code: def generate_candidates(self, input_ids, attn_masks, labels):
      tokens_to_generate = self.cfg.tokens_to_generate
      if self.cfg.library == "huggingface":
          param_dict = {
              "input_ids": input_ids,
              "attention_mask": attn_masks,
              "max_length": tokens_to_generate,
          }
          generated_tokens = self.language_model.generate(**param_dict)
  
      elif self.cfg.library == "megatron":
          _reconfigure_microbatch_calculator(
              rank=0,  # This doesn't matter since it is only used for logging
              rampup_batch_size=None,
              global_batch_size=1,
              micro_batch_size=1,  # Make sure that there is no "grad acc" while decoding.
              data_parallel_size=1,  # We check above to make sure that dataparallel size is always 1 at inference.
          )
          generated_tokens, _ = self.language_model.decode(
              input_ids, attn_masks, tokens_to_generate
          )
  
      generated_field = self.process_into_structured_fields(
          generated_tokens
      )
      ground_truth_field = self.process_into_structured_fields(labels)
  
      return generated_field, ground_truth_field
  
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 12 for calling the DialogueS2SGenerationModel obj's underlying member method code with example usage: obj.generate_candidates(input_ids, attn_masks, labels) and returns: generated_field,  ground_truth_field