Struct aws_sdk_sagemaker::model::hyper_parameter_tuning_resource_config::Builder

pub struct Builder { /* private fields */ }

A builder for HyperParameterTuningResourceConfig.

Implementations

impl Builder

pub fn instance_type(self, input: TrainingInstanceType) -> Self

The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.

pub fn set_instance_type(self, input: Option<TrainingInstanceType>) -> Self

The instance type used to run hyperparameter optimization tuning jobs. See descriptions of instance types for more information.

pub fn instance_count(self, input: i32) -> Self

The number of compute instances of type InstanceType to use. For distributed training, select a value greater than 1.

pub fn set_instance_count(self, input: Option<i32>) -> Self

The number of compute instances of type InstanceType to use. For distributed training, select a value greater than 1.

pub fn volume_size_in_gb(self, input: i32) -> Self

The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs is also specified.

Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.

SageMaker supports only the General Purpose SSD (gp2) storage volume type.

pub fn set_volume_size_in_gb(self, input: Option<i32>) -> Self

The volume size in GB for the storage volume to be used in processing hyperparameter optimization jobs (optional). These volumes store model artifacts, incremental states and optionally, scratch space for training algorithms. Do not provide a value for this parameter if a value for InstanceConfigs is also specified.

Some instance types have a fixed total local storage size. If you select one of these instances for training, VolumeSizeInGB cannot be greater than this total size. For a list of instance types with local instance storage and their sizes, see instance store volumes.

SageMaker supports only the General Purpose SSD (gp2) storage volume type.

pub fn volume_kms_key_id(self, input: impl Into<String>) -> Self

A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.

KMS Key ID:

"1234abcd-12ab-34cd-56ef-1234567890ab"

Amazon Resource Name (ARN) of a KMS key:

"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.

pub fn set_volume_kms_key_id(self, input: Option<String>) -> Self

A key used by Amazon Web Services Key Management Service to encrypt data on the storage volume attached to the compute instances used to run the training job. You can use either of the following formats to specify a key.

KMS Key ID:

"1234abcd-12ab-34cd-56ef-1234567890ab"

Amazon Resource Name (ARN) of a KMS key:

"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"

Some instances use local storage, which use a hardware module to encrypt storage volumes. If you choose one of these instance types, you cannot request a VolumeKmsKeyId. For a list of instance types that use local storage, see instance store volumes. For more information about Amazon Web Services Key Management Service, see KMS encryption for more information.

pub fn allocation_strategy(
    self,
    input: HyperParameterTuningAllocationStrategy
) -> Self

The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.

pub fn set_allocation_strategy(
    self,
    input: Option<HyperParameterTuningAllocationStrategy>
) -> Self

The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.

pub fn instance_configs(self, input: HyperParameterTuningInstanceConfig) -> Self

Appends an item to instance_configs.

To override the contents of this collection use set_instance_configs.

A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy controls the order in which multiple configurations provided in InstanceConfigs are used.

If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig API, do not provide a value for InstanceConfigs. Instead, use InstanceType, VolumeSizeInGB and InstanceCount. If you use InstanceConfigs, do not provide values for InstanceType, VolumeSizeInGB or InstanceCount.

pub fn set_instance_configs(
    self,
    input: Option<Vec<HyperParameterTuningInstanceConfig>>
) -> Self

A list containing the configuration(s) for one or more resources for processing hyperparameter jobs. These resources include compute instances and storage volumes to use in model training jobs launched by hyperparameter tuning jobs. The AllocationStrategy controls the order in which multiple configurations provided in InstanceConfigs are used.

If you only want to use a single instance configuration inside the HyperParameterTuningResourceConfig API, do not provide a value for InstanceConfigs. Instead, use InstanceType, VolumeSizeInGB and InstanceCount. If you use InstanceConfigs, do not provide values for InstanceType, VolumeSizeInGB or InstanceCount.

pub fn build(self) -> HyperParameterTuningResourceConfig

Consumes the builder and constructs a HyperParameterTuningResourceConfig.

Trait Implementations

impl Clone for Builder

fn clone(&self) -> Builder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Builder

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

Formats the value using the given formatter.

impl Default for Builder

fn default() -> Builder

Returns the “default value” for a type.

impl PartialEq<Builder> for Builder

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for Builder