code: def __init__(
      self,
      data,
      tokenizer,
      num_labels,
      max_token_length: int = 50,
      samples=None,
  ):
      super().__init__()
      self.texts = [item["text"] for item in data]  # text
      self.labels = [
          item["aspect_label_ids"] for item in data
      ]  # label ids
      self.tokenizer = tokenizer
      self.num_labels = num_labels
      self.max_token_length = max_token_length
      self.samples = samples
  
file_path: underthesea/examples/sentiment/data.py
imports: import torch
  from torch.utils.data import Dataset, DataLoader
  import pytorch_lightning
label_desc: Use image node_id 1 to create a new MultiLabelClassificationDataset object from inherited base classes: Dataset with example: obj = MultiLabelClassificationDataset(data, tokenizer, num_labels, max_token_length, samples)