[ aws . neptunedata ]

start-ml-model-transform-job

Description

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.

See also: AWS API Documentation

Synopsis

  start-ml-model-transform-job
[--id <value>]
[--data-processing-job-id <value>]
[--ml-model-training-job-id <value>]
[--training-job-name <value>]
--model-transform-output-s3-location <value>
[--sagemaker-iam-role-arn <value>]
[--neptune-iam-role-arn <value>]
[--custom-model-transform-parameters <value>]
[--base-processing-instance-type <value>]
[--base-processing-instance-volume-size-in-gb <value>]
[--subnets <value>]
[--security-group-ids <value>]
[--volume-encryption-kms-key <value>]
[--s3-output-encryption-kms-key <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--id (string)

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

--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 .

--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 .

--training-job-name (string)

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

--model-transform-output-s3-location (string)

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

--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.

--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.

--custom-model-transform-parameters (structure)

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:

sourceS3DirectoryPath -> (string)

The path to the Amazon S3 location where the Python module implementing your model is located. This must point to a valid existing Amazon S3 location that contains, at a minimum, a training script, a transform script, and a model-hpo-configuration.json file.

transformEntryPointScript -> (string)

The name of the entry point in your module of a script that should be run after the best model from the hyperparameter search has been identified, to compute the model artifacts necessary for model deployment. It should be able to run with no command-line arguments. The default is transform.py .

Shorthand Syntax:

sourceS3DirectoryPath=string,transformEntryPointScript=string

JSON Syntax:

{
  "sourceS3DirectoryPath": "string",
  "transformEntryPointScript": "string"
}

--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.

--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.

--subnets (list)

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

(string)

Syntax:

"string" "string" ...

--security-group-ids (list)

The VPC security group IDs. The default is None.

(string)

Syntax:

"string" "string" ...

--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.

--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.

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

• json
• text
• table
• yaml
• yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

• on
• off
• auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

• base64
• raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Output

id -> (string)

The unique ID of the new model transform job.

arn -> (string)

The ARN of the model transform job.

creationTimeInMillis -> (long)

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