合并分支 'shanweiqiao' 到 'caorunzhe'

13、15章图片颜色

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Chapter13/Figures/figure-curriculum-learning-framework.tex

@@ -4,10 +4,10 @@
 \tikzstyle{node}=[inner sep=0mm, draw,thick,minimum height=3em,minimum width=6em,rounded corners=5pt]
 
 
-\node[anchor=west,node,fill=ugreen!15] (n1) at (0,0) {训练集};
-\node[anchor=west,node,fill=yellow!15] (n2) at ([xshift=4em,yshift=0em]n1.east) {难度评估器};
-\node[anchor=west,node,fill=red!15] (n3) at ([xshift=4em,yshift=0em]n2.east) {训练调度器};
-\node[anchor=west,node,fill=blue!15] (n4) at ([xshift=4em,yshift=0em]n3.east) {模型训练器};
+\node[anchor=west,node,fill=ugreen!30] (n1) at (0,0) {训练集};
+\node[anchor=west,node,fill=yellow!30] (n2) at ([xshift=4em,yshift=0em]n1.east) {难度评估器};
+\node[anchor=west,node,fill=red!30] (n3) at ([xshift=4em,yshift=0em]n2.east) {训练调度器};
+\node[anchor=west,node,fill=blue!30] (n4) at ([xshift=4em,yshift=0em]n3.east) {模型训练器};
 
 \draw [->,very thick] ([xshift=0em,yshift=0em]n1.east) -- ([xshift=0em,yshift=0em]n2.west);
 \draw [->,very thick] ([xshift=0em,yshift=0em]n2.east) -- ([xshift=0em,yshift=0em]n3.west);

Chapter15/Figures/figure-encoder-structure-of-transformer-model-optimized-by-nas.tex

@@ -4,7 +4,7 @@
 %left
 \begin{scope}
 \foreach \x/\d in {1/2em, 2/8em}
-	\node[unit,fill=yellow!30] at (0,\d) (ln_\x) {层标准化};
+	\node[unit,fill=orange!30] at (0,\d) (ln_\x) {层标准化};
 
 \foreach \x/\d in {1/4em}
 	\node[unit,fill=green!30] at (0,\d) (sa_\x) {8头自注意力：512};
@@ -44,7 +44,7 @@
 
 
 \foreach \x/\d in {1/2em, 2/8em, 3/16em}
-	\node[unit,fill=yellow!30] at (0,\d) (ln_\x) {层标准化};
+	\node[unit,fill=orange!30] at (0,\d) (ln_\x) {层标准化};
 
 \foreach \x/\d in {1/6em, 2/14em, 3/20em}
 	\node[draw,circle,minimum size=1em,inner sep=1pt] at (0,\d) (add_\x) {\scriptsize\bfnew{+}};
@@ -83,7 +83,7 @@
 
 \node[minimum size=0.8em,inner sep=0pt,rounded corners=1pt,draw,fill=blue!30] (act) at (8em, 20em){};
 \node[anchor=west,font=\footnotesize] at ([xshift=0.1em]act.east){激活函数};
-\node[anchor=north,minimum size=0.8em,inner sep=0pt,rounded corners=1pt,draw,fill=yellow!30] (nor) at ([yshift=-0.6em]act.south){};
+\node[anchor=north,minimum size=0.8em,inner sep=0pt,rounded corners=1pt,draw,fill=orange!30] (nor) at ([yshift=-0.6em]act.south){};
 \node[anchor=west,font=\footnotesize] at ([xshift=0.1em]nor.east){层标准化};
 \node[anchor=north,minimum size=0.8em,inner sep=0pt,rounded corners=1pt,draw,fill=cyan!30] (wc) at ([yshift=-0.6em]nor.south){};
 \node[anchor=west,font=\footnotesize] at ([xshift=0.1em]wc.east){宽卷积};

Chapter15/Figures/figure-evolution-and-change-of-ml-methods.tex

 \begin{tikzpicture}
 
-\tikzstyle{opnode}=[rectangle,inner sep=0mm,minimum height=2em,minimum width=4em,rounded corners=5pt,fill=teal!30,draw,thick,drop shadow]
+\tikzstyle{opnode}=[rectangle,inner sep=0mm,minimum height=2em,minimum width=4em,rounded corners=5pt,fill=orange!30,draw,thick,drop shadow]
 \tikzstyle{cnode}=[circle,draw,minimum size=1.2em]
 \tikzstyle{mnode}=[rectangle,inner sep=0mm,minimum height=5em,minimum width=11em,rounded corners=5pt,fill=yellow!30,draw,thick,drop shadow]
 \tikzstyle{wnode}=[inner sep=0mm,minimum height=1.5em]

