code: def test_compute_loss(self, trainer, batch):
      # Test loss computation. Return torch.Tensor and dict.
      loss, log_metrics = trainer.compute_loss(batch)
      assert isinstance(loss, torch.Tensor)
      assert isinstance(log_metrics, dict)
  
imports: import pytest
  import torch
  import torch.nn
  from torch.utils.data import DataLoader, TensorDataset
  from kale.embed.image_cnn import SimpleCNNBuilder
  from kale.pipeline.base_nn_trainer import BaseNNTrainer, CNNTransformerTrainer, MultimodalNNTrainer
  from kale.predict.class_domain_nets import ClassNet
label_desc: Use image node_id 3 for calling the TestCNNTransformerTrainer obj's underlying member method code with example usage: obj.test_compute_loss(trainer, batch) without return types