def backward(  # type: ignore[override]
        self,
        tensor: Tensor,
        model: "pl.LightningModule",
        optimizer: Optional[Steppable],
        *args: Any,
        **kwargs: Any,
    ) -> None:
        r"""Performs the actual backpropagation.

        Args:
            tensor: the loss value obtained from the closure
            model: the model to be optimized
            optimizer: current optimizer being used. ``None`` if using manual optimization
            \*args: Positional arguments intended for the actual function that performs the backward, like
                :meth:`~torch.Tensor.backward`.
            \**kwargs: Keyword arguments for the same purpose as ``*args``.

        """
        model.backward(tensor, *args, **kwargs)
Performs the actual backpropagation.

        Args:
            tensor: the loss value obtained from the closure
            model: the model to be optimized
            optimizer: current optimizer being used. ``None`` if using manual optimization
            \*args: Positional arguments intended for the actual function that performs the backward, like
                :meth:`~torch.Tensor.backward`.
            \**kwargs: Keyword arguments for the same purpose as ``*args``.

        
src/lightning/pytorch/plugins/precision/precision.py