code: def create_dataset_no_subdir(
      self, n_samples: int
  ) -> Tuple[str, List[str]]:
      dataset = torchvision.datasets.FakeData(
          size=n_samples, image_size=(3, 32, 32)
      )
  
      tmp_dir = tempfile.mkdtemp()
      sample_names = [f"img_{i}.jpg" for i in range(n_samples)]
      for sample_idx in range(n_samples):
          data = dataset[sample_idx]
          path = os.path.join(tmp_dir, sample_names[sample_idx])
          data[0].save(path)
      return tmp_dir, sample_names
  
file_path: lightly/tests/embedding/test_embedding.py
imports: import os
  import tempfile
  import unittest
  from typing import List, Tuple
  import numpy
  import torch
  import torchvision
  from hydra.experimental import compose, initialize
  from torch import manual_seed
  from torch.utils.data import DataLoader
  from lightly.cli._helpers import get_model_from_config
  from lightly.data import LightlyDataset
label_desc: Use image node_id 2 for calling the TestLightlyDataset obj's underlying member method code with example usage: obj.create_dataset_no_subdir(n_samples) and returns: tmp_dir,  sample_names