p

com.thoughtworks

deeplearning

package deeplearning

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Type Members

  1. trait BufferedLayer extends Layer

    Author:

    杨博 (Yang Bo) <[email protected]>

  2. trait Layer extends AnyRef

    The layer of DeepLearning.Scala is similar to the layer of neural networks ,But there are some details is difference The layer in the neural networks means a layer of network, but the layer in DeepLearning.Scala means a operation, many operations could also compose together to be one layer(at this time , layer is means layer of neural networks).

    The layer of DeepLearning.Scala is similar to the layer of neural networks ,But there are some details is difference The layer in the neural networks means a layer of network, but the layer in DeepLearning.Scala means a operation, many operations could also compose together to be one layer(at this time , layer is means layer of neural networks). Every operation in DeepLearning.Scala is a layer. Every layer contains input,output and forward.

  3. trait Symbolic [NativeOutput] extends AnyRef
    Annotations
    @implicitNotFound( ... )

Value Members

  1. object BufferedLayer
  2. object DifferentiableAny

    Author:

    杨博 (Yang Bo) <[email protected]>

  3. object DifferentiableBoolean

    Author:

    杨博 (Yang Bo) <[email protected]>

  4. object DifferentiableCoproduct

    Author:

    杨博 (Yang Bo) <[email protected]>

  5. object DifferentiableDouble

    Author:

    杨博 (Yang Bo) <[email protected]>

  6. object DifferentiableFloat

    Author:

    杨博 (Yang Bo) <[email protected]>

  7. object DifferentiableHList

    Author:

    杨博 (Yang Bo) <[email protected]>

  8. object DifferentiableInt

    Author:

    杨博 (Yang Bo) <[email protected]>

  9. object DifferentiableNothing

    Author:

    杨博 (Yang Bo) <[email protected]>

  10. object DifferentiableSeq

    Author:

    杨博 (Yang Bo) <[email protected]>

  11. object Layer
  12. object Poly

    Author:

    杨博 (Yang Bo) <[email protected]>

  13. object Symbolic extends LowPrioritySymbolic

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