class_docstr: To run: "python -m unittest saliency.core.guided_ig_test" from the top-level directory.
docstr: Tests attributions of the linear function with provided baseline.
  
  The expected result should be equal to the regular Integrated Gradients
  attribution.
docstr_tok: ["Tests","attributions","of","the","linear","function","with","provided","baseline",".","The","expected","result","should","be","equal","to","the","regular","Integrated","Gradients","attribution","."]
code: def testGuidedIGLinearWithBaseline(self):
      """Tests attributions of the linear function with provided baseline.
  
      The expected result should be equal to the regular Integrated Gradients
      attribution.
      """
      gig = guided_ig.GuidedIG()
      mask = gig.GetMask(
          x_value=[10.0, 5.0],
          call_model_function=self._linear_test_func,
          call_model_args="airplane",
          x_baseline=[-1.0, -3.0],
          x_steps=10,
          fraction=0.1,
          max_dist=0.5,
      )
      np.testing.assert_allclose(mask, [22.0, 8.0])
  
file_path: saliency/saliency/core/guided_ig_test.py
imports: import unittest
  from .None import guided_ig
  from .base import INPUT_OUTPUT_GRADIENTS
  import numpy
label_desc: Use image node_id 4 for calling the GuidedIGTest obj's underlying member method code with example usage: obj.testGuidedIGLinearWithBaseline() without return types