Struct GraphData 

pub struct GraphData {
    pub x: Tensor,
    pub edge_index: Tensor,
    pub edge_attr: Option<Tensor>,
    pub batch: Option<Tensor>,
    pub num_nodes: usize,
    pub num_edges: usize,
}

Graph data structure for GNNs

Fields

x: Tensor

Node feature matrix (num_nodes x num_features)

edge_index: Tensor

Edge index matrix (2 x num_edges)

edge_attr: Option<Tensor>

Edge features (optional)

batch: Option<Tensor>

Batch assignment vector (optional, for batched graphs)

num_nodes: usize

Number of nodes

num_edges: usize

Number of edges

Implementations

impl GraphData

pub fn new(x: Tensor, edge_index: Tensor) -> Self

Create a new graph data structure

Arguments

• x - Node feature matrix with shape [num_nodes, num_features]
• edge_index - Edge connectivity with shape [2, num_edges]

Returns

A new GraphData instance

Example

use torsh_graph::GraphData;
use torsh_tensor::creation::from_vec;
use torsh_core::device::DeviceType;

// Create a simple triangle graph
let x = from_vec(vec![1.0, 2.0, 3.0], &[3, 1], DeviceType::Cpu).unwrap();
let edge_index = from_vec(
    vec![0.0, 1.0, 2.0, 1.0, 2.0, 0.0], // src, dst
    &[2, 3],
    DeviceType::Cpu
).unwrap();

let graph = GraphData::new(x, edge_index);
assert_eq!(graph.num_nodes, 3);
assert_eq!(graph.num_edges, 3);

pub fn with_edge_attr(self, edge_attr: Tensor) -> Self

Add edge attributes

pub fn with_batch(self, batch: Tensor) -> Self

Add batch assignment

pub fn with_edge_attr_opt(self, edge_attr: Option<Tensor>) -> Self

Add edge attributes (optional chaining)

pub fn memory_stats(&self) -> GraphMemoryStats

Get memory usage statistics

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

Validate graph structure

Checks that:

• All edge indices refer to valid nodes
• Edge attributes (if present) match the number of edges

Returns

• Ok(()) - Graph structure is valid
• Err(GraphValidationError) - Validation failed

Example

use torsh_graph::GraphData;
use torsh_tensor::creation::from_vec;
use torsh_core::device::DeviceType;

let x = from_vec(vec![1.0, 2.0], &[2, 1], DeviceType::Cpu).unwrap();
let edge_index = from_vec(vec![0.0, 1.0], &[2, 1], DeviceType::Cpu).unwrap();
let graph = GraphData::new(x, edge_index);

assert!(graph.validate().is_ok());

Trait Implementations

impl Clone for GraphData

fn clone(&self) -> GraphData

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for GraphData

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

Formats the value using the given formatter.