class_docstr: To run: "python -m unittest saliency.core.guided_ig_test" from the top-level directory.
docstr: Tests attributions of the quadratic function with independent partials.
  
  The expected result should be equal to the regular Integrated Gradients
  attribution regardless of the parameters. This method tests the case when
  the baseline values are higher than the input.
docstr_tok: ["Tests","attributions","of","the","quadratic","function","with","independent","partials",".","The","expected","result","should","be","equal","to","the","regular","Integrated","Gradients","attribution","regardless","of","the","parameters",".","This","method","tests","the","case","when","the","baseline","values","are","higher","than","the","input","."]
code: def testIndependentQuadraticInputIsLessThanBaseline(self):
      """Tests attributions of the quadratic function with independent partials.
  
      The expected result should be equal to the regular Integrated Gradients
      attribution regardless of the parameters. This method tests the case when
      the baseline values are higher than the input.
      """
      gig = guided_ig.GuidedIG()
      mask = gig.GetMask(
          x_value=[0, 0],
          call_model_function=self._quadratic_indep_test_func,
          x_baseline=[3, 3],
          x_steps=1000,
          fraction=0.1,
          max_dist=0.4,
      )
      np.testing.assert_allclose(mask, [-18.0, -9.0], rtol=0.01)
  
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 7 for calling the GuidedIGTest obj's underlying member method code with example usage: obj.testIndependentQuadraticInputIsLessThanBaseline() without return types