code: def __getitem__(self, idx):
      if self.train_phase == 1:
          return {
              "input_ids": self.chosen_dataset[idx]["input_ids"],
              "attention_mask": self.chosen_dataset[idx][
                  "attention_mask"
              ],
              "labels": self.chosen_dataset[idx]["input_ids"],
          }
      elif self.train_phase == 2:
          return (
              self.chosen_dataset[idx]["input_ids"],
              self.chosen_dataset[idx]["attention_mask"],
              self.reject_dataset[idx]["input_ids"],
              self.reject_dataset[idx]["attention_mask"],
          )
      elif self.train_phase == 3:
          return (
              self.prompt_dataset[idx]["input_ids"],
              self.prompt_dataset[idx]["attention_mask"],
              self.pad_token_id,
          )
  
imports: import torch
  from torch.utils.data import Dataset, Subset, ConcatDataset
  from torch.nn.utils.rnn import pad_sequence
  import torch.nn.functional
  from datasets import load_dataset
  import numpy
  import os
  import hashlib
  from itertools import chain
  from dschat.utils.data import raw_datasets
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 3 for calling the PromptDataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: dict, self,  self,  self,  self, self,  self,  self