Packages

  • package root
    Definition Classes
    root
  • package com
    Definition Classes
    root
  • package thoughtworks
    Definition Classes
    com
  • package deeplearning

    This is the documentation for the DeepLearning.Scala

    This is the documentation for the DeepLearning.Scala

    Overview

    BufferedLayer, DifferentiableAny, DifferentiableNothing, Layer, Poly and Symbolic are base packages which contains necessary operations , all other packages dependent on those base packages.

    If you want to implement a layer, you need to know how to use base packages.

    Imports guidelines

    If you want use some operations of Type T, you should import:

    import com.thoughtworks.deeplearning.DifferentiableT._

    it means: If you want use some operations of INDArray, you should import:

    import com.thoughtworks.deeplearning.DifferentiableINDArray._

    If you write something like this:

    def softmax(implicit scores: INDArray @Symbolic): INDArray @Symbolic = {
  val expScores = exp(scores)
  expScores / expScores.sum(1)
}

    If compiler shows error :

    Could not infer implicit value for com.thoughtworks.deeplearning.Symbolic[org.nd4j.linalg.api.ndarray.INDArray]

    you need add import this time :

    import com.thoughtworks.deeplearning.DifferentiableINDArray._

    If you write something like this:

    def crossEntropyLossFunction(
  implicit pair: (INDArray :: INDArray :: HNil) @Symbolic)
: Double @Symbolic = {
 val score = pair.head
 val label = pair.tail.head
 -(label * log(score * 0.9 + 0.1) + (1.0 - label) * log(1.0 - score * 0.9)).mean
}

    If the compiler shows error:

    value * is not a member of com.thoughtworks.deeplearning.Layer.Aux[com.thoughtworks.deeplearning.Layer.Tape.Aux[org.nd4j.linalg.api.ndarray.INDArray,org.nd4j.linalg.api.ndarray.INDArray],com.thoughtworks.deeplearning.DifferentiableINDArray.INDArrayPlaceholder.Tape]val bias = Nd4j.ones(numberOfOutputKernels).toWeight * 0.1...

    you need add import :

    import com.thoughtworks.deeplearning.Poly.MathMethods.*
import com.thoughtworks.deeplearning.DifferentiableINDArray._

    If the compiler shows error:

    not found: value log -(label * log(score * 0.9 + 0.1) + (1.0 - label) * log(1.0 - score * 0.9)).mean...

    you need add import:

    import com.thoughtworks.deeplearning.Poly.MathFunctions.*
import com.thoughtworks.deeplearning.DifferentiableINDArray._

    Those + - * / and log exp abs max min are defined at MathMethods and MathFunctions，those method are been implemented at DifferentiableType，so you need to import the implicit of DifferentiableType.

    Composability

    Neural networks created by DeepLearning.scala are composable. You can create large networks by combining smaller networks. If two larger networks share some sub-networks, the weights in shared sub-networks trained with one network affect the other network.

    Definition Classes
    thoughtworks
    See also

    Compose

  • object DifferentiableSeq

    A namespace of common operators for Seq layers.

    A namespace of common operators for Seq layers.

    After importing DifferentiableSeq._, the following methods will be available on Seq layers.

    Author:

    杨博 (Yang Bo) <[email protected]>

    Definition Classes
    deeplearning
  • object Layers
    Definition Classes
    DifferentiableSeq
  • final case class ToSeq [Input0 <: Tape, ElementData, ElementDelta](operands: Seq[Aux[Input0, Aux[ElementData, ElementDelta]]]) extends Layer with Product with Serializable
    Definition Classes
    Layers
  • Output

final class Output extends Tape with CloseableOnce

Linear Supertypes
CloseableOnce, Tape, AutoCloseable, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. Output
  2. CloseableOnce
  3. Tape
  4. AutoCloseable
  5. AnyRef
  6. Any
Implicitly
  1. by toSeqLayerOps
  2. by any2stringadd
  3. by StringFormat
  4. by Ensuring
  5. by ArrowAssoc
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Visibility
  1. Public
  2. All

Type Members

  1. type Data = Seq[ElementData]

    Type of the result of forward pass.

    Type of the result of forward pass.

