code: def test_surrogate_explainer(data_for_task_type, method):
      data, pipeline = data_for_task_type
      train, _ = train_test_data_setup(data)
      pipeline.fit(input_data=train)
  
      explainer = explain_pipeline(
          pipeline, data=train, method=method, visualization=False
      )
  
      assert isinstance(explainer, SurrogateExplainer)
      assert isinstance(explainer.surrogate, Pipeline)
      assert explainer.surrogate.is_fitted
      assert isinstance(explainer.score, float) and explainer.score > 0
  
file_path: FEDOT/test/unit/explainability/test_pipeline_explanation.py
imports: from copy import deepcopy
  from typing import Tuple
  import numpy
  import pytest
  from sklearn.datasets import load_iris, load_diabetes
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.explainability.explainers import explain_pipeline
  from fedot.explainability.surrogate_explainer import SurrogateExplainer, get_simple_pipeline
label_desc: Use image node_id 2 for calling a global function with example usage: test_surrogate_explainer(data_for_task_type, method) without return types