code: def test_distill_mbart(self):
      updates = {
          "student_encoder_layers": 2,
          "student_decoder_layers": 1,
          "num_train_epochs": 4,
          "val_check_interval": 0.25,
          "alpha_hid": 2.0,
          "task": "translation",
          "model_name_or_path": "IGNORE_THIS_IT_DOESNT_GET_USED",
          "tokenizer_name": MBART_TINY,
          "teacher": MBART_TINY,
          "src_lang": "en_XX",
          "tgt_lang": "ro_RO",
      }
      model = self._test_distiller_cli(updates, check_contents=False)
      assert model.model.config.model_type == "mbart"
  
      ckpts = list(Path(model.output_dir).glob("*.ckpt"))
      self.assertEqual(1, len(ckpts))
      transformer_ckpts = list(Path(model.output_dir).glob("**/*.bin"))
      all_files = list(Path(model.output_dir).glob("best_tfmr/*"))
      assert len(all_files) > 2
      self.assertEqual(len(transformer_ckpts), 2)
  
imports: import argparse
  import logging
  import os
  import sys
  import tempfile
  from pathlib import Path
  import lightning_base
  import pytest
  import pytorch_lightning
  import torch
  from convert_pl_checkpoint_to_hf import convert_pl_to_hf
  from distillation import distill_main
  from finetune import SummarizationModule, main
  from huggingface_hub import list_models
  from parameterized import parameterized
  from run_eval import generate_summaries_or_translations
  from torch import nn
  from transformers import AutoConfig, AutoModelForSeq2SeqLM
  from transformers.testing_utils import CaptureStderr, CaptureStdout, TestCasePlus, require_torch_gpu, slow
  from utils import label_smoothed_nll_loss, lmap, load_json
label_desc: Use image node_id 6 for calling the TestSummarizationDistiller obj's underlying member method code with example usage: obj.test_distill_mbart() without return types