class_docstr: Clip by global norm.
  The global norm is the sum of norm for **all** gradients.
  
  See :func:`tf.clip_by_global_norm` for more information.
class_docstr_tok: ["Clip","by","global","norm",".","The","global","norm","is","the","sum","of","norm","for","*","*","all","*","*","gradients",".","See",":","func",":","`","tf.clip_by_global_norm","`","for","more","information","."]
code: def _process(self, grads):
      g = [k[0] for k in grads]
      v = [k[1] for k in grads]
      g, _ = tf.clip_by_global_norm(
          g, self._norm, name="clip_by_global_norm"
      )
      return list(zip(g, v))
  
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 GlobalNormClip obj's underlying member method code with example usage: obj._process(grads) and returns: list