Describe Auto Ml Job V2
| sagemaker_describe_auto_ml_job_v2 | R Documentation |
Returns information about an AutoML job created by calling CreateAutoMLJobV2 or CreateAutoMLJob¶
Description¶
Returns information about an AutoML job created by calling
create_auto_ml_job_v2 or create_auto_ml_job.
Usage¶
Arguments¶
AutoMLJobName[required] Requests information about an AutoML job V2 using its unique name.
Value¶
A list with the following syntax:
list(
AutoMLJobName = "string",
AutoMLJobArn = "string",
AutoMLJobInputDataConfig = list(
list(
ChannelType = "training"|"validation",
ContentType = "string",
CompressionType = "None"|"Gzip",
DataSource = list(
S3DataSource = list(
S3DataType = "ManifestFile"|"S3Prefix"|"AugmentedManifestFile",
S3Uri = "string"
)
)
)
),
OutputDataConfig = list(
KmsKeyId = "string",
S3OutputPath = "string"
),
RoleArn = "string",
AutoMLJobObjective = list(
MetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss"
),
AutoMLProblemTypeConfig = list(
ImageClassificationJobConfig = list(
CompletionCriteria = list(
MaxCandidates = 123,
MaxRuntimePerTrainingJobInSeconds = 123,
MaxAutoMLJobRuntimeInSeconds = 123
)
),
TextClassificationJobConfig = list(
CompletionCriteria = list(
MaxCandidates = 123,
MaxRuntimePerTrainingJobInSeconds = 123,
MaxAutoMLJobRuntimeInSeconds = 123
),
ContentColumn = "string",
TargetLabelColumn = "string"
),
TimeSeriesForecastingJobConfig = list(
FeatureSpecificationS3Uri = "string",
CompletionCriteria = list(
MaxCandidates = 123,
MaxRuntimePerTrainingJobInSeconds = 123,
MaxAutoMLJobRuntimeInSeconds = 123
),
ForecastFrequency = "string",
ForecastHorizon = 123,
ForecastQuantiles = list(
"string"
),
Transformations = list(
Filling = list(
list(
"string"
)
),
Aggregation = list(
"sum"|"avg"|"first"|"min"|"max"
)
),
TimeSeriesConfig = list(
TargetAttributeName = "string",
TimestampAttributeName = "string",
ItemIdentifierAttributeName = "string",
GroupingAttributeNames = list(
"string"
)
),
HolidayConfig = list(
list(
CountryCode = "string"
)
),
CandidateGenerationConfig = list(
AlgorithmsConfig = list(
list(
AutoMLAlgorithms = list(
"xgboost"|"linear-learner"|"mlp"|"lightgbm"|"catboost"|"randomforest"|"extra-trees"|"nn-torch"|"fastai"|"cnn-qr"|"deepar"|"prophet"|"npts"|"arima"|"ets"
)
)
)
)
),
TabularJobConfig = list(
CandidateGenerationConfig = list(
AlgorithmsConfig = list(
list(
AutoMLAlgorithms = list(
"xgboost"|"linear-learner"|"mlp"|"lightgbm"|"catboost"|"randomforest"|"extra-trees"|"nn-torch"|"fastai"|"cnn-qr"|"deepar"|"prophet"|"npts"|"arima"|"ets"
)
)
)
),
CompletionCriteria = list(
MaxCandidates = 123,
MaxRuntimePerTrainingJobInSeconds = 123,
MaxAutoMLJobRuntimeInSeconds = 123
),
FeatureSpecificationS3Uri = "string",
Mode = "AUTO"|"ENSEMBLING"|"HYPERPARAMETER_TUNING",
GenerateCandidateDefinitionsOnly = TRUE|FALSE,
ProblemType = "BinaryClassification"|"MulticlassClassification"|"Regression",
TargetAttributeName = "string",
SampleWeightAttributeName = "string"
),
TextGenerationJobConfig = list(
CompletionCriteria = list(
MaxCandidates = 123,
MaxRuntimePerTrainingJobInSeconds = 123,
MaxAutoMLJobRuntimeInSeconds = 123
),
BaseModelName = "string",
TextGenerationHyperParameters = list(
"string"
),
ModelAccessConfig = list(
AcceptEula = TRUE|FALSE
)
)
),
AutoMLProblemTypeConfigName = "ImageClassification"|"TextClassification"|"TimeSeriesForecasting"|"Tabular"|"TextGeneration",
CreationTime = as.POSIXct(
"2015-01-01"
),
EndTime = as.POSIXct(
