Enum NeuralModelType 

pub enum NeuralModelType {
    Feedforward,
    Convolutional,
    Recurrent,
    Transformer,
    GAN,
    VAE,
    Diffusion,
    Hybrid,
}

Types of neural models available

Variants

Feedforward

Feedforward neural network for basic spatial synthesis

Convolutional

Convolutional neural network for temporal-spatial processing

Recurrent

Recurrent neural network for temporal modeling

Transformer

Transformer model for attention-based spatial processing

GAN

Generative Adversarial Network for high-quality synthesis

VAE

Variational Autoencoder for latent space spatial modeling

Diffusion

Diffusion model for high-fidelity spatial audio generation

Hybrid

Hybrid model combining multiple architectures

Trait Implementations

impl Clone for NeuralModelType

fn clone(&self) -> NeuralModelType

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NeuralModelType

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for NeuralModelType

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for NeuralModelType

fn eq(&self, other: &NeuralModelType) -> 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 Serialize for NeuralModelType

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for NeuralModelType

impl StructuralPartialEq for NeuralModelType