Struct TuningJob 

#[non_exhaustive]
pub struct TuningJob {

    pub name: String,
    pub tuned_model_display_name: String,
    pub description: String,
    pub state: JobState,
    pub create_time: Option<Timestamp>,
    pub start_time: Option<Timestamp>,
    pub end_time: Option<Timestamp>,
    pub update_time: Option<Timestamp>,
    pub error: Option<Status>,
    pub labels: HashMap<String, String>,
    pub experiment: String,
    pub tuned_model: Option<TunedModel>,
    pub tuning_data_stats: Option<TuningDataStats>,
    pub encryption_spec: Option<EncryptionSpec>,
    pub service_account: String,
    pub source_model: Option<SourceModel>,
    pub tuning_spec: Option<TuningSpec>,
    /* private fields */
}

Available on crate feature gen-ai-tuning-service only.

Represents a TuningJob that runs with Google owned models.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

name: String

Output only. Identifier. Resource name of a TuningJob. Format: projects/{project}/locations/{location}/tuningJobs/{tuning_job}

tuned_model_display_name: String

Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version.

description: String

Optional. The description of the TuningJob.

state: JobState

Output only. The detailed state of the job.

create_time: Option<Timestamp>

Output only. Time when the TuningJob was created.

start_time: Option<Timestamp>

Output only. Time when the TuningJob for the first time entered the JOB_STATE_RUNNING state.

end_time: Option<Timestamp>

Output only. Time when the TuningJob entered any of the following JobStates: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED, JOB_STATE_EXPIRED.

update_time: Option<Timestamp>

Output only. Time when the TuningJob was most recently updated.

error: Option<Status>

Output only. Only populated when job’s state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

labels: HashMap<String, String>

Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint.

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.

experiment: String

Output only. The Experiment associated with this TuningJob.

tuned_model: Option<TunedModel>

Output only. The tuned model resources associated with this TuningJob.

tuning_data_stats: Option<TuningDataStats>

Output only. The tuning data statistics associated with this TuningJob.

encryption_spec: Option<EncryptionSpec>

Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key.

service_account: String

The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-secure-fine-tuning-service-agent

Users starting the pipeline must have the iam.serviceAccounts.actAs permission on this service account.

source_model: Option<SourceModel>

tuning_spec: Option<TuningSpec>

Implementations

impl TuningJob

pub fn new() -> Self

pub fn set_name<T: Into<String>>(self, v: T) -> Self

Sets the value of name.

Example

let x = TuningJob::new().set_name("example");

pub fn set_tuned_model_display_name<T: Into<String>>(self, v: T) -> Self

Sets the value of tuned_model_display_name.

Example

let x = TuningJob::new().set_tuned_model_display_name("example");

pub fn set_description<T: Into<String>>(self, v: T) -> Self

Sets the value of description.

Example

let x = TuningJob::new().set_description("example");

pub fn set_state<T: Into<JobState>>(self, v: T) -> Self

Sets the value of state.

Example

use google_cloud_aiplatform_v1::model::JobState;
let x0 = TuningJob::new().set_state(JobState::Queued);
let x1 = TuningJob::new().set_state(JobState::Pending);
let x2 = TuningJob::new().set_state(JobState::Running);

pub fn set_create_time<T>(self, v: T) -> Self

where T: Into<Timestamp>,

Sets the value of create_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_create_time(Timestamp::default()/* use setters */);

pub fn set_or_clear_create_time<T>(self, v: Option<T>) -> Self

where T: Into<Timestamp>,

Sets or clears the value of create_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_or_clear_create_time(Some(Timestamp::default()/* use setters */));
let x = TuningJob::new().set_or_clear_create_time(None::<Timestamp>);

pub fn set_start_time<T>(self, v: T) -> Self

where T: Into<Timestamp>,

Sets the value of start_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_start_time(Timestamp::default()/* use setters */);

