code: def train_data(self):
      return torch.load(
          os.path.join(PATH, "data/mnist_clean_train_dataset_sample")
      ).data
  
imports: import os
  from copy import deepcopy
  import pytest
  import torch
  from pythae.customexception import BadInheritanceError
  from pythae.data.preprocessors import DataProcessor
  from pythae.models import AutoModel, FactorVAE, FactorVAEConfig
  from pythae.models.base.base_utils import ModelOutput
  from pythae.pipelines import GenerationPipeline, TrainingPipeline
  from pythae.samplers import GaussianMixtureSamplerConfig, IAFSamplerConfig, MAFSamplerConfig, NormalSamplerConfig, TwoStageVAESamplerConfig
  from pythae.trainers import AdversarialTrainer, AdversarialTrainerConfig, BaseTrainerConfig
  from tests.data.custom_architectures import Decoder_AE_Conv, Encoder_VAE_Conv, NetBadInheritance
label_desc: Use image node_id 1 for calling the Test_FactorVAE_Generation obj's underlying member method code with example usage: obj.train_data() and returns: torch