class_docstr: Base class for gradient clipping schedulers. We follow the same API
  as the standard PyTorch LR schedulers, but apply them to Opacus's
  `max_grad_norm` param instead.
  
  This means it only works when you pass a opacus.DPOptimizer, since that
  will have a `max_grad_norm` attribute.
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docstr: Loads the schedulers state.
  
  Args:
      state_dict (dict): scheduler state. Should be an object returned
          from a call to :meth:`state_dict`.
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code: def load_state_dict(self, state_dict: Dict):
      """Loads the schedulers state.
  
      Args:
          state_dict (dict): scheduler state. Should be an object returned
              from a call to :meth:`state_dict`.
      """
      self.__dict__.update(state_dict)
  
file_path: opacus/opacus/schedulers/grad_clip_scheduler.py
imports: from typing import Callable, Dict
  from opacus.optimizers import DPOptimizer
label_desc: Use image node_id 3 for calling the _GradClipScheduler obj's underlying member method code with example usage: obj.load_state_dict(state_dict) without return types