class_docstr: Defines the ExplainerManager for explaining a model.
class_docstr_tok: ["Defines","the","ExplainerManager","for","explaining","a","model","."]
docstr: List information about the ExplainerManager.
  
  :return: A dictionary of properties.
  :rtype: dict
docstr_tok: ["List","information","about","the","ExplainerManager",".",":","return",":","A","dictionary","of","properties",".",":","rtype",":","dict"]
code: def list(self):
      """List information about the ExplainerManager.
  
      :return: A dictionary of properties.
      :rtype: dict
      """
      props = {ListProperties.MANAGER_TYPE: self.name}
      if self._explanation:
          props[Keys.ID] = self._explanation.id
          props[Keys.METHOD] = self._explanation.method
          props[Keys.MODEL_TASK] = self._explanation.model_task
          props[Keys.MODEL_TYPE] = self._explanation.model_type
          if FeatureImportanceExplanation._does_quack(
              self._explanation
          ):
              props[Keys.IS_RAW] = self._explanation.is_raw
              props[
                  Keys.IS_ENGINEERED
              ] = self._explanation.is_engineered
          props[Keys.IS_COMPUTED] = True
      else:
          props[Keys.IS_COMPUTED] = False
      return props
  
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 7 for calling the ExplainerManager obj's underlying member method code with example usage: obj.list() and returns: props