case class GraphReadout[M <: GraphModule](m: M with GraphModule, pooling: PoolType) extends GenericModule[(Variable, Variable, Variable), Variable] with Product with Serializable
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Instance Constructors
- new GraphReadout(m: M with GraphModule, pooling: PoolType)
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def
apply[S](a: (Variable, Variable, Variable))(implicit arg0: Sc[S]): Variable
Alias of forward
Alias of forward
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def
forward[S](x: (Variable, Variable, Variable))(implicit arg0: Sc[S]): 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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- GraphReadout → GenericModule
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def
getClass(): Class[_]
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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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isInstanceOf[T0]: Boolean
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def
learnableParameters: Long
Returns the total number of optimizable parameters.
Returns the total number of optimizable parameters.
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- val m: M with GraphModule
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ne(arg0: AnyRef): Boolean
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notify(): Unit
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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
- val pooling: PoolType
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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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- GraphReadout → GenericModule
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synchronized[T0](arg0: ⇒ T0): T0
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