AWS Tools for Windows PowerShell
Command Reference

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Synopsis

Calls the Amazon SageMaker Service CreateInferenceComponent API operation.

Syntax

New-SMInferenceComponent
-Container_ArtifactUrl <String>
-Specification_BaseInferenceComponentName <String>
-StartupParameters_ContainerStartupHealthCheckTimeoutInSecond <Int32>
-RuntimeConfig_CopyCount <Int32>
-EndpointName <String>
-Container_Environment <Hashtable>
-Container_Image <String>
-InferenceComponentName <String>
-ComputeResourceRequirements_MaxMemoryRequiredInMb <Int32>
-ComputeResourceRequirements_MinMemoryRequiredInMb <Int32>
-StartupParameters_ModelDataDownloadTimeoutInSecond <Int32>
-Specification_ModelName <String>
-ComputeResourceRequirements_NumberOfAcceleratorDevicesRequired <Single>
-ComputeResourceRequirements_NumberOfCpuCoresRequired <Single>
-Tag <Tag[]>
-VariantName <String>
-Select <String>
-Force <SwitchParameter>
-ClientConfig <AmazonSageMakerConfig>

Description

Creates an inference component, which is a SageMaker AI hosting object that you can use to deploy a model to an endpoint. In the inference component settings, you specify the model, the endpoint, and how the model utilizes the resources that the endpoint hosts. You can optimize resource utilization by tailoring how the required CPU cores, accelerators, and memory are allocated. You can deploy multiple inference components to an endpoint, where each inference component contains one model and the resource utilization needs for that individual model. After you deploy an inference component, you can directly invoke the associated model when you use the InvokeEndpoint API action.

Parameters

-ClientConfig <AmazonSageMakerConfig>
Amazon.PowerShell.Cmdlets.SM.AmazonSageMakerClientCmdlet.ClientConfig
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-ComputeResourceRequirements_MaxMemoryRequiredInMb <Int32>
The maximum MB of memory to allocate to run a model that you assign to an inference component.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_ComputeResourceRequirements_MaxMemoryRequiredInMb
-ComputeResourceRequirements_MinMemoryRequiredInMb <Int32>
The minimum MB of memory to allocate to run a model that you assign to an inference component.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_ComputeResourceRequirements_MinMemoryRequiredInMb
-ComputeResourceRequirements_NumberOfAcceleratorDevicesRequired <Single>
The number of accelerators to allocate to run a model that you assign to an inference component. Accelerators include GPUs and Amazon Web Services Inferentia.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_ComputeResourceRequirements_NumberOfAcceleratorDevicesRequired
-ComputeResourceRequirements_NumberOfCpuCoresRequired <Single>
The number of CPU cores to allocate to run a model that you assign to an inference component.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_ComputeResourceRequirements_NumberOfCpuCoresRequired
-Container_ArtifactUrl <String>
The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_Container_ArtifactUrl
-Container_Environment <Hashtable>
The environment variables to set in the Docker container. Each key and value in the Environment string-to-string map can have length of up to 1024. We support up to 16 entries in the map. 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)
AliasesSpecification_Container_Environment
-Container_Image <String>
The Amazon Elastic Container Registry (Amazon ECR) path where the Docker image for the model is stored.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_Container_Image
-EndpointName <String>
The name of an existing endpoint where you host the inference component.
Required?True
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)
-InferenceComponentName <String>
A unique name to assign to the inference component.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
-RuntimeConfig_CopyCount <Int32>
The number of runtime copies of the model container to deploy with the inference component. Each copy can serve inference requests.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Select <String>
Use the -Select parameter to control the cmdlet output. The default value is 'InferenceComponentArn'. Specifying -Select '*' will result in the cmdlet returning the whole service response (Amazon.SageMaker.Model.CreateInferenceComponentResponse). Specifying the name of a property of type Amazon.SageMaker.Model.CreateInferenceComponentResponse 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)
-Specification_BaseInferenceComponentName <String>
The name of an existing inference component that is to contain the inference component that you're creating with your request.Specify this parameter only if your request is meant to create an adapter inference component. An adapter inference component contains the path to an adapter model. The purpose of the adapter model is to tailor the inference output of a base foundation model, which is hosted by the base inference component. The adapter inference component uses the compute resources that you assigned to the base inference component.When you create an adapter inference component, use the Container parameter to specify the location of the adapter artifacts. In the parameter value, use the ArtifactUrl parameter of the InferenceComponentContainerSpecification data type.Before you can create an adapter inference component, you must have an existing inference component that contains the foundation model that you want to adapt.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Specification_ModelName <String>
The name of an existing SageMaker AI model object in your account that you want to deploy with the inference component.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-StartupParameters_ContainerStartupHealthCheckTimeoutInSecond <Int32>
The timeout value, in seconds, for your inference container to pass health check by Amazon S3 Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_StartupParameters_ContainerStartupHealthCheckTimeoutInSeconds
-StartupParameters_ModelDataDownloadTimeoutInSecond <Int32>
The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this inference component.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSpecification_StartupParameters_ModelDataDownloadTimeoutInSeconds
-Tag <Tag[]>
A list of key-value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference. 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)
AliasesTags
-VariantName <String>
The name of an existing production variant where you host the inference component.
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

System.String or Amazon.SageMaker.Model.CreateInferenceComponentResponse
This cmdlet returns a System.String object. The service call response (type Amazon.SageMaker.Model.CreateInferenceComponentResponse) can be returned by specifying '-Select *'.
Developer Guide
Service API Reference
AWS Tools for PowerShell User Guide

Supported Version

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