AWS Tools for Windows PowerShell
Command Reference

AWS services or capabilities described in AWS Documentation may vary by region/location. Click Getting Started with Amazon AWS to see specific differences applicable to the China (Beijing) Region.

Synopsis

Calls the Amazon NeptuneData StartMLModelTrainingJob API operation.

Syntax

Start-NEPTMLModelTrainingJob
-Id <String>
-BaseProcessingInstanceType <String>
-DataProcessingJobId <String>
-EnableManagedSpotTraining <Boolean>
-MaxHPONumberOfTrainingJob <Int32>
-MaxHPOParallelTrainingJob <Int32>
-NeptuneIamRoleArn <String>
-PreviousModelTrainingJobId <String>
-S3OutputEncryptionKMSKey <String>
-SagemakerIamRoleArn <String>
-SecurityGroupId <String[]>
-CustomModelTrainingParameters_SourceS3DirectoryPath <String>
-Subnet <String[]>
-CustomModelTrainingParameters_TrainingEntryPointScript <String>
-TrainingInstanceType <String>
-TrainingInstanceVolumeSizeInGB <Int32>
-TrainingTimeOutInSecond <Int32>
-TrainModelS3Location <String>
-CustomModelTrainingParameters_TransformEntryPointScript <String>
-VolumeEncryptionKMSKey <String>
-Select <String>
-Force <SwitchParameter>
-ClientConfig <AmazonNeptunedataConfig>

Description

Creates a new Neptune ML model training job. See Model training using the modeltraining command. 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:StartMLModelTrainingJob IAM action in that cluster.

Parameters

-BaseProcessingInstanceType <String>
The type of ML instance used in preparing and managing training of ML models. This is a CPU instance chosen based on memory requirements for processing the training data and model.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-ClientConfig <AmazonNeptunedataConfig>
Amazon.PowerShell.Cmdlets.NEPT.AmazonNeptunedataClientCmdlet.ClientConfig
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-CustomModelTrainingParameters_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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-CustomModelTrainingParameters_TrainingEntryPointScript <String>
The name of the entry point in your module of a script that performs model training and takes hyperparameters as command-line arguments, including fixed hyperparameters. The default is training.py.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-CustomModelTrainingParameters_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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-DataProcessingJobId <String>
The job ID of the completed data-processing job that has created the data that the training will work with.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-EnableManagedSpotTraining <Boolean>
Optimizes the cost of training machine-learning models by using Amazon Elastic Compute Cloud spot instances. The default is False.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Force <SwitchParameter>
This parameter overrides confirmation prompts to force the cmdlet to continue its operation. This parameter should always be used with caution.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Id <String>
A unique identifier for the new job. The default is An autogenerated UUID.
Required?False
Position?1
Accept pipeline input?True (ByValue, ByPropertyName)
-MaxHPONumberOfTrainingJob <Int32>
Maximum total number of training jobs to start for the hyperparameter tuning job. The default is 2. Neptune ML automatically tunes the hyperparameters of the machine learning model. To obtain a model that performs well, use at least 10 jobs (in other words, set maxHPONumberOfTrainingJobs to 10). In general, the more tuning runs, the better the results.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesMaxHPONumberOfTrainingJobs
-MaxHPOParallelTrainingJob <Int32>
Maximum number of parallel training jobs to start for the hyperparameter tuning job. The default is 2. The number of parallel jobs you can run is limited by the available resources on your training instance.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesMaxHPOParallelTrainingJobs
-NeptuneIamRoleArn <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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-PreviousModelTrainingJobId <String>
The job ID of a completed model-training job that you want to update incrementally based on updated data.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-S3OutputEncryptionKMSKey <String>
The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-SagemakerIamRoleArn <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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-SecurityGroupId <String[]>
The VPC security group IDs. The default is None. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSecurityGroupIds
-Select <String>
Use the -Select parameter to control the cmdlet output. The default value is '*'. Specifying -Select '*' will result in the cmdlet returning the whole service response (Amazon.Neptunedata.Model.StartMLModelTrainingJobResponse). Specifying the name of a property of type Amazon.Neptunedata.Model.StartMLModelTrainingJobResponse will result in that property being returned. Specifying -Select '^ParameterName' will result in the cmdlet returning the selected cmdlet parameter value.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Subnet <String[]>
The IDs of the subnets in the Neptune VPC. The default is None. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSubnets
-TrainingInstanceType <String>
The type of ML instance used for model training. All Neptune ML models support CPU, GPU, and multiGPU training. The default is ml.p3.2xlarge. Choosing the right instance type for training depends on the task type, graph size, and your budget.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-TrainingInstanceVolumeSizeInGB <Int32>
The disk volume size of the training instance. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. The default is 0. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-TrainingTimeOutInSecond <Int32>
Timeout in seconds for the training job. The default is 86,400 (1 day).
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesTrainingTimeOutInSeconds
-TrainModelS3Location <String>
The location in Amazon S3 where the model artifacts are to be stored.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-VolumeEncryptionKMSKey <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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)

