case class TransformerDecoderBlock(attentionDecoderDecoder: MultiheadAttention, attentionEncoderDecoder: MultiheadAttention, layerNorm1: LayerNorm, layerNorm2: LayerNorm, layerNorm3: LayerNorm, layerNorm4: LayerNorm, w1: Constant, b1: Constant, w2: Constant, b2: Constant, dropout: Double, train: Boolean) extends GenericModule[(Variable, Variable, Option[STen]), Variable] with Product with Serializable
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- TransformerDecoderBlock
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- new TransformerDecoderBlock(attentionDecoderDecoder: MultiheadAttention, attentionEncoderDecoder: MultiheadAttention, layerNorm1: LayerNorm, layerNorm2: LayerNorm, layerNorm3: LayerNorm, layerNorm4: LayerNorm, w1: Constant, b1: Constant, w2: Constant, b2: Constant, dropout: Double, train: Boolean)
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- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- def apply[S](a: (Variable, Variable, Option[STen]))(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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- val attentionDecoderDecoder: MultiheadAttention
- val attentionEncoderDecoder: MultiheadAttention
- val b1: Constant
- val b2: Constant
- def clone(): AnyRef
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- protected[lang]
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- val dropout: Double
- final def eq(arg0: AnyRef): Boolean
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- def forward[S](x: (Variable, Variable, Option[STen]))(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.
- Definition Classes
- TransformerDecoderBlock → GenericModule
- final def getClass(): Class[_ <: AnyRef]
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- @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.
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- GenericModule
- final def isInstanceOf[T0]: Boolean
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- val layerNorm1: LayerNorm
- val layerNorm2: LayerNorm
- val layerNorm3: LayerNorm
- val layerNorm4: LayerNorm
- final def learnableParameters: Long
Returns the total number of optimizable parameters.
Returns the total number of optimizable parameters.
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- GenericModule
- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- final def notifyAll(): Unit
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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: List[(Constant, LeafTag)]
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
- TransformerDecoderBlock → GenericModule
- final def synchronized[T0](arg0: => T0): T0
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- val train: Boolean
- val w1: Constant
- val w2: Constant
- final def wait(arg0: Long, arg1: Int): Unit
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- final def zeroGrad(): Unit
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- def finalize(): Unit
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- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)