code: def train_dataset(self):
      return BaseDataset(torch.randn(3, 12), torch.ones(3))
  
imports: import os
  import shutil
  from copy import deepcopy
  import numpy
  import pytest
  import torch
  from torch.optim import Adam
  from pythae.data.datasets import BaseDataset
  from pythae.models import AutoModel
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.normalizing_flows import NFModel, RadialFlow, RadialFlowConfig
  from pythae.pipelines import TrainingPipeline
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
label_desc: Use image node_id 1 for calling the Test_RadialFlow_Training obj's underlying member method code with example usage: obj.train_dataset() and returns: BaseDataset