org.apache.mxnet.javaapi

sample_exponentialParam

Related Doc: package javaapi

class sample_exponentialParam extends AnyRef

This Param Object is specifically used for sample_exponential

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. sample_exponentialParam
  2. AnyRef
  3. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Instance Constructors

  1. new sample_exponentialParam(lam: NDArray)

    lam

    Lambda (rate) parameters of the distributions.

Value Members

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

    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    AnyRef → Any

  4. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  5. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef

  7. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

  8. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    AnyRef → Any

  10. def getDtype(): String

  11. def getLam(): NDArray

  12. def getOut(): mxnet.NDArray

  13. def getShape(): Shape

  14. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    AnyRef

  17. final def notify(): Unit

    Definition Classes
    AnyRef

  18. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  19. def setDtype(dtype: String): sample_exponentialParam

    dtype

    DType of the output in case this can't be inferred. Defaults to float32 if not defined (dtype=None).

  20. def setOut(out: NDArray): sample_exponentialParam

  21. def setShape(shape: Shape): sample_exponentialParam

    shape

    Shape to be sampled from each random distribution.

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

    Definition Classes
    AnyRef

  23. def toString(): String

    Definition Classes
    AnyRef → Any

  24. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from AnyRef

Inherited from Any

Ungrouped