code: def test_fits_in_generation_pipeline(
      self, ae_model, sampler_configs, train_data
  ):
      pipeline = GenerationPipeline(
          model=ae_model, sampler_config=sampler_configs
      )
      gen_data = pipeline(
          num_samples=11,
          batch_size=7,
          output_dir=None,
          return_gen=True,
          train_data=train_data,
          eval_data=train_data,
          training_config=BaseTrainerConfig(num_epochs=1),
      )
  
      assert gen_data.shape[0] == 11
  
imports: import os
  from copy import deepcopy
  import pytest
  import torch
  from pythae.customexception import BadInheritanceError
  from pythae.models import AutoModel, PoincareVAE, PoincareVAEConfig
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.pvae.pvae_utils import PoincareBall
  from pythae.pipelines import GenerationPipeline, TrainingPipeline
  from pythae.samplers import GaussianMixtureSamplerConfig, IAFSamplerConfig, MAFSamplerConfig, NormalSamplerConfig, PoincareDiskSamplerConfig, TwoStageVAESamplerConfig
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
  from tests.data.custom_architectures import Decoder_AE_Conv, Encoder_SVAE_Conv, Encoder_VAE_Conv, NetBadInheritance
label_desc: Use image node_id 5 for calling the Test_VAE_Generation obj's underlying member method code with example usage: obj.test_fits_in_generation_pipeline(ae_model, sampler_configs, train_data) without return types