Values_0.HyperParameterTuningInstanceConfigSourceThe 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).
type nonrec t = {instanceType : TrainingInstanceType.t;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.
*)instanceCount : TrainingInstanceCount.t;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.
*)volumeSizeInGB : VolumeSizeInGB.t;The volume size in GB of the data to be processed for hyperparameter optimization (optional).
*)}val make :
instanceType:TrainingInstanceType.t ->
instanceCount:TrainingInstanceCount.t ->
volumeSizeInGB:VolumeSizeInGB.t ->
unit ->
tval to_value :
t ->
[> `Structure of
(string * [> `Enum of string | `Integer of TrainingInstanceCount.t ])
list ]