class_docstr: Base class for all plugins handling the precision-specific parts of the training.
  
  The class attribute precision must be overwritten in child classes. The default value reflects fp32 training.
docstr: Called when loading a checkpoint, implement to reload precision plugin state given precision plugin
  state_dict.
  
  Args:
      state_dict: the precision plugin state returned by ``state_dict``.
docstr_tok: ["Called","when","loading","a","checkpoint",",","implement","to","reload","precision","plugin","state","given","precision","plugin","state_dict",".","Args",":","state_dict",":","the","precision","plugin","state","returned","by","``","state_dict","``","."]
code: def load_state_dict(self, state_dict: Dict[str, Any]) -> None:
      """Called when loading a checkpoint, implement to reload precision plugin state given precision plugin
      state_dict.
  
      Args:
          state_dict: the precision plugin state returned by ``state_dict``.
  
      """
      pass
  
imports: from contextlib import nullcontext
  from typing import Any, ContextManager, Dict, Literal, Optional, Union
  from torch import Tensor
  from torch.nn import Module
  from torch.optim import Optimizer
  from lightning.fabric.utilities.types import _PARAMETERS, Optimizable
label_desc: Use image node_id 14 for calling the Precision obj's underlying member method code with example usage: obj.load_state_dict(state_dict) without return types