code: def load_data(self, data_type):
      tmp_dataset = load_dataset(
          path="seamew/ChnSentiCorp", split=data_type
      )
      Data = {}
      # So enumerate will return a index, and  the line?
      # line is a dict, including 'text', 'label'
      if data_type == "train":
          for i in range(self.dataset_load):
              for idx, line in enumerate(tmp_dataset):
                  sample = line
                  Data[idx + i * len(tmp_dataset)] = sample
      else:
          for idx, line in enumerate(tmp_dataset):
              sample = line
              Data[idx] = sample
      return Data
  
imports: import torch
  import argparse
  import os
  import logging
  import time
  from torch import nn
  from contextlib import nullcontext
  from datasets import load_dataset
  from torch.utils.data import DataLoader
  from torch.utils.data.distributed import DistributedSampler
  import torch.distributed
  from transformers import BertTokenizer, BertModel, AdamW
label_desc: Use image node_id 2 for calling the Dataset obj's underlying member method code with example usage: obj.load_data(data_type) and returns: Data