code: def _get_config(
      self,
      max_steps,
      batch_size,
      log_every_n_steps,
      val_check_interval,
      tensorboard,
  ):
      config = {
          "trainer": {
              "params": {
                  "max_steps": max_steps,
                  "log_every_n_steps": log_every_n_steps,
                  "val_check_interval": val_check_interval,
              }
          },
          "training": {
              "batch_size": batch_size,
              "tensorboard": tensorboard,
          },
      }
      return get_config_with_defaults(config)
  
file_path: mmf/tests/trainers/lightning/test_logging.py
imports: import unittest
  from unittest.mock import MagicMock, patch
  from mmf.trainers.callbacks.logistics import LogisticsCallback
  from mmf.trainers.lightning_core.loop_callback import LightningLoopCallback
  from mmf.utils.timer import Timer
  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, run_lightning_trainer
label_desc: Use image node_id 3 for calling the TestLightningTrainerLogging obj's underlying member method code with example usage: obj._get_config(max_steps, batch_size, log_every_n_steps, val_check_interval, tensorboard) and returns: get_config_with_defaults