Class: Aws::Neptunedata::Types::StartMLModelTransformJobInput
- Inherits:
-
Struct
- Object
- Struct
- Aws::Neptunedata::Types::StartMLModelTransformJobInput
- Includes:
- Structure
- Defined in:
- lib/aws-sdk-neptunedata/types.rb
Overview
Constant Summary collapse
- SENSITIVE =
[]
Instance Attribute Summary collapse
-
#base_processing_instance_type ⇒ String
The type of ML instance used in preparing and managing training of ML models.
-
#base_processing_instance_volume_size_in_gb ⇒ Integer
The disk volume size of the training instance in gigabytes.
-
#custom_model_transform_parameters ⇒ Types::CustomModelTransformParameters
Configuration information for a model transform using a custom model.
-
#data_processing_job_id ⇒ String
The job ID of a completed data-processing job.
-
#id ⇒ String
A unique identifier for the new job.
-
#ml_model_training_job_id ⇒ String
The job ID of a completed model-training job.
-
#model_transform_output_s3_location ⇒ String
The location in Amazon S3 where the model artifacts are to be stored.
-
#neptune_iam_role_arn ⇒ String
The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources.
-
#s3_output_encryption_kms_key ⇒ String
The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job.
-
#sagemaker_iam_role_arn ⇒ String
The ARN of an IAM role for SageMaker execution.
-
#security_group_ids ⇒ Array<String>
The VPC security group IDs.
-
#subnets ⇒ Array<String>
The IDs of the subnets in the Neptune VPC.
-
#training_job_name ⇒ String
The name of a completed SageMaker training job.
-
#volume_encryption_kms_key ⇒ String
The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job.
Instance Attribute Details
#base_processing_instance_type ⇒ String
The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#base_processing_instance_volume_size_in_gb ⇒ Integer
The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#custom_model_transform_parameters ⇒ Types::CustomModelTransformParameters
Configuration information for a model transform using a custom model. The ‘customModelTransformParameters` object contains the following fields, which must have values compatible with the saved model parameters from the training job:
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#data_processing_job_id ⇒ String
The job ID of a completed data-processing job. You must include either ‘dataProcessingJobId` and a `mlModelTrainingJobId`, or a `trainingJobName`.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#id ⇒ String
A unique identifier for the new job. The default is an autogenerated UUID.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#ml_model_training_job_id ⇒ String
The job ID of a completed model-training job. You must include either ‘dataProcessingJobId` and a `mlModelTrainingJobId`, or a `trainingJobName`.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#model_transform_output_s3_location ⇒ String
The location in Amazon S3 where the model artifacts are to be stored.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#neptune_iam_role_arn ⇒ String
The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#s3_output_encryption_kms_key ⇒ String
The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#sagemaker_iam_role_arn ⇒ String
The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#security_group_ids ⇒ Array<String>
The VPC security group IDs. The default is None.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#subnets ⇒ Array<String>
The IDs of the subnets in the Neptune VPC. The default is None.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#training_job_name ⇒ String
The name of a completed SageMaker training job. You must include either ‘dataProcessingJobId` and a `mlModelTrainingJobId`, or a `trainingJobName`.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |
#volume_encryption_kms_key ⇒ String
The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.
3711 3712 3713 3714 3715 3716 3717 3718 3719 3720 3721 3722 3723 3724 3725 3726 3727 3728 |
# File 'lib/aws-sdk-neptunedata/types.rb', line 3711 class StartMLModelTransformJobInput < Struct.new( :id, :data_processing_job_id, :ml_model_training_job_id, :training_job_name, :model_transform_output_s3_location, :sagemaker_iam_role_arn, :neptune_iam_role_arn, :custom_model_transform_parameters, :base_processing_instance_type, :base_processing_instance_volume_size_in_gb, :subnets, :security_group_ids, :volume_encryption_kms_key, :s3_output_encryption_kms_key) SENSITIVE = [] include Aws::Structure end |