Object

ml.dmlc.mxnet

Random

Related Doc: package mxnet

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object Random

Random Number interface of mxnet.

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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 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. def normal(loc: Float, scale: Float, shape: Shape = null, ctx: Context = null, out: NDArray = null): NDArray

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    Generate normal(Gaussian) distribution N(mean, stdvar^^2) with shape.

    Generate normal(Gaussian) distribution N(mean, stdvar^^2) with shape.

    loc

    The mean of the normal distribution.

    scale

    The standard deviation of normal distribution.

    shape

    Output shape of the NDArray generated.

    ctx

    Context of output NDArray, will use default context if not specified.

    out

    Output place holder

    returns

    The result NDArray with generated result.

  14. final def notify(): Unit

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  15. final def notifyAll(): Unit

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  16. def seed(seedState: Int): Unit

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    Seed the random number generators in mxnet.

    Seed the random number generators in mxnet.

    This seed will affect behavior of functions in this module, as well as results from executors that contains Random number such as Dropout operators.

    seedState

    The random number seed to set to all devices.

    Note

    The random number generator of mxnet is by default device specific. This means if you set the same seed, the random number sequence generated from GPU0 can be different from CPU.

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

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  18. def toString(): String

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  19. def uniform(low: Float, high: Float, shape: Shape = null, ctx: Context = null, out: NDArray = null): NDArray

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    Generate uniform distribution in [low, high) with shape.

    Generate uniform distribution in [low, high) with shape.

    low

    The lower bound of distribution.

    high

    The upper bound of distribution.

    shape

    Output shape of the NDArray generated.

    ctx

    Context of output NDArray, will use default context if not specified.

    out

    Output place holder

    returns

    The result NDArray with generated result.

  20. final def wait(): Unit

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

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

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