def manual_backward(self, loss: Tensor, *args: Any, **kwargs: Any) -> None:
        """Call this directly from your :meth:`training_step` when doing optimizations manually. By using this,
        Lightning can ensure that all the proper scaling gets applied when using mixed precision.

        See :ref:`manual optimization<common/optimization:Manual optimization>` for more examples.

        Example::

            def training_step(...):
                opt = self.optimizers()
                loss = ...
                opt.zero_grad()
                # automatically applies scaling, etc...
                self.manual_backward(loss)
                opt.step()

        Args:
            loss: The tensor on which to compute gradients. Must have a graph attached.
            *args: Additional positional arguments to be forwarded to :meth:`~torch.Tensor.backward`
            **kwargs: Additional keyword arguments to be forwarded to :meth:`~torch.Tensor.backward`

        """
        if self._fabric:
            self._fabric.backward(loss, *args, **kwargs)
        else:
            self._verify_is_manual_optimization("manual_backward")
            self.trainer.strategy.backward(loss, None, *args, **kwargs)
Call this directly from your :meth:`training_step` when doing optimizations manually. By using this,
        Lightning can ensure that all the proper scaling gets applied when using mixed precision.

        See :ref:`manual optimization<common/optimization:Manual optimization>` for more examples.

        Example::

            def training_step(...):
                opt = self.optimizers()
                loss = ...
                opt.zero_grad()
                # automatically applies scaling, etc...
                self.manual_backward(loss)
                opt.step()

        Args:
            loss: The tensor on which to compute gradients. Must have a graph attached.
            *args: Additional positional arguments to be forwarded to :meth:`~torch.Tensor.backward`
            **kwargs: Additional keyword arguments to be forwarded to :meth:`~torch.Tensor.backward`

        
src/lightning/pytorch/core/module.py