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Creates a reusable AI workload configuration that defines datasets, data sources, and benchmark tool settings for consistent performance testing of generative AI inference deployments on Amazon SageMaker AI

Description

Creates a reusable AI workload configuration that defines datasets, data sources, and benchmark tool settings for consistent performance testing of generative AI inference deployments on Amazon SageMaker AI.

Usage

sagemaker_create_ai_workload_config(AIWorkloadConfigName, DatasetConfig,
  AIWorkloadConfigs, Tags)

Arguments

  • AIWorkloadConfigName

    [required] The name of the AI workload configuration. The name must be unique within your Amazon Web Services account in the current Amazon Web Services Region.

  • DatasetConfig

    The dataset configuration for the workload. Specify input data channels with their data sources for benchmark workloads.

  • AIWorkloadConfigs

    The benchmark tool configuration and workload specification. Provide the specification as an inline YAML or JSON string.

  • Tags

    The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.

Value

A list with the following syntax:

list(
  AIWorkloadConfigArn = "string"
)

Request syntax

svc$create_ai_workload_config(
  AIWorkloadConfigName = "string",
  DatasetConfig = list(
    InputDataConfig = list(
      list(
        ChannelName = "string",
        DataSource = list(
          S3DataSource = list(
            S3Uri = "string"
          )
        )
      )
    )
  ),
  AIWorkloadConfigs = list(
    WorkloadSpec = list(
      Inline = "string"
    )
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)