code: def update(
      model,
      attributions,
      X,
      y,
      masker,
      sort_order,
      perturbation_method,
      scores,
  ):
      metric = perturbation_method + " " + sort_order
      sp = perturbation.SequentialPerturbation(
          model, masker, sort_order, perturbation_method
      )
      xs, ys, auc = sp.model_score(attributions, X, y=y)
      scores["metrics"].append(metric)
      scores["values"][metric] = [xs, ys, auc]
  
file_path: shap/shap/benchmark/framework.py
imports: import itertools
  import matplotlib.pyplot
  import numpy
  import pandas
  from .None import perturbation
label_desc: Use image node_id 1 for calling a global function with example usage: update(model, attributions, X, y, masker, sort_order, perturbation_method, scores) without return types