class_docstr: Interface for weight compression algorithm that acts on a per-layer basis.
  
  This allows both options of either decompressing during inference or
  decompressing prior to inference (where compression occurs by applying a
  tool such as zip to the model file).
  
  This interface is a purely functional one.
class_docstr_tok: ["Interface","for","weight","compression","algorithm","that","acts","on","a","per-layer","basis",".","This","allows","both","options","of","either","decompressing","during","inference","or","decompressing","prior","to","inference","(","where","compression","occurs","by","applying","a","tool","such","as","zip","to","the","model","file",")",".","This","interface","is","a","purely","functional","one","."]
code: def get_update_ops(self):
      return self.update_ops
  
file_path: model-optimization/tensorflow_model_optimization/python/core/common/keras/compression/algorithm.py
imports: import abc
  from typing import List, Any
  import dataclasses
  import tensorflow
  from tensorflow_model_optimization.python.core.common.keras.compression.internal import optimize
label_desc: Use image node_id 7 for calling the WeightCompressor obj's underlying member method code with example usage: obj.get_update_ops() and returns: self