}\item \textbf{ Sequential} (const bool model, const bool owns\+Layers) \begin{DoxyCompactList}\small\item\em Create the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} object using the specified parameters. \end{DoxyCompactList}\item \textbf{ $\sim$\+Sequential} () \begin{DoxyCompactList}\small\item\em Destroy the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} object. \end{DoxyCompactList}\item {\footnotesize template$<$class Layer\+Type , class... Args$>$ }\\void \textbf{ Add} (Args... args) \item void \textbf{ Add} (\textbf{ Layer\+Types}$<$ Custom\+Layers... $>$ layer) \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, using 3rd-\/order tensors as input, calculating the function f(x) by propagating x backwards through f. \end{DoxyCompactList}\item arma\+::mat const \& \textbf{ Delta} () const \begin{DoxyCompactList}\small\item\em Get the delta. \end{DoxyCompactList}\item arma\+::mat \& \textbf{ Delta} () \begin{DoxyCompactList}\small\item\em Modify the delta. \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 $>$ \&error, arma\+::\+Mat$<$ eT $>$ \&) \item arma\+::mat const \& \textbf{ Gradient} () const \begin{DoxyCompactList}\small\item\em Get the gradient. \end{DoxyCompactList}\item arma\+::mat \& \textbf{ Gradient} () \begin{DoxyCompactList}\small\item\em Modify the gradient. \end{DoxyCompactList}\item arma\+::mat const \& \textbf{ Input\+Parameter} () const \begin{DoxyCompactList}\small\item\em Get the input parameter. \end{DoxyCompactList}\item arma\+::mat \& \textbf{ Input\+Parameter} () \begin{DoxyCompactList}\small\item\em Modify the input parameter. \end{DoxyCompactList}\item std\+::vector$<$ \textbf{ Layer\+Types}$<$ Custom\+Layers... $>$ $>$ \& \textbf{ Model} () \begin{DoxyCompactList}\small\item\em Return the model modules. \end{DoxyCompactList}\item arma\+::mat const \& \textbf{ Output\+Parameter} () const \begin{DoxyCompactList}\small\item\em Get the output parameter. \end{DoxyCompactList}\item arma\+::mat \& \textbf{ Output\+Parameter} () \begin{DoxyCompactList}\small\item\em Modify the output parameter. \end{DoxyCompactList}\item const arma\+::mat \& \textbf{ Parameters} () const \begin{DoxyCompactList}\small\item\em Return the initial point for the optimization. \end{DoxyCompactList}\item arma\+::mat \& \textbf{ Parameters} () \begin{DoxyCompactList}\small\item\em Modify the initial point for the optimization. \end{DoxyCompactList}\item {\footnotesize template$<$typename Archive $>$ }\\void \textbf{ serialize} (Archive \&, 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, bool Residual = false, typename... Custom\+Layers$>$\newline class mlpack\+::ann\+::\+Sequential$<$ Input\+Data\+Type, Output\+Data\+Type, Residual, Custom\+Layers $>$} Implementation of the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} class. The sequential class works as a feed-\/forward fully connected network container which plugs various layers together. This class can also be used as a container for a residual block. In that case, the sizes of the input and output matrices of this class should be equal. A typedef has been added for use as a Residual$<$$>$ class. For more information, refer the following paper. \begin{DoxyCode} @article\{He15, author = \{Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun\}, title = \{Deep Residual Learning \textcolor{keywordflow}{for} Image Recognition\}, year = \{2015\}, url = \{https:\textcolor{comment}{//arxiv.org/abs/1512.03385\},} eprint = \{1512.03385\}, \} \end{DoxyCode} Note\+: If this class is used as the first layer of a network, it should be preceded by Identity\+Layer$<$$>$. Note\+: This class should at least have two layers for a call to its \doxyref{Gradient()}{p.}{classmlpack_1_1ann_1_1Sequential_a59e16b7142696049a5543ff35547ebd9} function. \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 {\em Residual} & If true, use the object as a Residual block. \\ \hline \end{DoxyTemplParams} Definition at line 110 of file layer\+\_\+types.\+hpp. \subsection{Constructor \& Destructor Documentation} \mbox{\label{classmlpack_1_1ann_1_1Sequential_a01b828c8a9d0398c7d899fe5a0159cf0}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Sequential@{Sequential}} \index{Sequential@{Sequential}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Sequential()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily \textbf{ Sequential} (\begin{DoxyParamCaption}\item[{const bool}]{model = {\ttfamily true} }\end{DoxyParamCaption})} Create the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} object using the specified parameters. \begin{DoxyParams}{Parameters} {\em model} & Expose the all network modules. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1Sequential_a54e8b8c60e747977fcb5d1d33181d2d6}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Sequential@{Sequential}} \index{Sequential@{Sequential}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Sequential()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily \textbf{ Sequential} (\begin{DoxyParamCaption}\item[{const bool}]{model, }\item[{const bool}]{owns\+Layers }\end{DoxyParamCaption})} Create the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} object using the specified parameters. \begin{DoxyParams}{Parameters} {\em model} & Expose all the network modules. \\ \hline {\em owns\+Layers} & If true, then this module will delete its layers when deallocated. \\ \hline \end{DoxyParams} \mbox{\label{classmlpack_1_1ann_1_1Sequential_a104b6c42467bc2edb7c514afca99bcec}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!````~Sequential@{$\sim$\+Sequential}} \index{````~Sequential@{$\sim$\+Sequential}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{$\sim$\+Sequential()} {\footnotesize\ttfamily $\sim$\textbf{ Sequential} (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})} Destroy the \doxyref{Sequential}{p.}{classmlpack_1_1ann_1_1Sequential} object. \subsection{Member Function Documentation} \mbox{\label{classmlpack_1_1ann_1_1Sequential_a8b5234495846c00f6b2c8296ca6bc718}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Add@{Add}} \index{Add@{Add}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Add()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily void \textbf{ Add} (\begin{DoxyParamCaption}\item[{Args...}]{args }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Definition at line 135 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a503a807740e6c729be9efc89520db728}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Add@{Add}} \index{Add@{Add}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Add()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily void \textbf{ Add} (\begin{DoxyParamCaption}\item[{\textbf{ Layer\+Types}$<$ Custom\+Layers... $>$}]{layer }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Definition at line 142 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_ad9ad1a3bdb0f3fff5c839ed155e4bbf8}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Backward@{Backward}} \index{Backward@{Backward}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \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, using 3rd-\/order tensors as input, calculating the function f(x) by propagating x backwards through 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_1Sequential_a6126fc05a10e2e988ea7e75aada214fd}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Delta@{Delta}} \index{Delta@{Delta}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Delta()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily arma\+::mat const\& Delta (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the delta. Definition at line 171 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a49c3606024580071e0c65e2e4d080e1e}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Delta@{Delta}} \index{Delta@{Delta}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Delta()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily arma\+::mat\& Delta (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the delta. Definition at line 173 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a461f849bc638c15bec262dc9c3a58abe}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Forward@{Forward}} \index{Forward@{Forward}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \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_1Sequential_a505acb56ef67da2fc73190d3d4931969}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Gradient@{Gradient}} \index{Gradient@{Gradient}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \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 $>$ \&}]{error, }\item[{arma\+::\+Mat$<$ eT $>$ \&}]{ }\end{DoxyParamCaption})} \mbox{\label{classmlpack_1_1ann_1_1Sequential_a13444d1f198ceeef85e7a288a7d1d9c2}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Gradient@{Gradient}} \index{Gradient@{Gradient}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Gradient()\hspace{0.1cm}{\footnotesize\ttfamily [2/3]}} {\footnotesize\ttfamily arma\+::mat const\& Gradient (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the gradient. Definition at line 176 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a59e16b7142696049a5543ff35547ebd9}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Gradient@{Gradient}} \index{Gradient@{Gradient}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Gradient()\hspace{0.1cm}{\footnotesize\ttfamily [3/3]}} {\footnotesize\ttfamily arma\+::mat\& Gradient (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the gradient. Definition at line 178 of file sequential.