pub fn set_or_clear_start_time<T>(self, v: Option<T>) -> Self

where T: Into<Timestamp>,

Sets or clears the value of start_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_or_clear_start_time(Some(Timestamp::default()/* use setters */));
let x = TuningJob::new().set_or_clear_start_time(None::<Timestamp>);

pub fn set_end_time<T>(self, v: T) -> Self

where T: Into<Timestamp>,

Sets the value of end_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_end_time(Timestamp::default()/* use setters */);

pub fn set_or_clear_end_time<T>(self, v: Option<T>) -> Self

where T: Into<Timestamp>,

Sets or clears the value of end_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_or_clear_end_time(Some(Timestamp::default()/* use setters */));
let x = TuningJob::new().set_or_clear_end_time(None::<Timestamp>);

pub fn set_update_time<T>(self, v: T) -> Self

where T: Into<Timestamp>,

Sets the value of update_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_update_time(Timestamp::default()/* use setters */);

pub fn set_or_clear_update_time<T>(self, v: Option<T>) -> Self

where T: Into<Timestamp>,

Sets or clears the value of update_time.

Example

use wkt::Timestamp;
let x = TuningJob::new().set_or_clear_update_time(Some(Timestamp::default()/* use setters */));
let x = TuningJob::new().set_or_clear_update_time(None::<Timestamp>);

pub fn set_error<T>(self, v: T) -> Self

where T: Into<Status>,

Sets the value of error.

Example

use rpc::model::Status;
let x = TuningJob::new().set_error(Status::default()/* use setters */);

pub fn set_or_clear_error<T>(self, v: Option<T>) -> Self

where T: Into<Status>,

Sets or clears the value of error.

Example

use rpc::model::Status;
let x = TuningJob::new().set_or_clear_error(Some(Status::default()/* use setters */));
let x = TuningJob::new().set_or_clear_error(None::<Status>);

pub fn set_labels<T, K, V>(self, v: T) -> Self

where T: IntoIterator<Item = (K, V)>, K: Into<String>, V: Into<String>,

Sets the value of labels.

Example

let x = TuningJob::new().set_labels([
    ("key0", "abc"),
    ("key1", "xyz"),
]);

pub fn set_experiment<T: Into<String>>(self, v: T) -> Self

Sets the value of experiment.

Example

let x = TuningJob::new().set_experiment("example");

pub fn set_tuned_model<T>(self, v: T) -> Self

where T: Into<TunedModel>,

Sets the value of tuned_model.

Example

use google_cloud_aiplatform_v1::model::TunedModel;
let x = TuningJob::new().set_tuned_model(TunedModel::default()/* use setters */);

pub fn set_or_clear_tuned_model<T>(self, v: Option<T>) -> Self

where T: Into<TunedModel>,

Sets or clears the value of tuned_model.

Example

use google_cloud_aiplatform_v1::model::TunedModel;
let x = TuningJob::new().set_or_clear_tuned_model(Some(TunedModel::default()/* use setters */));
let x = TuningJob::new().set_or_clear_tuned_model(None::<TunedModel>);

pub fn set_tuning_data_stats<T>(self, v: T) -> Self

where T: Into<TuningDataStats>,

Sets the value of tuning_data_stats.

Example

use google_cloud_aiplatform_v1::model::TuningDataStats;
let x = TuningJob::new().set_tuning_data_stats(TuningDataStats::default()/* use setters */);

pub fn set_or_clear_tuning_data_stats<T>(self, v: Option<T>) -> Self

where T: Into<TuningDataStats>,

Sets or clears the value of tuning_data_stats.

Example

use google_cloud_aiplatform_v1::model::TuningDataStats;
let x = TuningJob::new().set_or_clear_tuning_data_stats(Some(TuningDataStats::default()/* use setters */));
let x = TuningJob::new().set_or_clear_tuning_data_stats(None::<TuningDataStats>);

pub fn set_encryption_spec<T>(self, v: T) -> Self

where T: Into<EncryptionSpec>,

Sets the value of encryption_spec.

