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- def charsToIntegers(text: String, chars: Map[Char, Int]): Vector[Int]
- def charsToIntegers(text: String): (Map[Char, Int], Vector[Int])
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- def convertIntegersToText(tensor: STen, vocab: Map[Int, Char]): Seq[String]
Convert back to text.
Convert back to text. Tensor shape: time x batch
- def convertLogitsToText(tensor: STen, vocab: Map[Int, Char])(implicit scope: Scope): Seq[String]
Convert back to text.
Convert back to text. Tensor shape: time x batch x dim
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- def makePredictionBatch(examples: Seq[Vector[Long]], device: Device)(implicit scope: Scope): Variable
- def minibatchesFromText(text: Vector[Int], minibatchSize: Int, timeSteps: Int, rng: Random): BatchStream[(Constant, STen), Int, Unit]
Yields tensors of shape (time step x batch size)
- final def ne(arg0: AnyRef): Boolean
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- def sentenceToPaddedVec(sentence: String, maxLength: Int, pad: Int, vocabulary: Map[Char, Int]): Array[Int]
- def sentencesToPaddedMatrix(sentences: Seq[String], maxLength: Int, pad: Int, vocabulary: Map[Char, Int]): Seq[Array[Int]]
- def sequencePrediction[T, M <: StatefulModule[Variable, Variable, T]](batch: Seq[Vector[Long]], device: Device, module: M with StatefulModule[Variable, Variable, T], steps: Int)(implicit is: InitState[M, T], scope: Scope): STen
- def sequencePredictionBeam[T, M <: StatefulModule[Variable, Variable, T]](prefix: Vector[Long], device: Device, module: M with StatefulModule[Variable, Variable, T], steps: Int, startSequence: Int, endOfSequence: Int)(implicit is: InitState[M, T], scope: Scope): Seq[(STen, Double)]
- final def synchronized[T0](arg0: => T0): T0
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- def wordsToIntegers(text: String, minimumTokenId: Int, minimumFrequency: Int): (Array[Int], Map[String, Int])
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- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)