code: def _update_config(self, settings):
      self._config = FilterConfig(
          attribution_method=settings["attribution_method"],
          attribution_arguments=settings["arguments"],
          prediction=settings["prediction"],
          classes=settings["classes"],
          num_examples=4,
      )
  
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 3 for calling the AttributionVisualizer obj's underlying member method code with example usage: obj._update_config(settings) without return types