code: def register_to_random_name(grad_f):
      """Register a gradient function to a random string.
  
      In order to use a custom gradient in TensorFlow, it must be registered to a
      string. This is both a hassle, and -- because only one function can every be
      registered to a string -- annoying to iterate on in an interactive
      environemnt.
  
      This function registers a function to a unique random string of the form:
  
        {FUNCTION_NAME}_{RANDOM_SALT}
  
      And then returns the random string. This is a helper in creating more
      convenient gradient overrides.
  
      Args:
        grad_f: gradient function to register. Should map (op, grad) -> grad(s)
  
      Returns:
        String that gradient function was registered to.
      """
      grad_f_name = grad_f.__name__ + "_" + str(uuid.uuid4())
      tf.RegisterGradient(grad_f_name)(grad_f)
      return grad_f_name
  
imports: from contextlib import contextmanager
  import numpy
  import tensorflow
  import uuid
label_desc: Use image node_id 1 for calling a global function with example usage: register_to_random_name(grad_f) and returns: grad_f_name