code: def __init__(
      self, train_dataset, test_dataset, val_dataset, batch_size=24
  ):
      super().__init__()
      self.train_dataset = train_dataset
      self.val_dataset = val_dataset
      self.test_dataset = test_dataset
      self.batch_size = batch_size
  
imports: import torch
  import hydra
  import torch.nn
  import pytorch_lightning
  from omegaconf import DictConfig
  from torchmetrics import F1Score
  from torch.utils.data import Dataset, DataLoader
  from transformers import AutoTokenizer, AdamW, RobertaModel, BertPreTrainedModel, RobertaConfig
  from underthesea import word_tokenize
  from underthesea.datasets.uit_absa_hotel.uit_absa_hotel import UITABSAHotel
label_desc: Use image node_id 1 to create a new UITABSADataModule object from inherited base classes: pl with example: obj = UITABSADataModule(train_dataset, test_dataset, val_dataset, batch_size)