code: def forward(self, p_score, n_score):
      if self.adv_flag:
          return (
              self.get_weights(n_score)
              * torch.max(p_score - n_score, -self.margin)
          ).sum(dim=-1).mean() + self.margin
      else:
          return (
              torch.max(p_score - n_score, -self.margin)
          ).mean() + self.margin
  
file_path: OpenKE/openke/module/loss/MarginLoss.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import numpy
  from .Loss import Loss
label_desc: Use image node_id 3 for calling the MarginLoss obj's underlying member method code with example usage: obj.forward(p_score, n_score) and returns: unknown, unknown