sagemaker_describe_training_job(TrainingJobName)

list(
  TrainingJobName = "string",
  TrainingJobArn = "string",
  TuningJobArn = "string",
  LabelingJobArn = "string",
  AutoMLJobArn = "string",
  ModelArtifacts = list(
    S3ModelArtifacts = "string"
  ),
  TrainingJobStatus = "InProgress"|"Completed"|"Failed"|"Stopping"|"Stopped",
  SecondaryStatus = "Starting"|"LaunchingMLInstances"|"PreparingTrainingStack"|"Downloading"|"DownloadingTrainingImage"|"Training"|"Uploading"|"Stopping"|"Stopped"|"MaxRuntimeExceeded"|"Completed"|"Failed"|"Interrupted"|"MaxWaitTimeExceeded"|"Updating",
  FailureReason = "string",
  HyperParameters = list(
    "string"
  ),
  AlgorithmSpecification = list(
    TrainingImage = "string",
    AlgorithmName = "string",
    TrainingInputMode = "Pipe"|"File",
    MetricDefinitions = list(
      list(
        Name = "string",
        Regex = "string"
      )
    ),
    EnableSageMakerMetricsTimeSeries = TRUE|FALSE
  ),
  RoleArn = "string",
  InputDataConfig = list(
    list(
      ChannelName = "string",
      DataSource = list(
        S3DataSource = list(
          S3DataType = "ManifestFile"|"S3Prefix"|"AugmentedManifestFile",
          S3Uri = "string",
          S3DataDistributionType = "FullyReplicated"|"ShardedByS3Key",
          AttributeNames = list(
            "string"
          )
        ),
        FileSystemDataSource = list(
          FileSystemId = "string",
          FileSystemAccessMode = "rw"|"ro",
          FileSystemType = "EFS"|"FSxLustre",
          DirectoryPath = "string"
        )
      ),
      ContentType = "string",
      CompressionType = "None"|"Gzip",
      RecordWrapperType = "None"|"RecordIO",
      InputMode = "Pipe"|"File",
      ShuffleConfig = list(
        Seed = 123
      )
    )
  ),
  OutputDataConfig = list(
    KmsKeyId = "string",
    S3OutputPath = "string"
  ),
  ResourceConfig = list(
    InstanceType = "ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p3dn.24xlarge"|"ml.p4d.24xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.c5n.xlarge"|"ml.c5n.2xlarge"|"ml.c5n.4xlarge"|"ml.c5n.9xlarge"|"ml.c5n.18xlarge",
    InstanceCount = 123,
    VolumeSizeInGB = 123,
    VolumeKmsKeyId = "string"
  ),
  VpcConfig = list(
    SecurityGroupIds = list(
      "string"
    ),
    Subnets = list(
      "string"
    )
  ),
  StoppingCondition = list(
    MaxRuntimeInSeconds = 123,
    MaxWaitTimeInSeconds = 123
  ),
  CreationTime = as.POSIXct(
    "2015-01-01"
  ),
  TrainingStartTime = as.POSIXct(
    "2015-01-01"
  ),
  TrainingEndTime = as.POSIXct(
    "2015-01-01"
  ),
  LastModifiedTime = as.POSIXct(
    "2015-01-01"
  ),
  SecondaryStatusTransitions = list(
    list(
      Status = "Starting"|"LaunchingMLInstances"|"PreparingTrainingStack"|"Downloading"|"DownloadingTrainingImage"|"Training"|"Uploading"|"Stopping"|"Stopped"|"MaxRuntimeExceeded"|"Completed"|"Failed"|"Interrupted"|"MaxWaitTimeExceeded"|"Updating",
      StartTime = as.POSIXct(
        "2015-01-01"
      ),
      EndTime = as.POSIXct(
        "2015-01-01"
      ),
      StatusMessage = "string"
    )
  ),
  FinalMetricDataList = list(
    list(
      MetricName = "string",
      Value = 123.0,
      Timestamp = as.POSIXct(
        "2015-01-01"
      )
    )
  ),
  EnableNetworkIsolation = TRUE|FALSE,
  EnableInterContainerTrafficEncryption = TRUE|FALSE,
  EnableManagedSpotTraining = TRUE|FALSE,
  CheckpointConfig = list(
    S3Uri = "string",
    LocalPath = "string"
  ),
  TrainingTimeInSeconds = 123,
  BillableTimeInSeconds = 123,
  DebugHookConfig = list(
    LocalPath = "string",
    S3OutputPath = "string",
    HookParameters = list(
      "string"
    ),
    CollectionConfigurations = list(
      list(
        CollectionName = "string",
        CollectionParameters = list(
          "string"
        )
      )
    )
  ),
  ExperimentConfig = list(
    ExperimentName = "string",
    TrialName = "string",
    TrialComponentDisplayName = "string"
  ),
  DebugRuleConfigurations = list(
    list(
      RuleConfigurationName = "string",
      LocalPath = "string",
      S3OutputPath = "string",
      RuleEvaluatorImage = "string",
      InstanceType = "ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge",
      VolumeSizeInGB = 123,
      RuleParameters = list(
        "string"
      )
    )
  ),
  TensorBoardOutputConfig = list(
    LocalPath = "string",
    S3OutputPath = "string"
  ),
  DebugRuleEvaluationStatuses = list(
    list(
      RuleConfigurationName = "string",
      RuleEvaluationJobArn = "string",
      RuleEvaluationStatus = "InProgress"|"NoIssuesFound"|"IssuesFound"|"Error"|"Stopping"|"Stopped",
      StatusDetails = "string",
      LastModifiedTime = as.POSIXct(
        "2015-01-01"
      )
    )
  ),
  ProfilerConfig = list(
    S3OutputPath = "string",
    ProfilingIntervalInMilliseconds = 123,
    ProfilingParameters = list(
      "string"
    )
  ),
  ProfilerRuleConfigurations = list(
    list(
      RuleConfigurationName = "string",
      LocalPath = "string",
      S3OutputPath = "string",
      RuleEvaluatorImage = "string",
      InstanceType = "ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge",
      VolumeSizeInGB = 123,
      RuleParameters = list(
        "string"
      )
    )
  ),
  ProfilerRuleEvaluationStatuses = list(
    list(
      RuleConfigurationName = "string",
      RuleEvaluationJobArn = "string",
      RuleEvaluationStatus = "InProgress"|"NoIssuesFound"|"IssuesFound"|"Error"|"Stopping"|"Stopped",
      StatusDetails = "string",
      LastModifiedTime = as.POSIXct(
        "2015-01-01"
      )
    )
  ),
  ProfilingStatus = "Enabled"|"Disabled"
)

svc$describe_training_job(
  TrainingJobName = "string"
)