Example

use google_cloud_aiplatform_v1::model::EncryptionSpec;
let x = TuningJob::new().set_encryption_spec(EncryptionSpec::default()/* use setters */);

pub fn set_or_clear_encryption_spec<T>(self, v: Option<T>) -> Self

where T: Into<EncryptionSpec>,

Sets or clears the value of encryption_spec.

Example

use google_cloud_aiplatform_v1::model::EncryptionSpec;
let x = TuningJob::new().set_or_clear_encryption_spec(Some(EncryptionSpec::default()/* use setters */));
let x = TuningJob::new().set_or_clear_encryption_spec(None::<EncryptionSpec>);

pub fn set_service_account<T: Into<String>>(self, v: T) -> Self

Sets the value of service_account.

Example

let x = TuningJob::new().set_service_account("example");

pub fn set_source_model<T: Into<Option<SourceModel>>>(self, v: T) -> Self

Sets the value of source_model.

Note that all the setters affecting source_model are mutually exclusive.

Example

use google_cloud_aiplatform_v1::model::tuning_job::SourceModel;
let x = TuningJob::new().set_source_model(Some(SourceModel::BaseModel("example".to_string())));

pub fn base_model(&self) -> Option<&String>

The value of source_model if it holds a BaseModel, None if the field is not set or holds a different branch.

pub fn set_base_model<T: Into<String>>(self, v: T) -> Self

Sets the value of source_model to hold a BaseModel.

Note that all the setters affecting source_model are mutually exclusive.

Example

let x = TuningJob::new().set_base_model("example");
assert!(x.base_model().is_some());
assert!(x.pre_tuned_model().is_none());

pub fn pre_tuned_model(&self) -> Option<&Box<PreTunedModel>>

The value of source_model if it holds a PreTunedModel, None if the field is not set or holds a different branch.

pub fn set_pre_tuned_model<T: Into<Box<PreTunedModel>>>(self, v: T) -> Self

Sets the value of source_model to hold a PreTunedModel.

Note that all the setters affecting source_model are mutually exclusive.

Example

use google_cloud_aiplatform_v1::model::PreTunedModel;
let x = TuningJob::new().set_pre_tuned_model(PreTunedModel::default()/* use setters */);
assert!(x.pre_tuned_model().is_some());
assert!(x.base_model().is_none());

pub fn set_tuning_spec<T: Into<Option<TuningSpec>>>(self, v: T) -> Self

Sets the value of tuning_spec.

Note that all the setters affecting tuning_spec are mutually exclusive.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningSpec;
let x = TuningJob::new().set_tuning_spec(Some(
    google_cloud_aiplatform_v1::model::tuning_job::TuningSpec::SupervisedTuningSpec(SupervisedTuningSpec::default().into())));

pub fn supervised_tuning_spec(&self) -> Option<&Box<SupervisedTuningSpec>>

The value of tuning_spec if it holds a SupervisedTuningSpec, None if the field is not set or holds a different branch.

pub fn set_supervised_tuning_spec<T: Into<Box<SupervisedTuningSpec>>>( self, v: T, ) -> Self

Sets the value of tuning_spec to hold a SupervisedTuningSpec.

Note that all the setters affecting tuning_spec are mutually exclusive.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningSpec;
let x = TuningJob::new().set_supervised_tuning_spec(SupervisedTuningSpec::default()/* use setters */);
assert!(x.supervised_tuning_spec().is_some());

Trait Implementations

impl Clone for TuningJob

fn clone(&self) -> TuningJob

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TuningJob

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

Formats the value using the given formatter.

impl Default for TuningJob

fn default() -> TuningJob

Returns the “default value” for a type.

impl Message for TuningJob

fn typename() -> &'static str

The typename of this message.

impl PartialEq for TuningJob

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

Tests for self and other values to be equal, and is used by ==.

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

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for TuningJob