code: def __init__(self, tokenizer):
      super().__init__()
  
      self.tokenizer = tokenizer
      self.input_ids = []
      self.attn_masks = []
      self.labels = []
      self.txt_list = netflix_descriptions = load_dataset(
          "hugginglearners/netflix-shows", split="train"
      )["description"]
      self.max_length = max(
          [
              len(self.tokenizer.encode(description))
              for description in netflix_descriptions
          ]
      )
  
      for txt in self.txt_list:
          encodings_dict = self.tokenizer(
              "</s>" + txt + "</s>",
              truncation=True,
              max_length=self.max_length,
              padding="max_length",
          )
          self.input_ids.append(
              torch.tensor(encodings_dict["input_ids"])
          )
          self.attn_masks.append(
              torch.tensor(encodings_dict["attention_mask"])
          )
  
file_path: ColossalAI/examples/language/opt/data.py
imports: import torch
  from datasets import load_dataset
  from torch.utils.data import Dataset
label_desc: Use image node_id 1 to create a new NetflixDataset object from inherited base classes: Dataset with example: obj = NetflixDataset(tokenizer)