class_docstr: Encoding stage applying clipping by value (L-infinity ball projection).
  
  See `tf.clip_by_value` for more information.
class_docstr_tok: ["Encoding","stage","applying","clipping","by","value","(","L-infinity","ball","projection",")",".","See","`","tf.clip_by_value","`","for","more","information","."]
docstr: Initializer for the `ClipByValueEncodingStage`.
  
  Args:
    clip_value_min: A scalar, the minimum value to which to clip.
    clip_value_max: A scalar, the maximum value to which to clip.
docstr_tok: ["Initializer","for","the","`","ClipByValueEncodingStage","`",".","Args",":","clip_value_min",":","A","scalar",",","the","minimum","value","to","which","to","clip",".","clip_value_max",":","A","scalar",",","the","maximum","value","to","which","to","clip","."]
code: def __init__(self, clip_value_min, clip_value_max):
      """Initializer for the `ClipByValueEncodingStage`.
  
      Args:
        clip_value_min: A scalar, the minimum value to which to clip.
        clip_value_max: A scalar, the maximum value to which to clip.
      """
      self._clip_value_min = clip_value_min
      self._clip_value_max = clip_value_max
  
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 ClipByValueEncodingStage object from inherited base classes: encoding_stage with example: obj = ClipByValueEncodingStage(clip_value_min, clip_value_max)