\+hpp. References Sequential$<$ Input\+Data\+Type, Output\+Data\+Type, Residual, Custom\+Layers $>$\+::serialize(). \mbox{\label{classmlpack_1_1ann_1_1Sequential_a9b1735296084fc571524101988744884}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Input\+Parameter@{Input\+Parameter}} \index{Input\+Parameter@{Input\+Parameter}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Input\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily arma\+::mat const\& Input\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the input parameter. Definition at line 161 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a818d585c592c80d8e8c101f67bc389ad}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Input\+Parameter@{Input\+Parameter}} \index{Input\+Parameter@{Input\+Parameter}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Input\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily arma\+::mat\& Input\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the input parameter. Definition at line 163 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a4cb1e93bff99ccf1f8f974065a3b13c3}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Model@{Model}} \index{Model@{Model}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Model()} {\footnotesize\ttfamily std\+::vector$<$\textbf{ Layer\+Types}$<$Custom\+Layers...$>$ $>$\& Model (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Return the model modules. Definition at line 145 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a712dc230c489d0caf3175cbdfc59639f}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily arma\+::mat const\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Get the output parameter. Definition at line 166 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a28ce681558d0bf02302f868d1c811f2a}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Output\+Parameter@{Output\+Parameter}} \index{Output\+Parameter@{Output\+Parameter}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Output\+Parameter()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily arma\+::mat\& Output\+Parameter (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the output parameter. Definition at line 168 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_aa68d74dc1e86e4352e00a3cab83a0e4a}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Parameters@{Parameters}} \index{Parameters@{Parameters}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Parameters()\hspace{0.1cm}{\footnotesize\ttfamily [1/2]}} {\footnotesize\ttfamily const arma\+::mat\& Parameters (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption}) const\hspace{0.3cm}{\ttfamily [inline]}} Return the initial point for the optimization. Definition at line 156 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_a043f0ccd62e6711a18e0d81047be9a0a}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!Parameters@{Parameters}} \index{Parameters@{Parameters}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{Parameters()\hspace{0.1cm}{\footnotesize\ttfamily [2/2]}} {\footnotesize\ttfamily arma\+::mat\& Parameters (\begin{DoxyParamCaption}{ }\end{DoxyParamCaption})\hspace{0.3cm}{\ttfamily [inline]}} Modify the initial point for the optimization. Definition at line 158 of file sequential.\+hpp. \mbox{\label{classmlpack_1_1ann_1_1Sequential_aa5b3dd8336182f751ebec27167c22415}} \index{mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}!serialize@{serialize}} \index{serialize@{serialize}!mlpack\+::ann\+::\+Sequential@{mlpack\+::ann\+::\+Sequential}} \subsubsection{serialize()} {\footnotesize\ttfamily void serialize (\begin{DoxyParamCaption}\item[{Archive \&}]{, }\item[{const unsigned}]{int }\end{DoxyParamCaption})} Serialize the layer. Referenced by Sequential$<$ Input\+Data\+Type, Output\+Data\+Type, Residual, Custom\+Layers $>$\+::\+Gradient(). The documentation for this class was generated from the following files\+:\begin{DoxyCompactItemize} \item /var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+0/src/mlpack/methods/ann/layer/\textbf{ layer\+\_\+types.\+hpp}\item /var/www/mlpack.\+ratml.\+org/mlpack.\+org/\+\_\+src/mlpack-\/3.\+3.\+0/src/mlpack/methods/ann/layer/\textbf{ sequential.\+hpp}\end{DoxyCompactItemize}