Platform for AI (PAI) supports custom images. You can add images from Alibaba Cloud Container Registry to a PAI workspace and use the images in different modules of PAI. This topic describes how to add and view custom images.
Permission requirements
Alibaba Cloud account: An Alibaba Cloud account has the permissions to perform all operations that are described in this topic.
RAM user: A Resource Access Management (RAM) user must obtain the required permissions to perform the operations that are described in this topic. To grant the RAM user the required permissions, add the RAM user as a workspace member and assign the corresponding role. For information about the permissions of each role, see Appendix: Roles and permissions. For information about how to add a workspace member, see Manage members of a workspace.
Add a custom image
Go to the Images page.
Log on to the PAI console.
In the left-side navigation pane, click Workspaces. On the Workspaces page, click the name of the workspace that you want to manage.
In the left-side navigation pane, choose .
On the Images page, click the Custom Image tab.
Click Add Image.
In the Add Image panel, configure the parameters. The following table describes the parameters.
Parameter
Description
Image Name
The name of the image that you want to add. The name is displayed in the image list.
Image Type
Valid values:
NoteAn image upload and download restriction is imposed on Container Registry Personal Edition. We recommend that you use Container Registry Enterprise Edition. For more information, see Announcement about image upload and download restrictions of Container Registry Personal Edition.
Personal Edition Image (Container Registry): provides basic container images for individual developers.
Enterprise Edition Image (Container Registry): allows enterprises to manage and distribute Open Container Initiative (OCI) artifacts, such as container images, Helm charts, and Kubernetes operators, in a secure and efficient manner.
Enterprise Edition Instance (Container Registry)
If you set the Image Type parameter to Enterprise Edition Image (Container Registry), you must configure this parameter.
Select the Container Registry Enterprise Edition instance to which the custom image is pushed.
NoteIf the system prompts that you do not have the permission, grant the AliyunContainerRegistryReadOnlyAccess permission to the RAM user that you use. For more information, see Grant permissions to a RAM user.
Image Namespace
Select a namespace. You can manage a collection of repositories in the namespace.
Image Repository
Select the image repository that you created. For information about how to create an image repository, see Main features of a repository and Step 2: Create an image repository.
Image Version
Select an image version.
Use Custom Domain Name
This parameter is available only if you set the Image Type parameter to Enterprise Edition Image (Container Registry).
If you specify a custom domain name, you can use it to access the Enterprise Edition instance over HTTP.
Visibility
The visibility of the custom image. Valid values:
Visible to Me: The image is visible only to you and the administrator of the current workspace.
Visible to Current Workspace: The image is visible to all members of the current workspace.
CPU/GPU
You can select CPU or GPU to ensure that the image can run in a specific environment.
Description
The description of the image. Enter a description based on your business requirements to facilitate image management.
Click OK.
View a custom image
On the Images page, click the Custom Image tab.
Find the image that you want to view in the image list. The following information is available:
Image ID: Move the pointer over the image name to view the image ID.
Image address: Click the
icon in the Image Address column to copy the address of the image. Public endpoint: Click View Container Registry images in the Actions column. On the Details page, you can view the public endpoint that is used to access the image. Copy the endpoint to use the image for model training.
References
For information about the official images supported by PAI, see Official PAI images.
After you configure images, resources, code builds, and datasets, you can submit a Deep Learning Container (DLC) job. For more information, see Submit training jobs.