object GraphAttention extends Serializable
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- def apply[S](nodeDim: Int, edgeDim: Int, attentionKeyHiddenDimPerHead: Int, attentionNumHeads: Int, valueDimPerHead: Int, dropout: Double, tOpt: STenOptions, dotProductAttention: Boolean, nonLinearity: Boolean)(implicit arg0: Sc[S]): GraphAttention
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- implicit val load: Load[GraphAttention]
- def multiheadGraphAttention[S](nodeFeatures: Variable, edgeFeatures: Variable, edgeI: STen, edgeJ: STen, wNodeKey1: Variable, wNodeKey2: Variable, wEdgeKey: Variable, wNodeValue: Variable, wAttention: Option[Variable], numHeads: Int)(implicit arg0: Sc[S]): 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]
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- implicit val tr: TrainingMode[GraphAttention]
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- case object Weights extends LeafTag with Product with Serializable
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(Since version 9)