Struct SupervisedTuningDataStats 

#[non_exhaustive]
pub struct SupervisedTuningDataStats {
    pub tuning_dataset_example_count: i64,
    pub total_tuning_character_count: i64,
    pub total_billable_character_count: i64,
    pub total_billable_token_count: i64,
    pub tuning_step_count: i64,
    pub user_input_token_distribution: Option<SupervisedTuningDatasetDistribution>,
    pub user_output_token_distribution: Option<SupervisedTuningDatasetDistribution>,
    pub user_message_per_example_distribution: Option<SupervisedTuningDatasetDistribution>,
    pub user_dataset_examples: Vec<Content>,
    pub total_truncated_example_count: i64,
    pub truncated_example_indices: Vec<i64>,
    pub dropped_example_reasons: Vec<String>,
    /* private fields */
}

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

Tuning data statistics for Supervised Tuning.

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.

tuning_dataset_example_count: i64

Output only. Number of examples in the tuning dataset.

total_tuning_character_count: i64

Output only. Number of tuning characters in the tuning dataset.

total_billable_character_count: i64

👎Deprecated

Output only. Number of billable characters in the tuning dataset.

total_billable_token_count: i64

Output only. Number of billable tokens in the tuning dataset.

tuning_step_count: i64

Output only. Number of tuning steps for this Tuning Job.

user_input_token_distribution: Option<SupervisedTuningDatasetDistribution>

Output only. Dataset distributions for the user input tokens.

user_output_token_distribution: Option<SupervisedTuningDatasetDistribution>

Output only. Dataset distributions for the user output tokens.

user_message_per_example_distribution: Option<SupervisedTuningDatasetDistribution>

Output only. Dataset distributions for the messages per example.

user_dataset_examples: Vec<Content>

Output only. Sample user messages in the training dataset uri.

total_truncated_example_count: i64

Output only. The number of examples in the dataset that have been dropped. An example can be dropped for reasons including: too many tokens, contains an invalid image, contains too many images, etc.

truncated_example_indices: Vec<i64>

Output only. A partial sample of the indices (starting from 1) of the dropped examples.

dropped_example_reasons: Vec<String>

Output only. For each index in truncated_example_indices, the user-facing reason why the example was dropped.

Implementations

impl SupervisedTuningDataStats

pub fn new() -> Self

pub fn set_tuning_dataset_example_count<T: Into<i64>>(self, v: T) -> Self

Sets the value of tuning_dataset_example_count.

Example

let x = SupervisedTuningDataStats::new().set_tuning_dataset_example_count(42);

pub fn set_total_tuning_character_count<T: Into<i64>>(self, v: T) -> Self

Sets the value of total_tuning_character_count.

Example

let x = SupervisedTuningDataStats::new().set_total_tuning_character_count(42);

pub fn set_total_billable_character_count<T: Into<i64>>(self, v: T) -> Self

👎Deprecated

Sets the value of total_billable_character_count.

Example

let x = SupervisedTuningDataStats::new().set_total_billable_character_count(42);

pub fn set_total_billable_token_count<T: Into<i64>>(self, v: T) -> Self

Sets the value of total_billable_token_count.

Example

let x = SupervisedTuningDataStats::new().set_total_billable_token_count(42);

pub fn set_tuning_step_count<T: Into<i64>>(self, v: T) -> Self

Sets the value of tuning_step_count.

Example

let x = SupervisedTuningDataStats::new().set_tuning_step_count(42);

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

where T: Into<SupervisedTuningDatasetDistribution>,

Sets the value of user_input_token_distribution.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningDatasetDistribution;
let x = SupervisedTuningDataStats::new().set_user_input_token_distribution(SupervisedTuningDatasetDistribution::default()/* use setters */);

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

where T: Into<SupervisedTuningDatasetDistribution>,

Sets or clears the value of user_input_token_distribution.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningDatasetDistribution;
let x = SupervisedTuningDataStats::new().set_or_clear_user_input_token_distribution(Some(SupervisedTuningDatasetDistribution::default()/* use setters */));
let x = SupervisedTuningDataStats::new().set_or_clear_user_input_token_distribution(None::<SupervisedTuningDatasetDistribution>);

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

where T: Into<SupervisedTuningDatasetDistribution>,

Sets the value of user_output_token_distribution.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningDatasetDistribution;
let x = SupervisedTuningDataStats::new().set_user_output_token_distribution(SupervisedTuningDatasetDistribution::default()/* use setters */);

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

where T: Into<SupervisedTuningDatasetDistribution>,

Sets or clears the value of user_output_token_distribution.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningDatasetDistribution;
let x = SupervisedTuningDataStats::new().set_or_clear_user_output_token_distribution(Some(SupervisedTuningDatasetDistribution::default()/* use setters */));
let x = SupervisedTuningDataStats::new().set_or_clear_user_output_token_distribution(None::<SupervisedTuningDatasetDistribution>);

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

where T: Into<SupervisedTuningDatasetDistribution>,

Sets the value of user_message_per_example_distribution.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningDatasetDistribution;
let x = SupervisedTuningDataStats::new().set_user_message_per_example_distribution(SupervisedTuningDatasetDistribution::default()/* use setters */);

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

where T: Into<SupervisedTuningDatasetDistribution>,

Sets or clears the value of user_message_per_example_distribution.

Example

use google_cloud_aiplatform_v1::model::SupervisedTuningDatasetDistribution;
let x = SupervisedTuningDataStats::new().set_or_clear_user_message_per_example_distribution(Some(SupervisedTuningDatasetDistribution::default()/* use setters */));
let x = SupervisedTuningDataStats::new().set_or_clear_user_message_per_example_distribution(None::<SupervisedTuningDatasetDistribution>);

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

where T: IntoIterator<Item = V>, V: Into<Content>,

Sets the value of user_dataset_examples.

Example

use google_cloud_aiplatform_v1::model::Content;
let x = SupervisedTuningDataStats::new()
    .set_user_dataset_examples([
        Content::default()/* use setters */,
        Content::default()/* use (different) setters */,
    ]);

pub fn set_total_truncated_example_count<T: Into<i64>>(self, v: T) -> Self

Sets the value of total_truncated_example_count.

Example

let x = SupervisedTuningDataStats::new().set_total_truncated_example_count(42);

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

where T: IntoIterator<Item = V>, V: Into<i64>,

Sets the value of truncated_example_indices.

Example

let x = SupervisedTuningDataStats::new().set_truncated_example_indices([1, 2, 3]);

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

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

Sets the value of dropped_example_reasons.

Example

let x = SupervisedTuningDataStats::new().set_dropped_example_reasons(["a", "b", "c"]);

Trait Implementations

impl Clone for SupervisedTuningDataStats

fn clone(&self) -> SupervisedTuningDataStats

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for SupervisedTuningDataStats

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

Formats the value using the given formatter.

impl Default for SupervisedTuningDataStats

fn default() -> SupervisedTuningDataStats

Returns the “default value” for a type.

impl Message for SupervisedTuningDataStats

fn typename() -> &'static str

The typename of this message.

impl PartialEq for SupervisedTuningDataStats

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