docstr: Called at the end of test to aggregate outputs.
  :param outputs: list of individual outputs of each test step.
docstr_tok: ["Called","at","the","end","of","test","to","aggregate","outputs",".",":","param","outputs",":","list","of","individual","outputs","of","each","test","step","."]
code: def on_test_epoch_end(self):
      """
      Called at the end of test to aggregate outputs.
      :param outputs: list of individual outputs of each test step.
      """
      return self.on_validation_epoch_end()
  
imports: import os
  import pathlib
  from typing import Dict, List, Optional
  import torch
  from omegaconf import DictConfig, OmegaConf
  from pytorch_lightning import Trainer
  from torch.utils.data import DataLoader
  from nemo.collections.common.losses import AggregatorLoss, CrossEntropyLoss
  from nemo.collections.nlp.data.intent_slot_classification import IntentSlotClassificationDataset, IntentSlotDataDesc, IntentSlotInferenceDataset
  from nemo.collections.nlp.metrics.classification_report import ClassificationReport
  from nemo.collections.nlp.models.nlp_model import NLPModel
  from nemo.collections.nlp.modules.common import SequenceTokenClassifier
  from nemo.collections.nlp.parts.utils_funcs import tensor2list
  from nemo.core.classes import typecheck
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging
label_desc: Use image node_id 13 for calling the IntentSlotClassificationModel obj's underlying member method code with example usage: obj.on_test_epoch_end() and returns: self