class_docstr: Encoding stage applying clipping by norm (L-2 ball projection).
  
  See `tf.clip_by_norm` for more information.
class_docstr_tok: ["Encoding","stage","applying","clipping","by","norm","(","L-2","ball","projection",")",".","See","`","tf.clip_by_norm","`","for","more","information","."]
docstr: Initializer for the `ClipByNormEncodingStage`.
  
  Args:
    clip_norm: A scalar, norm of the ball onto which to project.
docstr_tok: ["Initializer","for","the","`","ClipByNormEncodingStage","`",".","Args",":","clip_norm",":","A","scalar",",","norm","of","the","ball","onto","which","to","project","."]
code: def __init__(self, clip_norm):
      """Initializer for the `ClipByNormEncodingStage`.
  
      Args:
        clip_norm: A scalar, norm of the ball onto which to project.
      """
      self._clip_norm = clip_norm
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import tensorflow
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.core import encoding_stage
label_desc: Use image node_id 1 to create a new ClipByNormEncodingStage object from inherited base classes: encoding_stage with example: obj = ClipByNormEncodingStage(clip_norm)