code: def plot_homoscedasticity_diagnostics(model: SklearnModel, ax=None):
      if ax is None:
          _, ax = plt.subplots(1, 1, figsize=(5, 5))
      sns.regplot(
          model.predict(model.data.X.values),
          model.residuals(model.data.X.values),
          ax=ax,
      )
      ax.set_title("Fitted Values V Residuals")
      ax.set_xlabel("Fitted Value")
      ax.set_ylabel("Residual")
      return ax
  
imports: import seaborn
  import statsmodels.api
  from matplotlib import pyplot
  from ..sklearnmodel import SklearnModel
label_desc: Use image node_id 2 for calling a global function with example usage: plot_homoscedasticity_diagnostics(model, ax) and returns: ax