Common Credential and Region Parameters

-AccessKey <String>
The AWS access key for the user account. This can be a temporary access key if the corresponding session token is supplied to the -SessionToken parameter.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAK
-Credential <AWSCredentials>
An AWSCredentials object instance containing access and secret key information, and optionally a token for session-based credentials.
Required?False
Position?Named
Accept pipeline input?True (ByValue, ByPropertyName)
-EndpointUrl <String>
The endpoint to make the call against.Note: This parameter is primarily for internal AWS use and is not required/should not be specified for normal usage. The cmdlets normally determine which endpoint to call based on the region specified to the -Region parameter or set as default in the shell (via Set-DefaultAWSRegion). Only specify this parameter if you must direct the call to a specific custom endpoint.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-NetworkCredential <PSCredential>
Used with SAML-based authentication when ProfileName references a SAML role profile. Contains the network credentials to be supplied during authentication with the configured identity provider's endpoint. This parameter is not required if the user's default network identity can or should be used during authentication.
Required?False
Position?Named
Accept pipeline input?True (ByValue, ByPropertyName)
-ProfileLocation <String>
Used to specify the name and location of the ini-format credential file (shared with the AWS CLI and other AWS SDKs)If this optional parameter is omitted this cmdlet will search the encrypted credential file used by the AWS SDK for .NET and AWS Toolkit for Visual Studio first. If the profile is not found then the cmdlet will search in the ini-format credential file at the default location: (user's home directory)\.aws\credentials.If this parameter is specified then this cmdlet will only search the ini-format credential file at the location given.As the current folder can vary in a shell or during script execution it is advised that you use specify a fully qualified path instead of a relative path.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAWSProfilesLocation, ProfilesLocation
-ProfileName <String>
The user-defined name of an AWS credentials or SAML-based role profile containing credential information. The profile is expected to be found in the secure credential file shared with the AWS SDK for .NET and AWS Toolkit for Visual Studio. You can also specify the name of a profile stored in the .ini-format credential file used with the AWS CLI and other AWS SDKs.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesStoredCredentials, AWSProfileName
-Region <Object>
The system name of an AWS region or an AWSRegion instance. This governs the endpoint that will be used when calling service operations. Note that the AWS resources referenced in a call are usually region-specific.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesRegionToCall
-SecretKey <String>
The AWS secret key for the user account. This can be a temporary secret key if the corresponding session token is supplied to the -SessionToken parameter.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSK, SecretAccessKey
-SessionToken <String>
The session token if the access and secret keys are temporary session-based credentials.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesST

Outputs

Amazon.Neptunedata.Model.StartMLModelTrainingJobResponse
This cmdlet returns an Amazon.Neptunedata.Model.StartMLModelTrainingJobResponse object containing multiple properties.
AWS Tools for PowerShell User Guide

Supported Version

AWS Tools for PowerShell: 2.x.y.z