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
  • object Layers
    Definition Classes
    Symbolic
  • Identity
  • Literal

object Identity extends Serializable

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Serializable, Serializable, AnyRef, Any
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  1. final def !=(arg0: Any): Boolean
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  10. def hashCode(): Int
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  11. implicit def implicitlyApply[Data, Delta]: Identity[Data, Delta]
  12. implicit def inputPlaceholderToLayer[InputData, InputDelta]: Aux[Identity[InputData, InputDelta], Aux[InputData, InputDelta], InputData, InputDelta]
  13. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  14. final def ne(arg0: AnyRef): Boolean
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  15. final def notify(): Unit
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  17. final def synchronized[T0](arg0: ⇒ T0): T0
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  18. def toString(): String
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  19. final def wait(): Unit
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  20. final def wait(arg0: Long, arg1: Int): Unit
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  21. final def wait(arg0: Long): Unit
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