Struct MetaLearningGene 

pub struct MetaLearningGene {
    pub innovation_number: Arc<str>,
    pub learning_rate: f32,
    pub learning_threshold: f32,
}

Gene that defines the meta-learning rules for the neural network.

Fields

• innovation_number - Unique identifier for this particular gene.
• learning_rate - Learning rate for synaptic adjustments.
• learning_threshold - Learning threshold for synaptic adjustments.

Fields

innovation_number: Arc<str>

learning_rate: f32

learning_threshold: f32

Trait Implementations

impl Clone for MetaLearningGene

fn clone(&self) -> MetaLearningGene

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MetaLearningGene

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

Formats the value using the given formatter.

impl Default for MetaLearningGene

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for MetaLearningGene

fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for MetaLearningGene

fn eq(&self, other: &MetaLearningGene) -> 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 MetaLearningGene

fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>

where S: Serializer,

Serialize this value into the given Serde serializer.

impl ToPyObject for MetaLearningGene

fn to_object(&self, py: Python<'_>) -> PyObject

Converts self into a Python object.

impl StructuralPartialEq for MetaLearningGene