Class

com.intel.analytics.bigdl.optim

Adam

Related Doc: package optim

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class Adam[T] extends OptimMethod[T]

Linear Supertypes
OptimMethod[T], Serializable, Serializable, AnyRef, Any
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Instance Constructors

  1. new Adam()(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

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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 clearHistory(state: Table): Table

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    Clear the history information in the state

    Clear the history information in the state

    Definition Classes
    AdamOptimMethod
  6. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  10. final def getClass(): Class[_]

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  11. def getHyperParameter(config: Table): String

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    Get hyper parameter from config table.

    Get hyper parameter from config table.

    config

    a table contains the hyper parameter.

    Definition Classes
    OptimMethod
  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 optimize(feval: (Tensor[T]) ⇒ (T, Tensor[T]), parameter: Tensor[T], config: Table, state: Table): (Tensor[T], Array[T])

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    An implementation of Adam http://arxiv.org/pdf/1412.6980.pdf

    An implementation of Adam http://arxiv.org/pdf/1412.6980.pdf

    feval

    a function that takes a single input (X), the point of a evaluation, and returns f(X) and df/dX

    parameter

    the initial point

    config

    a table with hyper-parameters for the optimizer config("learningRate") : learning rate config("learningRateDecay") : learning rate decay config("beta1") : first moment coefficient config("beta2") : second moment coefficient config("Epsilon"): for numerical stability

    state

    a table describing the state of the optimizer; after each call the state is modified state("s") : 1st moment variables state("r"): 2nd moment variables state("denom"): A tmp tensor to hold the sqrt(v) + epsilon

    returns

    the new x vector and the function list {fx}, evaluated before the update

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

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  19. def toString(): String

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  20. def updateHyperParameter(config: Table, state: Table): Unit

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    Update hyper parameter.

    Update hyper parameter. We have updated hyper parameter in method optimize(). But in DistriOptimizer, the method optimize() is only called on the executor side, the driver's hyper parameter is unchanged. So this method is using to update hyper parameter on the driver side.

    config

    config table.

    state

    state Table.

    returns

    A string.

    Definition Classes
    OptimMethod
  21. final def wait(): Unit

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    @throws( ... )
  22. final def wait(arg0: Long, arg1: Int): Unit

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

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Inherited from OptimMethod[T]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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