code: def test_gradient_override_map():
      def gradient_override(op, grad):
          return tf.constant(42)
  
      with tf.Session().as_default() as sess:
          global_step = tf.train.get_or_create_global_step()
          init_global_step = tf.variables_initializer([global_step])
          init_global_step.run()
  
          a = tf.constant(1.0)
          standard_relu = tf.nn.relu(a)
          grad_wrt_a = tf.gradients(standard_relu, a, [1.0])[0]
          with gradient_override_map({"Relu": gradient_override}):
              overriden_relu = tf.nn.relu(a)
              overriden_grad_wrt_a = tf.gradients(
                  overriden_relu, a, [1.0]
              )[0]
          assert grad_wrt_a.eval() != overriden_grad_wrt_a.eval()
          assert overriden_grad_wrt_a.eval() == 42
  
file_path: lucid/tests/misc/test_gradient_override.py
imports: import pytest
  import tensorflow
  from lucid.misc.gradient_override import use_gradient
  from lucid.misc.gradient_override import gradient_override_map
  from lucid.misc.redirected_relu_grad import redirected_relu_grad, redirected_relu6_grad
label_desc: Use image node_id 2 for calling a global function with example usage: test_gradient_override_map() and returns: tf