code: def test_ig_init_args(
      self, autorun, class_key, interpolation_steps, normalize
  ):
      params = {}
      if autorun is not None:
          params["autorun"] = autorun
      if class_key is not None:
          params["class_key"] = class_key
      if interpolation_steps is not None:
          params["interpolation_steps"] = interpolation_steps
      if normalize is not None:
          params["normalize"] = normalize
  
      ig = gradient_maps.IntegratedGradients(**params)
      config_spec = ig.config_spec()
  
      if autorun is not None:
          self.assertEqual(ig.meta_spec()["saliency"].autorun, autorun)
      if class_key is not None:
          self.assertEqual(config_spec[_CLASS_KEY].default, class_key)
      if interpolation_steps is not None:
          self.assertEqual(
              config_spec[_INTERPOLATION_KEY].default,
              interpolation_steps,
          )
      if normalize is not None:
          self.assertEqual(
              config_spec[_NORMALIZATION_KEY].default, normalize
          )
  
file_path: lit/lit_nlp/components/gradient_maps_test.py
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from lit_nlp.api import dataset
  from lit_nlp.components import gradient_maps
  from lit_nlp.lib import testing_utils
  import numpy
label_desc: Use image node_id 6 for calling the GradientMapsTest obj's underlying member method code with example usage: obj.test_ig_init_args(autorun, class_key, interpolation_steps, normalize) without return types