code: def create_fake_dataset(self):
      n_data = 5
      self.dataset = torchvision.datasets.FakeData(
          size=n_data, image_size=(3, 32, 32)
      )
  
      self.folder_path = tempfile.mkdtemp()
      sample_names = [f"img_{i}.jpg" for i in range(n_data)]
      self.sample_names = sample_names
      for sample_idx in range(n_data):
          data = self.dataset[sample_idx]
          path = os.path.join(
              self.folder_path, sample_names[sample_idx]
          )
          data[0].save(path)
  
file_path: lightly/tests/cli/test_cli_train.py
imports: import os
  import re
  import sys
  import tempfile
  import torchvision
  from hydra.experimental import compose, initialize
  from lightly import cli
  from tests.api_workflow.mocked_api_workflow_client import MockedApiWorkflowClient, MockedApiWorkflowSetup
label_desc: Use image node_id 2 for calling the TestCLITrain obj's underlying member method code with example usage: obj.create_fake_dataset() without return types