code: def zou_et_al_criterion_rescaling(
      criterion, n_samples, noise_variance
  ):
      """Rescale the information criterion to follow the definition of Zou et al."""
      return (
          criterion
          - n_samples * np.log(2 * np.pi * noise_variance)
          - n_samples
      )
  
imports: from sklearn.datasets import load_diabetes
  from sklearn.linear_model import LassoLarsIC
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  import numpy
  import matplotlib.pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: zou_et_al_criterion_rescaling(criterion, n_samples, noise_variance) and returns: unknown