case class GCN[M <: Module](transform: M with Module) extends GenericModule[(Variable, Variable), (Variable, Variable)] with Product with Serializable
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- def apply[S](a: (Variable, Variable))(implicit arg0: Sc[S]): (Variable, Variable)
Alias of forward
Alias of forward
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- def forward[S](x: (Variable, Variable))(implicit arg0: Sc[S]): (Variable, Variable)
The implementation of the function.
The implementation of the function.
In addition of
x
it can also use all thestate to compute its value.
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- GCN → GenericModule
- final def getClass(): Class[_ <: AnyRef]
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- final def gradients(loss: Variable, zeroGrad: Boolean = true): Seq[Option[STen]]
Computes the gradient of loss with respect to the parameters.
Computes the gradient of loss with respect to the parameters.
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- final def isInstanceOf[T0]: Boolean
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- final def learnableParameters: Long
Returns the total number of optimizable parameters.
Returns the total number of optimizable parameters.
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- final def parameters: Seq[(Constant, PTag)]
Returns the state variables which need gradient computation.
Returns the state variables which need gradient computation.
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- GenericModule
- def productElementNames: Iterator[String]
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- Product
- def state: Seq[(Constant, PTag)]
List of optimizable, or non-optimizable, but stateful parameters
List of optimizable, or non-optimizable, but stateful parameters
Stateful means that the state is carried over the repeated forward calls.
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- GCN → GenericModule
- final def synchronized[T0](arg0: => T0): T0
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- val transform: M with Module
- final def wait(): Unit
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- final def zeroGrad(): Unit
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- GenericModule