Struct TrainingDataset 

pub struct TrainingDataset {
    pub features: Vec<Vec<f32>>,
    pub labels: Vec<f32>,
    pub soft_targets: Option<Vec<f32>>,
}

Training dataset with features and labels

Fields

features: Vec<Vec<f32>>

Input features (N x input_dim)

labels: Vec<f32>

Target labels (N)

soft_targets: Option<Vec<f32>>

Optional teacher soft targets for distillation (N)

Implementations

impl TrainingDataset

pub fn new(features: Vec<Vec<f32>>, labels: Vec<f32>) -> Result<Self>

Create a new training dataset

pub fn with_soft_targets(self, soft_targets: Vec<f32>) -> Result<Self>

Add soft targets from teacher model for knowledge distillation

pub fn split(&self, val_ratio: f32) -> Result<(Self, Self)>

Split dataset into train and validation sets

pub fn normalize(&mut self) -> Result<(Vec<f32>, Vec<f32>)>

Normalize features using z-score normalization

pub fn len(&self) -> usize

Get number of samples

pub fn is_empty(&self) -> bool

Check if dataset is empty

Trait Implementations

impl Clone for TrainingDataset

fn clone(&self) -> TrainingDataset

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TrainingDataset

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

Formats the value using the given formatter.