class_docstr: use AutoModelForMaskedLM, and select the output by another layer in the lit model
code: def forward(self, x):
      return self.model(x)
  
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 3 for calling the BertLitModel obj's underlying member method code with example usage: obj.forward(x) and returns: self