Struct GraphSAGELayer 

pub struct GraphSAGELayer {
    pub weights: Vec<Vec<f64>>,
    pub bias: Vec<f64>,
    pub out_dim: usize,
    pub aggregation: MessagePassing,
    pub use_activation: bool,
}

GraphSAGE layer - legacy Vec API

Fields

weights: Vec<Vec<f64>>

Weight matrix for concatenated [self || neighbor_agg] (out × 2*in)

bias: Vec<f64>

Bias (out_dim)

out_dim: usize

Output dimension

aggregation: MessagePassing

Aggregation strategy

use_activation: bool

Whether to apply ReLU

Implementations

impl GraphSAGELayer

pub fn new(in_dim: usize, out_dim: usize) -> Self

Create a new GraphSAGE layer

Trait Implementations

impl Clone for GraphSAGELayer

fn clone(&self) -> GraphSAGELayer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GraphSAGELayer

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

Formats the value using the given formatter.

impl MessagePassingLayer for GraphSAGELayer

fn aggregate( &self, node_features: &[Vec<f64>], adjacency: &[(usize, usize, f64)], n_nodes: usize, ) -> Result<Vec<Vec<f64>>>

Aggregate messages from the neighborhood of each node

fn update( &self, aggregated: &[Vec<f64>], _node_features: &[Vec<f64>], ) -> Result<Vec<Vec<f64>>>

Update node embeddings using aggregated messages and self-features

fn forward( &self, node_features: &[Vec<f64>], adjacency: &[(usize, usize, f64)], ) -> Result<Vec<Vec<f64>>>

Run one full forward pass: aggregate + update