Struct TrainingDataSet 

pub struct TrainingDataSet {
    pub training: ImageDataSet,
    pub regularization: Option<ImageDataSet>,
}

A training data set.

Fields

training: ImageDataSet

The training images.

regularization: Option<ImageDataSet>

The regularization images.

Implementations

impl TrainingDataSet

pub fn new(training: ImageDataSet) -> Self

Create a new training data set.

Examples found in repository

examples/train-lora.rs (line 9)

fn main() {
    let kohya_ss = std::env::var("KOHYA_SS_PATH").expect("KOHYA_SS_PATH not set");
    let environment = Environment::new().with_kohya_ss(kohya_ss);

    let prompt = Prompt::new("bacana", "white dog");
    let image_data_set = ImageDataSet::from_dir("examples/training/lora/bacana/images");
    let data_set = TrainingDataSet::new(image_data_set);
    let output = Output::new("{prompt.instance}({prompt.class})d{network.dimension}a{network.alpha}", "examples/training/lora/bacana/output");
    let parameters = Parameters::new(prompt, data_set, output);

    Trainer::new()
        .with_environment(environment)
        .start(&parameters);
}

pub fn with_regularization_images( self, regularization_images: ImageDataSet, ) -> Self

Set the regularization images for the training data set.

Trait Implementations

impl Debug for TrainingDataSet

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for TrainingDataSet

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for TrainingDataSet

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.