code: def trainer(self, pixelcnn, train_dataset, training_configs):
      trainer = BaseTrainer(
          model=pixelcnn,
          train_dataset=train_dataset,
          eval_dataset=train_dataset,
          training_config=training_configs,
      )
  
      trainer.prepare_training()
  
      return trainer
  
imports: import os
  from copy import deepcopy
  import numpy
  import pytest
  import torch
  from pydantic import ValidationError
  from pythae.models import AutoModel
  from pythae.models.base.base_utils import ModelOutput
  from pythae.models.normalizing_flows import PixelCNN, PixelCNNConfig
  from pythae.pipelines import TrainingPipeline
  from pythae.trainers import BaseTrainer, BaseTrainerConfig
label_desc: Use image node_id 5 for calling the Test_PixelCNN_Training obj's underlying member method code with example usage: obj.trainer(pixelcnn, train_dataset, training_configs) and returns: trainer