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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def learning_rate_schedule(hparams):
 """Learning rate schedule based on hparams."""

  mlperf_log.transformer_print(key=mlperf_log.OPT_LR, deferred=True)
  mlperf_log.transformer_print(
      key=mlperf_log.OPT_LR_WARMUP_STEPS,
      value=hparams.learning_rate_warmup_steps)
  step_num = _global_step(hparams)
  schedule_string = hparams.learning_rate_schedule
  names = schedule_string.split("*")
  names = [name.strip() for name in names if name.strip()]
  ret = tf.constant(1.0)
  for name in names:
    ret *= learning_rate_factor(name, step_num, hparams)
  return ret