def test_convolutional_network():
    """Test smaller version of convolutional_network.ipynb"""
    skip.skip_if_no_data()
    yaml_file_path = os.path.abspath(os.path.join(os.path.dirname(__file__),
                                                  '..'))
    save_path = os.path.dirname(os.path.realpath(__file__))
    # Escape potential backslashes in Windows filenames, since
    # they will be processed when the YAML parser will read it
    # as a string
    save_path.replace('\\', r'\\')

    yaml = open("{0}/conv.yaml".format(yaml_file_path), 'r').read()
    hyper_params = {'train_stop': 50,
                    'valid_stop': 50050,
                    'test_stop': 50,
                    'batch_size': 50,
                    'output_channels_h2': 4,
                    'output_channels_h3': 4,
                    'max_epochs': 1,
                    'save_path': save_path}
    yaml = yaml % (hyper_params)
    train = yaml_parse.load(yaml)
    train.main_loop()

    try:
        os.remove("{}/convolutional_network_best.pkl".format(save_path))
    except __HOLE__:
        pass
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/scripts/tutorials/convolutional_network/tests/test_convnet.py/test_convolutional_network