Trait

com.thoughtworks.deeplearning.DifferentiableAny

Trainable

Related Doc: package DifferentiableAny

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trait Trainable[-Data, +Delta] extends AnyRef

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  1. Trainable
  2. AnyRef
  3. Any
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  1. by toAnyLayerOps
  2. by any2stringadd
  3. by StringFormat
  4. by Ensuring
  5. by ArrowAssoc
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Abstract Value Members

  1. abstract def apply(data: Data): Delta

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Concrete 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 Trainable[Data, Delta] to any2stringadd[Trainable[Data, Delta]] performed by method any2stringadd in scala.Predef.
    Definition Classes
    any2stringadd

  4. def ->[B](y: B): (Trainable[Data, Delta], B)

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    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] to ArrowAssoc[Trainable[Data, Delta]] 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[G, NewInput <: Batch, 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]]

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    Returns a Layer that accepts another layer's output as input of this layer

    Returns a Layer that accepts another layer's output as input of this layer

    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] 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[Trainable[Data, Delta], Input, OutputData, OutputDelta] is in scope.
    Definition Classes
    AnyLayerOps
    Example: 

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

  9. def ensuring(cond: (Trainable[Data, Delta]) ⇒ Boolean, msg: ⇒ Any): Trainable[Data, Delta]

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    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] to Ensuring[Trainable[Data, Delta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  10. def ensuring(cond: (Trainable[Data, Delta]) ⇒ Boolean): Trainable[Data, Delta]

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    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] to Ensuring[Trainable[Data, Delta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  11. def ensuring(cond: Boolean, msg: ⇒ Any): Trainable[Data, Delta]

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    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] to Ensuring[Trainable[Data, Delta]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring

  12. def ensuring(cond: Boolean): Trainable[Data, Delta]

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    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] to Ensuring[Trainable[Data, Delta]] 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 Trainable[Data, Delta] to StringFormat[Trainable[Data, Delta]] 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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    Return a Layer that accepts input and will only forward.

    Return a Layer that accepts input and will only forward. If you want to test the accuracy of network assertions, you can not let your network backward, then you need to use predict.

    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] 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[Trainable[Data, Delta], Input, OutputData, OutputDelta] is in scope.
    Definition Classes
    AnyLayerOps
    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
def composeNetwork(implicit input: 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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    Return a Layer that accepts input and will forward & backward.

    Return a Layer that accepts input and will forward & backward. If you want to train your network,you need your network backward, then you need to use train.

    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] 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[Trainable[Data, Delta], Input, OutputData, OutputDelta] is in scope.
    Definition Classes
    AnyLayerOps
    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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    In DeepLearning.Scala,operation is not immediately run, but first filled with placeholders, the entire network will be running ,then the real data will come into networks.

    In DeepLearning.Scala,operation is not immediately run, but first filled with placeholders, the entire network will be running ,then the real data will come into networks. So if you want to see some vars's intermediate state,you need to use withOutputDataHook.

    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] 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[Trainable[Data, Delta], Input, OutputData, OutputDelta] is in scope.
    Definition Classes
    AnyLayerOps
    Example: 

    1. import com.thoughtworks.deeplearning.DifferentiableAny._
(var:From[INDArray]##`@`).withOutputDataHook{ data => println(data) }

  31. def →[B](y: B): (Trainable[Data, Delta], B)

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    Implicit information
    This member is added by an implicit conversion from Trainable[Data, Delta] to ArrowAssoc[Trainable[Data, Delta]] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc

Inherited from AnyRef

Inherited from Any

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

Inherited by implicit conversion any2stringadd from Trainable[Data, Delta] to any2stringadd[Trainable[Data, Delta]]

Inherited by implicit conversion StringFormat from Trainable[Data, Delta] to StringFormat[Trainable[Data, Delta]]

Inherited by implicit conversion Ensuring from Trainable[Data, Delta] to Ensuring[Trainable[Data, Delta]]

Inherited by implicit conversion ArrowAssoc from Trainable[Data, Delta] to ArrowAssoc[Trainable[Data, Delta]]

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