code: def plot(self, xs, ys, auc):
      pl.plot(xs, ys, label="AUC %0.4f" % auc)
      pl.legend()
      xlabel = (
          "Percent Unmasked"
          if self.perturbation == "keep"
          else "Percent Masked"
      )
      pl.xlabel(xlabel)
      pl.ylabel("Model Output")
      pl.show()
  
file_path: shap/shap/benchmark/_sequential.py
imports: import time
  import matplotlib.pyplot
  import numpy
  import pandas
  import sklearn
  from tqdm.auto import tqdm
  from shap import Explanation, links
  from shap.maskers import FixedComposite, Image, Text
  from shap.utils import MaskedModel
  from ._result import BenchmarkResult
label_desc: Use image node_id 4 for calling the SequentialPerturbation obj's underlying member method code with example usage: obj.plot(xs, ys, auc) without return types