class_docstr: Base class for all gradient processors.
  Gradient processors can be applied to optimizers by
  :func:`optimizer.apply_grad_processors`.
  
  Subclass should override the ``_process()`` method.
class_docstr_tok: ["Base","class","for","all","gradient","processors",".","Gradient","processors","can","be","applied","to","optimizers","by",":","func",":","`","optimizer.apply_grad_processors","`",".","Subclass","should","override","the","``","_process","(",")","``","method","."]
code: def _process(self, grads):
      pass
  
imports: import inspect
  import re
  from abc import ABCMeta, abstractmethod
  import six
  import tensorflow
  from ..compat import tfv1
  from ..utils import logger
  from .summary import add_moving_summary
  from .symbolic_functions import print_stat, rms
label_desc: Use image node_id 2 for calling the GradientProcessor obj's underlying member method code with example usage: obj._process(grads) without return types