How to use the dtlpy.entities function in dtlpy

def run(self, dataset_obj, model_specs, hp_values, config=None, progress=None):

        download_data(dataset_obj)

        # get project
        project = dataset_obj.project
        assert isinstance(project, dl.entities.Project)

        cls = getattr(import_module('.adapter', 'zoo.' + model_specs['name']), 'AdapterModel')
        final = 1
        devices = {'gpu_index': 0}

        adapter = cls(devices, model_specs, hp_values, final)
        if hasattr(adapter, 'reformat'):
            adapter.reformat()
        if hasattr(adapter, 'data_loader'):
            adapter.data_loader()
        if hasattr(adapter, 'preprocess'):
            adapter.preprocess()
        if hasattr(adapter, 'build'):
            adapter.build()
        adapter.train()

def run(self, dataset, configs=None, progress=None):
        project = dataset.project
        assert isinstance(project, dl.entities.Project)
        pipeline_id = str(uuid.uuid1())
        local_path = os.path.join(os.getcwd(), pipeline_id)
        #######################
        # download for resume #
        #######################
        project.artifacts.download(plugin_name='tuner',
                                   session_id=pipeline_id,
                                   local_path=local_path)

        # start tune

        # deploy trainers
        trainer_deployment = project.deployments.get(deployment_name='trainer')
        for i in range(5):
            trainer_deployment.sessions.create()