code: def _parse_policy_info(
      name, prob, level, replace_value, augmentation_hparams
  ):
      """Return the function that corresponds to `name` and update `level` param."""
      func = NAME_TO_FUNC[name]
      args = level_to_arg(augmentation_hparams)[name](level)
  
      # Check to see if prob is passed into function. This is used for operations
      # where we alter bboxes independently.
      # pytype:disable=wrong-arg-types
      if "prob" in inspect.getfullargspec(func).args:
          args = tuple([prob] + list(args))
      # pytype:enable=wrong-arg-types
  
      # Add in replace arg if it is required for the function that is being called.
      # pytype:disable=wrong-arg-types
      if "replace" in inspect.getfullargspec(func).args:
          # Make sure replace is the final argument
          assert "replace" == inspect.getfullargspec(func).args[-1]
          args = tuple(list(args) + [replace_value])
      # pytype:enable=wrong-arg-types
  
      return (func, prob, args)
  
imports: import dataclasses
  import inspect
  import math
  import tensorflow.compat.v1
  from tensorflow_addons import image
label_desc: Use image node_id 29 for calling a global function with example usage: _parse_policy_info(name, prob, level, replace_value, augmentation_hparams) and returns: func,  prob,  args