Packages

  • package root
    Definition Classes
    root
  • package com
    Definition Classes
    root
  • package thoughtworks
    Definition Classes
    com
  • package deeplearning
    Definition Classes
    thoughtworks
  • object Symbolic extends LowPrioritySymbolic

    There are two ways to convert a value to Layer.

    There are two ways to convert a value to Layer.

    The first way is invoke toLayer, such as:

    def createMyNeuralNetwork(implicit input: Float @Symbolic): Float @Symbolic = {
      val floatLayer: Float @Symbolic = 1.0f.toLayer
      floatLayer
    }

    The second way is autoToLayer, such as:

    def createMyNeuralNetwork(implicit input: Float @Symbolic): Float @Symbolic = {
      val floatLayer: Float @Symbolic = 1.0f
      floatLayer
    }

    In order to compile the above code through, you will need:

    import com.thoughtworks.deeplearning.Symbolic._
    import com.thoughtworks.deeplearning.Symbolic
    import com.thoughtworks.deeplearning.DifferentiableFloat._
    Definition Classes
    deeplearning
  • Layers
  • ToLayer
  • ToLayerOps
  • ToLiteral
  • ToTapeOps

object Layers

Linear Supertypes
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Type Members

  1. final case class Identity [Data0, Delta0]() extends Layer with Product with Serializable
  2. final case class Literal [Data0](value0: Data0) extends Layer with Tape with Product with Serializable

Value Members

  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. final def asInstanceOf[T0]: T0
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  6. final def eq(arg0: AnyRef): Boolean
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  8. def finalize(): Unit
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  9. final def getClass(): Class[_]
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  10. def hashCode(): Int
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  11. final def isInstanceOf[T0]: Boolean
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  12. final def ne(arg0: AnyRef): Boolean
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  13. final def notify(): Unit
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  14. final def notifyAll(): Unit
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  15. final def synchronized[T0](arg0: ⇒ T0): T0
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  16. def toString(): String
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  17. final def wait(): Unit
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  18. final def wait(arg0: Long, arg1: Int): Unit
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  19. final def wait(arg0: Long): Unit
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  20. object Identity extends Serializable

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