code: def process_into_structured_fields(
      self, generated_tokens, labels, template_length=None
  ):
      generated_field = []
  
      for i in range(generated_tokens.size(0)):
          start_point = (
              0
              if template_length is None
              else template_length[i].item()
          )
          stop_point = generated_tokens.size(1)
  
          for j in range(start_point, stop_point):
              if (
                  generated_tokens.data[i, j]
                  == self.tokenizer.tokenizer.pad_token_id
              ):
                  stop_point = j
                  break
  
          # this is to account for the tokens ' Answer: ' + 'yes'/'no'/'true'/'false'
          if self.eval_mode == "binary_score":
              stop_point -= 3
  
          one_generated_field = self.decode(
              generated_tokens[i, start_point:stop_point]
          ).strip()
          generated_field.append(one_generated_field)
  
      ground_truth_field = self.process_ground_truth_field(labels)
  
      return generated_field, ground_truth_field
  
imports: import collections
  import copy
  import os
  import random
  from typing import Dict, Optional, Union
  import numpy
  import torch
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from torch.utils.data import DataLoader
  from transformers import AutoModelWithLMHead
  from nemo.collections.nlp.data.dialogue import DialogueGPTClassificationDataset, DialogueSGDDataProcessor
  from nemo.collections.nlp.data.dialogue.data_processor.assistant_data_processor import DialogueAssistantDataProcessor
  from nemo.collections.nlp.data.dialogue.data_processor.design_data_processor import DialogueDesignDataProcessor
  from nemo.collections.nlp.metrics.classification_report import ClassificationReport
  from nemo.collections.nlp.metrics.dialogue_metrics import DialogueClassificationMetrics
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_model import MegatronGPTModel
  from nemo.collections.nlp.models.language_modeling.megatron_gpt_prompt_learning_model import MegatronGPTPromptLearningModel
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.collections.nlp.modules.common import VirtualPromptSource, VirtualPromptStyle
  from nemo.collections.nlp.modules.common.text_generation_utils import get_default_sampling_params, megatron_gpt_generate
  from nemo.collections.nlp.modules.common.transformer.text_generation import LengthParam
  from nemo.collections.nlp.parts.nlp_overrides import NLPSaveRestoreConnector
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging
label_desc: Use image node_id 22 for calling the DialogueGPTClassificationModel obj's underlying member method code with example usage: obj.process_into_structured_fields(generated_tokens, labels, template_length) and returns: generated_field,  ground_truth_field