class_docstr: To run: "python -m unittest saliency.core.guided_ig_test" from the top-level directory.
docstr: Returns gradient of a quadratic function 2 * x1^2 + x2^2.
  
  The partial derivatives of the function with respect to x1 and x2 are
  independent from each other. For such functions, the Guided IG result
  should be equivalent to regular Integrated Gradients.
docstr_tok: ["Returns","gradient","of","a","quadratic","function","2","*","x1^2","+","x2^2",".","The","partial","derivatives","of","the","function","with","respect","to","x1","and","x2","are","independent","from","each","other",".","For","such","functions",",","the","Guided","IG","result","should","be","equivalent","to","regular","Integrated","Gradients","."]
code: def _quadratic_indep_test_func(
      self, x_value_batch, call_model_args, expected_keys
  ):
      """Returns gradient of a quadratic function 2 * x1^2 + x2^2.
  
      The partial derivatives of the function with respect to x1 and x2 are
      independent from each other. For such functions, the Guided IG result
      should be equivalent to regular Integrated Gradients.
      """
      self.assertListEqual(expected_keys, [INPUT_OUTPUT_GRADIENTS])
      return {
          INPUT_OUTPUT_GRADIENTS: [
              [4 * x_value_batch[0, 0], 2 * x_value_batch[0, 1]]
          ]
      }
  
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 2 for calling the GuidedIGTest obj's underlying member method code with example usage: obj._quadratic_indep_test_func(x_value_batch, call_model_args, expected_keys) and returns: dict