% superfig golden example 1 -- one horizontal paper-figure pipeline.
% Main path is input -> model -> prediction. Loss is a side object, not a
% station on the forward path.
%   ../scripts/build.sh pipeline.tex
\documentclass[border=10pt]{standalone}
\usepackage[cjk]{superfig}

\sfsetrole{input}{sfTeal}
\sfsetrole{model}{sfOrange}
\sfsetrole{loss}{sfCoral}
\sfsetrole{output}{sfViolet}

\begin{document}
\begin{tikzpicture}

\sfstage{SA}{推理流程：一次前向}
\sfrow{R1}{16mm}
  \sfnode[role=input]{x}{输入 $x$}{16mm}{12mm}
  \sfconn{e1}{预处理}
  \sfnode[role=model]{f}{模型 $f_\theta$}{18mm}{12mm}
  \sfconn{e2}{logits}
  \sfnode[role=output]{y}{预测 $\hat y$}{16mm}{12mm}
\sfrowend

% Loss compares the prediction with the target; it is not on the main path.
% Hang it below ŷ with enough shaft that no caption sits on the arrow.
\sfnode[role=loss, at={($(y.south)+(0,-22mm)$)}]{s}{损失 $L$}{14mm}{12mm}
\sfarrowlabel{y.south}{s.north}{$L(\hat y,y)$}

\sflane{R1}
\sfcaption{x}{$x$}{原始输入}
\sfcaption{f}{$f_\theta$}{可学习参数}
\sfnolane
\sfcaption{s}{$L$}{与真值比较}

\sfbbox{all}
\sftopformula{F}{%
  $x \;\xrightarrow{\;f_\theta\;}\; \hat y,\qquad
   \min_\theta\; L\bigl(f_\theta(x),\,y\bigr)$}
\sfmeaningbox{mb}{96mm}{all}
  {一次从输入到预测的前向；损失在预测之后单独计算}
  {数据、模型参数、预测、损失}
  {预处理后送入模型；模型产生 logits 得到预测；损失比较预测与真值，梯度再回到参数}
\sfsignature{推理流程示意}{mb}

\end{tikzpicture}
\end{document}