class_docstr: Base class for noise multiplier schedulers. We follow the same API
  as the standard PyTorch LR schedulers, but apply them to Opacus's noise
  multiplier param instead.
  
  This means it only works when you pass a opacus.DPOptimizer, since that
  will have a `noise_multiplier` attribute.
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code: def step(self):
      self.last_epoch += 1
      noise_multiplier = self.get_noise_multiplier()
      self.optimizer.noise_multiplier = noise_multiplier
  
file_path: opacus/opacus/schedulers/noise_scheduler.py
imports: from typing import Callable, Dict
  from opacus.optimizers import DPOptimizer
label_desc: Use image node_id 5 for calling the _NoiseScheduler obj's underlying member method code with example usage: obj.step() without return types