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	TrainingJobDefinition.getResourceConfig() The resources, including the ML compute instances and ML storage volumes, to use for model training.
ResourceConfig	TrainingJob.getResourceConfig() Resources, including ML compute instances and ML storage volumes, that are configured for model training.
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	HyperParameterTrainingJobDefinition.getResourceConfig() The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
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 AWS Key Management Service (AWS 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.
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	TrainingJobDefinition.setResourceConfig(ResourceConfig resourceConfig) The resources, including the ML compute instances and ML storage volumes, to use for model training.
void	TrainingJob.setResourceConfig(ResourceConfig resourceConfig) Resources, including ML compute instances and ML storage volumes, that are configured for model training.
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.
void	HyperParameterTrainingJobDefinition.setResourceConfig(ResourceConfig resourceConfig) The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
TrainingJobDefinition	TrainingJobDefinition.withResourceConfig(ResourceConfig resourceConfig) The resources, including the ML compute instances and ML storage volumes, to use for model training.
TrainingJob	TrainingJob.withResourceConfig(ResourceConfig resourceConfig) Resources, including ML compute instances and ML storage volumes, that are configured 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.
HyperParameterTrainingJobDefinition	HyperParameterTrainingJobDefinition.withResourceConfig(ResourceConfig resourceConfig) The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.