pulumi-google-native-kotlin/com.pulumi.googlenative.datalabeling.v1beta1.kotlin.outputs/GetEvaluationJobResult

GetEvaluationJobResult

data class GetEvaluationJobResult(val annotationSpecSet: String, val attempts: List<GoogleCloudDatalabelingV1beta1AttemptResponse>, val createTime: String, val description: String, val evaluationJobConfig: GoogleCloudDatalabelingV1beta1EvaluationJobConfigResponse, val labelMissingGroundTruth: Boolean, val modelVersion: String, val name: String, val schedule: String, val state: String)

Constructors

fun GetEvaluationJobResult(annotationSpecSet: String, attempts: List<GoogleCloudDatalabelingV1beta1AttemptResponse>, createTime: String, description: String, evaluationJobConfig: GoogleCloudDatalabelingV1beta1EvaluationJobConfigResponse, labelMissingGroundTruth: Boolean, modelVersion: String, name: String, schedule: String, state: String)

Types

Companion

object Companion

Properties

annotationSpecSet

val annotationSpecSet: String

Name of the AnnotationSpecSet describing all the labels that your machine learning model outputs. You must create this resource before you create an evaluation job and provide its name in the following format: "projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}"

attempts

val attempts: List<GoogleCloudDatalabelingV1beta1AttemptResponse>

Every time the evaluation job runs and an error occurs, the failed attempt is appended to this array.

createTime

val createTime: String

Timestamp of when this evaluation job was created.

description

val description: String

Description of the job. The description can be up to 25,000 characters long.

evaluationJobConfig

val evaluationJobConfig: GoogleCloudDatalabelingV1beta1EvaluationJobConfigResponse

Configuration details for the evaluation job.

labelMissingGroundTruth

val labelMissingGroundTruth: Boolean

Whether you want Data Labeling Service to provide ground truth labels for prediction input. If you want the service to assign human labelers to annotate your data, set this to true. If you want to provide your own ground truth labels in the evaluation job's BigQuery table, set this to false.

modelVersion

val modelVersion: String

The /ml-engine/docs/prediction-overview to be evaluated. Prediction input and output is sampled from this model version. When creating an evaluation job, specify the model version in the following format: "projects/{project_id}/models/{model_name}/versions/{version_name}" There can only be one evaluation job per model version.

name

val name: String

After you create a job, Data Labeling Service assigns a name to the job with the following format: "projects/{project_id}/evaluationJobs/ {evaluation_job_id}"

schedule

val schedule: String

Describes the interval at which the job runs. This interval must be at least 1 day, and it is rounded to the nearest day. For example, if you specify a 50-hour interval, the job runs every 2 days. You can provide the schedule in /scheduler/docs/configuring/cron-job-schedules or in an /appengine/docs/standard/python/config/cronref#schedule_format. Regardless of what you specify, the job will run at 10:00 AM UTC. Only the interval from this schedule is used, not the specific time of day.

state

val state: String

Describes the current state of the job.