lamp-core/lamp.nn.graph/MPNN

MPNN

case class MPNN[M1 <: Module, M2 <: Module](messageTransform: M1 & Module, vertexTransform: M2 & Module, degreeNormalizeI: Boolean, degreeNormalizeJ: Boolean, aggregateJ: Boolean) extends GraphModule
Companion:
object
trait Serializable
trait Product
trait Equals
class Object
trait Matchable
class Any

Value members

Concrete methods

override def forward[S : Sc](x: Graph): Graph
Definition Classes
def state: Seq[(Constant, PTag)]

Inherited methods

def apply[S : Sc](a: Graph): Graph

Alias of forward

Alias of forward

Inherited from:
GenericModule
final def gradients(loss: Variable, zeroGrad: Boolean): Seq[Option[STen]]

Computes the gradient of loss with respect to the parameters.

Computes the gradient of loss with respect to the parameters.

Inherited from:
GenericModule
final def learnableParameters: Long

Returns the total number of optimizable parameters.

Returns the total number of optimizable parameters.

Inherited from:
GenericModule
final def parameters: Seq[(Constant, PTag)]

Returns the state variables which need gradient computation.

Returns the state variables which need gradient computation.

Inherited from:
GenericModule
def productElementNames: Iterator[String]
Inherited from:
Product
def productIterator: Iterator[Any]
Inherited from:
Product
final def zeroGrad(): Unit
Inherited from:
GenericModule