Uses of Class
com.amazonaws.services.sagemaker.model.ResourceConfig

Packages that use ResourceConfig

Package	Description
com.amazonaws.services.sagemaker.model

Uses of ResourceConfig in com.amazonaws.services.sagemaker.model

Methods in com.amazonaws.services.sagemaker.model that return ResourceConfig

Modifier and Type	Method and Description
ResourceConfig	ResourceConfig.clone()
ResourceConfig	DescribeTrainingJobResult.getResourceConfig() Resources, including ML compute instances and ML storage volumes, that are configured for model training.
ResourceConfig	CreateTrainingJobRequest.getResourceConfig() The resources, including the ML compute instances and ML storage volumes, to use for model training.
ResourceConfig	ResourceConfig.withInstanceCount(Integer instanceCount) The number of ML compute instances to use.
ResourceConfig	ResourceConfig.withInstanceType(String instanceType) The ML compute instance type.
ResourceConfig	ResourceConfig.withInstanceType(TrainingInstanceType instanceType) The ML compute instance type.
ResourceConfig	ResourceConfig.withVolumeKmsKeyId(String volumeKmsKeyId) The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
ResourceConfig	ResourceConfig.withVolumeSizeInGB(Integer volumeSizeInGB) The size of the ML storage volume that you want to provision.

Methods in com.amazonaws.services.sagemaker.model with parameters of type ResourceConfig

Modifier and Type	Method and Description
void	DescribeTrainingJobResult.setResourceConfig(ResourceConfig resourceConfig) Resources, including ML compute instances and ML storage volumes, that are configured for model training.
void	CreateTrainingJobRequest.setResourceConfig(ResourceConfig resourceConfig) The resources, including the ML compute instances and ML storage volumes, to use for model training.
DescribeTrainingJobResult	DescribeTrainingJobResult.withResourceConfig(ResourceConfig resourceConfig) Resources, including ML compute instances and ML storage volumes, that are configured for model training.
CreateTrainingJobRequest	CreateTrainingJobRequest.withResourceConfig(ResourceConfig resourceConfig) The resources, including the ML compute instances and ML storage volumes, to use for model training.