Class

com.thoughtworks.deeplearning.DifferentiableAny

AnyLayerOps

Related Doc: package DifferentiableAny

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final class AnyLayerOps[Input <: Tape, OutputData, OutputDelta] extends AnyRef

A helper that contains common operations for any layers.

Example: 

  1. import com.thoughtworks.deeplearning.DifferentiableAny._
(input:INDArray @Symbolic).compose(anotherLayer)
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Inherited
  1. AnyLayerOps
  2. AnyRef
  3. Any
Implicitly
  1. by toAnyLayerOps
  2. by any2stringadd
  3. by StringFormat
  4. by Ensuring
  5. by ArrowAssoc
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  1. Public
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Instance Constructors

  1. new AnyLayerOps(anyLayer: Aux[Input, Aux[OutputData, OutputDelta]])

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. def +(other: String): String

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to any2stringadd[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method any2stringadd in scala.Predef.
    Definition Classes
    any2stringadd

  4. def ->[B](y: B): (AnyLayerOps[Input, OutputData, OutputDelta], B)

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to ArrowAssoc[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc
    Annotations
    @inline()

  5. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  8. def compose[NewInput <: Tape](g: Aux[NewInput, Input]): Aux[NewInput, Aux[OutputData, OutputDelta]]

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    [use case]

    [use case]
    Full Signature

    def compose[G, NewInput <: Tape, InputData, InputDelta](g: G)(implicit toLayer: Aux[G, NewInput, InputData, InputDelta], toInput: <:<[Aux[NewInput, Aux[InputData, InputDelta]], Aux[NewInput, Input]]): Aux[NewInput, Aux[OutputData, OutputDelta]]

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit thisLayer: INDArray @Symbolic)(anotherLayer: INDArray @Symbolic) = {
  thisLayer.compose(anotherLayer)

  9. def ensuring(cond: (AnyLayerOps[Input, OutputData, OutputDelta]) ⇒ Boolean, msg: ⇒ Any): AnyLayerOps[Input, OutputData, OutputDelta]

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to Ensuring[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  10. def ensuring(cond: (AnyLayerOps[Input, OutputData, OutputDelta]) ⇒ Boolean): AnyLayerOps[Input, OutputData, OutputDelta]

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to Ensuring[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  11. def ensuring(cond: Boolean, msg: ⇒ Any): AnyLayerOps[Input, OutputData, OutputDelta]

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to Ensuring[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  12. def ensuring(cond: Boolean): AnyLayerOps[Input, OutputData, OutputDelta]

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to Ensuring[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  13. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  15. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  16. def formatted(fmtstr: String): String

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to StringFormat[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method StringFormat in scala.Predef.
    Definition Classes
    StringFormat
    Annotations
    @inline()

  17. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any

  18. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  19. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  20. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  21. final def notify(): Unit

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    Definition Classes
    AnyRef

  22. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  23. def predict[InputData, InputDelta](inputData: InputData)(implicit ev: <:<[Aux[Input, Aux[OutputData, OutputDelta]], Aux[Aux[InputData, InputDelta], Aux[OutputData, OutputDelta]]]): OutputData

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    Returns the result of inputData's forward.

    Returns the result of inputData's forward.

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit inputData: INDArray @Symbolic) = ???
val predictor = composeNetwork
predictor.predict(testData)

  24. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  25. def toString(): String

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    Definition Classes
    AnyRef → Any

  26. def train[InputData, InputDelta](inputData: InputData)(implicit ev: <:<[Aux[Input, Aux[OutputData, OutputDelta]], Aux[Aux[InputData, InputDelta], Aux[OutputData, OutputDelta]]], outputDataIsOutputDelta: Trainable[OutputData, OutputDelta]): OutputData

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    Updates those weights embedded in anyLayer according to the result of inputData's backward.

    Updates those weights embedded in anyLayer according to the result of inputData's backward.

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit input: INDArray @Symbolic) = ???
val yourNetwork=composeNetwork
yourNetwork.train(testData)

  27. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  28. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  29. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  30. def withOutputDataHook(hook: (OutputData) ⇒ Unit): Aux[Input, Aux[OutputData, OutputDelta]]

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    Returns a new Layer which is a wrapper of result of anyLayer's forward and will invoke hook(anyLayer.forward(input).value).

    Returns a new Layer which is a wrapper of result of anyLayer's forward and will invoke hook(anyLayer.forward(input).value). In DeepLearning.Scala, operation is not immediately run, but first filled the network with placeholders, until the entire network is running, the real data will replace placeholders. So if you want to know some layers's intermediate state, you need to use withOutputDataHook.

