GraphAttention

Companion:
class
trait Product
trait Mirror
class Object
trait Matchable
class Any

Type members

Classlikes

case object Weights extends LeafTag

Inherited types

type MirroredElemLabels <: Tuple

The names of the product elements

The names of the product elements

Inherited from:
Mirror
type MirroredLabel <: String

The name of the type

The name of the type

Inherited from:
Mirror

Value members

Concrete methods

def apply[S : Sc](nodeDim: Int, edgeDim: Int, attentionKeyHiddenDimPerHead: Int, attentionNumHeads: Int, valueDimPerHead: Int, dropout: Double, tOpt: STenOptions, dotProductAttention: Boolean, nonLinearity: Boolean): GraphAttention
def multiheadGraphAttention[S : Sc](nodeFeatures: Variable, edgeFeatures: Variable, edgeI: STen, edgeJ: STen, wNodeKey1: Variable, wNodeKey2: Variable, wEdgeKey: Variable, wNodeValue: Variable, wAttention: Option[Variable], numHeads: Int): Variable

Graph Attention Network https://arxiv.org/pdf/1710.10903.pdf Non-linearity in eq 4 and dropout is not applied to the final vertex activations

Graph Attention Network https://arxiv.org/pdf/1710.10903.pdf Non-linearity in eq 4 and dropout is not applied to the final vertex activations

Needs self edges to be already present in the graph

Returns:

next node representation (without relu, dropout) and a tensor with the original node and edge features ligned up like [N_i, N_j, E_ij]

Implicits

Implicits

implicit val load: Load[GraphAttention]