How to use the dtlpy.__version__ function in dtlpy

def __init__(self, configs, time, test_dataset_id, query):
        logger.info('dtlpy version: ' + str(dl.__version__))
        logger.info('dtlpy info: ' + str(dl.info()))
        time = int(time)
        dl.setenv('prod')
        configs = json.loads(configs)
        query = json.loads(query)
        self.configs_input = dl.FunctionIO(type='Json', name='configs', value=configs)
        self.service = dl.services.get('zazu')
        project_name = configs['dataloop']['project']
        self.project = dl.projects.get(project_name)
        test_dataset = self.project.datasets.get(dataset_id=test_dataset_id)
        maybe_download_pred_data(dataset_obj=test_dataset, val_query=query)

        # add gt annotations
        filters = dl.Filters()
        filters.custom_filter = query
        dataset_name = test_dataset.name

def push_and_deploy_package(self, project, package_name):
    logger.info('dtlpy version:', dl.__version__)
    dataset_input = dl.FunctionIO(type='Dataset', name='dataset')
    hp_value_input = dl.FunctionIO(type='Json', name='hp_values')
    model_specs_input = dl.FunctionIO(type='Json', name='model_specs')
    init_specs_input = dl.FunctionIO(type='Json', name='package_name')
    input_to_init = {
        'package_name': package_name
    }

    inputs = [dataset_input, hp_value_input, model_specs_input]
    function = dl.PackageFunction(name='run', inputs=inputs, outputs=[], description='')
    module = dl.PackageModule(entry_point='dataloop_services/service_executor.py', name='service_executor',
                              functions=[function],
                              init_inputs=init_specs_input)

    package = project.packages.push(
        package_name=package_name,