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diff --git a/Master/texmf-dist/tex/latex/nndraw/nndraw.sty b/Master/texmf-dist/tex/latex/nndraw/nndraw.sty new file mode 100644 index 00000000000..f7bd217d10e --- /dev/null +++ b/Master/texmf-dist/tex/latex/nndraw/nndraw.sty @@ -0,0 +1,150 @@ +%% +%% This is file `nndraw.sty', +%% generated with the docstrip utility. +%% +%% The original source files were: +%% +%% nndraw.dtx (with options: `package') +%% +%% This is a generated file. +%% +%% Copyright (C) 2021 by Carlos Cardoso Dias <carlosdias.dev@gmail.com> +%% -------------------------------------------------------------------------- +%% This work may be distributed and/or modified under the +%% conditions of the LaTeX Project Public License, either version 1.3 +%% of this license or (at your option) any later version. +%% The latest version of this license is in +%% http://www.latex-project.org/lppl.txt +%% and version 1.3 or later is part of all distributions of LaTeX +%% version 2005/12/01 or later. +%% +\NeedsTeXFormat{LaTeX2e}[1999/12/01] +\ProvidesPackage{nndraw} + [2021/06/22 1.0 nndraw is a LaTeX package which provides utilities to draw neural networks.] +\textbf{nndraw} is a \LaTeX package which provides utilities to draw neural networks in an efficient way. +Currently this package provides utilities to draw fully connected feedforward neural networks with an arbitrary +number of layers described inside the `fullyconnectednn` environment using the command `nnlayer`. +An example of usage is shown below, in this example, a fully connected feedforward +deep neural network is provided with two inputs in the first layer, one hidden layer +with four neurons and one output layer with one output. This example shows how easy it is +to customize the presence/absence of biases in any layer as well as its position. + +\begin{verbatim} +\begin{fullyconnectednn}[biasy = -4.5, + titley = 1, + inout = false] + \nnlayer[title = Input layer]{2} + \nnlayer[title = Hidden layer]{4} + \nnlayer[title = Ouput layer, hasbias = false]{1} +\end{fullyconnectednn} +\end{verbatim} + +\noindent Which is drawn as + +\begin{fullyconnectednn}[biasy = -4.5, + titley = 1, + inout = false] + \nnlayer[title = Input layer]{2} + \nnlayer[title = Hidden layer]{4} + \nnlayer[title = Ouput layer, hasbias = false]{1} +\end{fullyconnectednn} +\NeedsTeXFormat{LaTeX2e} +\ProvidesPackage{nndraw}[2021/06/20 Neural Networks Draw LaTeX package] +\RequirePackage{tikz} +\pgfdeclarelayer{back} +\pgfsetlayers{back,main} +\newcommand\nnlayerNoText[1]{} +\newif\ifnnlayerHasBias +\pgfkeys{ + /nnlayer/.is family, /nnlayer, + default/.style = {title = , text = \nnlayerNoText, hasbias = true, bias = , color = , biascolor = }, + title/.estore in = \nnlayerTitle, + text/.store in = \nnlayerText, + hasbias/.is if = nnlayerHasBias, + bias/.estore in = \nnlayerBias, + color/.estore in = \nnlayerColor, + biascolor/.estore in = \nnlayerBiasColor, +} +\newcounter{numlayers} +\newcounter{nninputlayer} +\newcounter{lastnnsize} +\tikzstyle{neuron}=[circle, minimum size=6mm, fill=gray!70] +\tikzstyle{neuron_connection}=[->, shorten >=1pt, gray!70] +\newcommand\nnlayer[2][]{ + \pgfkeys{/nnlayer, default, #1} + \node[text width = \fullyconnectednnTextWidth, align = center] at (\fullyconnectednnLayersep * + \thenumlayers,\fullyconnectednnTitleY) {\nnlayerTitle}; + \if\thenninputlayer0 + \setcounter{nninputlayer}{#2} + \fi + \foreach \i in {1,...,#2} + { + \node[neuron, yshift=(#2 - \thenninputlayer)*5 mm, fill=\nnlayerColor] (\thenumlayers-\i) at (\thenumlayers * \fullyconnectednnLayersep,-\i) {\nnlayerText{\i}}; + } + \if\thelastnnsize0 + \else + \ifnnlayerHasBias + \node[neuron, yshift=5mm, fill=\nnlayerBiasColor] (bias-\thenumlayers) at (\thenumlayers * \fullyconnectednnLayersep -\fullyconnectednnLayersep + \fullyconnectednnBiasX, \fullyconnectednnBiasY) {\nnlayerBias}; + \fi + \begin{pgfonlayer}{back} + \foreach \i in {1,...,\thelastnnsize} + { + \foreach \j in {1,...,#2} + { + \draw[neuron_connection] (\the\numexpr\thenumlayers-1\relax-\i) -- (\thenumlayers-\j); + } + } + \ifnnlayerHasBias + \foreach \j in {1,...,#2} + { + \draw[neuron_connection] (bias-\thenumlayers) -- (\thenumlayers-\j); + } + \fi + \end{pgfonlayer} + \fi + \setcounter{lastnnsize}{#2} + \stepcounter{numlayers} +} +\newif\iffullyconnectednnInout +\pgfkeys{ + /fullyconnectednn/.is family, /fullyconnectednn, + default/.style = {input = \nnlayerNoText, output = \nnlayerNoText, layersep = 3, biasx = 0.75, biasy = -8.75, titley = 0.75, inout = true, text width = 2cm}, + input/.store in = \fullyconnectednnInput, + output/.store in = \fullyconnectednnOutput, + layersep/.estore in = \fullyconnectednnLayersep, + biasx/.estore in = \fullyconnectednnBiasX, + biasy/.estore in = \fullyconnectednnBiasY, + titley/.estore in = \fullyconnectednnTitleY, + inout/.is if = fullyconnectednnInout, + text width/.estore in = \fullyconnectednnTextWidth, +} +\newenvironment{fullyconnectednn}[1][] + { + \pgfkeys{/fullyconnectednn, default, #1} + \begin{center} + \begin{tikzpicture} + \setcounter{numlayers}{0} + \setcounter{nninputlayer}{0} + \setcounter{lastnnsize}{0} + } + { + \iffullyconnectednnInout + \begin{pgfonlayer}{back} + \foreach \i in {1,...,\thenninputlayer} + { + \draw[<-, shorten <=1pt] (0-\i) -- ++(-1,0) node[left]{\fullyconnectednnInput{\i}}; + } + + \foreach \i in {1,...,\thelastnnsize} + { + \draw[->, shorten <=1pt] (\the\numexpr\thenumlayers-1\relax-\i) -- ++(1,0) node[right]{\fullyconnectednnOutput{\i}}; + } + \end{pgfonlayer} + \fi + \end{tikzpicture} + \end{center} + } + +\endinput +%% +%% End of file `nndraw.sty'. |