code: def test_return_sampling_with_eval(
      self,
      dummy_data,
      training_config,
      sampler,
      num_sample_and_batch_size,
  ):
      num_samples, batch_size = (
          num_sample_and_batch_size[0],
          num_sample_and_batch_size[1],
      )
  
      start_flow = deepcopy(sampler.pixelcnn_model)
  
      sampler.fit(
          train_data=dummy_data,
          eval_data=dummy_data,
          training_config=training_config,
      )
  
      final_flow = deepcopy(sampler.pixelcnn_model)
  
      gen_samples = sampler.sample(
          num_samples=num_samples,
          batch_size=batch_size,
          return_gen=True,
      )
  
      assert gen_samples.shape[0] == num_samples
      assert start_flow != final_flow
  
imports: import os
  from copy import deepcopy
  import pytest
  import torch
  from pythae.models import VQVAE, VQVAEConfig
  from pythae.pipelines import GenerationPipeline
  from pythae.samplers import NormalSampler, NormalSamplerConfig, PixelCNNSampler, PixelCNNSamplerConfig
  from pythae.trainers import BaseTrainerConfig
  from pythae.data.preprocessors import DataProcessor
label_desc: Use image node_id 2 for calling the Test_PixelCNNSampler_Sampling obj's underlying member method code with example usage: obj.test_return_sampling_with_eval(dummy_data, training_config, sampler, num_sample_and_batch_size) without return types