pub struct CreateCompilationJobFluentBuilder { /* private fields */ }Expand description
Fluent builder constructing a request to CreateCompilationJob.
Starts a model compilation job. After the model has been compiled, Amazon SageMaker AI 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 AI 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 AI 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.
Implementations§
Source§impl CreateCompilationJobFluentBuilder
impl CreateCompilationJobFluentBuilder
Sourcepub fn as_input(&self) -> &CreateCompilationJobInputBuilder
pub fn as_input(&self) -> &CreateCompilationJobInputBuilder
Access the CreateCompilationJob as a reference.
Sourcepub async fn send(
self,
) -> Result<CreateCompilationJobOutput, SdkError<CreateCompilationJobError, HttpResponse>>
pub async fn send( self, ) -> Result<CreateCompilationJobOutput, SdkError<CreateCompilationJobError, HttpResponse>>
Sends the request and returns the response.
If an error occurs, an SdkError will be returned with additional details that
can be matched against.
By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.
Sourcepub fn customize(
self,
) -> CustomizableOperation<CreateCompilationJobOutput, CreateCompilationJobError, Self>
pub fn customize( self, ) -> CustomizableOperation<CreateCompilationJobOutput, CreateCompilationJobError, Self>
Consumes this builder, creating a customizable operation that can be modified before being sent.
Sourcepub fn compilation_job_name(self, input: impl Into<String>) -> Self
pub fn compilation_job_name(self, input: impl Into<String>) -> Self
A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
Sourcepub fn set_compilation_job_name(self, input: Option<String>) -> Self
pub fn set_compilation_job_name(self, input: Option<String>) -> Self
A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
Sourcepub fn get_compilation_job_name(&self) -> &Option<String>
pub fn get_compilation_job_name(&self) -> &Option<String>
A name for the model compilation job. The name must be unique within the Amazon Web Services Region and within your Amazon Web Services account.
Sourcepub fn role_arn(self, input: impl Into<String>) -> Self
pub fn role_arn(self, input: impl Into<String>) -> Self
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model compilation, Amazon SageMaker AI needs your permission to:
-
Read input data from an S3 bucket
-
Write model artifacts to an S3 bucket
-
Write logs to Amazon CloudWatch Logs
-
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
Sourcepub fn set_role_arn(self, input: Option<String>) -> Self
pub fn set_role_arn(self, input: Option<String>) -> Self
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model compilation, Amazon SageMaker AI needs your permission to:
-
Read input data from an S3 bucket
-
Write model artifacts to an S3 bucket
-
Write logs to Amazon CloudWatch Logs
-
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
Sourcepub fn get_role_arn(&self) -> &Option<String>
pub fn get_role_arn(&self) -> &Option<String>
The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker AI to perform tasks on your behalf.
During model compilation, Amazon SageMaker AI needs your permission to:
-
Read input data from an S3 bucket
-
Write model artifacts to an S3 bucket
-
Write logs to Amazon CloudWatch Logs
-
Publish metrics to Amazon CloudWatch
You grant permissions for all of these tasks to an IAM role. To pass this role to Amazon SageMaker AI, the caller of this API must have the iam:PassRole permission. For more information, see Amazon SageMaker AI Roles.
Sourcepub fn model_package_version_arn(self, input: impl Into<String>) -> Self
pub fn model_package_version_arn(self, input: impl Into<String>) -> Self
The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
Sourcepub fn set_model_package_version_arn(self, input: Option<String>) -> Self
pub fn set_model_package_version_arn(self, input: Option<String>) -> Self
The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
Sourcepub fn get_model_package_version_arn(&self) -> &Option<String>
pub fn get_model_package_version_arn(&self) -> &Option<String>
The Amazon Resource Name (ARN) of a versioned model package. Provide either a ModelPackageVersionArn or an InputConfig object in the request syntax. The presence of both objects in the CreateCompilationJob request will return an exception.
Sourcepub fn input_config(self, input: InputConfig) -> Self
pub fn input_config(self, input: InputConfig) -> Self
Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
Sourcepub fn set_input_config(self, input: Option<InputConfig>) -> Self
pub fn set_input_config(self, input: Option<InputConfig>) -> Self
Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
Sourcepub fn get_input_config(&self) -> &Option<InputConfig>
pub fn get_input_config(&self) -> &Option<InputConfig>
Provides information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
Sourcepub fn output_config(self, input: OutputConfig) -> Self
pub fn output_config(self, input: OutputConfig) -> Self
Provides information about the output location for the compiled model and the target device the model runs on.
Sourcepub fn set_output_config(self, input: Option<OutputConfig>) -> Self
pub fn set_output_config(self, input: Option<OutputConfig>) -> Self
Provides information about the output location for the compiled model and the target device the model runs on.
Sourcepub fn get_output_config(&self) -> &Option<OutputConfig>
pub fn get_output_config(&self) -> &Option<OutputConfig>
Provides information about the output location for the compiled model and the target device the model runs on.
Sourcepub fn vpc_config(self, input: NeoVpcConfig) -> Self
pub fn vpc_config(self, input: NeoVpcConfig) -> Self
A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
Sourcepub fn set_vpc_config(self, input: Option<NeoVpcConfig>) -> Self
pub fn set_vpc_config(self, input: Option<NeoVpcConfig>) -> Self
A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
Sourcepub fn get_vpc_config(&self) -> &Option<NeoVpcConfig>
pub fn get_vpc_config(&self) -> &Option<NeoVpcConfig>
A VpcConfig object that specifies the VPC that you want your compilation job to connect to. Control access to your models by configuring the VPC. For more information, see Protect Compilation Jobs by Using an Amazon Virtual Private Cloud.
Sourcepub fn stopping_condition(self, input: StoppingCondition) -> Self
pub fn stopping_condition(self, input: StoppingCondition) -> Self
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
Sourcepub fn set_stopping_condition(self, input: Option<StoppingCondition>) -> Self
pub fn set_stopping_condition(self, input: Option<StoppingCondition>) -> Self
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
Sourcepub fn get_stopping_condition(&self) -> &Option<StoppingCondition>
pub fn get_stopping_condition(&self) -> &Option<StoppingCondition>
Specifies a limit to how long a model compilation job can run. When the job reaches the time limit, Amazon SageMaker AI ends the compilation job. Use this API to cap model training costs.
Appends an item to Tags.
To override the contents of this collection use set_tags.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
Trait Implementations§
Source§impl Clone for CreateCompilationJobFluentBuilder
impl Clone for CreateCompilationJobFluentBuilder
Source§fn clone(&self) -> CreateCompilationJobFluentBuilder
fn clone(&self) -> CreateCompilationJobFluentBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreAuto Trait Implementations§
impl Freeze for CreateCompilationJobFluentBuilder
impl !RefUnwindSafe for CreateCompilationJobFluentBuilder
impl Send for CreateCompilationJobFluentBuilder
impl Sync for CreateCompilationJobFluentBuilder
impl Unpin for CreateCompilationJobFluentBuilder
impl !UnwindSafe for CreateCompilationJobFluentBuilder
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