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: A contextmanager for managing model forward/training_step/evaluation_step/predict_step.
docstr_tok: ["A","contextmanager","for","managing","model","forward\/training_step\/evaluation_step\/predict_step","."]
code: def forward_context(self) -> ContextManager:
      """A contextmanager for managing model forward/training_step/evaluation_step/predict_step."""
      return nullcontext()
  
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 4 for calling the Precision obj's underlying member method code with example usage: obj.forward_context() and returns: nullcontext