Struct SupervisedTuningSpec 

#[non_exhaustive]
pub struct SupervisedTuningSpec {
    pub training_dataset_uri: String,
    pub validation_dataset_uri: String,
    pub hyper_parameters: Option<SupervisedHyperParameters>,
    pub export_last_checkpoint_only: bool,
    pub evaluation_config: Option<EvaluationConfig>,
    /* private fields */
}

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

Tuning Spec for Supervised Tuning for first party 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.

training_dataset_uri: String

Required. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file.

validation_dataset_uri: String

Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file.

hyper_parameters: Option<SupervisedHyperParameters>

Optional. Hyperparameters for SFT.

export_last_checkpoint_only: bool

Optional. If set to true, disable intermediate checkpoints for SFT and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for SFT. Default is false.

evaluation_config: Option<EvaluationConfig>

Optional. Evaluation Config for Tuning Job.

Implementations

impl SupervisedTuningSpec

pub fn new() -> Self

Creates a new default instance.

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

Sets the value of training_dataset_uri.

Example

let x = SupervisedTuningSpec::new().set_training_dataset_uri("example");

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

Sets the value of validation_dataset_uri.

Example

let x = SupervisedTuningSpec::new().set_validation_dataset_uri("example");

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

where T: Into<SupervisedHyperParameters>,

Sets the value of hyper_parameters.

Example

use google_cloud_aiplatform_v1::model::SupervisedHyperParameters;
let x = SupervisedTuningSpec::new().set_hyper_parameters(SupervisedHyperParameters::default()/* use setters */);

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

where T: Into<SupervisedHyperParameters>,

Sets or clears the value of hyper_parameters.

Example

use google_cloud_aiplatform_v1::model::SupervisedHyperParameters;
let x = SupervisedTuningSpec::new().set_or_clear_hyper_parameters(Some(SupervisedHyperParameters::default()/* use setters */));
let x = SupervisedTuningSpec::new().set_or_clear_hyper_parameters(None::<SupervisedHyperParameters>);

pub fn set_export_last_checkpoint_only<T: Into<bool>>(self, v: T) -> Self

Sets the value of export_last_checkpoint_only.

Example

let x = SupervisedTuningSpec::new().set_export_last_checkpoint_only(true);

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

where T: Into<EvaluationConfig>,

Sets the value of evaluation_config.

Example

use google_cloud_aiplatform_v1::model::EvaluationConfig;
let x = SupervisedTuningSpec::new().set_evaluation_config(EvaluationConfig::default()/* use setters */);

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

where T: Into<EvaluationConfig>,

Sets or clears the value of evaluation_config.

Example

use google_cloud_aiplatform_v1::model::EvaluationConfig;
let x = SupervisedTuningSpec::new().set_or_clear_evaluation_config(Some(EvaluationConfig::default()/* use setters */));
let x = SupervisedTuningSpec::new().set_or_clear_evaluation_config(None::<EvaluationConfig>);

Trait Implementations

impl Clone for SupervisedTuningSpec

fn clone(&self) -> SupervisedTuningSpec

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SupervisedTuningSpec

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

Formats the value using the given formatter.

impl Default for SupervisedTuningSpec

fn default() -> SupervisedTuningSpec

Returns the “default value” for a type.

impl Message for SupervisedTuningSpec

fn typename() -> &'static str

The typename of this message.

impl PartialEq for SupervisedTuningSpec

fn eq(&self, other: &SupervisedTuningSpec) -> 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 SupervisedTuningSpec