code: def test_regression(self):
      interpreter = image_gradient_maps.GuidedIG()
      model = RegressionTestModel()
      self.assertTrue(
          interpreter.is_compatible(
              model, lit_dataset.NoneDataset({"test": model})
          )
      )
  
      input_image_array = np.zeros(shape=[20, 15, 3], dtype=np.uint8)
      input_image_array[0, 0, 0] = 10
      input_image_array[1, 0, 0] = 20
  
      pil_image = PILImage.fromarray(input_image_array, mode="RGB")
  
      inp = {"image": image_utils.convert_pil_to_image_str(pil_image)}
      run_output = interpreter.run(
          inputs=[inp], model=model, dataset=lit_dataset.Dataset()
      )[0]
      self.assertIn("grads", run_output)
      overlay_str = run_output["grads"]
      overlay_bytes = image_utils.convert_image_str_to_array(
          overlay_str, shape=RegressionTestModel.GRADIENT_SHAPE
      )
      self.assertIsNotNone(overlay_bytes)
      self.assertSequenceEqual(
          overlay_bytes.shape, RegressionTestModel.GRADIENT_SHAPE
      )
  
imports: from absl.testing import absltest
  from lit_nlp.api import dataset
  from lit_nlp.api import model
  from lit_nlp.api import types
  from lit_nlp.components import image_gradient_maps
  from lit_nlp.lib import image_utils
  import numpy
  from PIL import Image
label_desc: Use image node_id 2 for calling the ImageGradientsMapsTest obj's underlying member method code with example usage: obj.test_regression() without return types