class_docstr: Defines the ExplainerManager for explaining a text-based model.
class_docstr_tok: ["Defines","the","ExplainerManager","for","explaining","a","text-based","model","."]
docstr: Get explanation data
  
  :return: A array of ModelExplanationData.
  :rtype: List[ModelExplanationData]
docstr_tok: ["Get","explanation","data",":","return",":","A","array","of","ModelExplanationData",".",":","rtype",":","List","[","ModelExplanationData","]"]
code: def get_data(self):
      """Get explanation data
  
      :return: A array of ModelExplanationData.
      :rtype: List[ModelExplanationData]
      """
      return [self._get_interpret(i) for i in self.get()]
  
imports: import json
  import pickle
  import warnings
  from pathlib import Path
  from typing import Any, List, Optional
  import numpy
  import pandas
  import shap
  from raiutils.data_processing import convert_to_list
  from responsibleai._interfaces import FeatureImportance, ModelExplanationData, PrecomputedExplanations, TextFeatureImportance
  from responsibleai._internal.constants import ExplainerManagerKeys
  from responsibleai._internal.constants import ListProperties, ManagerNames, Metadata
  from responsibleai._tools.shared.state_directory_management import DirectoryManager
  from responsibleai.exceptions import UserConfigValidationException
  from responsibleai.managers.base_manager import BaseManager
  from responsibleai_text.common.constants import ModelTask, QuestionAnsweringFields, Tokens
  from responsibleai_text.utils.question_answering import QAPredictor
label_desc: Use image node_id 6 for calling the ExplainerManager obj's underlying member method code with example usage: obj.get_data() and returns: unknown