code: def learning_rate_scheduler(
      epoch, values=(0.1, 0.01, 0.001), breakpoints=(100, 150)
  ):
      """Piecewise constant schedule for learning rate."""
      idx = sum(1 if epoch > b else 0 for b in breakpoints)
      return values[idx]
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/trainer.py
imports: from absl import logging
  import gin
  from multi_representation_adversary import data
  from multi_representation_adversary import helper
  from multi_representation_adversary import resnet
  from multi_representation_adversary import selectors
  import tensorflow.compat.v2
label_desc: Use image node_id 1 for calling a global function with example usage: learning_rate_scheduler(epoch, values, breakpoints) and returns: values