DataLabelingJobArgs constructor

const DataLabelingJobArgs({ Input<GoogleCloudAiplatformV1ActiveLearningConfig>? activeLearningConfig, Input<Map<String, String>>? annotationLabels, required Input<List<String>> datasets, required Input<String> displayName, Input<GoogleCloudAiplatformV1EncryptionSpec>? encryptionSpec, required Input inputs, required Input<String> inputsSchemaUri, required Input<String> instructionUri, required Input<int> labelerCount, Input<Map<String, String>>? labels, Input<String>? location, Input<String>? project, Input<List<String>>? specialistPools, })

Creates a new DataLabelingJobArgs. activeLearningConfig Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy. annotationLabels Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. datasets Dataset resource names. Right now we only support labeling from a single Dataset. Format: projects/{project}/locations/{location}/datasets/{dataset} displayName The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob. encryptionSpec Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to. inputs Input config parameters for the DataLabelingJob. inputsSchemaUri Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder. instructionUri The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets. labelerCount Number of labelers to work on each DataItem. labels The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title. location Optional. project Optional. specialistPools The SpecialistPools' resource names associated with this job.

Implementation

const DataLabelingJobArgs({
  this.activeLearningConfig,
  this.annotationLabels,
  required this.datasets,
  required this.displayName,
  this.encryptionSpec,
  required this.inputs,
  required this.inputsSchemaUri,
  required this.instructionUri,
  required this.labelerCount,
  this.labels,
  this.location,
  this.project,
  this.specialistPools,
});