Struct CodeGan 

pub struct CodeGan {
    pub config: CodeGanConfig,
    pub generator: Generator,
    pub discriminator: Discriminator,
    pub stats: CodeGanStats,
    /* private fields */
}

Complete Code GAN for generating Rust AST

Fields

config: CodeGanConfig

Configuration

generator: Generator

Generator network

discriminator: Discriminator

Discriminator network

stats: CodeGanStats

Training statistics

Implementations

impl CodeGan

pub fn new(config: CodeGanConfig) -> Self

Create a new Code GAN

pub fn with_seed(config: CodeGanConfig, seed: u64) -> Self

Create a new Code GAN with a seed for reproducibility

pub fn sample_latent(&mut self, batch_size: usize) -> Vec<LatentCode>

Sample latent codes for generation

pub fn generate(&self, latent_codes: &[LatentCode]) -> Vec<Vec<u32>>

Generate code from latent codes

pub fn generate_one(&mut self) -> Vec<u32>

Generate a single code sample

pub fn discriminate(&self, samples: &[Vec<u32>]) -> Vec<f32>

Discriminate a batch of code samples

pub fn discriminator_loss( &self, real_samples: &[Vec<u32>], fake_samples: &[Vec<u32>], ) -> f32

Compute discriminator loss (binary cross-entropy)

pub fn generator_loss(&self, fake_samples: &[Vec<u32>]) -> f32

Compute generator loss (try to fool discriminator)

pub fn detect_mode_collapse(&mut self, num_samples: usize) -> f32

Detect mode collapse by measuring diversity of generated samples

pub fn interpolate( &self, z1: &LatentCode, z2: &LatentCode, steps: usize, ) -> Vec<Vec<u32>>

Interpolate between two latent codes and generate intermediate samples

pub fn num_parameters(&self) -> usize

Get total number of parameters

pub fn record_step(&mut self, result: &TrainingResult)

Record training step

pub fn avg_gen_loss(&self) -> f32

Get average generator loss over recent history

pub fn avg_disc_loss(&self) -> f32

Get average discriminator loss over recent history