Struct aws_sdk_sagemaker::operation::create_processing_job::CreateProcessingJobInput

#[non_exhaustive]
pub struct CreateProcessingJobInput {
    pub processing_inputs: Option<Vec<ProcessingInput>>,
    pub processing_output_config: Option<ProcessingOutputConfig>,
    pub processing_job_name: Option<String>,
    pub processing_resources: Option<ProcessingResources>,
    pub stopping_condition: Option<ProcessingStoppingCondition>,
    pub app_specification: Option<AppSpecification>,
    pub environment: Option<HashMap<String, String>>,
    pub network_config: Option<NetworkConfig>,
    pub role_arn: Option<String>,
    pub tags: Option<Vec<Tag>>,
    pub experiment_config: Option<ExperimentConfig>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

processing_inputs: Option<Vec<ProcessingInput>>

An array of inputs configuring the data to download into the processing container.

processing_output_config: Option<ProcessingOutputConfig>

Output configuration for the processing job.

processing_job_name: Option<String>

The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.

processing_resources: Option<ProcessingResources>

Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.

stopping_condition: Option<ProcessingStoppingCondition>

The time limit for how long the processing job is allowed to run.

app_specification: Option<AppSpecification>

Configures the processing job to run a specified Docker container image.

environment: Option<HashMap<String, String>>

The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.

network_config: Option<NetworkConfig>

Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.

role_arn: Option<String>

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

tags: Option<Vec<Tag>>

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.

experiment_config: Option<ExperimentConfig>

Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:

• CreateProcessingJob

• CreateTrainingJob

• CreateTransformJob

Implementations

impl CreateProcessingJobInput

pub fn processing_inputs(&self) -> &[ProcessingInput]

An array of inputs configuring the data to download into the processing container.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .processing_inputs.is_none().

pub fn processing_output_config(&self) -> Option<&ProcessingOutputConfig>

Output configuration for the processing job.

pub fn processing_job_name(&self) -> Option<&str>

The name of the processing job. The name must be unique within an Amazon Web Services Region in the Amazon Web Services account.

pub fn processing_resources(&self) -> Option<&ProcessingResources>

Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.

pub fn stopping_condition(&self) -> Option<&ProcessingStoppingCondition>

The time limit for how long the processing job is allowed to run.

pub fn app_specification(&self) -> Option<&AppSpecification>

Configures the processing job to run a specified Docker container image.

pub fn environment(&self) -> Option<&HashMap<String, String>>

The environment variables to set in the Docker container. Up to 100 key and values entries in the map are supported.

pub fn network_config(&self) -> Option<&NetworkConfig>

Networking options for a processing job, such as whether to allow inbound and outbound network calls to and from processing containers, and the VPC subnets and security groups to use for VPC-enabled processing jobs.

pub fn role_arn(&self) -> Option<&str>

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.

pub fn tags(&self) -> &[Tag]

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .tags.is_none().

pub fn experiment_config(&self) -> Option<&ExperimentConfig>

Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:

• CreateProcessingJob

• CreateTrainingJob

• CreateTransformJob

impl CreateProcessingJobInput

pub fn builder() -> CreateProcessingJobInputBuilder

Creates a new builder-style object to manufacture CreateProcessingJobInput.

Trait Implementations

impl Clone for CreateProcessingJobInput

fn clone(&self) -> CreateProcessingJobInput

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateProcessingJobInput

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for CreateProcessingJobInput

fn eq(&self, other: &CreateProcessingJobInput) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateProcessingJobInput