code: def _init_tensor_dummy_dataset(self):
      dummy_dataset_dict = {
          "input_ids": [
              torch.tensor([5303, 3621]),
              torch.tensor([3666, 1438, 318]),
              torch.tensor([5303, 3621]),
          ],
          "attention_mask": [
              torch.tensor([1, 1]),
              torch.tensor([1, 1, 1]),
              torch.tensor([1, 1]),
          ],
          "labels": [
              torch.tensor([5303, 3621]),
              torch.tensor([3666, 1438, 318]),
              torch.tensor([5303, 3621]),
          ],
      }
  
      dummy_dataset = Dataset.from_dict(dummy_dataset_dict)
      dummy_dataset.set_format("torch")
      return dummy_dataset
  
file_path: trl/tests/test_iterative_sft_trainer.py
imports: import tempfile
  import unittest
  import torch
  from datasets import Dataset
  from parameterized import parameterized
  from transformers import AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoTokenizer, TrainingArguments
  from trl import IterativeSFTTrainer
label_desc: Use image node_id 2 for calling the IterativeTrainerTester obj's underlying member method code with example usage: obj._init_tensor_dummy_dataset() and returns: dummy_dataset