object RNNOutputLayer extends api.tf.learn.Layer[LSTMTuple[Float], Output[Float]]
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- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- def +(other: Layer[LSTMTuple[Float], Output[Float]]): Concatenate[LSTMTuple[Float], Output[Float]]
- Definition Classes
- Layer
- def ++(others: Seq[Layer[LSTMTuple[Float], Output[Float]]]): Concatenate[LSTMTuple[Float], Output[Float]]
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- Layer
- final def ==(arg0: Any): Boolean
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- AnyRef → Any
- def >>[S](other: Layer[Output[Float], S]): Compose[LSTMTuple[Float], Output[Float], S]
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- Layer
- def apply(input: LSTMTuple[Float])(implicit mode: Mode): Output[Float]
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- final def asInstanceOf[T0]: T0
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def compose[S](other: Layer[Output[Float], S]): Compose[LSTMTuple[Float], Output[Float], S]
- Definition Classes
- Layer
- def concatenate(others: Layer[LSTMTuple[Float], Output[Float]]*): Concatenate[LSTMTuple[Float], Output[Float]]
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- Layer
- final def currentStep: Output[Long]
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- final def eq(arg0: AnyRef): Boolean
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- def equals(arg0: AnyRef): Boolean
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- def forward(input: LSTMTuple[Float])(implicit mode: Mode): Output[Float]
- Definition Classes
- Layer
- def forwardWithoutContext(input: LSTMTuple[Float])(implicit mode: api.tf.learn.Mode): Output[Float]
- Definition Classes
- RNNOutputLayer → Layer
- final def getClass(): Class[_ <: AnyRef]
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- @native() @HotSpotIntrinsicCandidate()
- def getParameter[P](name: String, shape: Shape, initializer: Initializer, regularizer: Regularizer, trainable: Boolean, reuse: Reuse, collections: Set[Key[Variable[Any]]], cachingDevice: (OpSpecification) => String)(implicit arg0: TF[P]): Output[P]
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- def hashCode(): Int
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- final def isInstanceOf[T0]: Boolean
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- val layerType: String
- Definition Classes
- RNNOutputLayer → Layer
- def map[MR](mapFn: (Output[Float]) => MR): Layer[LSTMTuple[Float], MR]
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- Layer
- val name: String
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- Layer
- final def ne(arg0: AnyRef): Boolean
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- final def wait(arg0: Long, arg1: Int): Unit
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- final def wait(arg0: Long): Unit
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