sagemaker/aws.sdk.kotlin.services.sagemaker.model/HyperParameterTuningInstanceConfig

HyperParameterTuningInstanceConfig

class HyperParameterTuningInstanceConfig

The configuration for hyperparameter tuning resources for use in training jobs launched by the tuning job. These resources include compute instances and storage volumes. Specify one or more compute instance configurations and allocation strategies to select resources (optional).

Types

Builder

class Builder

Companion

object Companion

Properties

instanceCount

val instanceCount: Int?

The number of instances of the type specified by InstanceType. Choose an instance count larger than 1 for distributed training algorithms. See Step 2: Launch a SageMaker Distributed Training Job Using the SageMaker Python SDK for more information.

instanceType

val instanceType: TrainingInstanceType?

The instance type used for processing of hyperparameter optimization jobs. Choose from general purpose (no GPUs) instance types: ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more information about instance types, see instance type descriptions.

volumeSizeInGb

val volumeSizeInGb: Int?

The volume size in GB of the data to be processed for hyperparameter optimization (optional).

Functions

copy

inline fun copy(block: HyperParameterTuningInstanceConfig.Builder.() -> Unit = {}): HyperParameterTuningInstanceConfig

equals

open operator override fun equals(other: Any?): Boolean

hashCode

open override fun hashCode(): Int

toString

open override fun toString(): String