case class BertLoss(pretrain: BertPretrainModule, mlmLoss: LossFunction, wholeSentenceLoss: LossFunction) extends GenericModule[BertLossInput, Variable] with Product with Serializable
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Instance Constructors
- new BertLoss(pretrain: BertPretrainModule, mlmLoss: LossFunction, wholeSentenceLoss: LossFunction)
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
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- def apply[S](a: BertLossInput)(implicit arg0: Sc[S]): Variable
Alias of forward
Alias of forward
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- GenericModule
- final def asInstanceOf[T0]: T0
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- def clone(): AnyRef
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def forward[S](x: BertLossInput)(implicit arg0: Sc[S]): Variable
The implementation of the function.
The implementation of the function.
In addition of
xit can also use all thestate to compute its value.- Definition Classes
- BertLoss → GenericModule
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @IntrinsicCandidate() @native()
- 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.
- Definition Classes
- GenericModule
- final def isInstanceOf[T0]: Boolean
- Definition Classes
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- final def learnableParameters: Long
Returns the total number of optimizable parameters.
Returns the total number of optimizable parameters.
- Definition Classes
- GenericModule
- val mlmLoss: LossFunction
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
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- final def notify(): Unit
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- @IntrinsicCandidate() @native()
- final def notifyAll(): Unit
- Definition Classes
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- @IntrinsicCandidate() @native()
- final def parameters: Seq[(Constant, PTag)]
Returns the state variables which need gradient computation.
Returns the state variables which need gradient computation.
- Definition Classes
- GenericModule
- val pretrain: BertPretrainModule
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- def state: List[(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.
- Definition Classes
- BertLoss → GenericModule
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
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- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
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- final def wait(): Unit
- Definition Classes
- AnyRef
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- @throws(classOf[java.lang.InterruptedException])
- val wholeSentenceLoss: LossFunction
- final def zeroGrad(): Unit
- Definition Classes
- GenericModule
Deprecated Value Members
- def finalize(): Unit
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- protected[lang]
- Definition Classes
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- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)