class_docstr: Overall loss function of the second training phase of the DSR model.
  
  The total loss consists of:
      - MSE loss between non-anomalous quantized input image and anomalous subspace-reconstructed
        non-quantized input (hi and lo)
      - MSE loss between input image and reconstructed image through object-specific decoder,
      - Focal loss between computed segmentation mask and ground truth mask.
code: def __init__(self) -> None:
      super().__init__()
  
      self.l2_loss = nn.modules.loss.MSELoss()
      self.focal_loss = FocalLoss(alpha=1, reduction="mean")
  
file_path: anomalib/src/anomalib/models/dsr/loss.py
imports: from kornia.losses import FocalLoss
  from torch import Tensor, nn
label_desc: Use image node_id 1 to create a new DsrSecondStageLoss object from inherited base classes: nn with example: obj = DsrSecondStageLoss()