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 saving a checkpoint, implement to generate precision plugin state_dict.
  
  Returns:
      A dictionary containing precision plugin state.
docstr_tok: ["Called","when","saving","a","checkpoint",",","implement","to","generate","precision","plugin","state_dict",".","Returns",":","A","dictionary","containing","precision","plugin","state","."]
code: def state_dict(self) -> Dict[str, Any]:
      """Called when saving a checkpoint, implement to generate precision plugin state_dict.
  
      Returns:
          A dictionary containing precision plugin state.
  
      """
      return {}
  
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 13 for calling the Precision obj's underlying member method code with example usage: obj.state_dict() and returns: dict