Object

com.thoughtworks.deeplearning.DifferentiableDouble

Optimizers

Related Doc: package DifferentiableDouble

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object Optimizers

Optimizers of Double.

Example: 

  1. implicit val optimizerFactory = new DifferentiableDouble.OptimizerFactory {
  override def doubleOptimizer(weight: Weight): Optimizer = {
    new LearningRate with L2Regularization {
      var learningRate = 0.00003
      override protected def l2Regularization: Double = 0.003
      override protected def currentLearningRate(): Double = {
      learningRate * 0.75
      learningRate
     }
   }
 }
}
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Content Hierarchy
L2RegularizationL1RegularizationLearningRateOptimizer
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Type Members

  1. trait L1Regularization extends Optimizer

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  2. trait L2Regularization extends Optimizer

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  3. trait LearningRate extends Optimizer

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  4. trait Optimizer extends AnyRef

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Value Members

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

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  2. final def ##(): Int

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

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  16. def toString(): String

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  17. final def wait(): Unit

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

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

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