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Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify.
If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with Amazon Web Services IoT Greengrass. In that case, deploy them as an ML resource.
In the request body, you provide the following:
A name for the compilation job
Information about the input model artifacts
The output location for the compiled model and the device (target) that the model runs on
The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.
You can also provide a Tag
to track the model compilation job's resource use
and costs. The response body contains the CompilationJobArn
for the compiled
job.
To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.
For .NET Core this operation is only available in asynchronous form. Please refer to CreateCompilationJobAsync.
Namespace: Amazon.SageMaker
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z
public abstract CreateCompilationJobResponse CreateCompilationJob( CreateCompilationJobRequest request )
Container for the necessary parameters to execute the CreateCompilationJob service method.
Exception | Condition |
---|---|
ResourceInUseException | Resource being accessed is in use. |
ResourceLimitExceededException | You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. |
.NET Framework:
Supported in: 4.5 and newer, 3.5