code: def forward(self, input_ids, attention_masks, labels):
      if self.cfg.library == "huggingface":
          output = self.language_model(
              input_ids=input_ids,
              attention_mask=attention_masks,
              labels=labels,
          )
          loss = output["loss"]
      elif self.cfg.library == "megatron":
          labels = torch.where(
              labels != -100, labels, torch.zeros_like(labels)
          )
          decoder_attn_masks = torch.where(
              labels > 0,
              torch.ones_like(labels),
              torch.zeros_like(labels),
          )
  
          unmasked_unreduced_loss = self.language_model(
              input_ids,
              labels[:, :-1],
              attention_masks,
              decoder_attn_masks[:, :-1],
              lm_labels=labels[:, 1:],
          )
          loss = self.language_model.loss_func(
              decoder_attn_masks[:, 1:].contiguous(),
              unmasked_unreduced_loss,
          )
      return loss
  
imports: import os
  from typing import Dict, Optional, Union
  import numpy
  import torch
  from omegaconf import DictConfig, OmegaConf, open_dict
  from pytorch_lightning import Trainer
  from torch.utils.data import DataLoader
  from transformers import AutoModelForSeq2SeqLM
  from nemo.collections.nlp.data.dialogue import DialogueSGDDataProcessor
  from nemo.collections.nlp.data.dialogue.data_processor.mellon_qa_data_processor import DialogueMellonQADataProcessor
  from nemo.collections.nlp.data.dialogue.data_processor.ms_marco_data_processor import DialogueMSMarcoDataProcessor
  from nemo.collections.nlp.data.dialogue.dataset.dialogue_s2s_generation_dataset import DialogueS2SGenerationDataset
  from nemo.collections.nlp.metrics.dialogue_metrics import DialogueGenerationMetrics
  from nemo.collections.nlp.models.language_modeling.megatron_t5_model import MegatronT5Model
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging
label_desc: Use image node_id 9 for calling the DialogueS2SGenerationModel obj's underlying member method code with example usage: obj.forward(input_ids, attention_masks, labels) and returns: loss