code: def _get_mmf_config(
      self, max_updates, max_epochs, batch_size, evaluation_interval
  ):
      config = {
          "training": {
              "max_updates": max_updates,
              "max_epochs": max_epochs,
              "batch_size": batch_size,
              "evaluation_interval": evaluation_interval,
          }
      }
      return get_config_with_defaults(config)
  
imports: import gc
  import unittest
  from typing import Any, Dict, Optional
  from unittest.mock import MagicMock, patch
  from mmf.common.meter import Meter
  from mmf.trainers.callbacks.logistics import LogisticsCallback
  from mmf.trainers.lightning_core.loop_callback import LightningLoopCallback
  from mmf.trainers.lightning_core.loop_callback_with_torchmetrics import LightningTorchMetricsCallback
  from mmf.trainers.lightning_core.torchmetric import LightningTorchMetrics
  from mmf.utils.logger import TensorboardLogger
  from mmf.utils.timer import Timer
  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 8 for calling the TestLightningTrainerValidation obj's underlying member method code with example usage: obj._get_mmf_config(max_updates, max_epochs, batch_size, evaluation_interval) and returns: get_config_with_defaults