How to not repeat sns.kdeplot computation when looping through multiple method?

Question

I need to visualize a dataset distribution using several multiple method. Then I created a multiplehue_kdeplots function to generate three visual of the same dataset. It's working as expected, but as far as I can see on large dataset, the distribution is calculated three time (which takes time). How could I calculate it once and only change the way the distribution is displayed ?

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

np.random.seed(42)

df = pd.DataFrame({
    'category': np.random.randint(0, 4, size=500),
    'value': np.random.uniform(-10, 10, size=500)
})

def multiplehue_kdeplots(df, val_col, cat_col,
                         mults = ['layer', 'stack', 'fill'], leg_idx = None, pal = None,
                         **kwargs):
    fig, axs = plt.subplots(nrows=len(mults), sharex=True, **kwargs)
    if len(mults) == 1:
        axs = [axs]
    
    for i, m in enumerate(mults):
        leg = None
        if leg_idx == i:
            leg = True
        sns.kdeplot(data=df, x=val_col, hue=cat_col, fill=True, alpha=0.5, multiple=m,
            legend = leg, palette=pal, ax=axs[i])
        axs[i].set_title(mults[i].title())
        axs[i].set_ylabel('Density')

    fig.subplots_adjust(hspace=0.3)
    plt.show()

multiplehue_kdeplots(df, 'value', 'category')