Chapter15/Figures/figure-main-flow-of-neural-network-structure-search.tex

@@ -6,8 +6,8 @@
 \tikzstyle{every node}=[scale=0.36]
 
 \node[draw,very thick,rounded corners=3pt,drop shadow,fill=red!30,minimum width=40em,minimum height=25em] (rec3) at (2.25,0){};
-\node[draw,very thick,rounded corners=3pt,drop shadow,fill=green!30,minimum width=22em,minimum height=25em] (rec2) at (-12.4,0){};
-\node[draw,very thick,rounded corners=3pt,drop shadow,fill=yellow!30,minimum width=24em,minimum height=25em] (rec1) at (-24,0){};
+\node[draw,very thick,rounded corners=3pt,drop shadow,fill=yellow!30,minimum width=22em,minimum height=25em] (rec2) at (-12.4,0){};
+\node[draw,very thick,rounded corners=3pt,drop shadow,fill=orange!30,minimum width=24em,minimum height=25em] (rec1) at (-24,0){};
 
 %left
 \node[] (label1) at (-26.4,4){\Huge\bfnew{结构空间}};

Chapter15/Figures/figure-multi-task-structure.tex

@@ -2,7 +2,7 @@
 \begin{tikzpicture}
 \begin{scope}
 
-\tikzstyle{enode}=[rectangle,inner sep=0mm,minimum height=5em,minimum width=5em,rounded corners=7pt,fill=green!30,draw,thick]
+\tikzstyle{enode}=[rectangle,inner sep=0mm,minimum height=5em,minimum width=5em,rounded corners=7pt,fill=blue!30,draw,thick]
 \tikzstyle{dnode}=[rectangle,inner sep=0mm,minimum height=2em,minimum width=6.5em,rounded corners=5pt,fill=red!30,draw,thick]
 \tikzstyle{wnode}=[inner sep=0mm,minimum height=2em,minimum width=4em]
 

Chapter15/Figures/figure-structure-search-based-on-gradient-method.tex

@@ -4,9 +4,9 @@
 \begin{tikzpicture}
 \tikzstyle{node}=[minimum height=6em,inner sep=4pt,align=left,draw,font=\footnotesize,rounded corners=4pt,thick,drop shadow]
 
-\node[node,fill=red!30] (n1) at (0,0){\scriptsize\bfnew{超网络}： \\ [1ex] 模型结构参数 \\[0.4ex] 网络参数};
+\node[node,fill=orange!30] (n1) at (0,0){\scriptsize\bfnew{超网络}： \\ [1ex] 模型结构参数 \\[0.4ex] 网络参数};
 \node[anchor=west,node,fill=yellow!30] (n2) at ([xshift=4em]n1.east){\scriptsize\bfnew{优化后的超网络}： \\ [1ex]模型{\color{red}结构参数}（已优化） \\ [0.4ex]网络参数（已优化）};
-\node[anchor=west,node,fill=green!30] (n3) at ([xshift=6em]n2.east){\scriptsize\bfnew{找到的模型结构}};
+\node[anchor=west,node,fill=red!30] (n3) at ([xshift=6em]n2.east){\scriptsize\bfnew{找到的模型结构}};
 
 \draw[-latex,thick] (n1.0) -- node[above,align=center,font=\scriptsize]{优化后的\\超网络}(n2.180);
 \draw[-latex,thick] (n2.0) -- node[above,align=center,font=\scriptsize]{根据结构参数\\离散化结构}(n3.180);

Chapter15/Figures/figure-structure-search-based-on-reinforcement-learning.tex

@@ -5,7 +5,7 @@
 \tikzstyle{node}=[minimum height=2.5em,minimum width=8em,draw,rounded corners=2pt,thick,drop shadow]
 
 \node[node,fill=red!30] (n1) at (0,0){\small\bfnew{环境}};
-\node[anchor=south,node,fill=green!30] (n2) at ([yshift=5em]n1.north){\small\bfnew{智能体}};
+\node[anchor=south,node,fill=blue!30] (n2) at ([yshift=5em]n1.north){\small\bfnew{智能体}};
 \node[anchor=north,font=\footnotesize] at ([yshift=-0.2em]n1.south){（结构所应用于的任务）};
 \node[anchor=south,font=\footnotesize] at ([yshift=0.2em]n2.north){（结构生成器）};