NAME
Paws::SageMaker::CreateLabelingJob - Arguments for method CreateLabelingJob on Paws::SageMaker
DESCRIPTION
This class represents the parameters used for calling the method CreateLabelingJob on the Amazon SageMaker Service service. Use the attributes of this class as arguments to method CreateLabelingJob.
You shouldn't make instances of this class. Each attribute should be used as a named argument in the call to CreateLabelingJob.
SYNOPSIS
my $api.sagemaker = Paws->service('SageMaker');
my $CreateLabelingJobResponse = $api . sagemaker->CreateLabelingJob(
HumanTaskConfig => {
AnnotationConsolidationConfig => {
AnnotationConsolidationLambdaArn => 'MyLambdaFunctionArn', # max: 2048
},
NumberOfHumanWorkersPerDataObject => 1, # min: 1, max: 9
PreHumanTaskLambdaArn => 'MyLambdaFunctionArn', # max: 2048
TaskDescription => 'MyTaskDescription', # min: 1, max: 255
TaskTimeLimitInSeconds => 1, # min: 30
TaskTitle => 'MyTaskTitle', # min: 1, max: 128
UiConfig => {
HumanTaskUiArn => 'MyHumanTaskUiArn', # max: 1024; OPTIONAL
UiTemplateS3Uri => 'MyS3Uri', # max: 1024; OPTIONAL
},
WorkteamArn => 'MyWorkteamArn', # max: 256
MaxConcurrentTaskCount => 1, # min: 1, max: 1000; OPTIONAL
PublicWorkforceTaskPrice => {
AmountInUsd => {
Cents => 1, # max: 99; OPTIONAL
Dollars => 1, # max: 2; OPTIONAL
TenthFractionsOfACent => 1, # max: 9; OPTIONAL
}, # OPTIONAL
}, # OPTIONAL
TaskAvailabilityLifetimeInSeconds => 1, # min: 60; OPTIONAL
TaskKeywords => [
'MyTaskKeyword', ... # min: 1, max: 30
], # min: 1, max: 5; OPTIONAL
},
InputConfig => {
DataSource => {
S3DataSource => {
ManifestS3Uri => 'MyS3Uri', # max: 1024; OPTIONAL
}, # OPTIONAL
SnsDataSource => {
SnsTopicArn => 'MySnsTopicArn', # max: 2048
}, # OPTIONAL
},
DataAttributes => {
ContentClassifiers => [
'FreeOfPersonallyIdentifiableInformation',
... # values: FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent
], # max: 256; OPTIONAL
}, # OPTIONAL
},
LabelAttributeName => 'MyLabelAttributeName',
LabelingJobName => 'MyLabelingJobName',
OutputConfig => {
S3OutputPath => 'MyS3Uri', # max: 1024; OPTIONAL
KmsKeyId => 'MyKmsKeyId', # max: 2048; OPTIONAL
SnsTopicArn => 'MySnsTopicArn', # max: 2048
},
RoleArn => 'MyRoleArn',
LabelCategoryConfigS3Uri => 'MyS3Uri', # OPTIONAL
LabelingJobAlgorithmsConfig => {
LabelingJobAlgorithmSpecificationArn =>
'MyLabelingJobAlgorithmSpecificationArn', # max: 2048
InitialActiveLearningModelArn =>
'MyModelArn', # min: 20, max: 2048; OPTIONAL
LabelingJobResourceConfig => {
VolumeKmsKeyId => 'MyKmsKeyId', # max: 2048; OPTIONAL
}, # OPTIONAL
}, # OPTIONAL
StoppingConditions => {
MaxHumanLabeledObjectCount => 1, # min: 1; OPTIONAL
MaxPercentageOfInputDatasetLabeled => 1, # min: 1, max: 100; OPTIONAL
}, # OPTIONAL
Tags => [
{
Key => 'MyTagKey', # min: 1, max: 128
Value => 'MyTagValue', # max: 256
},
...
], # OPTIONAL
);
# Results:
my $LabelingJobArn = $CreateLabelingJobResponse->LabelingJobArn;
# Returns a L<Paws::SageMaker::CreateLabelingJobResponse> object.Values for attributes that are native types (Int, String, Float, etc) can passed as-is (scalar values). Values for complex Types (objects) can be passed as a HashRef. The keys and values of the hashref will be used to instance the underlying object. For the AWS API documentation, see https://docs.aws.amazon.com/goto/WebAPI/api.sagemaker/CreateLabelingJob
ATTRIBUTES
REQUIRED HumanTaskConfig => Paws::SageMaker::HumanTaskConfig
Configures the labeling task and how it is presented to workers; including, but not limited to price, keywords, and batch size (task count).
