Struct googapis::google::cloud::datalabeling::v1beta1::EvaluationJob

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

pub fn state(&self) -> State

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)

Sets state to the provided enum value.

Trait Implementations

impl Clone for EvaluationJob

fn clone(&self) -> EvaluationJob

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for EvaluationJob

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for EvaluationJob

fn default() -> Self

Returns the “default value” for a type.

impl Message for EvaluationJob

fn encode_raw<B>(&self, buf: &mut B) where
    B: BufMut, 

fn merge_field<B>(
    &mut self,
    tag: u32,
    wire_type: WireType,
    buf: &mut B,
    ctx: DecodeContext
) -> Result<(), DecodeError> where
    B: Buf, 

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
    B: BufMut, 

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8, Global>

Encodes the message to a newly allocated buffer.

fn encode_length_delimited<B>(&self, buf: &mut B) -> Result<(), EncodeError> where
    B: BufMut, 

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8, Global>

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode<B>(buf: B) -> Result<Self, DecodeError> where
    Self: Default,
    B: Buf, 

Decodes an instance of the message from a buffer.

fn decode_length_delimited<B>(buf: B) -> Result<Self, DecodeError> where
    Self: Default,
    B: Buf, 

Decodes a length-delimited instance of the message from the buffer.

fn merge<B>(&mut self, buf: B) -> Result<(), DecodeError> where
    B: Buf, 

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited<B>(&mut self, buf: B) -> Result<(), DecodeError> where
    B: Buf, 

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq<EvaluationJob> for EvaluationJob

fn eq(&self, other: &EvaluationJob) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &EvaluationJob) -> bool

This method tests for !=.

impl StructuralPartialEq for EvaluationJob