"2015-01-01"
),
LastModifiedTime = as.POSIXct(
"2015-01-01"
),
FailureReason = "string",
PartialFailureReasons = list(
list(
PartialFailureMessage = "string"
)
),
BestCandidate = list(
CandidateName = "string",
FinalAutoMLJobObjectiveMetric = list(
Type = "Maximize"|"Minimize",
MetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss",
Value = 123.0,
StandardMetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss"
),
ObjectiveStatus = "Succeeded"|"Pending"|"Failed",
CandidateSteps = list(
list(
CandidateStepType = "AWS::SageMaker::TrainingJob"|"AWS::SageMaker::TransformJob"|"AWS::SageMaker::ProcessingJob",
CandidateStepArn = "string",
CandidateStepName = "string"
)
),
CandidateStatus = "Completed"|"InProgress"|"Failed"|"Stopped"|"Stopping",
InferenceContainers = list(
list(
Image = "string",
ModelDataUrl = "string",
Environment = list(
"string"
)
)
),
CreationTime = as.POSIXct(
"2015-01-01"
),
EndTime = as.POSIXct(
"2015-01-01"
),
LastModifiedTime = as.POSIXct(
"2015-01-01"
),
FailureReason = "string",
CandidateProperties = list(
CandidateArtifactLocations = list(
Explainability = "string",
ModelInsights = "string",
BacktestResults = "string"
),
CandidateMetrics = list(
list(
MetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss",
Value = 123.0,
Set = "Train"|"Validation"|"Test",
StandardMetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"MAE"|"R2"|"BalancedAccuracy"|"Precision"|"PrecisionMacro"|"Recall"|"RecallMacro"|"LogLoss"|"InferenceLatency"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss"|"Rouge1"|"Rouge2"|"RougeL"|"RougeLSum"|"Perplexity"|"ValidationLoss"|"TrainingLoss"
)
)
),
InferenceContainerDefinitions = list(
list(
list(
Image = "string",
ModelDataUrl = "string",
Environment = list(
"string"
)
)
)
)
),
AutoMLJobStatus = "Completed"|"InProgress"|"Failed"|"Stopped"|"Stopping",
AutoMLJobSecondaryStatus = "Starting"|"MaxCandidatesReached"|"Failed"|"Stopped"|"MaxAutoMLJobRuntimeReached"|"Stopping"|"CandidateDefinitionsGenerated"|"Completed"|"ExplainabilityError"|"DeployingModel"|"ModelDeploymentError"|"GeneratingModelInsightsReport"|"ModelInsightsError"|"AnalyzingData"|"FeatureEngineering"|"ModelTuning"|"GeneratingExplainabilityReport"|"TrainingModels"|"PreTraining",
AutoMLJobArtifacts = list(
CandidateDefinitionNotebookLocation = "string",
DataExplorationNotebookLocation = "string"
),
ResolvedAttributes = list(
AutoMLJobObjective = list(
MetricName = "Accuracy"|"MSE"|"F1"|"F1macro"|"AUC"|"RMSE"|"BalancedAccuracy"|"R2"|"Recall"|"RecallMacro"|"Precision"|"PrecisionMacro"|"MAE"|"MAPE"|"MASE"|"WAPE"|"AverageWeightedQuantileLoss"
),
CompletionCriteria = list(
MaxCandidates = 123,
MaxRuntimePerTrainingJobInSeconds = 123,
MaxAutoMLJobRuntimeInSeconds = 123
),
AutoMLProblemTypeResolvedAttributes = list(
TabularResolvedAttributes = list(
ProblemType = "BinaryClassification"|"MulticlassClassification"|"Regression"
),
TextGenerationResolvedAttributes = list(
BaseModelName = "string"
)
)
),
ModelDeployConfig = list(
AutoGenerateEndpointName = TRUE|FALSE,
EndpointName = "string"
),
ModelDeployResult = list(
EndpointName = "string"
),
DataSplitConfig = list(
ValidationFraction = 123.0
),
SecurityConfig = list(
VolumeKmsKeyId = "string",
EnableInterContainerTrafficEncryption = TRUE|FALSE,
VpcConfig = list(
SecurityGroupIds = list(
"string"
),
Subnets = list(
"string"
)
)
),
AutoMLComputeConfig = list(
EmrServerlessComputeConfig = list(
ExecutionRoleARN = "string"
)
)
)