Struct gapi_grpc::google::cloud::datalabeling::v1beta1::EvaluationJob[][src]

pub struct EvaluationJob {
    pub name: String,
    pub description: String,
    pub state: i32,
    pub schedule: String,
    pub model_version: String,
    pub evaluation_job_config: Option<EvaluationJobConfig>,
    pub annotation_spec_set: String,
    pub label_missing_ground_truth: bool,
    pub attempts: Vec<Attempt>,
    pub create_time: Option<Timestamp>,
}

Defines an evaluation job that runs periodically to generate [Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. Creating an evaluation job is the starting point for using continuous evaluation.

Fields

name: String

Output only. 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}

description: String

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

state: i32

Output only. Describes the current state of the job.

schedule: String

Required. 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 crontab format or in an English-like 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.

model_version: String

Required. The AI Platform Prediction model version 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.

evaluation_job_config: Option<EvaluationJobConfig>

Required. Configuration details for the evaluation job.

annotation_spec_set: String

Required. Name of the [AnnotationSpecSet][google.cloud.datalabeling.v1beta1.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}

label_missing_ground_truth: bool

Required. 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.

attempts: Vec<Attempt>

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

create_time: Option<Timestamp>

Output only. Timestamp of when this evaluation job was created.

Implementations

impl EvaluationJob[src]

pub fn state(&self) -> State[src]

Returns the enum value of state, or the default if the field is set to an invalid enum value.

pub fn set_state(&mut self, value: State)[src]

Sets state to the provided enum value.

Trait Implementations

impl Clone for EvaluationJob[src]

impl Debug for EvaluationJob[src]

impl Default for EvaluationJob[src]

impl Message for EvaluationJob[src]

impl PartialEq<EvaluationJob> for EvaluationJob[src]

impl StructuralPartialEq for EvaluationJob[src]

Auto Trait Implementations

impl RefUnwindSafe for EvaluationJob

impl Send for EvaluationJob

impl Sync for EvaluationJob

impl Unpin for EvaluationJob

impl UnwindSafe for EvaluationJob

Blanket Implementations

impl<T> Any for T where
    T: 'static + ?Sized
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impl<T> Borrow<T> for T where
    T: ?Sized
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impl<T> BorrowMut<T> for T where
    T: ?Sized
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impl<T> From<T> for T[src]

impl<T> Instrument for T[src]

impl<T> Instrument for T[src]

impl<T, U> Into<U> for T where
    U: From<T>, 
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impl<T> IntoRequest<T> for T[src]

impl<T> ToOwned for T where
    T: Clone
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type Owned = T

The resulting type after obtaining ownership.

impl<T, U> TryFrom<U> for T where
    U: Into<T>, 
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type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
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type Error = <U as TryFrom<T>>::Error

The type returned in the event of a conversion error.

impl<V, T> VZip<V> for T where
    V: MultiLane<T>, 
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impl<T> WithSubscriber for T[src]