AWS Tools for Windows PowerShell
Command Reference

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Synopsis

Calls the Amazon SageMaker Service CreateAlgorithm API operation.

Syntax

New-SMAlgorithm
-AlgorithmName <String>
-AlgorithmDescription <String>
-CertifyForMarketplace <Boolean>
-InferenceSpecification_Container <ModelPackageContainerDefinition[]>
-TrainingSpecification_MetricDefinition <MetricDefinition[]>
-InferenceSpecification_SupportedContentType <String[]>
-TrainingSpecification_SupportedHyperParameter <HyperParameterSpecification[]>
-InferenceSpecification_SupportedRealtimeInferenceInstanceType <String[]>
-InferenceSpecification_SupportedResponseMIMEType <String[]>
-TrainingSpecification_SupportedTrainingInstanceType <String[]>
-InferenceSpecification_SupportedTransformInstanceType <String[]>
-TrainingSpecification_SupportedTuningJobObjectiveMetric <HyperParameterTuningJobObjective[]>
-TrainingSpecification_SupportsDistributedTraining <Boolean>
-TrainingSpecification_TrainingChannel <ChannelSpecification[]>
-TrainingSpecification_TrainingImage <String>
-TrainingSpecification_TrainingImageDigest <String>
-ValidationSpecification_ValidationProfile <AlgorithmValidationProfile[]>
-ValidationSpecification_ValidationRole <String>
-Force <SwitchParameter>

Description

Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.

Parameters

-AlgorithmDescription <String>
A description of the algorithm.
Required?False
Position?Named
Accept pipeline input?False
-AlgorithmName <String>
The name of the algorithm.
Required?False
Position?1
Accept pipeline input?True (ByValue, )
-CertifyForMarketplace <Boolean>
Whether to certify the algorithm so that it can be listed in AWS Marketplace.
Required?False
Position?Named
Accept pipeline input?False
-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?False
-InferenceSpecification_Container <ModelPackageContainerDefinition[]>
The Amazon ECR registry path of the Docker image that contains the inference code.
Required?False
Position?Named
Accept pipeline input?False
AliasesInferenceSpecification_Containers
-InferenceSpecification_SupportedContentType <String[]>
The supported MIME types for the input data.
Required?False
Position?Named
Accept pipeline input?False
AliasesInferenceSpecification_SupportedContentTypes
-InferenceSpecification_SupportedRealtimeInferenceInstanceType <String[]>
A list of the instance types that are used to generate inferences in real-time.
Required?False
Position?Named
Accept pipeline input?False
AliasesInferenceSpecification_SupportedRealtimeInferenceInstanceTypes
-InferenceSpecification_SupportedResponseMIMEType <String[]>
The supported MIME types for the output data.
Required?False
Position?Named
Accept pipeline input?False
AliasesInferenceSpecification_SupportedResponseMIMETypes
-InferenceSpecification_SupportedTransformInstanceType <String[]>
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
Required?False
Position?Named
Accept pipeline input?False
AliasesInferenceSpecification_SupportedTransformInstanceTypes
-TrainingSpecification_MetricDefinition <MetricDefinition[]>
A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.
Required?False
Position?Named
Accept pipeline input?False
AliasesTrainingSpecification_MetricDefinitions
-TrainingSpecification_SupportedHyperParameter <HyperParameterSpecification[]>
A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
Required?False
Position?Named
Accept pipeline input?False
AliasesTrainingSpecification_SupportedHyperParameters
-TrainingSpecification_SupportedTrainingInstanceType <String[]>
A list of the instance types that this algorithm can use for training.
Required?False
Position?Named
Accept pipeline input?False
AliasesTrainingSpecification_SupportedTrainingInstanceTypes
-TrainingSpecification_SupportedTuningJobObjectiveMetric <HyperParameterTuningJobObjective[]>
A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
Required?False
Position?Named
Accept pipeline input?False
AliasesTrainingSpecification_SupportedTuningJobObjectiveMetrics
-TrainingSpecification_SupportsDistributedTraining <Boolean>
Indicates whether the algorithm supports distributed training. If set to false, buyers can’t request more than one instance during training.
Required?False
Position?Named
Accept pipeline input?False
-TrainingSpecification_TrainingChannel <ChannelSpecification[]>
A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.
Required?False
Position?Named
Accept pipeline input?False
AliasesTrainingSpecification_TrainingChannels
-TrainingSpecification_TrainingImage <String>
The Amazon ECR registry path of the Docker image that contains the training algorithm.
Required?False
Position?Named
Accept pipeline input?False
-TrainingSpecification_TrainingImageDigest <String>
An MD5 hash of the training algorithm that identifies the Docker image used for training.
Required?False
Position?Named
Accept pipeline input?False
-ValidationSpecification_ValidationProfile <AlgorithmValidationProfile[]>
An array of AlgorithmValidationProfile objects, each of which specifies a training job and batch transform job that Amazon SageMaker runs to validate your algorithm.
Required?False
Position?Named
Accept pipeline input?False
AliasesValidationSpecification_ValidationProfiles
-ValidationSpecification_ValidationRole <String>
The IAM roles that Amazon SageMaker uses to run the training jobs.
Required?False
Position?Named
Accept pipeline input?False

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? False
-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? False
-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. Note that the encrypted credential file is not supported on all platforms. It will be skipped when searching for profiles on Windows Nano Server, Mac, and Linux platforms.

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? False
-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? False
-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? False
-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? False
-SessionToken <String>
The session token if the access and secret keys are temporary session-based credentials.
Required? False
Position? Named
Accept pipeline input? False
-Region <String>
The system name of the AWS region in which the operation should be invoked. For example, us-east-1, eu-west-1 etc.
Required? False
Position? Named
Accept pipeline input? False
-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? False

Inputs

You can pipe a String object to this cmdlet for the AlgorithmName parameter.

Outputs

This cmdlet returns a System.String object. The service call response (type Amazon.SageMaker.Model.CreateAlgorithmResponse) can also be referenced from properties attached to the cmdlet entry in the $AWSHistory stack.

Supported Version

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