code: def test_avmnist_dataset(dummy_data):
      # Initialize AVMNISTDataset with temporary data directory
      dataset = AVMNISTDataset(dummy_data)
  
      # Test train, validation, and test data loaders
      train_loader = dataset.get_train_loader()
      valid_loader = dataset.get_valid_loader()
      test_loader = dataset.get_test_loader()
  
      # Check if the loaders are working and have the correct dimensions
      for loader in [train_loader, valid_loader, test_loader]:
          for images, audios, labels in loader:
              assert images.shape[1:] == (1, 28, 28)
              assert audios.shape[1:] == (1, 112, 112)
              assert labels.min() >= 0
              assert labels.max() < 10
              break
  
file_path: pykale/tests/loaddata/test_avmnist_datasets.py
imports: import os
  import tempfile
  import numpy
  import pytest
  from kale.loaddata.avmnist_datasets import AVMNISTDataset
label_desc: Use image node_id 3 for calling a global function with example usage: test_avmnist_dataset(dummy_data) without return types