\begin{figure}[!tbh]
\definecolor{blue}{RGB}{42, 179, 205}
\definecolor{green}{RGB}{250, 231, 35}
\definecolor{orange}{RGB}{253, 127, 116}
\definecolor{red}{RGB}{150, 55, 173}
\centering
    \begin{tikzpicture}
        \pgfplotstableread[col sep=comma]{figures/esoteric/norms/conv2d_norms_pivoted_acdc.csv}\datatable
\begin{axis}[
ylabel={$\|W_{d}\|_{2}$},
xlabel={Depth},
xtick={0,2,...,32},
ytick={0, 5, ..., 20},
ylabel style={align=center},
width=0.8\linewidth,
height=6cm,
grid=both,grid style={line width=.1pt, draw=gray!10},major grid style={line width=.1pt,draw=gray!10}, clip=false
]
 \addplot[black!80!white,mark=*] table [x index=0, y index=1] {\datatable};
 % \addlegendentry{None};

 \addplot[blue,mark=square*] table [x index=0, y index=2] {\datatable};
 % \addlegendentry{Augmix};

 \addplot[green,mark=diamond*] table [x index=0, y index=3] {\datatable};
 % \addlegendentry{Prime};

 \addplot[orange,mark=triangle*] table [x index=0, y index=4] {\datatable};

  \addplot[red,mark=x] table [x index=0, y index=5] {\datatable};

 % \addlegendentry{TA};
\end{axis}
\end{tikzpicture}
    
\begin{tikzpicture}
    \begin{customlegend}[legend columns=-1,legend style={draw=none,column sep=1ex},legend entries={\scriptsize No Aug., \scriptsize Base, \scriptsize w/ MixUp, \scriptsize w/ AFA, \scriptsize w/ AugMix + AFA}]
    \addlegendimage{black,fill=black!80!white,mark=*,mark options={scale=0.5}, sharp plot}
    \addlegendimage{blue,fill=blue,mark=square*}
    \addlegendimage{green,fill=green,mark=diamond*}
    \addlegendimage{orange,fill=orange,mark=triangle*}
    \addlegendimage{red,fill=red,mark=x}
    \end{customlegend}
\end{tikzpicture}
\caption{The norm of the weights of convolutional kernels $W$ at different depths, $d$, for different nnU-Nets trained on ACDC with different augmentation techniques. The plot highlights the regularisation effect the methods have on the model weights.}
\label{fig:reg_effect_acdc}
\end{figure}
