content: import torch.nn.functional as F
  
  from ..registry import LOSSES
  from .base import BaseWeightedLoss
  
  
  @LOSSES.register_module()
  class CrossEntropyLoss(BaseWeightedLoss):
      """Cross Entropy Loss."""
  
      def _forward(self, cls_score, label, **kwargs):
          """Forward function.
  
          Args:
              cls_score (torch.Tensor): The class score.
              label (torch.Tensor): The ground truth label.
              kwargs: Any keyword argument to be used to calculate
                  CrossEntropy loss.
  
          Returns:
              torch.Tensor: The returned CrossEntropy loss.
          """
          loss_cls = F.cross_entropy(cls_score, label, **kwargs)
          return loss_cls
  
  
  @LOSSES.register_module()
  class BCELossWithLogits(BaseWeightedLoss):
      """Binary Cross Entropy Loss with logits."""
  
      def _forward(self, cls_score, label, **kwargs):
          """Forward function.
  
          Args:
              cls_score (torch.Tensor): The class score.
              label (torch.Tensor): The ground truth label.
              kwargs: Any keyword argument to be used to calculate
                  bce loss with logits.
  
          Returns:
              torch.Tensor: The returned bce loss with logits.
          """
          loss_cls = F.binary_cross_entropy_with_logits(cls_score, label,
                                                        **kwargs)
          return loss_cls
  