/AWS1/CL_SGMLABELINGJOBALGSCFG¶
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.
CONSTRUCTOR¶
IMPORTING¶
Required arguments:¶
iv_labelingjobalgspecarn TYPE /AWS1/SGMLABELINGJOBALGSPECARN /AWS1/SGMLABELINGJOBALGSPECARN¶
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classificationText classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classificationObject detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detectionSemantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Optional arguments:¶
iv_initialactlearningmdelarn TYPE /AWS1/SGMMODELARN /AWS1/SGMMODELARN¶
At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
io_labelingjobresourceconfig TYPE REF TO /AWS1/CL_SGMLABELINGJOBRESRC00 /AWS1/CL_SGMLABELINGJOBRESRC00¶
Provides configuration information for a labeling job.
Queryable Attributes¶
LabelingJobAlgorithmSpecificationArn¶
Specifies the Amazon Resource Name (ARN) of the algorithm used for auto-labeling. You must select one of the following ARNs:
Image classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classificationText classification
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classificationObject detection
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detectionSemantic Segmentation
arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_LABELINGJOBALGSPECARN() |
Getter for LABELINGJOBALGORITHMSPECARN, with configurable de |
ASK_LABELINGJOBALGSPECARN() |
Getter for LABELINGJOBALGORITHMSPECARN w/ exceptions if fiel |
HAS_LABELINGJOBALGSPECARN() |
Determine if LABELINGJOBALGORITHMSPECARN has a value |
InitialActiveLearningModelArn¶
At the end of an auto-label job Ground Truth sends the Amazon Resource Name (ARN) of the final model used for auto-labeling. You can use this model as the starting point for subsequent similar jobs by providing the ARN of the model here.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_INITIALACTLEARNINGMDEL00() |
Getter for INITIALACTLEARNINGMODELARN, with configurable def |
ASK_INITIALACTLEARNINGMDEL00() |
Getter for INITIALACTLEARNINGMODELARN w/ exceptions if field |
HAS_INITIALACTLEARNINGMDEL00() |
Determine if INITIALACTLEARNINGMODELARN has a value |
LabelingJobResourceConfig¶
Provides configuration information for a labeling job.
Accessible with the following methods¶
| Method | Description |
|---|---|
GET_LABELINGJOBRESOURCECFG() |
Getter for LABELINGJOBRESOURCECONFIG |