amazonka-sagemaker-2.0: Amazon SageMaker Service SDK.
Copyright(c) 2013-2023 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellSafe-Inferred
LanguageHaskell2010

Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

Description

 
Synopsis

Documentation

data HyperParameterTuningResourceConfig Source #

The configuration of resources, including compute instances and storage volumes for use in training jobs launched by hyperparameter tuning jobs. HyperParameterTuningResourceConfig is similar to ResourceConfig, but has the additional InstanceConfigs and AllocationStrategy fields to allow for flexible instance management. Specify one or more instance types, count, and the allocation strategy for instance selection.

HyperParameterTuningResourceConfig supports the capabilities of ResourceConfig with the exception of KeepAlivePeriodInSeconds. Hyperparameter tuning jobs use warm pools by default, which reuse clusters between training jobs.

See: newHyperParameterTuningResourceConfig smart constructor.

Constructors

HyperParameterTuningResourceConfig' 

Fields

  • allocationStrategy :: Maybe HyperParameterTuningAllocationStrategy

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

  • instanceConfigs :: Maybe (NonEmpty HyperParameterTuningInstanceConfig)

    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.

  • instanceCount :: Maybe Natural

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

  • instanceType :: Maybe TrainingInstanceType

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

  • volumeKmsKeyId :: Maybe Text

    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.

  • volumeSizeInGB :: Maybe Natural

    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.

Instances

Instances details
FromJSON HyperParameterTuningResourceConfig Source # 
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Defined in Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

ToJSON HyperParameterTuningResourceConfig Source # 
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Defined in Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

Generic HyperParameterTuningResourceConfig Source # 
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Defined in Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

Associated Types

type Rep HyperParameterTuningResourceConfig :: Type -> Type #

Read HyperParameterTuningResourceConfig Source # 
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Defined in Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

Show HyperParameterTuningResourceConfig Source # 
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NFData HyperParameterTuningResourceConfig Source # 
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Eq HyperParameterTuningResourceConfig Source # 
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Hashable HyperParameterTuningResourceConfig Source # 
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Defined in Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

type Rep HyperParameterTuningResourceConfig Source # 
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Defined in Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig

type Rep HyperParameterTuningResourceConfig = D1 ('MetaData "HyperParameterTuningResourceConfig" "Amazonka.SageMaker.Types.HyperParameterTuningResourceConfig" "amazonka-sagemaker-2.0-9SyrKZ4KqhsL1qX9u3ILA3" 'False) (C1 ('MetaCons "HyperParameterTuningResourceConfig'" 'PrefixI 'True) ((S1 ('MetaSel ('Just "allocationStrategy") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe HyperParameterTuningAllocationStrategy)) :*: (S1 ('MetaSel ('Just "instanceConfigs") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe (NonEmpty HyperParameterTuningInstanceConfig))) :*: S1 ('MetaSel ('Just "instanceCount") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural)))) :*: (S1 ('MetaSel ('Just "instanceType") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe TrainingInstanceType)) :*: (S1 ('MetaSel ('Just "volumeKmsKeyId") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Text)) :*: S1 ('MetaSel ('Just "volumeSizeInGB") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 (Maybe Natural))))))

newHyperParameterTuningResourceConfig :: HyperParameterTuningResourceConfig Source #

Create a value of HyperParameterTuningResourceConfig with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:allocationStrategy:HyperParameterTuningResourceConfig', hyperParameterTuningResourceConfig_allocationStrategy - The strategy that determines the order of preference for resources specified in InstanceConfigs used in hyperparameter optimization.

$sel:instanceConfigs:HyperParameterTuningResourceConfig', hyperParameterTuningResourceConfig_instanceConfigs - 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.

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

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

$sel:volumeKmsKeyId:HyperParameterTuningResourceConfig', hyperParameterTuningResourceConfig_volumeKmsKeyId - 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.

HyperParameterTuningResourceConfig, hyperParameterTuningResourceConfig_volumeSizeInGB - 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.

hyperParameterTuningResourceConfig_allocationStrategy :: Lens' HyperParameterTuningResourceConfig (Maybe HyperParameterTuningAllocationStrategy) Source #

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

hyperParameterTuningResourceConfig_instanceConfigs :: Lens' HyperParameterTuningResourceConfig (Maybe (NonEmpty HyperParameterTuningInstanceConfig)) Source #

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.

hyperParameterTuningResourceConfig_instanceCount :: Lens' HyperParameterTuningResourceConfig (Maybe Natural) Source #

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

hyperParameterTuningResourceConfig_instanceType :: Lens' HyperParameterTuningResourceConfig (Maybe TrainingInstanceType) Source #

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

hyperParameterTuningResourceConfig_volumeKmsKeyId :: Lens' HyperParameterTuningResourceConfig (Maybe Text) Source #

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.

hyperParameterTuningResourceConfig_volumeSizeInGB :: Lens' HyperParameterTuningResourceConfig (Maybe Natural) Source #

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.