Start-LFVModelPackagingJob Cmdlet

Amazon.PowerShell.Cmdlets.LFV.AmazonLookoutforVisionClientCmdlet.ClientConfig

ClientToken is an idempotency token that ensures a call to StartModelPackagingJob completes only once. You choose the value to pass. For example, An issue might prevent you from getting a response from StartModelPackagingJob. In this case, safely retry your call to StartModelPackagingJob by using the same ClientToken parameter value.If you don't supply a value for ClientToken, the AWS SDK you are using inserts a value for you. This prevents retries after a network error from making multiple dataset creation requests. You'll need to provide your own value for other use cases.An error occurs if the other input parameters are not the same as in the first request. Using a different value for ClientToken is considered a new call to StartModelPackagingJob. An idempotency token is active for 8 hours.

A description for the model packaging job.

This parameter overrides confirmation prompts to force the cmdlet to continue its operation. This parameter should always be used with caution.

Additional compiler options for the Greengrass component. Currently, only NVIDIA Graphics Processing Units (GPU) and CPU accelerators are supported. If you specify TargetDevice, don't specify CompilerOptions.For more information, see Compiler options in the Amazon Lookout for Vision Developer Guide.

A description for the AWS IoT Greengrass component.

A name for the AWS IoT Greengrass component.

A Version for the AWS IoT Greengrass component. If you don't provide a value, a default value of Model Version.0.0 is used.

A set of tags (key-value pairs) that you want to attach to the AWS IoT Greengrass component.

The target device for the model. Currently the only supported value is jetson_xavier. If you specify TargetDevice, you can't specify TargetPlatform.

A name for the model packaging job. If you don't supply a value, the service creates a job name for you.

The version of the model within the project that you want to package.

The name of the project which contains the version of the model that you want to package.

The S3 bucket that contains the training or model packaging job output. If you are training a model, the bucket must in your AWS account. If you use an S3 bucket for a model packaging job, the S3 bucket must be in the same AWS Region and AWS account in which you use AWS IoT Greengrass.

The path of the folder, within the S3 bucket, that contains the output.

Use the -Select parameter to control the cmdlet output. The default value is 'JobName'. Specifying -Select '*' will result in the cmdlet returning the whole service response (Amazon.LookoutforVision.Model.StartModelPackagingJobResponse). Specifying the name of a property of type Amazon.LookoutforVision.Model.StartModelPackagingJobResponse will result in that property being returned. Specifying -Select '^ParameterName' will result in the cmdlet returning the selected cmdlet parameter value.

The target accelerator for the model. Currently, Amazon Lookout for Vision only supports NVIDIA (Nvidia graphics processing unit) and CPU accelerators. If you specify NVIDIA as an accelerator, you must also specify the gpu-code, trt-ver, and cuda-ver compiler options. If you don't specify an accelerator, Lookout for Vision uses the CPU for compilation and we highly recommend that you use the GreengrassConfiguration$CompilerOptions field. For example, you can use the following compiler options for CPU:

• mcpu: CPU micro-architecture. For example, {'mcpu': 'skylake-avx512'}
• mattr: CPU flags. For example, {'mattr': ['+neon', '+vfpv4']}

The target architecture for the model. The currently supported architectures are X86_64 (64-bit version of the x86 instruction set) and ARM_64 (ARMv8 64-bit CPU).

The target operating system for the model. Linux is the only operating system that is currently supported.

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.

An AWSCredentials object instance containing access and secret key information, and optionally a token for session-based credentials.

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.

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.

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.

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.

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.

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.

The session token if the access and secret keys are temporary session-based credentials.