class_docstr: Defines the ExplainerManager for explaining a model.
class_docstr_tok: ["Defines","the","ExplainerManager","for","explaining","a","model","."]
code: def _find_first_explanation(self, key, mli_explanations):
      if mli_explanations is None:
          return None
      new_array = [
          explanation
          for explanation in mli_explanations
          if explanation[ExplanationKeys.EXPLANATION_TYPE_KEY] == key
      ]
      if len(new_array) > 0:
          return new_array[0]["value"]
      return None
  
imports: import json
  import warnings
  from pathlib import Path
  from typing import Any, List, Optional
  import numpy
  import pandas
  from interpret_community.explanation.explanation import FeatureImportanceExplanation, load_explanation, save_explanation
  from interpret_community.mimic.mimic_explainer import MimicExplainer
  from interpret_community.mimic.models.lightgbm_model import LGBMExplainableModel
  from interpret_community.mimic.models.linear_model import LinearExplainableModel
  from scipy.sparse import issparse
  from raiutils.data_processing import convert_to_list
  from raiutils.exceptions import UserConfigValidationException
  from raiutils.models import ModelTask
  from responsibleai._interfaces import EBMGlobalExplanation, FeatureImportance, ModelExplanationData, PrecomputedExplanations
  from responsibleai._internal.constants import ExplainerManagerKeys
  from responsibleai._internal.constants import ExplanationKeys, ListProperties, ManagerNames, Metadata
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.managers.base_manager import BaseManager
  from responsibleai.utils import _find_features_having_missing_values, _measure_time
label_desc: Use image node_id 14 for calling the ExplainerManager obj's underlying member method code with example usage: obj._find_first_explanation(key, mli_explanations) and returns: None, None, new_array