code: def distill_loss_computation(
      student_logits_list,
      teacher_logits_list,
      labels,
      losses,
      edges=None,
  ):
      assert len(student_logits_list) == len(teacher_logits_list)
      check_logits_losses(student_logits_list, losses)
  
      loss_list = []
      for i in range(len(student_logits_list)):
          s_logits = student_logits_list[i]
          t_logits = teacher_logits_list[i]
          loss_i = losses["types"][i]
          loss_list.append(
              losses["coef"][i] * loss_i(s_logits, t_logits, labels)
          )
      return loss_list
  
file_path: PaddleSeg/deploy/slim/distill/distill_utils.py
imports: import os
  import time
  from collections import deque
  import shutil
  import paddle
  from paddle.distributed import fleet
  import paddle.nn.functional
  from paddleseg.utils import TimeAverager, calculate_eta, resume, logger, worker_init_fn
  from paddleseg.core.val import evaluate
  from paddleseg.models.losses import DistillCrossEntropyLoss
label_desc: Use image node_id 3 for calling a global function with example usage: distill_loss_computation(student_logits_list, teacher_logits_list, labels, losses, edges) and returns: loss_list