Update the Approval Status of a Model
After you create a model version, you typically want to evaluate its performance
before you deploy it to a production endpoint. If it performs to your requirements,
you can update the approval status of the model version to Approved.
Setting the status to Approved can initiate CI/CD deployment for the
model. If the model version does not perform to your requirements, you can update
the approval status to Rejected.
You can manually update the approval status of a model version after you register it, or you can create a condition step to evaluate the model when you create a SageMaker AI pipeline. For information about creating a condition step in a SageMaker AI pipeline, see Pipelines steps.
When you use one of the SageMaker AI provided project templates and the approval status of a model version changes, the following action occurs. Only valid transitions are shown.
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PendingManualApprovaltoApproved– initiates CI/CD deployment for the approved model version -
PendingManualApprovaltoRejected– No action -
RejectedtoApproved– initiates CI/CD deployment for the approved model version -
ApprovedtoRejected– initiates CI/CD to deploy the latest model version with anApprovedstatus
You can update the approval status of a model version by using the AWS SDK for Python (Boto3) or by using the Amazon SageMaker Studio console. You can also update the approval status of a model version as part of a condition step in a SageMaker AI pipeline. For information about using a model approval step in a SageMaker AI pipeline, see Pipelines overview.
Update the Approval Status of a Model (Boto3)
When you created the model version in Register a Model Version, you set the
ModelApprovalStatus to PendingManualApproval. You
update the approval status for the model by calling
update_model_package. Note that you can automate this process
by writing code that, for example, sets the approval status of a model depending
on the result of an evaluation of some measure of the model's performance. You
can also create a step in a pipeline that automatically deploys a new model
version when it is approved. The following code snippet shows how to manually
change the approval status to Approved.
model_package_update_input_dict = { "ModelPackageArn" : model_package_arn, "ModelApprovalStatus" : "Approved" } model_package_update_response = sm_client.update_model_package(**model_package_update_input_dict)
Update the Approval Status of a Model (Studio or Studio Classic)
To manually change the approval status in the Amazon SageMaker Studio console, complete the following steps based on whether you use Studio or Studio Classic.
For us-east-1, us-west-2, ap-northeast-1,
and eu-west-1 regions, you can use the following instructions to access
the lineage details for logged and registered model versions:
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Open the SageMaker Studio console by following the instructions in Launch Amazon SageMaker Studio.
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Choose Models from the left navigation pane.
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Choose the Logged models tab, if not selected already, then select Registered Models.
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Select a model and choose View Latest Version.
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Choose the Governance tab.
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The Deploy section under Governance overview displays the current approval status. Select the updated approval status from the dropdown menu.