code: def forward(self, batch):
      outputs = self.model(
          input_ids=batch.enc_idxs,
          attention_mask=batch.enc_attn,
          decoder_input_ids=batch.dec_idxs,
          decoder_attention_mask=batch.dec_attn,
          labels=batch.lbl_idxs,
          return_dict=True,
      )
      loss = outputs["loss"]
  
      return loss
  
file_path: DeepKE/src/deepke/event_extraction/standard/degree/model.py
imports: import logging
  import numpy
  import torch
  import torch.nn
  from transformers import AutoConfig, AutoModelForPreTraining
  import ipdb
label_desc: Use image node_id 2 for calling the GenerativeModel obj's underlying member method code with example usage: obj.forward(batch) and returns: loss