Request Syntax URI Request Parameters Request Body Response Syntax Response Elements Errors See Also

StartMLModelTransformJob

Creates a new model transform job. See Use a trained model to generate new model artifacts.

When invoking this operation in a Neptune cluster that has IAM authentication enabled, the IAM user or role making the request must have a policy attached that allows the neptune-db:StartMLModelTransformJob IAM action in that cluster.

Request Syntax


POST /ml/modeltransform HTTP/1.1
Content-type: application/json

{
   "baseProcessingInstanceType": "string",
   "baseProcessingInstanceVolumeSizeInGB": number,
   "customModelTransformParameters": { 
      "sourceS3DirectoryPath": "string",
      "transformEntryPointScript": "string"
   },
   "dataProcessingJobId": "string",
   "id": "string",
   "mlModelTrainingJobId": "string",
   "modelTransformOutputS3Location": "string",
   "neptuneIamRoleArn": "string",
   "s3OutputEncryptionKMSKey": "string",
   "sagemakerIamRoleArn": "string",
   "securityGroupIds": [ "string" ],
   "subnets": [ "string" ],
   "trainingJobName": "string",
   "volumeEncryptionKMSKey": "string"
}

URI Request Parameters

The request does not use any URI parameters.

Request Body

The request accepts the following data in JSON format.

baseProcessingInstanceType

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.

Type: String

Required: No

baseProcessingInstanceVolumeSizeInGB

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.

Type: Integer

Required: No

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:

Type: CustomModelTransformParameters object

Required: No

dataProcessingJobId

The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Type: String

Required: No

id

A unique identifier for the new job. The default is an autogenerated UUID.

Type: String

Required: No

mlModelTrainingJobId

The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Type: String

Required: No

modelTransformOutputS3Location

The location in Amazon S3 where the model artifacts are to be stored.

Type: String

Required: Yes

neptuneIamRoleArn

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.

Type: String

Required: No

s3OutputEncryptionKMSKey

The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.

Type: String

Required: No

sagemakerIamRoleArn

The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.

Type: String

Required: No

securityGroupIds

The VPC security group IDs. The default is None.

Type: Array of strings

Required: No

subnets

The IDs of the subnets in the Neptune VPC. The default is None.

Type: Array of strings

Required: No

trainingJobName

The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Type: String

Required: No

volumeEncryptionKMSKey

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.

Type: String

Required: No

Response Syntax


HTTP/1.1 200
Content-type: application/json

{
   "arn": "string",
   "creationTimeInMillis": number,
   "id": "string"
}

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.

arn

The ARN of the model transform job.

Type: String

creationTimeInMillis

The creation time of the model transform job, in milliseconds.

Type: Long

id

The unique ID of the new model transform job.

Type: String

Errors

For information about the errors that are common to all actions, see Common Errors.

BadRequestException

Raised when a request is submitted that cannot be processed.

HTTP Status Code: 400

ClientTimeoutException

Raised when a request timed out in the client.

HTTP Status Code: 408

ConstraintViolationException

Raised when a value in a request field did not satisfy required constraints.

HTTP Status Code: 400

IllegalArgumentException

Raised when an argument in a request is not supported.

HTTP Status Code: 400

InvalidArgumentException

Raised when an argument in a request has an invalid value.

HTTP Status Code: 400

InvalidParameterException

Raised when a parameter value is not valid.

HTTP Status Code: 400

MissingParameterException

Raised when a required parameter is missing.

HTTP Status Code: 400

MLResourceNotFoundException

Raised when a specified machine-learning resource could not be found.

HTTP Status Code: 404

PreconditionsFailedException

Raised when a precondition for processing a request is not satisfied.

HTTP Status Code: 400

TooManyRequestsException

Raised when the number of requests being processed exceeds the limit.

HTTP Status Code: 429

UnsupportedOperationException

Raised when a request attempts to initiate an operation that is not supported.

HTTP Status Code: 400