def do_load_model(): request_data = request.json adapter_servings_config(request_data) retcode, retmsg = publish_model.load_model(config_data=request_data) try: if not retcode: with DB.connection_context(): model = MLModel.get_or_none(MLModel.f_role == request_data.get("local").get("role"), MLModel.f_party_id == request_data.get("local").get("party_id"), MLModel.f_model_id == request_data.get("job_parameters").get("model_id"), MLModel.f_model_version == request_data.get("job_parameters").get("model_version")) if model: count = model.f_loaded_times model.f_loaded_times = count + 1 model.save() except Exception as modify_err: stat_logger.exception(modify_err) try: party_model_id = gen_party_model_id(role=request_data.get("local").get("role"), party_id=request_data.get("local").get("party_id"), model_id=request_data.get("job_parameters").get("model_id")) src_model_path = os.path.join(file_utils.get_project_base_directory(), 'model_local_cache', party_model_id, request_data.get("job_parameters").get("model_version")) dst_model_path = os.path.join(file_utils.get_project_base_directory(), 'loaded_model_backup', party_model_id, request_data.get("job_parameters").get("model_version")) if not os.path.exists(dst_model_path): shutil.copytree(src=src_model_path, dst=dst_model_path) except Exception as copy_err: stat_logger.exception(copy_err) operation_record(request_data, "load", "success" if not retcode else "failed") return get_json_result(retcode=retcode, retmsg=retmsg)
def do_load_model(): request_data = request.json request_data['servings'] = RuntimeConfig.SERVICE_DB.get_urls('servings') role = request_data['local']['role'] party_id = request_data['local']['party_id'] model_id = request_data['job_parameters']['model_id'] model_version = request_data['job_parameters']['model_version'] party_model_id = model_utils.gen_party_model_id(model_id, role, party_id) if get_base_config('enable_model_store', False): pipeline_model = pipelined_model.PipelinedModel( party_model_id, model_version) component_parameters = { 'model_id': party_model_id, 'model_version': model_version, 'store_address': ServiceRegistry.MODEL_STORE_ADDRESS, } model_storage = get_model_storage(component_parameters) if pipeline_model.exists() and not model_storage.exists( **component_parameters): stat_logger.info( f'Uploading {pipeline_model.model_path} to model storage.') model_storage.store(**component_parameters) elif not pipeline_model.exists() and model_storage.exists( **component_parameters): stat_logger.info( f'Downloading {pipeline_model.model_path} from model storage.') model_storage.restore(**component_parameters) if not model_utils.check_if_deployed(role, party_id, model_id, model_version): return get_json_result( retcode=100, retmsg= "Only deployed models could be used to execute process of loading. " "Please deploy model before loading.") retcode, retmsg = publish_model.load_model(request_data) try: if not retcode: with DB.connection_context(): model = MLModel.get_or_none( MLModel.f_role == request_data["local"]["role"], MLModel.f_party_id == request_data["local"]["party_id"], MLModel.f_model_id == request_data["job_parameters"] ["model_id"], MLModel.f_model_version == request_data["job_parameters"]["model_version"]) if model: model.f_loaded_times += 1 model.save() except Exception as modify_err: stat_logger.exception(modify_err) operation_record(request_data, "load", "success" if not retcode else "failed") return get_json_result(retcode=retcode, retmsg=retmsg)