code: def test_nll_compute(self, vae, demo_data, nll_params):
      nll = vae.get_nll(
          data=demo_data["data"],
          n_samples=nll_params[0],
          batch_size=nll_params[1],
      )
  
      assert isinstance(nll, float)
      assert nll < 0
  
imports: import os
  from copy import deepcopy
  import pytest
  import torch
  from pythae.customexception import BadInheritanceError
  from pythae.models import VAE, AutoModel, VAEConfig
  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 BaseTrainer, BaseTrainerConfig
  from tests.data.custom_architectures import Decoder_AE_Conv, Encoder_VAE_Conv, NetBadInheritance
label_desc: Use image node_id 4 for calling the Test_NLL_Compute obj's underlying member method code with example usage: obj.test_nll_compute(vae, demo_data, nll_params) without return types