code: def forward(self, embeddings, labels, indices_tuple=None):
      if self.miners:
          assert indices_tuple is None
      total_loss = 0
      iterable = (
          self.losses.items()
          if self.is_dict
          else enumerate(self.losses)
      )
      for i, loss_func in iterable:
          curr_indices_tuple = self.get_indices_tuple(
              i, embeddings, labels, indices_tuple
          )
          total_loss += (
              loss_func(embeddings, labels, curr_indices_tuple)
              * self.weights[i]
          )
      return total_loss
  
imports: import torch
  from ..utils import common_functions
label_desc: Use image node_id 2 for calling the MultipleLosses obj's underlying member method code with example usage: obj.forward(embeddings, labels, indices_tuple) and returns: total_loss