class_docstr: SigLoss.
  
      This follows `AdaBins <https://arxiv.org/abs/2011.14141>`_.
  
  Args:
      valid_mask (bool): Whether filter invalid gt (gt > 0). Default: True.
      loss_weight (float): Weight of the loss. Default: 1.0.
      max_depth (int): When filtering invalid gt, set a max threshold. Default: None.
      warm_up (bool): A simple warm up stage to help convergence. Default: False.
      warm_iter (int): The number of warm up stage. Default: 100.
docstr: Forward function.
docstr_tok: ["Forward","function","."]
code: def forward(self, depth_pred, depth_gt):
      """Forward function."""
  
      loss_depth = self.loss_weight * self.sigloss(depth_pred, depth_gt)
      return loss_depth
  
file_path: dinov2/dinov2/eval/depth/models/losses/sigloss.py
imports: import torch
  import torch.nn
  from ...models.builder import LOSSES
label_desc: Use image node_id 3 for calling the SigLoss obj's underlying member method code with example usage: obj.forward(depth_pred, depth_gt) and returns: loss_depth