class_docstr: To run: "python -m unittest saliency.tf1.guided_ig_test" from the top-level directory.
class_docstr_tok: ["To","run",":","``","python","-m","unittest","saliency.tf1.guided_ig_test","''","from","the","top-level","directory","."]
docstr: Returns input and output for linear function 2 * x1 + x2.
  
  Guided IG for linear function produces tha same attribution as Integrated
  Gradients regardless of the parameters.
docstr_tok: ["Returns","input","and","output","for","linear","function","2","*","x1","+","x2",".","Guided","IG","for","linear","function","produces","tha","same","attribution","as","Integrated","Gradients","regardless","of","the","parameters","."]
code: def _linear_test_model(self):
      """Returns input and output for linear function 2 * x1 + x2.
  
      Guided IG for linear function produces tha same attribution as Integrated
      Gradients regardless of the parameters.
      """
      x = tf.placeholder(tf.float32, (None, 2), "input")
      y = 2 * x[:, 0] + x[:, 1]
      return x, y
  
file_path: saliency/saliency/tf1/guided_ig_test.py
imports: import unittest
  from .None import guided_ig
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling the GuidedIGTest obj's underlying member method code with example usage: obj._linear_test_model() and returns: x,  y