code: def compute_losses(self, net_out, data):
      loss_list = []
      for i in range(len(self.criteria["types"])):
          loss_i = self.criteria["types"][i]
          coef_i = self.criteria["coef"][i]
          # Do a 'literal' check to find `MixedLoss` objects
          if loss_i.__class__.__name__ == "MixedLoss":
              mixed_loss_list = loss_i(data, net_out)
              for mixed_loss in mixed_loss_list:
                  loss_list.append(coef_i * mixed_loss)
          else:
              loss_list.append(coef_i * loss_i(data, net_out))
      return loss_list
  
imports: import abc
  import paddle
  from paddlepanseg.core import infer
label_desc: Use image node_id 4 for calling the PanSegRunner obj's underlying member method code with example usage: obj.compute_losses(net_out, data) and returns: loss_list