Help Center/ ModelArts/ SDK Reference/ Service Management/ Updating Service Configurations

Updated on 2024-03-21 GMT+08:00

View PDF

Updating Service Configurations

You can use the API to update the configurations of a service object.

Sample Code

In ModelArts notebook, you do not need to enter authentication parameters for session authentication. For details about session authentication of other development environments, see Session Authentication.

Method 1: Update the configurations of a service based on the service object created in Deploying a Real-Time Service.

      
           from modelarts.session import Session
from modelarts.model import Predictor
from modelarts.config.model_config import ServiceConfig

session = Session()
predictor_instance = Predictor(session, service_id="your_service_id")
configs = [ServiceConfig(weight="100", instance_count=1, specification="modelarts.vm.cpu.2u",model_id="your_model_id")]
service_config = predictor_instance.update_service_config(description="description",
                                                              status="running",
                                                              configs=configs)

Method 2: Update the configurations of a service based on the service object returned in Obtaining Service Objects.

      
           from modelarts.session import Session
from modelarts.model import Predictor
from modelarts.config.model_config import ServiceConfig

session = Session()
predictor_object_list = Predictor.get_service_object_list(session)
predictor_instance = predictor_object_list[0]                  
configs = [ServiceConfig(weight="100", instance_count=1, specification="modelarts.vm.cpu.2u",model_id="your_model_id")]
predictor_config = predictor_instance.update_service_config(description="description",
                                                                status="running",
                                                                configs=configs)

Parameters

**Table 1** Parameters for deploying **predictor**
Parameter	Mandatory	Type	Description
description	No	String	Service description, which contains a maximum of 100 characters. If this parameter is not set, the service description is not updated.
status	No	String	Service status. The value can be running or stopped. If this parameter is not set, the service status is not changed. status and configs cannot be modified at the same time. If both parameters exist, modify only the status parameter.
configs	No	predictor configs and transformer configs	Service configurations. If this parameter is not set, the service is not updated. For details about how to generate configs, see Deploying a Real-Time Service.

The restrictions on updating service configurations are as follows:

The specified status cannot be the same as the current service status.
If the service status is deploying, stopping, or deleting, status cannot be set to running or configs is not allowed to configure.
If the service status is waiting, status cannot be set to running.
If the service status is concerning, status cannot be set to running.

**Table 2** **configs** parameters of **predictor**
Parameter	Mandatory	Type	Description
model_id	Yes	String	Model ID. You can obtain the value by calling the API described in Obtaining Models or from the ModelArts management console.
weight	Yes	Integer	Weight of traffic allocated to a model. This parameter is mandatory only when infer_type is set to real-time. The sum of multiple weights must be equal to 100. If multiple model versions are configured in a real-time service and different traffic weights are set, ModelArts continuously accesses the prediction API of the service and forwards prediction requests to the model instances of the corresponding versions based on the weights.
specification	Yes	String	Resource flavor. Currently, modelarts.vm.cpu.2u, modelarts.vm.gpu.p4 (you must apply for it), and modelarts.vm.ai1.a310 (you must apply for it) are available. To use a flavor that requires permission, submit a service ticket on HUAWEI CLOUD and ModelArts O&M engineers will grant you the permission.
instance_count	Yes	Integer	Number of instances deployed in a model. The maximum number of instances is 5. To use more instances, submit a service ticket.
envs	No	Map<String, String>	(Optional) Environment variable key-value pair required for running a model. By default, this parameter is left blank.

**Table 3** **configs** parameters of **transformer**
Parameter	Mandatory	Type	Description
model_id	Yes	String	Model ID. You can obtain the value by calling the API described in Obtaining Models or from the ModelArts management console.
specification	Yes	String	Resource flavor. Currently, modelarts.vm.cpu.2u and modelarts.vm.gpu.p4 are available.
instance_count	Yes	Integer	Number of instances deployed in a model. The maximum number of instances is 5. To use more instances, submit a service ticket.
envs	No	Map<String, String>	(Optional) Environment variable key-value pair required for running a model. By default, this parameter is left blank.
src_path	Yes	String	OBS path of the input data of a batch job
dest_path	Yes	String	OBS path of the output data of a batch job
req_uri	Yes	String	Inference API called in batch tasks. You must select an API URL from the config.json file of the model for inference.
mapping_type	Yes	String	Mapping type of the input data. The value can be file or csv. If you select file, each inference request corresponds to a file in the input data path. When this mode is used, req_uri of a model can have only one input parameter and the type of this parameter is file. If you select csv, each inference request corresponds to a row of data in the CSV file. When this mode is used, the files in the input data path can only be in CSV format and mapping_rule needs to be configured to map the index of each parameter in the inference request body to the CSV file.
mapping_rule	No	Map	Mapping between input parameters and CSV data. This parameter is mandatory only when mapping_type is set to csv. The mapping rule is similar to the definition of the input parameters in the config.json file. You only need to configure the index parameters under each parameter of the string, number, integer, or boolean type, and the value of this parameter to the values of the index parameters in the CSV file to send an inference request. Use commas (,) to separate multiple pieces of CSV data. The values of the index parameters start from 0. If the value of the index parameter is -1, ignore this parameter.

**Table 4** **update_service_config** response parameters
Parameter	Mandatory	Type	Description
error_code	Yes	String	Error code when the API call fails. This parameter is not included when the API call succeeds.
error_msg	Yes	String	Error message when the API call fails. This parameter is not included when the API call succeeds.