code: def test_relu_gradient(self):
      out_layer = layers.ReLU(
          nonlinear_mxts_mode=layers.NonlinearMxtsMode.Gradient
      )
      (
          fprop_results,
          bprop_results_each_task,
      ) = self.set_up_prediction_func_and_deeplift_func(out_layer)
  
      np.testing.assert_almost_equal(
          np.array(bprop_results_each_task[0]),
          np.array([np.array(self.w1), np.array(self.w1)]),
          decimal=5,
      )
      np.testing.assert_almost_equal(
          np.array(bprop_results_each_task[1]),
          np.array([np.zeros_like(self.w2), np.zeros_like(self.w2)]),
          decimal=5,
      )
  
file_path: deeplift/tests/layers/test_activation.py
imports: from __future__ import division
  from __future__ import print_function
  from __future__ import absolute_import
  import unittest
  from unittest import skip
  import sys
  import os
  import numpy
  import deeplift.layers
  from deeplift.layers import DenseMxtsMode
  from deeplift.util import compile_func
  import tensorflow
label_desc: Use image node_id 4 for calling the TestActivations obj's underlying member method code with example usage: obj.test_relu_gradient() without return types