Object/Class

com.github.nearbydelta.deepspark.data

Weight

Related Docs: class Weight | package data

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object Weight extends Serializable

Companion object for Weight. This class adjusts clipping behavior.

For more information, see the paper, On the difficulty of training recurrent neural networks by Pascanu et al., 2013.

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  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 check[K, X <: Tensor[K, Double]](x: X)(implicit normImpl: breeze.linalg.norm.Impl[X, Double], mul: breeze.linalg.operators.OpMulScalar.Impl2[X, Double, X]): X

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    Check scale, and do scaling down if required.

    Check scale, and do scaling down if required.

    x

    Target value

    returns

    Scaled down value.

  6. def clearInvalid[K, X <: Tensor[K, Double]](x: X, resetNaN: Double = 0.0): Unit

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  7. def clone(): AnyRef

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

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. def scaleCheck(x: Matrix): Matrix

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  18. def scaleCheck(x: DataVec): DataVec

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  19. def scalingDownBy(thr: Double): Unit

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    Set scaling down threshold.

    Set scaling down threshold.

    thr

    Threshold for scalind down.

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

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  21. def toString(): String

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  22. final def wait(): Unit

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

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

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