code: def get_insights_config(self):
      return {
          "classes": self.classes,
          "methods": list(ATTRIBUTION_NAMES_TO_METHODS.keys()),
          "method_arguments": namedtuple_to_dict(
              {
                  k: v.params
                  for (k, v) in ATTRIBUTION_METHOD_CONFIG.items()
              }
          ),
          "selected_method": self._config.attribution_method,
      }
  
imports: from collections import namedtuple
  from itertools import cycle
  from typing import Any, Callable, Dict, Iterable, List, NamedTuple, Optional, Tuple, Union
  import torch
  from captum.attr import IntegratedGradients
  from captum.attr._utils.batching import _batched_generator
  from captum.insights.attr_vis.attribution_calculation import AttributionCalculation, OutputScore
  from captum.insights.attr_vis.config import ATTRIBUTION_METHOD_CONFIG, ATTRIBUTION_NAMES_TO_METHODS
  from captum.insights.attr_vis.features import BaseFeature
  from captum.insights.attr_vis.server import namedtuple_to_dict
  from captum.log import log_usage
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 13 for calling the AttributionVisualizer obj's underlying member method code with example usage: obj.get_insights_config() and returns: dict