class_docstr: Guided Integrated Gradients interpreter.
class_docstr_tok: ["Guided","Integrated","Gradients","interpreter","."]
code: def get_visualization_params(self) -> dict[str, Any]:
      return {
          "cm_name": DIVERGING_COLOR_MAP,
          "clip_fraction": CLIPPING_FRACTION,
          "alpha_mul": PIXEL_SALIENCY_ALPHA_MUL,
          "signed": True,
          "pixel_saliency": True,
      }
  
imports: import abc
  from collections.abc import Callable
  from typing import Any, NamedTuple, Optional, cast
  from absl import logging
  from lit_nlp.api import components
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.lib import image_utils
  from lit_nlp.lib import utils
  import numpy
  import saliency
label_desc: Use image node_id 4 for calling the GuidedIG obj's underlying member method code with example usage: obj.get_visualization_params() and returns: dict