Describe Ai Recommendation Job

sagemaker_describe_ai_recommendation_job

R Documentation

Returns details of an AI recommendation job, including its status, model source, performance targets, optimization recommendations, and deployment configurations

Description

Returns details of an AI recommendation job, including its status, model source, performance targets, optimization recommendations, and deployment configurations.

Usage

sagemaker_describe_ai_recommendation_job(AIRecommendationJobName)

Arguments

AIRecommendationJobName

[required] The name of the AI recommendation job to describe.

Value

A list with the following syntax:

list(
  AIRecommendationJobName = "string",
  AIRecommendationJobArn = "string",
  AIRecommendationJobStatus = "InProgress"|"Completed"|"Failed"|"Stopping"|"Stopped",
  FailureReason = "string",
  ModelSource = list(
    S3 = list(
      S3Uri = "string"
    )
  ),
  OutputConfig = list(
    S3OutputLocation = "string",
    ModelPackageGroupIdentifier = "string"
  ),
  InferenceSpecification = list(
    Framework = "LMI"|"VLLM"
  ),
  AIWorkloadConfigIdentifier = "string",
  OptimizeModel = TRUE|FALSE,
  PerformanceTarget = list(
    Constraints = list(
      list(
        Metric = "ttft-ms"|"throughput"|"cost"
      )
    )
  ),
  Recommendations = list(
    list(
      RecommendationDescription = "string",
      OptimizationDetails = list(
        list(
          OptimizationType = "SpeculativeDecoding"|"KernelTuning",
          OptimizationConfig = list(
            "string"
          )
        )
      ),
      ModelDetails = list(
        ModelPackageArn = "string",
        InferenceSpecificationName = "string",
        InstanceDetails = list(
          list(
            InstanceType = "ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.12xlarge"|"ml.g5.16xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p4d.24xlarge"|"ml.p4de.24xlarge"|"ml.p5.4xlarge"|"ml.p5.48xlarge"|"ml.p5e.48xlarge"|"ml.p5en.48xlarge"|"ml.p6-b200.48xlarge",
            InstanceCount = 123,
            CopyCountPerInstance = 123
          )
        )
      ),
      DeploymentConfiguration = list(
        S3 = list(
          list(
            ChannelName = "string",
            Uri = "string"
          )
        ),
        ImageUri = "string",
        InstanceType = "ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.12xlarge"|"ml.g5.16xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p4d.24xlarge"|"ml.p4de.24xlarge"|"ml.p5.4xlarge"|"ml.p5.48xlarge"|"ml.p5e.48xlarge"|"ml.p5en.48xlarge"|"ml.p6-b200.48xlarge",
        InstanceCount = 123,
        CopyCountPerInstance = 123,
        EnvironmentVariables = list(
          "string"
        )
      ),
      AIBenchmarkJobArn = "string",
      ExpectedPerformance = list(
        list(
          Metric = "string",
          Stat = "string",
          Value = "string",
          Unit = "string"
        )
      )
    )
  ),
  RoleArn = "string",
  ComputeSpec = list(
    InstanceTypes = list(
      "ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.12xlarge"|"ml.g5.16xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p4d.24xlarge"|"ml.p4de.24xlarge"|"ml.p5.4xlarge"|"ml.p5.48xlarge"|"ml.p5e.48xlarge"|"ml.p5en.48xlarge"|"ml.p6-b200.48xlarge"
    ),
    CapacityReservationConfig = list(
      CapacityReservationPreference = "capacity-reservations-only",
      MlReservationArns = list(
        "string"
      )
    )
  ),
  CreationTime = as.POSIXct(
    "2015-01-01"
  ),
  StartTime = as.POSIXct(
    "2015-01-01"
  ),
  EndTime = as.POSIXct(
    "2015-01-01"
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)

Request syntax

svc$describe_ai_recommendation_job(
  AIRecommendationJobName = "string"
)