code: def test_save_SimilartyExplainer(
      similarity_explainer, ffn_classifier, iris_data
  ):
      X = iris_data["X_test"][:2]
      exp0 = similarity_explainer.explain(X)
      with tempfile.TemporaryDirectory() as temp_dir:
          similarity_explainer.save(temp_dir)
          similarity_explainer1 = load_explainer(
              temp_dir, predictor=ffn_classifier
          )
          assert isinstance(similarity_explainer1, GradientSimilarity)
          assert similarity_explainer.meta == similarity_explainer1.meta
          exp1 = similarity_explainer1.explain(X)
          assert exp0.meta == exp1.meta
          assert (exp0.data["scores"] == exp1.data["scores"]).all()
          assert (
              exp0.data["ordered_indices"]
              == exp1.data["ordered_indices"]
          ).all()
          assert (
              exp0.data["most_similar"] == exp1.data["most_similar"]
          ).all()
          assert (
              exp0.data["least_similar"] == exp1.data["least_similar"]
          ).all()
  
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 30 for calling a global function with example usage: test_save_SimilartyExplainer(similarity_explainer, ffn_classifier, iris_data) without return types