code: def test_trainer_save_current_parity_with_mmf(self):
      with mock_env_with_temp(
          "mmf.utils.checkpoint.get_mmf_env"
      ) as tmp_d, mock_env_with_temp(
          "mmf.common.test_reporter.get_mmf_env"
      ) as _:
          mmf_trainer = self._get_mmf_trainer()
          mmf_trainer.training_loop()
          mmf_ckpt_current = torch.load(
              os.path.join(tmp_d, "current.ckpt")
          )
  
      with mock_env_with_temp(
          "mmf.trainers.lightning_trainer.get_mmf_env"
      ) as tmp_d:
          lightning = self._get_lightning_trainer()
          lightning.trainer.fit(
              lightning.model, train_dataloaders=lightning.train_loader
          )
          lightning_ckpt_current = torch.load(
              os.path.join(tmp_d, "current.ckpt")
          )
  
      self._assert_same_dict(
          mmf_ckpt_current["model"],
          lightning_ckpt_current["state_dict"],
      )
  
imports: import contextlib
  import os
  import tempfile
  import unittest
  from unittest.mock import patch
  import torch
  from mmf.trainers.callbacks.checkpoint import CheckpointCallback
  from mmf.trainers.callbacks.early_stopping import EarlyStoppingCallback
  from mmf.trainers.lightning_core.loop_callback import LightningLoopCallback
  from mmf.utils.checkpoint import get_ckpt_path_from_folder
  from mmf.utils.download import download_pretrained_model
  from tests.test_utils import skip_if_no_network
  from tests.trainers.test_utils import get_config_with_defaults, get_lightning_trainer, get_mmf_trainer, prepare_lightning_trainer
label_desc: Use image node_id 9 for calling the TestLightningCheckpoint obj's underlying member method code with example usage: obj.test_trainer_save_current_parity_with_mmf() without return types