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You are right that the way to reference the stage is to propagate the tags all the way down to Model, EndpointConfig and Endpoint. When you do that through the MLOps template, CodeBuild and CloudFormation take care of the tagging.
You might need to create_model from the model package as well, here's a working example:
import boto3 client = boto3.client('sagemaker') role = '<my_role_arn>' model_package_arn = '<my_model_package_arn>' my_tags = [ {'Key': 'sagemaker:deployment-stage', 'Value': 'my_stage'}, {'Key': 'sagemaker:project-id', 'Value': 'my_project_id'}, {'Key': 'sagemaker:project-name', 'Value': 'my_project_name'}, ] client.create_model( ModelName='testing-stage-model', PrimaryContainer={ 'ModelPackageName': model_package_arn, }, ExecutionRoleArn=role, Tags=my_tags ) client.create_endpoint_config( EndpointConfigName='testing-stage-endpoint-config', ProductionVariants=[ { 'VariantName': 'AllTraffic', 'ModelName': 'testing-stage-model', 'InitialInstanceCount': 1, 'InstanceType': 'ml.t2.medium', }, ], Tags=my_tags ) client.create_endpoint( EndpointName='testing-stage-endpoint', EndpointConfigName='testing-stage-endpoint-config', Tags=my_tags )
answered 5 years ago
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