REQUIRED InputConfig => Paws::SageMaker::LabelingJobInputConfig
Input data for the labeling job, such as the Amazon S3 location of the data objects and the location of the manifest file that describes the data objects.
You must specify at least one of the following: S3DataSource or SnsDataSource.
Use
SnsDataSourceto specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job that stops after all data objects in the input manifest file have been labeled.Use
S3DataSourceto specify an input manifest file for both streaming and one-time labeling jobs. Adding anS3DataSourceis optional if you useSnsDataSourceto create a streaming labeling job.
If you use the Amazon Mechanical Turk workforce, your input data should not include confidential information, personal information or protected health information. Use ContentClassifiers to specify that your data is free of personally identifiable information and adult content.
REQUIRED LabelAttributeName => Str
The attribute name to use for the label in the output manifest file. This is the key for the key/value pair formed with the label that a worker assigns to the object. The LabelAttributeName must meet the following requirements.
The name can't end with "-metadata".
If you are using one of the following built-in task types (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html), the attribute name must end with "-ref". If the task type you are using is not listed below, the attribute name must not end with "-ref".
Image semantic segmentation (
SemanticSegmentation), and adjustment (AdjustmentSemanticSegmentation) and verification (VerificationSemanticSegmentation) labeling jobs for this task type.Video frame object detection (
VideoObjectDetection), and adjustment and verification (AdjustmentVideoObjectDetection) labeling jobs for this task type.Video frame object tracking (
VideoObjectTracking), and adjustment and verification (AdjustmentVideoObjectTracking) labeling jobs for this task type.3D point cloud semantic segmentation (
3DPointCloudSemanticSegmentation), and adjustment and verification (Adjustment3DPointCloudSemanticSegmentation) labeling jobs for this task type.3D point cloud object tracking (
3DPointCloudObjectTracking), and adjustment and verification (Adjustment3DPointCloudObjectTracking) labeling jobs for this task type.
If you are creating an adjustment or verification labeling job, you must use a different LabelAttributeName than the one used in the original labeling job. The original labeling job is the Ground Truth labeling job that produced the labels that you want verified or adjusted. To learn more about adjustment and verification labeling jobs, see Verify and Adjust Labels (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html).
LabelCategoryConfigS3Uri => Str
The S3 URI of the file, referred to as a label category configuration file, that defines the categories used to label the data objects.
For 3D point cloud and video frame task types, you can add label category attributes and frame attributes to your label category configuration file. To learn how, see Create a Labeling Category Configuration File for 3D Point Cloud Labeling Jobs (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.html).
For all other built-in task types (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html) and custom tasks (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html), your label category configuration file must be a JSON file in the following format. Identify the labels you want to use by replacing label_1, label_2,...,label_n with your label categories.
{
"document-version": "2018-11-28",
"labels": [{"label": "label_1"},{"label": "label_2"},...{"label": "label_n"}]
}
Note the following about the label category configuration file:
For image classification and text classification (single and multi-label) you must specify at least two label categories. For all other task types, the minimum number of label categories required is one.
Each label category must be unique, you cannot specify duplicate label categories.
If you create a 3D point cloud or video frame adjustment or verification labeling job, you must include
auditLabelAttributeNamein the label category configuration. Use this parameter to enter theLabelAttributeName(https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html#sagemaker-CreateLabelingJob-request-LabelAttributeName) of the labeling job you want to adjust or verify annotations of.
LabelingJobAlgorithmsConfig => Paws::SageMaker::LabelingJobAlgorithmsConfig
Configures the information required to perform automated data labeling.
REQUIRED LabelingJobName => Str
The name of the labeling job. This name is used to identify the job in a list of labeling jobs. Labeling job names must be unique within an Amazon Web Services account and region. LabelingJobName is not case sensitive. For example, Example-job and example-job are considered the same labeling job name by Ground Truth.
REQUIRED OutputConfig => Paws::SageMaker::LabelingJobOutputConfig
The location of the output data and the Amazon Web Services Key Management Service key ID for the key used to encrypt the output data, if any.
REQUIRED RoleArn => Str
The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during data labeling. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete data labeling.
StoppingConditions => Paws::SageMaker::LabelingJobStoppingConditions
A set of conditions for stopping the labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
Tags => ArrayRef[Paws::SageMaker::Tag]
An array of key/value pairs. For more information, see Using Cost Allocation Tags (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what) in the Amazon Web Services Billing and Cost Management User Guide.
SEE ALSO
This class forms part of Paws, documenting arguments for method CreateLabelingJob in Paws::SageMaker
BUGS and CONTRIBUTIONS
The source code is located here: https://github.com/pplu/aws-sdk-perl
Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues