Enum gapi_grpc::google::cloud::datalabeling::v1beta1::evaluation_job::State[][src]

#[repr(i32)]pub enum State {
    Unspecified,
    Scheduled,
    Running,
    Paused,
    Stopped,
}

State of the job.

Variants

Unspecified
Scheduled

The job is scheduled to run at the [configured interval][google.cloud.datalabeling.v1beta1.EvaluationJob.schedule]. You can [pause][google.cloud.datalabeling.v1beta1.DataLabelingService.PauseEvaluationJob] or [delete][google.cloud.datalabeling.v1beta1.DataLabelingService.DeleteEvaluationJob] the job.

When the job is in this state, it samples prediction input and output from your model version into your BigQuery table as predictions occur.

Running

The job is currently running. When the job runs, Data Labeling Service does several things:

  1. If you have configured your job to use Data Labeling Service for ground truth labeling, the service creates a [Dataset][google.cloud.datalabeling.v1beta1.Dataset] and a labeling task for all data sampled since the last time the job ran. Human labelers provide ground truth labels for your data. Human labeling may take hours, or even days, depending on how much data has been sampled. The job remains in the RUNNING state during this time, and it can even be running multiple times in parallel if it gets triggered again (for example 24 hours later) before the earlier run has completed. When human labelers have finished labeling the data, the next step occurs.

    If you have configured your job to provide your own ground truth labels, Data Labeling Service still creates a [Dataset][google.cloud.datalabeling.v1beta1.Dataset] for newly sampled data, but it expects that you have already added ground truth labels to the BigQuery table by this time. The next step occurs immediately.

  2. Data Labeling Service creates an [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation] by comparing your model version’s predictions with the ground truth labels.

If the job remains in this state for a long time, it continues to sample prediction data into your BigQuery table and will run again at the next interval, even if it causes the job to run multiple times in parallel.

Paused

The job is not sampling prediction input and output into your BigQuery table and it will not run according to its schedule. You can [resume][google.cloud.datalabeling.v1beta1.DataLabelingService.ResumeEvaluationJob] the job.

Stopped

The job has this state right before it is deleted.

Implementations

impl State[src]

pub fn is_valid(value: i32) -> bool[src]

Returns true if value is a variant of State.

pub fn from_i32(value: i32) -> Option<State>[src]

Converts an i32 to a State, or None if value is not a valid variant.

Trait Implementations

impl Clone for State[src]

impl Copy for State[src]

impl Debug for State[src]

impl Default for State[src]

impl Eq for State[src]

impl From<State> for i32[src]

impl Hash for State[src]

impl Ord for State[src]

impl PartialEq<State> for State[src]

impl PartialOrd<State> for State[src]

impl StructuralEq for State[src]

impl StructuralPartialEq for State[src]

Auto Trait Implementations

impl RefUnwindSafe for State

impl Send for State

impl Sync for State

impl Unpin for State

impl UnwindSafe for State

Blanket Implementations

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

impl<T> BorrowMut<T> for T where
    T: ?Sized
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impl<Q, K> Equivalent<K> for Q where
    K: Borrow<Q> + ?Sized,
    Q: Eq + ?Sized
[src]

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>, 
[src]

impl<T> IntoRequest<T> for T[src]

impl<T> ToOwned for T where
    T: Clone
[src]

type Owned = T

The resulting type after obtaining ownership.

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

type Error = Infallible

The type returned in the event of a conversion error.

impl<T, U> TryInto<U> for T where
    U: TryFrom<T>, 
[src]

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]