code: def test_update_frequency_same_model_params(self, a):
      trainer1 = self._train_with_condition(
          num_train_data=100,
          max_updates=2,
          max_epochs=None,
          update_frequency=2,
          batch_size=2,
      )
      trainer1.load_datasets()
      trainer2 = self._train_with_condition(
          num_train_data=100,
          max_updates=2,
          max_epochs=None,
          update_frequency=1,
          batch_size=4,
      )
      trainer2.load_datasets()
      self._compare_model_params(trainer1, trainer2)
  
imports: import unittest
  from unittest.mock import MagicMock, patch
  import torch
  from mmf.common.registry import registry
  from mmf.utils.general import get_batch_size
  from tests.test_utils import SimpleModel, SimpleNaNLossModel
  from tests.trainers.test_trainer_mocks import TrainerTrainingLoopMock
  from tests.trainers.test_utils import add_model, add_optimizer, get_config_with_defaults, get_mmf_trainer
label_desc: Use image node_id 4 for calling the TestTrainingLoop obj's underlying member method code with example usage: obj.test_update_frequency_same_model_params(a) without return types