code: def forward(self, output, label):
      probs = output.view(-1)
      mask = label.view(-1)
      smooth = 1
      intersection = torch.sum(probs * mask)
      den1 = torch.sum(probs)
      den2 = torch.sum(mask)
      soft_dice = (2 * intersection + smooth) / (den1 + den2 + smooth)
      return -soft_dice
  
imports: import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the SoftDiceLoss obj's underlying member method code with example usage: obj.forward(output, label) and returns: unknown