code: def test_textagumentor_deepcopy():
      dataset = ALL_DATASETS["ae"]()
      metric_name = dataset.metric
  
      predictor = MultiModalPredictor(
          label=dataset.label_columns[0],
          problem_type=dataset.problem_type,
          eval_metric=metric_name,
      )
      hyperparameters = {
          "optimization.max_epochs": 1,
          "env.num_workers": 0,
          "env.num_workers_evaluation": 0,
          "data.categorical.convert_to_text": False,
          "data.numerical.convert_to_text": False,
          "model.hf_text.checkpoint_name": "sentence-transformers/all-MiniLM-L6-v2",
          "model.hf_text.text_trivial_aug_maxscale": 0.05,
          "model.hf_text.text_train_augment_types": ["identity"],
          "optimization.top_k_average_method": "uniform_soup",
      }
  
      with tempfile.TemporaryDirectory() as save_path:
          if os.path.isdir(save_path):
              shutil.rmtree(save_path)
          predictor.fit(
              train_data=dataset.train_df,
              time_limit=10,
              save_path=save_path,
              hyperparameters=hyperparameters,
          )
  
      # Deepcopy data processors
      predictor._learner._data_processors = copy.deepcopy(
          predictor._learner._data_processors
      )
  
      # Test copied data processors
      predictor.fit(
          train_data=dataset.train_df,
          hyperparameters=hyperparameters,
          time_limit=10,
      )
  
      # Copy data processors via pickle + load
      predictor._learner._data_processors = pickle.loads(
          pickle.dumps(predictor._learner._data_processors)
      )
  
      # Test copied data processors
      predictor.fit(
          train_data=dataset.train_df,
          hyperparameters=hyperparameters,
          time_limit=10,
      )
  
file_path: autogluon/multimodal/tests/unittests/others_2/test_data_augmentation.py
imports: import copy
  import os
  import pickle
  import shutil
  import tempfile
  import pytest
  from torchvision import transforms
  from autogluon.multimodal import MultiModalPredictor
  from autogluon.multimodal.constants import BEST, BINARY, BIT_FIT, DATA, DISTILLER, ENVIRONMENT, GREEDY_SOUP, LORA, LORA_BIAS, LORA_NORM, MODEL, MULTICLASS, NORM_FIT, OPTIMIZATION, UNIFORM_SOUP
  from autogluon.multimodal.utils.misc import shopee_dataset
  from ..predictor.test_predictor import verify_predictor_save_load
  from ..utils.unittest_datasets import AEDataset, HatefulMeMesDataset, IDChangeDetectionDataset, PetFinderDataset
label_desc: Use image node_id 2 for calling a global function with example usage: test_textagumentor_deepcopy() without return types