GradientTester

Value Members

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

   Definition Classes

   AnyRef

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

   Definition Classes

   Any

3. final def ##(): Int

   Definition Classes

   AnyRef → Any

4. final def ==(arg0: AnyRef): Boolean

   Definition Classes

   AnyRef

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

   Definition Classes

   Any

6. final def asInstanceOf[T0]: T0

   Definition Classes

   Any

7. def clone(): AnyRef

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

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

   Definition Classes

   AnyRef

9. def equals(arg0: Any): Boolean

   Definition Classes

   AnyRef → Any

10. def finalize(): Unit

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes

    AnyRef → Any

12. def hashCode(): Int

    Definition Classes

    AnyRef → Any

13. final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

14. lazy val logger: Logger

    Attributes

    protected

    Definition Classes

    Logging

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

    Definition Classes

    AnyRef

16. final def notify(): Unit

    Definition Classes

    AnyRef

17. final def notifyAll(): Unit

    Definition Classes

    AnyRef

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

    Definition Classes

    AnyRef

19. def test[K, T](f: DiffFunction[T], x: T, randFraction: Double = 0.01, skipZeros: Boolean = false, epsilon: Double = 1E-8, tolerance: Double = 1E-3, toString: (K) ⇒ String = _:K).toString)(implicit view2: <:<[T, NumericOps[T]], view: <:<[T, Tensor[K, Double]], copy: CanCopy[T], canNorm: linalg.norm.Impl[T, Double], opSub: linalg.operators.OpSub.Impl2[T, T, T]): T

    Tests a gradient by comparing the gradient to the empirically calculated gradient from finite differences, returning those that are bad, logging bad ones on WARN, ok ones on DEBUG, and overall statistics on INFO.

    Tests a gradient by comparing the gradient to the empirically calculated gradient from finite differences, returning those that are bad, logging bad ones on WARN, ok ones on DEBUG, and overall statistics on INFO.

    K

    T

    f

    the function to test

    x

    point to test from

    randFraction

    what percentage of x's domain to try.

    skipZeros

    should we skip components of x where the calculated gradient is 0. (Sometimes useful with sparse features. You might want to check that 0's are always 0's though!)

    epsilon

    Difference to try

    tolerance

    How big a relative difference before we start complaining.

    toString

    toString function for converting elements of x's domain to a string.

    returns

    differences in each component

20. def testIndices[T, K](f: DiffFunction[T], x: T, indices: Traversable[K], skipZeros: Boolean = false, toString: (K) ⇒ String = _:K).toString, epsilon: Double = 1e-8, tolerance: Double = 1E-3)(implicit view2: <:<[T, NumericOps[T]], view: <:<[T, Tensor[K, Double]], copy: CanCopy[T], canNorm: linalg.norm.Impl[T, Double], opSub: linalg.operators.OpSub.Impl2[T, T, T]): T

21. def toString(): String

    Definition Classes

    AnyRef → Any

22. final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )