code: def exp_exact():
      """Creates an exact explanation object."""
      meta = deepcopy(DEFAULT_META_PERMUTATION_IMPORTANCE)
      data = deepcopy(DEFAULT_DATA_PERMUTATION_IMPORTANCE)
  
      meta["params"] = {
          "feature_names": ["f_0", "f_1", "f_2", "f_3", "f_4"],
          "method": "exact",
          "kind": "difference",
          "n_repeats": 50,
          "sample_weight": None,
      }
  
      data["feature_names"] = ["f_0", "f_2", "f_4"]
      data["metric_names"] = [
          "mean_squared_error",
          "mean_absolute_error",
          "r2",
      ]
      data["feature_importance"] = [
          [3088.364, 7939.829, 4702.336],
          [35.848, 63.491, 50.199],
          [0.212, 0.539, 0.415],
      ]
      return Explanation(meta=meta, data=data)
  
imports: import re
  from copy import deepcopy
  import matplotlib.pyplot
  import numpy
  import pytest
  from pytest_lazyfixture import lazy_fixture
  from sklearn.metrics import accuracy_score, f1_score, max_error
  from alibi.api.defaults import DEFAULT_DATA_PERMUTATION_IMPORTANCE, DEFAULT_META_PERMUTATION_IMPORTANCE
  from alibi.api.interfaces import Explanation
  from alibi.explainers import PermutationImportance, plot_permutation_importance
label_desc: Use image node_id 17 for calling a global function with example usage: exp_exact() and returns: Explanation