code: def test_training_pipeline_no_len_dataset(
      self,
      tmpdir,
      training_pipeline,
      train_dataset,
      custom_no_len_train_dataset,
  ):
      tmpdir.mkdir("dummy_folder")
      dir_path = os.path.join(tmpdir, "dummy_folder")
      training_pipeline.training_config.output_dir = dir_path
      training_pipeline.training_config.num_epochs = 1
  
      with pytest.raises(DatasetError):
          training_pipeline(train_data=custom_no_len_train_dataset)
  
      with pytest.raises(DatasetError):
          training_pipeline(
              train_data=train_dataset.data,
              eval_data=custom_no_len_train_dataset,
          )
  
imports: import os
  import pytest
  import torch
  from torch.utils.data import Dataset, DataLoader
  from pythae.customexception import DatasetError
  from pythae.data.datasets import DatasetOutput
  from pythae.models import VAE, VAEConfig, Adversarial_AE, Adversarial_AE_Config, RAE_L2, RAE_L2_Config, VAEGAN, VAEGANConfig
  from pythae.pipelines import *
  from pythae.samplers import NormalSampler, NormalSamplerConfig
  from pythae.trainers import BaseTrainerConfig
label_desc: Use image node_id 11 for calling the Test_Pipeline_Standalone obj's underlying member method code with example usage: obj.test_training_pipeline_no_len_dataset(tmpdir, training_pipeline, train_dataset, custom_no_len_train_dataset) without return types