CNN_draw.tex

\documentclass{article}

\usepackage{tikz}
\usepackage{verbatim}




\documentclass{article2}


\begin{comment}
:Title: Neural network
:Tags: Foreach

The ``\foreach`` command is very useful for quickly creating structured graphics
like this neural network diagram.

\end{comment}

\begin{document}
\pagestyle{empty}

\def\layersep{2.5cm}

%\begin{tikzpicture}[shorten >=1pt,->,draw=black!50, node distance=\layersep]
%    \tikzstyle{every pin edge}=[<-,shorten <=1pt]
%    \tikzstyle{neuron}=[circle,fill=black!25,minimum size=17pt,inner sep=0pt]
%    \tikzstyle{input neuron}=[neuron, fill=green!50];
%    \tikzstyle{output neuron}=[neuron, fill=red!50];
%    \tikzstyle{hidden neuron}=[neuron, fill=orange!50];
%    \tikzstyle{annot} = [text width=4em, text centered]
%
%    % Draw the input layer nodes
%    \foreach \name / \y in {1,...,4}
%    % This is the same as writing \foreach \name / \y in {1/1,2/2,3/3,4/4}
%        \node[input neuron, pin=left:Input \-\y] (I-\name) at (0,-\y) {};
%
%    % Draw the hidden layer nodes
%    \foreach \name / \y in {1,...,5}
%        \path[yshift=0.5cm]
%            node[hidden neuron] (H-\name) at (\layersep,-\y cm) {};
%
%    % Draw the output layer node
%    \node[output neuron,pin={[pin edge={->}]right:Output}, right of=H-3] (O) {};
%
%    % Connect every node in the input layer with every node in the
%    % hidden layer.
%    \foreach \source in {1,...,4}
%        \foreach \dest in {1,...,5}
%            \path (I-\source) edge (H-\dest);
%
%    % Connect every node in the hidden layer with the output layer
%    \foreach \source in {1,...,5}
%        \path (H-\source) edge (O);
%
%    % Annotate the layers
%    \node[annot,above of=H-1, node distance=1cm] (hl) {Hidden layer};
%    \node[annot,left of=hl] {Input layer};
%    \node[annot,right of=hl] {Output layer};
%\end{tikzpicture}
% End of code

\begin{comment}
:Title: Convolutional Neural network
:Tags: Foreach

The ``\foreach`` command is very useful for quickly creating structured graphics
like this neural network diagram.

\end{comment}

\begin{document}
\pagestyle{empty}

\def\layersep{2.5cm}

\begin{tikzpicture}[shorten >=1pt,->,draw=black!50, node distance=\layersep]
    \tikzstyle{every pin edge}=[<-,shorten <=1pt]
    \tikzstyle{neuron}=[circle,fill=black!25,minimum size=17pt,inner sep=0pt]
    \tikzstyle{input neuron}=[neuron, fill=green!50];
    \tikzstyle{output neuron}=[neuron, fill=red!50];
    \tikzstyle{hidden neuron}=[neuron, fill=blue!50];
    \tikzstyle{hidden neuron2}=[neuron, fill=black!50];
    \tikzstyle{hidden neuron3}=[neuron, fill=orange!50];
    \tikzstyle{annot} = [text width=4em, text centered]

    % Draw the input layer nodes
    \foreach \name / \y in {1,...,4}
    % This is the same as writing \foreach \name / \y in {1/1,2/2,3/3,4/4}
        \node[input neuron, pin=left:Input \-\y] (I-\name) at (0,-\y) {};

    % Draw the hidden layer nodes
    \foreach \name / \y in {1,...,5}
        \path[yshift=0.5cm]
            node[hidden neuron] (H-\name) at (\layersep,-\y cm) {};


    \foreach \name / \y in {1,...,5}
        \path[yshift=0.5cm]
            node[hidden neuron2] (J-\name) at (5,-\y) {};


    \foreach \name / \y in {1,...,5}
        \path[yshift=0.5cm]
            node[hidden neuron3] (K-\name) at (7.5,-\y) {};		  

    % Draw the output layer node
    \node[output neuron,pin={[pin edge={->}]right:Output}, right of=K-3] (O) {};

    % Connect every node in the input layer with every node in the
    % hidden layer.
    \foreach \source in {1,...,4}
        \foreach \dest in {1,...,5}
            \path (I-\source) edge (H-\dest);

    \foreach \source in {1,...,5}
        \foreach \dest in {1,...,5}
            \path (H-\source) edge (J-\dest);   

    \foreach \source in {1,...,5}
        \foreach \dest in {1,...,5}
            \path (J-\source) edge (K-\dest);   

    % Connect every node in the hidden layer with the output layer
    \foreach \source in {1,...,5}
        \path (K-\source) edge (O);

    % Annotate the layers
    \node[annot,above of=H-1, node distance=1cm] (hl) {Convolutional layer};
    \node[annot,left of=hl] {Input layer};Convolutional
    \node[annot,right of=hl] {Pooling layer};
\node[annot,above of=K-1, node distance=1cm] (kl) { Fully connected layer};
\node[annot,right of=kl] {Output layer};

\end{tikzpicture}






\end{document}