def forward(self, inputs, return_loss=True, **kwargs):
        """Calls either :func:`forward_train` or :func:`forward_test` depending
        on whether ``return_loss`` is ``True``.

        Note this setting will change the expected inputs. When
        ``return_loss=True``, img and img_meta are single-nested (i.e. Tensor
        and List[dict]), and when ``resturn_loss=False``, img and img_meta
        should be double nested (i.e.  List[Tensor], List[List[dict]]), with
        the outer list indicating test time augmentations.
        """
        if return_loss:
            return self.forward_train(inputs, **kwargs)
        else:
            return self.forward_test(inputs, **kwargs)
Calls either :func:`forward_train` or :func:`forward_test` depending
        on whether ``return_loss`` is ``True``.

        Note this setting will change the expected inputs. When
        ``return_loss=True``, img and img_meta are single-nested (i.e. Tensor
        and List[dict]), and when ``resturn_loss=False``, img and img_meta
        should be double nested (i.e.  List[Tensor], List[List[dict]]), with
        the outer list indicating test time augmentations.
        
ppdet/modeling/architectures/multi_stream_detector.py