code: def test_save_KernelShap(kshap_explainer, lr_classifier, adult_data):
      predictor = predict_fcn(
          predict_type="proba",
          clf=lr_classifier,
          preproc=adult_data["preprocessor"],
      )
      X = adult_data["X_test"][:2]
  
      exp0 = kshap_explainer.explain(X)
  
      with tempfile.TemporaryDirectory() as temp_dir:
          kshap_explainer.save(temp_dir)
          kshap_explainer1 = load_explainer(
              temp_dir, predictor=predictor
          )
  
          assert isinstance(kshap_explainer1, KernelShap)
          assert kshap_explainer.meta == kshap_explainer1.meta
  
          exp1 = kshap_explainer.explain(X)
          assert exp0.meta == exp1.meta
  
imports: import numbers
  import sys
  import numpy
  from numpy.testing import assert_allclose
  import pytest
  from pytest_lazyfixture import lazy_fixture
  from sklearn.linear_model import LogisticRegression
  from sklearn.ensemble import RandomForestClassifier
  import tempfile
  import tensorflow
  from typing import List, Union
  from alibi.explainers import ALE, AnchorImage, AnchorTabular, AnchorText, IntegratedGradients, KernelShap, TreeShap, CounterfactualRLTabular, GradientSimilarity
  from alibi.explainers.integrated_gradients import LayerState
  from alibi.saving import load_explainer
  from alibi_testing.data import get_adult_data, get_iris_data, get_movie_sentiment_data
  import alibi_testing
  from alibi.utils.download import spacy_model
  from alibi.explainers.tests.utils import predict_fcn
label_desc: Use image node_id 27 for calling a global function with example usage: test_save_KernelShap(kshap_explainer, lr_classifier, adult_data) without return types