    Definition Classes
    Output → Tape
    See also

    value

  2. type Delta = (Int, ElementDelta)

    Type of the information passing in backward pass, usually the partial derivative of Data.

    Type of the information passing in backward pass, usually the partial derivative of Data.

    Definition Classes
    Output → Tape
    See also

    backward

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. def +(other: String): String
    Implicit
    This member is added by an implicit conversion from Output to any2stringadd[Output] performed by method any2stringadd in scala.Predef.
    Definition Classes
    any2stringadd
  4. def ->[B](y: B): (Output, B)
    Implicit
    This member is added by an implicit conversion from Output to ArrowAssoc[Output] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc
    Annotations
    @inline()
  5. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  6. def apply(i: Int): Aux[Input, Aux[ElementData, ElementDelta]]
    Implicit
    This member is added by an implicit conversion from Output to SeqLayerOps[Input, ElementData, ElementDelta] performed by method toSeqLayerOps in com.thoughtworks.deeplearning.DifferentiableSeq. This conversion will take place only if an implicit value of type Aux[Output, Input, SeqData, SeqDelta] is in scope and at the same time an implicit value of type <:<[Aux[Input, Aux[SeqData, SeqDelta]], Aux[Input, Aux[Seq[ElementData], (Int, ElementDelta)]]] is in scope.
    Definition Classes
    SeqLayerOps
  7. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  8. final def backward(delta: ⇒ Delta): Unit

    invoke forceBackward if isTrainable is true

    invoke forceBackward if isTrainable is true

    Definition Classes
    Tape
    Annotations
    @inline()
    See also

    Delta

  9. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  10. def close(): Unit
    Definition Classes
    Output → CloseableOnce → AutoCloseable
  11. def duplicate(): Output

    Returns a new Tape that shares the same value and backward behavior with this Tape.

    Returns a new Tape that shares the same value and backward behavior with this Tape.

    Definition Classes
    Output → Tape
    Note

    The newly created Tape and this Tape must be closed independently.

  12. def ensuring(cond: (Output) ⇒ Boolean, msg: ⇒ Any): Output
    Implicit
    This member is added by an implicit conversion from Output to Ensuring[Output] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  13. def ensuring(cond: (Output) ⇒ Boolean): Output
    Implicit
    This member is added by an implicit conversion from Output to Ensuring[Output] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  14. def ensuring(cond: Boolean, msg: ⇒ Any): Output
    Implicit
    This member is added by an implicit conversion from Output to Ensuring[Output] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  15. def ensuring(cond: Boolean): Output
    Implicit
    This member is added by an implicit conversion from Output to Ensuring[Output] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  16. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  17. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  18. def finalize(): Unit
    Attributes
    protected
    Definition Classes
    CloseableOnce → AnyRef
  19. def forceBackward(pair: (Int, ElementDelta)): Unit
    Attributes
    protected
    Definition Classes
    Output → Tape
  20. def formatted(fmtstr: String): String
    Implicit
    This member is added by an implicit conversion from Output to StringFormat[Output] performed by method StringFormat in scala.Predef.
    Definition Classes
    StringFormat
    Annotations
    @inline()
  21. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  22. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  23. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  24. val isTrainable: Boolean
    Definition Classes
    Output → Tape
  25. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  26. final def notify(): Unit
    Definition Classes
    AnyRef
  27. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  28. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  29. def toString(): String
    Definition Classes
    AnyRef → Any
  30. val value: Data
    Definition Classes
    Output → Tape
  31. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  33. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  34. def →[B](y: B): (Output, B)
    Implicit
    This member is added by an implicit conversion from Output to ArrowAssoc[Output] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc

Inherited from CloseableOnce

Inherited from Tape

Inherited from AutoCloseable

Inherited from AnyRef

Inherited from Any

Inherited by implicit conversion toSeqLayerOps from Output to SeqLayerOps[Input, ElementData, ElementDelta]

Inherited by implicit conversion any2stringadd from Output to any2stringadd[Output]

Inherited by implicit conversion StringFormat from Output to StringFormat[Output]

Inherited by implicit conversion Ensuring from Output to Ensuring[Output]

Inherited by implicit conversion ArrowAssoc from Output to ArrowAssoc[Output]

Ungrouped