sagemaker_create_edge_packaging_job: Starts a SageMaker Edge Manager model packaging job
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

sagemaker_create_edge_packaging_job

R Documentation

Starts a SageMaker Edge Manager model packaging job

Description

Starts a SageMaker Edge Manager model packaging job. Edge Manager will use the model artifacts from the Amazon Simple Storage Service bucket that you specify. After the model has been packaged, Amazon SageMaker saves the resulting artifacts to an S3 bucket that you specify.

See https://www.paws-r-sdk.com/docs/sagemaker_create_edge_packaging_job/ for full documentation.

Usage

sagemaker_create_edge_packaging_job(
  EdgePackagingJobName,
  CompilationJobName,
  ModelName,
  ModelVersion,
  RoleArn,
  OutputConfig,
  ResourceKey = NULL,
  Tags = NULL
)

Arguments

`EdgePackagingJobName`	[required] The name of the edge packaging job.
`CompilationJobName`	[required] The name of the SageMaker Neo compilation job that will be used to locate model artifacts for packaging.
`ModelName`	[required] The name of the model.
`ModelVersion`	[required] The version of the model.
`RoleArn`	[required] The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to download and upload the model, and to contact SageMaker Neo.
`OutputConfig`	[required] Provides information about the output location for the packaged model.
`ResourceKey`	The Amazon Web Services KMS key to use when encrypting the EBS volume the edge packaging job runs on.
`Tags`	Creates tags for the packaging job.