class_docstr: Hinge Discriminator Loss 
class_docstr_tok: ["Hinge","Discriminator","Loss"]
code: def forward(self, score_fake, score_real):
      loss_real = torch.mean(F.relu(1.0 - score_real))
      loss_fake = torch.mean(F.relu(1.0 + score_fake))
      loss_d = loss_real + loss_fake
      return loss_d, loss_real, loss_fake
  
imports: import torch
  from torch import nn
  from torch.nn import functional
label_desc: Use image node_id 1 for calling the HingeDLoss obj's underlying member method code with example usage: obj.forward(score_fake, score_real) and returns: loss_d,  loss_real,  loss_fake