code: def data():
      # Create dummy data for testing. The dimension is following the CIFAR10 dataset.
      x = torch.randn(8, 3, 32, 32)
      y = torch.randint(0, 2, (8,))
      return TensorDataset(x, y)
  
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 1 for calling a global function with example usage: data() and returns: TensorDataset