Struct NeuralAdaptiveConfig 

pub struct NeuralAdaptiveConfig {

    pub hidden_layers: usize,
    pub neurons_per_layer: usize,
    pub learningrate: f64,
    pub memory_capacity: usize,
    pub reinforcement_learning: bool,
    pub attention_heads: usize,
    pub self_attention: bool,
    pub rl_algorithm: RLAlgorithm,
    pub exploration_rate: f64,
    pub discountfactor: f64,
    pub replay_buffer_size: usize,
    pub modeldim: usize,
    pub ff_dim: usize,
    pub transformer_layers: usize,
}

Neural-adaptive sparse matrix processor configuration

Fields

hidden_layers: usize

Number of hidden layers in the neural network

neurons_per_layer: usize

Neurons per hidden layer

learningrate: f64

Learning rate for adaptive optimization

memory_capacity: usize

Memory capacity for pattern learning

reinforcement_learning: bool

Enable reinforcement learning

attention_heads: usize

Attention mechanism configuration

self_attention: bool

Enable transformer-style self-attention

rl_algorithm: RLAlgorithm

Reinforcement learning algorithm

exploration_rate: f64

Exploration rate for RL

discountfactor: f64

Discount factor for future rewards

replay_buffer_size: usize

Experience replay buffer size

modeldim: usize

Transformer model dimension

ff_dim: usize

Feed-forward network dimension in transformer

transformer_layers: usize

Number of transformer layers

Implementations

impl NeuralAdaptiveConfig

pub fn new() -> Self

Create a new configuration with default values

pub fn with_hidden_layers(self, layers: usize) -> Self

Set the number of hidden layers

pub fn with_neurons_per_layer(self, neurons: usize) -> Self

Set neurons per layer

pub fn with_learning_rate(self, rate: f64) -> Self

Set learning rate

pub fn with_memory_capacity(self, capacity: usize) -> Self

Set memory capacity

pub fn with_reinforcement_learning(self, enabled: bool) -> Self

Enable or disable reinforcement learning

pub fn with_attention_heads(self, heads: usize) -> Self

Set number of attention heads

pub fn with_self_attention(self, enabled: bool) -> Self

Enable or disable self-attention

pub fn with_rl_algorithm(self, algorithm: RLAlgorithm) -> Self

Set RL algorithm

pub fn with_exploration_rate(self, rate: f64) -> Self

Set exploration rate

pub fn with_discount_factor(self, factor: f64) -> Self

Set discount factor

pub fn with_replay_buffer_size(self, size: usize) -> Self

Set replay buffer size

pub fn with_model_dim(self, dim: usize) -> Self

Set transformer model dimension

pub fn with_ff_dim(self, dim: usize) -> Self

Set feed-forward dimension

pub fn with_transformer_layers(self, layers: usize) -> Self

Set number of transformer layers

pub fn validate(&self) -> Result<(), String>

Validate configuration parameters

pub fn lightweight() -> Self

Create a lightweight configuration for testing

pub fn high_performance() -> Self

Create a high-performance configuration

pub fn memory_efficient() -> Self

Create a memory-efficient configuration

Trait Implementations

impl Clone for NeuralAdaptiveConfig

fn clone(&self) -> NeuralAdaptiveConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NeuralAdaptiveConfig

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

Formats the value using the given formatter.

impl Default for NeuralAdaptiveConfig

fn default() -> Self

Returns the “default value” for a type.