ResourceConfig

class aws_cdk.aws_stepfunctions_tasks.ResourceConfig(*, instance_count, instance_type, volume_size_in_gb, volume_encryption_key=None)

Bases: object

__init__(*, instance_count, instance_type, volume_size_in_gb, volume_encryption_key=None)

Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.

Parameters
  • instance_count (Union[int, float]) – The number of ML compute instances to use. Default: 1 instance.

  • instance_type (InstanceType) – ML compute instance type. Default: is the ‘m4.xlarge’ instance type.

  • volume_size_in_gb (Union[int, float]) – Size of the ML storage volume that you want to provision. Default: 10 GB EBS volume.

  • volume_encryption_key (Optional[IKey]) – KMS key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job. Default: - Amazon SageMaker uses the default KMS key for Amazon S3 for your role’s account

stability :stability: experimental

Attributes

instance_count

The number of ML compute instances to use.

default :default: 1 instance.

stability :stability: experimental

Return type

Union[int, float]

instance_type

ML compute instance type.

default :default: is the ‘m4.xlarge’ instance type.

stability :stability: experimental

Return type

InstanceType

volume_encryption_key

KMS key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.

default :default: - Amazon SageMaker uses the default KMS key for Amazon S3 for your role’s account

stability :stability: experimental

Return type

Optional[IKey]

volume_size_in_gb

Size of the ML storage volume that you want to provision.

default :default: 10 GB EBS volume.

stability :stability: experimental

Return type

Union[int, float]