Class: Aws::Neptunedata::Types::StartMLModelTransformJobInput

Inherits:

Struct

• Object
• Struct
• Aws::Neptunedata::Types::StartMLModelTransformJobInput

Defined in:

gems/aws-sdk-neptunedata/lib/aws-sdk-neptunedata/types.rb

Overview

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (Integer)

# File 'gems/aws-sdk-neptunedata/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:

Returns:

• (Types::CustomModelTransformParameters)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (Array<String>)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (Array<String>)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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.

Returns:

• (String)

# File 'gems/aws-sdk-neptunedata/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