class_docstr: Guided Integrated Gradients interpreter.
class_docstr_tok: ["Guided","Integrated","Gradients","interpreter","."]
code: def config_spec(self) -> types.Spec:
      return super().config_spec() | {
          INTERPOLATION_KEY: types.Scalar(
              min_val=5,
              max_val=200,
              default=IG_STEPS,
              step=1,
              required=False,
          ),
          MAX_DIST_KEY: types.Scalar(
              min_val=0.0,
              max_val=1.0,
              default=0.1,
              step=0.02,
              required=False,
          ),
      }
  
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 3 for calling the GuidedIG obj's underlying member method code with example usage: obj.config_spec() and returns: unknown