* 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.
*
* The instance type used to run hyperparameter optimization tuning jobs. See descriptions of * instance types for more information. *
*/ private String instanceType; /** *
* The number of compute instances of type InstanceType to use. For distributed training,
* select a value greater than 1.
*
* 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. *
** 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.
*
* The strategy that determines the order of preference for resources specified in InstanceConfigs used
* in hyperparameter optimization.
*
* 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.
*
* The instance type used to run hyperparameter optimization tuning jobs. See descriptions of * instance types for more information. *
* * @param instanceType * The instance type used to run hyperparameter optimization tuning jobs. See * descriptions of instance types for more information. * @see TrainingInstanceType */ public void setInstanceType(String instanceType) { this.instanceType = instanceType; } /** ** The instance type used to run hyperparameter optimization tuning jobs. See descriptions of * instance types for more information. *
* * @return The instance type used to run hyperparameter optimization tuning jobs. See * descriptions of instance types for more information. * @see TrainingInstanceType */ public String getInstanceType() { return this.instanceType; } /** ** The instance type used to run hyperparameter optimization tuning jobs. See descriptions of * instance types for more information. *
* * @param instanceType * The instance type used to run hyperparameter optimization tuning jobs. See * descriptions of instance types for more information. * @return Returns a reference to this object so that method calls can be chained together. * @see TrainingInstanceType */ public HyperParameterTuningResourceConfig withInstanceType(String instanceType) { setInstanceType(instanceType); return this; } /** ** The instance type used to run hyperparameter optimization tuning jobs. See descriptions of * instance types for more information. *
* * @param instanceType * The instance type used to run hyperparameter optimization tuning jobs. See * descriptions of instance types for more information. * @return Returns a reference to this object so that method calls can be chained together. * @see TrainingInstanceType */ public HyperParameterTuningResourceConfig withInstanceType(TrainingInstanceType instanceType) { this.instanceType = instanceType.toString(); return this; } /** *
* The number of compute instances of type InstanceType to use. For distributed training,
* select a value greater than 1.
*
InstanceType to use. For distributed
* training, select a value greater than 1.
*/
public void setInstanceCount(Integer instanceCount) {
this.instanceCount = instanceCount;
}
/**
*
* The number of compute instances of type InstanceType to use. For distributed training,
* select a value greater than 1.
*
InstanceType to use. For distributed
* training, select a value greater than 1.
*/
public Integer getInstanceCount() {
return this.instanceCount;
}
/**
*
* The number of compute instances of type InstanceType to use. For distributed training,
* select a value greater than 1.
*
InstanceType to use. For distributed
* training, select a value greater than 1.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public HyperParameterTuningResourceConfig withInstanceCount(Integer instanceCount) {
setInstanceCount(instanceCount);
return this;
}
/**
*
* 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. *
*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. *
*/ public void setVolumeSizeInGB(Integer volumeSizeInGB) { this.volumeSizeInGB = 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. *
*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. *
*/ public Integer getVolumeSizeInGB() { return this.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. *
*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. *
* @return Returns a reference to this object so that method calls can be chained together. */ public HyperParameterTuningResourceConfig withVolumeSizeInGB(Integer volumeSizeInGB) { setVolumeSizeInGB(volumeSizeInGB); return this; } /** ** 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.
*
* 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.
*/
public void setVolumeKmsKeyId(String volumeKmsKeyId) {
this.volumeKmsKeyId = 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.
*
* 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.
*/
public String getVolumeKmsKeyId() {
return this.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.
*
* 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.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public HyperParameterTuningResourceConfig withVolumeKmsKeyId(String volumeKmsKeyId) {
setVolumeKmsKeyId(volumeKmsKeyId);
return this;
}
/**
*
* The strategy that determines the order of preference for resources specified in InstanceConfigs used
* in hyperparameter optimization.
*
InstanceConfigs used in hyperparameter optimization.
* @see HyperParameterTuningAllocationStrategy
*/
public void setAllocationStrategy(String allocationStrategy) {
this.allocationStrategy = allocationStrategy;
}
/**
*
* The strategy that determines the order of preference for resources specified in InstanceConfigs used
* in hyperparameter optimization.
*
InstanceConfigs used in hyperparameter optimization.
* @see HyperParameterTuningAllocationStrategy
*/
public String getAllocationStrategy() {
return this.allocationStrategy;
}
/**
*
* The strategy that determines the order of preference for resources specified in InstanceConfigs used
* in hyperparameter optimization.
*
InstanceConfigs used in hyperparameter optimization.
* @return Returns a reference to this object so that method calls can be chained together.
* @see HyperParameterTuningAllocationStrategy
*/
public HyperParameterTuningResourceConfig withAllocationStrategy(String allocationStrategy) {
setAllocationStrategy(allocationStrategy);
return this;
}
/**
*
* The strategy that determines the order of preference for resources specified in InstanceConfigs used
* in hyperparameter optimization.
*
InstanceConfigs used in hyperparameter optimization.
* @return Returns a reference to this object so that method calls can be chained together.
* @see HyperParameterTuningAllocationStrategy
*/
public HyperParameterTuningResourceConfig withAllocationStrategy(HyperParameterTuningAllocationStrategy allocationStrategy) {
this.allocationStrategy = allocationStrategy.toString();
return this;
}
/**
*
* 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.
*
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.
*
* 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.
*
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.
*
* 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.
*
* NOTE: This method appends the values to the existing list (if any). Use * {@link #setInstanceConfigs(java.util.Collection)} or {@link #withInstanceConfigs(java.util.Collection)} if you * want to override the existing values. *
* * @param 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. TheAllocationStrategy 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.
*
* 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.
*
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.
*