class_docstr: Defines the ExplainerManager for explaining a model.
class_docstr_tok: ["Defines","the","ExplainerManager","for","explaining","a","model","."]
docstr: Creates an explanation by running the explainer on the model.
docstr_tok: ["Creates","an","explanation","by","running","the","explainer","on","the","model","."]
code: def compute(self):
      """Creates an explanation by running the explainer on the model."""
  
      print("Explanations")
      print(
          "Current Status: Explaining {0} features".format(
              len(self._features)
          )
      )
      if not self._is_added:
          return
      if self._is_run:
          return
      self._explanation = self._compute_explanations(
          local=True, data=self._evaluation_examples
      )
      self._is_run = True
  
      print(
          "Current Status: Explained {0} features.".format(
              len(self._features)
          )
      )
  
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 5 for calling the ExplainerManager obj's underlying member method code with example usage: obj.compute() without return types