code: def __init__(self, corpus, tokenizer, **kwargs):
      super().__init__()
      self.corpus = corpus
      # num_labels = corpus.num_labels
      num_labels = corpus.num_aspect_labels
      samples = None
      if "samples" in kwargs:
          samples = kwargs["samples"]
      del kwargs["samples"]
      self.dataset_kwargs = {
          "tokenizer": tokenizer,
          "num_labels": num_labels,
          "max_token_length": 300,
          "samples": samples,
      }
      self.kwargs = kwargs
  
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 MultiLabelClassificationDatamodule object from inherited base classes: pl with example: obj = MultiLabelClassificationDatamodule(corpus, tokenizer)