code: def orthogonalLoss(rel_embeddings, norm_embeddings):
      return torch.sum(
          torch.sum(
              norm_embeddings * rel_embeddings, dim=1, keepdim=True
          )
          ** 2
          / torch.sum(rel_embeddings**2, dim=1, keepdim=True)
      )
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  from recbole.model.abstract_recommender import KnowledgeRecommender
  from recbole.model.init import xavier_uniform_initialization
  from recbole.model.loss import BPRLoss, EmbMarginLoss
  from recbole.utils import InputType
label_desc: Use image node_id 1 for calling a global function with example usage: orthogonalLoss(rel_embeddings, norm_embeddings) and returns: torch