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
(var:INDArray @Symbolic).withOutputDataHook{ data => println(data) }

  31. def →[B](y: B): (AnyLayerOps[Input, OutputData, OutputDelta], B)

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    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to ArrowAssoc[AnyLayerOps[Input, OutputData, OutputDelta]] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc

Shadowed Implicit Value Members

  1. def compose[NewInput <: Tape](g: Aux[NewInput, Input]): Aux[NewInput, Aux[OutputData, OutputDelta]]

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    [use case]

    [use case]
    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to AnyLayerOps[Input, OutputData, OutputDelta] performed by method toAnyLayerOps in com.thoughtworks.deeplearning.DifferentiableAny. This conversion will take place only if an implicit value of type Aux[AnyLayerOps[Input, OutputData, OutputDelta], Input, OutputData, OutputDelta] is in scope.
    Shadowing
    This implicitly inherited member is shadowed by one or more members in this class.
    To access this member you can use a type ascription:
    (anyLayerOps: AnyLayerOps[Input, OutputData, OutputDelta]).compose(g)
    Full Signature

    def compose[G, NewInput <: Tape, InputData, InputDelta](g: G)(implicit toLayer: Aux[G, NewInput, InputData, InputDelta], toInput: <:<[Aux[NewInput, Aux[InputData, InputDelta]], Aux[NewInput, Input]]): Aux[NewInput, Aux[OutputData, OutputDelta]]

    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit thisLayer: INDArray @Symbolic)(anotherLayer: INDArray @Symbolic) = {
  thisLayer.compose(anotherLayer)

  2. def predict[InputData, InputDelta](inputData: InputData)(implicit ev: <:<[Aux[Input, Aux[OutputData, OutputDelta]], Aux[Aux[InputData, InputDelta], Aux[OutputData, OutputDelta]]]): OutputData

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    Returns the result of inputData's forward.

    Returns the result of inputData's forward.

    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to AnyLayerOps[Input, OutputData, OutputDelta] performed by method toAnyLayerOps in com.thoughtworks.deeplearning.DifferentiableAny. This conversion will take place only if an implicit value of type Aux[AnyLayerOps[Input, OutputData, OutputDelta], Input, OutputData, OutputDelta] is in scope.
    Shadowing
    This implicitly inherited member is shadowed by one or more members in this class.
    To access this member you can use a type ascription:
    (anyLayerOps: AnyLayerOps[Input, OutputData, OutputDelta]).predict(inputData)(ev)
    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit inputData: INDArray @Symbolic) = ???
val predictor = composeNetwork
predictor.predict(testData)

  3. def train[InputData, InputDelta](inputData: InputData)(implicit ev: <:<[Aux[Input, Aux[OutputData, OutputDelta]], Aux[Aux[InputData, InputDelta], Aux[OutputData, OutputDelta]]], outputDataIsOutputDelta: Trainable[OutputData, OutputDelta]): OutputData

    Permalink

    Updates those weights embedded in anyLayer according to the result of inputData's backward.

    Updates those weights embedded in anyLayer according to the result of inputData's backward.

    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to AnyLayerOps[Input, OutputData, OutputDelta] performed by method toAnyLayerOps in com.thoughtworks.deeplearning.DifferentiableAny. This conversion will take place only if an implicit value of type Aux[AnyLayerOps[Input, OutputData, OutputDelta], Input, OutputData, OutputDelta] is in scope.
    Shadowing
    This implicitly inherited member is shadowed by one or more members in this class.
    To access this member you can use a type ascription:
    (anyLayerOps: AnyLayerOps[Input, OutputData, OutputDelta]).train(inputData)(ev, outputDataIsOutputDelta)
    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit input: INDArray @Symbolic) = ???
val yourNetwork=composeNetwork
yourNetwork.train(testData)

  4. def withOutputDataHook(hook: (OutputData) ⇒ Unit): Aux[Input, Aux[OutputData, OutputDelta]]

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    Returns a new Layer which is a wrapper of result of anyLayer's forward and will invoke hook(anyLayer.forward(input).value).

    Returns a new Layer which is a wrapper of result of anyLayer's forward and will invoke hook(anyLayer.forward(input).value). In DeepLearning.Scala, operation is not immediately run, but first filled the network with placeholders, until the entire network is running, the real data will replace placeholders. So if you want to know some layers's intermediate state, you need to use withOutputDataHook.

    Implicit information
    This member is added by an implicit conversion from AnyLayerOps[Input, OutputData, OutputDelta] to AnyLayerOps[Input, OutputData, OutputDelta] performed by method toAnyLayerOps in com.thoughtworks.deeplearning.DifferentiableAny. This conversion will take place only if an implicit value of type Aux[AnyLayerOps[Input, OutputData, OutputDelta], Input, OutputData, OutputDelta] is in scope.
    Shadowing
    This implicitly inherited member is shadowed by one or more members in this class.
    To access this member you can use a type ascription:
    (anyLayerOps: AnyLayerOps[Input, OutputData, OutputDelta]).withOutputDataHook(hook)
    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
(var:INDArray @Symbolic).withOutputDataHook{ data => println(data) }

Inherited from AnyRef

Inherited from Any

Inherited by implicit conversion toAnyLayerOps from AnyLayerOps[Input, OutputData, OutputDelta] to AnyLayerOps[Input, OutputData, OutputDelta]

Inherited by implicit conversion any2stringadd from AnyLayerOps[Input, OutputData, OutputDelta] to any2stringadd[AnyLayerOps[Input, OutputData, OutputDelta]]

Inherited by implicit conversion StringFormat from AnyLayerOps[Input, OutputData, OutputDelta] to StringFormat[AnyLayerOps[Input, OutputData, OutputDelta]]

Inherited by implicit conversion Ensuring from AnyLayerOps[Input, OutputData, OutputDelta] to Ensuring[AnyLayerOps[Input, OutputData, OutputDelta]]

Inherited by implicit conversion ArrowAssoc from AnyLayerOps[Input, OutputData, OutputDelta] to ArrowAssoc[AnyLayerOps[Input, OutputData, OutputDelta]]

Ungrouped