code: def test_gradient_maps(self):
      self.ig = gradient_maps.IntegratedGradients()
  
      # Basic test with dummy outputs from the model.
      inputs = [{"segment": "_"}]
      model = testing_utils.ClassificationModelForTesting()
      dataset = lit_dataset.Dataset(None, None)
      output = self.ig.run(inputs, model, dataset)
  
      self.assertLen(output, 1)
  
      salience = output[0]["input_embs_grad"].salience
      target = np.array([0.25, 0.25, 0.25, 0.25])
      self.assertTrue((salience == target).all())
  
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 2 for calling the GradientMapsTest obj's underlying member method code with example usage: obj.test_gradient_maps() without return types