pub struct Rescal {
pub entity_emb: Vec<Vec<f32>>,
pub relation_mat: Vec<Vec<Vec<f32>>>,
pub dim: usize,
}Expand description
RESCAL: Bilinear model for knowledge graph embedding.
Each relation has a full dim×dim matrix. Scoring: h^T * M_r * t
Fields§
§entity_emb: Vec<Vec<f32>>Entity embeddings: [num_entities][dim]
relation_mat: Vec<Vec<Vec<f32>>>Relation matrices: [num_relations][dim][dim]
dim: usizeEmbedding dimension
Implementations§
Source§impl Rescal
impl Rescal
Sourcepub fn new(num_entities: usize, num_relations: usize, dim: usize) -> Self
pub fn new(num_entities: usize, num_relations: usize, dim: usize) -> Self
Create a new RESCAL model.
Sourcepub fn score(&self, head: usize, relation: usize, tail: usize) -> f32
pub fn score(&self, head: usize, relation: usize, tail: usize) -> f32
Compute score = h^T * M_r * t
Sourcepub fn update(
&mut self,
head: usize,
relation: usize,
tail: usize,
label: f32,
lr: f32,
)
pub fn update( &mut self, head: usize, relation: usize, tail: usize, label: f32, lr: f32, )
SGD update step minimizing squared loss (score - label)^2.
Sourcepub fn relation_matrix(&self, relation: usize) -> &Vec<Vec<f32>>
pub fn relation_matrix(&self, relation: usize) -> &Vec<Vec<f32>>
Access the relation matrix for a given relation.
Sourcepub fn entity_count(&self) -> usize
pub fn entity_count(&self) -> usize
Number of entities
Sourcepub fn relation_count(&self) -> usize
pub fn relation_count(&self) -> usize
Number of relations
Trait Implementations§
Auto Trait Implementations§
impl Freeze for Rescal
impl RefUnwindSafe for Rescal
impl Send for Rescal
impl Sync for Rescal
impl Unpin for Rescal
impl UnsafeUnpin for Rescal
impl UnwindSafe for Rescal
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T: ?Sized,
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The inclusion map: converts
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