trait OptimMethod[T] extends Serializable

Similar to torch Optim method, which is used to update the parameter

Linear Supertypes
Serializable, Serializable, AnyRef, Any
Known Subclasses
Adadelta, Adagrad, Adam, Adamax, Ftrl, LBFGS, LarsSGD, ParallelAdam, RMSprop, SGD
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Inherited
  1. OptimMethod
  2. Serializable
  3. Serializable
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Visibility
  1. Public
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Abstract Value Members

  1. abstract def clearHistory(): Unit

    Clear the history information in the OptimMethod state

  2. abstract def getLearningRate(): Double

    get learning rate

  3. abstract def loadFromTable(config: Table): OptimMethod.this.type

    load optimMethod parameters from Table

  4. abstract def optimize(feval: (Tensor[T]) ⇒ (T, Tensor[T]), parameter: Tensor[T]): (Tensor[T], Array[T])

    Optimize the model parameter

    Optimize the model parameter

    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

    returns

    the new x vector and the function list, evaluated before the update

Concrete 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(): OptimMethod[T]

    clone OptimMethod

    clone OptimMethod

    Definition Classes
    OptimMethod → AnyRef
  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
    Annotations
    @native()
  10. def getHyperParameter(): String

    Get hyper parameter from config table.

  11. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  13. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  15. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  16. def save(path: String, overWrite: Boolean = false): OptimMethod.this.type

    save OptimMethod

    save OptimMethod

    path

    path

    overWrite

    whether to overwrite

  17. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  18. def toString(): String
    Definition Classes
    AnyRef → Any
  19. def updateHyperParameter(): Unit

    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.

    returns

    A string.

  20. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )

Deprecated Value Members

  1. def clearHistory(state: Table): Table

    Clear the history information in the state

    Clear the history information in the state

    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Please use clearHistory() instead

  2. def getHyperParameter(config: Table): String

    Get hyper parameter from config table.

    Get hyper parameter from config table.

    config

    a table contains the hyper parameter.

    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Please use getHyperParameter() instead

  3. def optimize(feval: (Tensor[T]) ⇒ (T, Tensor[T]), parameter: Tensor[T], config: Table, state: Table = null): (Tensor[T], Array[T])

    Optimize the model parameter

    Optimize the model parameter

    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 configuration parameters for the optimizer

    state

    a table describing the state of the optimizer; after each call the state is modified

    returns

    the new x vector and the function list, evaluated before the update

    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Please initialize OptimMethod with parameters when creating it instead of importing table

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

    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.

    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Please use updateHyperParameter() instead

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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