code: def test_training_pipeline_with_dataloader(
      self, tmpdir, training_pipeline, train_dataloader
  ):
      # Simulate a training run with a DataLoader
      tmpdir.mkdir("dataloader_test")
      dir_path = os.path.join(tmpdir, "dataloader_test")
      training_pipeline.training_config.output_dir = dir_path
      training_pipeline.training_config.num_epochs = 1
      training_pipeline(
          train_data=train_dataloader, eval_data=train_dataloader
      )
  
      assert isinstance(
          training_pipeline.trainer.train_loader, DataLoader
      )
      assert isinstance(
          training_pipeline.trainer.eval_loader, DataLoader
      )
  
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 14 for calling the Test_Pipeline_Standalone obj's underlying member method code with example usage: obj.test_training_pipeline_with_dataloader(tmpdir, training_pipeline, train_dataloader) without return types