class_docstr: AMP for Fully Sharded Data Parallel (FSDP) Training.
  
  .. deprecated:: Use :class:`FSDPPrecision` instead.
  
  .. warning::  This is an :ref:`experimental <versioning:Experimental API>` feature.
class_docstr_tok: ["AMP","for","Fully","Sharded","Data","Parallel","(","FSDP",")","Training",".","..","deprecated",":",":","Use",":","class",":","`","FSDPPrecision","`","instead",".","..","warning",":",":","This","is","an",":","ref",":","`","experimental","<","versioning",":","Experimental","API",">","`","feature","."]
code: def __init__(
      self,
      precision: Literal["16-mixed", "bf16-mixed"],
      device: str,
      scaler: Optional["ShardedGradScaler"] = None,
  ) -> None:
      rank_zero_deprecation(
          f"The `{type(self).__name__}` is deprecated."
          " Use `lightning.pytorch.plugins.precision.FSDPPrecision` instead."
      )
      super().__init__(precision=precision, scaler=scaler)
  
file_path: pytorch-lightning/src/lightning/pytorch/_graveyard/precision.py
imports: import sys
  from typing import TYPE_CHECKING, Any, Literal, Optional
  import lightning.pytorch
  from lightning.fabric.utilities.rank_zero import rank_zero_deprecation
  from lightning.pytorch.plugins.precision import BitsandbytesPrecision, DeepSpeedPrecision, DoublePrecision, FSDPPrecision, HalfPrecision, MixedPrecision, Precision, TransformerEnginePrecision, XLAPrecision
label_desc: Use image node_id 1 to create a new FSDPMixedPrecisionPlugin object from inherited base classes: FSDPPrecision with example: obj = FSDPMixedPrecisionPlugin(precision, device, scaler)