class_docstr: Plugin for Automatic Mixed Precision (AMP) training with ``torch.autocast``.
  
  Args:
      precision: Whether to use ``torch.float16`` (``'16-mixed'``) or ``torch.bfloat16`` (``'bf16-mixed'``).
      device: The device for ``torch.autocast``.
      scaler: An optional :class:`torch.cuda.amp.GradScaler` to use.
code: def autocast_context_manager(self) -> torch.autocast:
      return torch.autocast(
          self.device,
          dtype=(
              torch.bfloat16
              if self.precision == "bf16-mixed"
              else torch.half
          ),
      )
  
imports: from contextlib import contextmanager
  from typing import Any, Callable, Dict, Generator, Literal, Optional, Union
  import torch
  from torch import Tensor
  from torch.optim import LBFGS, Optimizer
  from typing_extensions import override
  import lightning.pytorch
  from lightning.fabric.accelerators.cuda import _patch_cuda_is_available
  from lightning.fabric.plugins.precision.amp import _optimizer_handles_unscaling
  from lightning.fabric.utilities.types import Optimizable
  from lightning.pytorch.plugins.precision.precision import Precision
  from lightning.pytorch.utilities import GradClipAlgorithmType
  from lightning.pytorch.utilities.exceptions import MisconfigurationException
label_desc: Use image node_id 5 for calling the MixedPrecision obj's underlying member method code with example usage: obj.autocast_context_manager() and returns: torch