Viewing Details About an AI Application
- Log in to the ModelArts management console. In the navigation pane on the left, choose AI Application Management > AI Applications. The AI Applications page is displayed.
- Click the name of the target AI application. The application details page is displayed.
On the application details page, you can view the basic information and model precision of the AI application, and switch tab pages to view more information.
Table 1 Basic information about an AI application Parameter
Description
Name
Name of an AI application
Status
Status of an AI application
Version
Current version of an AI application
ID
ID of an AI application
Description
Click the edit button to add the description of an AI application.
Deployment Type
Types of the services that an AI application can be deployed
Meta Model Source
Source of the meta model, which can be training jobs, OBS, or container images.
Training Name
Associated training job if the meta model comes from a training job. Click the training job name to go to its details page.
Training Version
Training job version if the meta model comes from an old-version training job.
Storage path of the meta model
Path to the meta model if the meta model comes from OBS.
Container Image Storage Path
Path to the container image if the meta model comes from a container image.
AI Engine
AI engine if the meta model comes from a training job or OBS.
Engine Package Address
Engine package address if the meta model comes from OBS and AI Engine is Custom.
Runtime Environment
Runtime environment on which the meta model depends if the meta model comes from a training job or OBS and a preset AI engine is used.
Container API
Protocol and port number for starting the AI application if the meta model comes from OBS (AI Engine is Custom) or a container image.
Inference Code
Path to the inference code if the meta model comes from an olde-version training job.
Image Replication
Image replication status if the meta model comes from OBS or a container image.
Dynamic loading
Dynamic loading status if the meta model comes from a training job or OBS.
Size
Size of an AI application
Health Check
Health check status if the meta model comes from OBS or a container image. If health check is enabled, the following parameters are displayed: Check Mode, Health Check URL, Health Check Period, Delay, and Maximum Failures.
AI Application Description
Description document added during the creation of an AI application.
Instruction Set Architecture
System architecture.
Inference Accelerator
Type of inference accelerator cards.
Table 2 Details page of an AI application Parameter
Description
Model Precision
Model recall, precision, accuracy, and F1 score of an AI application
Parameter Configuration
API configuration, input parameters, and output parameters of an AI application
Runtime Dependency
Model dependency on the environment. If creating a job failed, edit the runtime dependency. After the modification is saved, the system will automatically use the original image to create the job again.
Events
The progress of key operations during AI application creation
Events are stored for three months and will be automatically cleared then.
For details about how to view events of an AI application, see Viewing Events of an AI Application.
Constraint
Displays the constraints of service deployment, such as the request mode, boot command, and model encryption, based on the settings during AI application creation. For AI applications in asynchronous request mode, parameters including the input mode, output mode, service startup parameters, and job configuration parameters can be displayed.
Associated Services
The list of services that an AI application was deployed. Click a service name to go to the service details page.
Feedback
Was this page helpful?
Provide feedbackThank you very much for your feedback. We will continue working to improve the documentation.See the reply and handling status in My Cloud VOC.
For any further questions, feel free to contact us through the chatbot.
Chatbot