code: def mask_hook(grad_input, st, ed):
      mask = torch.zeros((grad_input.shape[0], 1)).type_as(grad_input)
      mask[st:ed] += 1.0  # 只优化id为1～8的token
      # for the speaker unused token12
      mask[1:3] += 1.0
      return grad_input * mask
  
imports: import json
  import torch
  import torch.nn
  import torch.nn.functional
  import numpy
  from .base import BaseLitModel
  from .util import dialog_f1_eval, f1_eval, compute_f1, acc, f1_score
  from transformers.optimization import get_linear_schedule_with_warmup
  from functools import partial
label_desc: Use image node_id 1 for calling a global function with example usage: mask_hook(grad_input, st, ed) and returns: unknown