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","."]
docstr: Args:
      global_norm(float): the threshold to clip with.
docstr_tok: ["Args",":","global_norm","(","float",")",":","the","threshold","to","clip","with","."]
code: def __init__(self, global_norm):
      """
      Args:
          global_norm(float): the threshold to clip with.
      """
      super(GlobalNormClip, self).__init__()
      self._norm = float(global_norm)
  
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 1 to create a new GlobalNormClip object from inherited base classes: GradientProcessor with example: obj = GlobalNormClip(global_norm)