OptimMethod

Abstract Value Members

abstract def clearHistory(): Unit

Clear the history information in the OptimMethod state
Clear the history information in the OptimMethod state
returns
abstract def getLearningRate(): Double

get learning rate
get learning rate
returns
abstract def loadFromTable(config: Table): OptimMethod.this.type

load optimMethod parameters from Table
load optimMethod parameters from Table
config
returns
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

final def !=(arg0: AnyRef): Boolean

Definition Classes
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final def !=(arg0: Any): Boolean

Definition Classes
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final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: AnyRef): Boolean

Definition Classes
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final def ==(arg0: Any): Boolean

Definition Classes
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final def asInstanceOf[T0]: T0

Definition Classes
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def clone(): OptimMethod[T]

clone OptimMethod
clone OptimMethod
returns

Definition Classes
OptimMethod → AnyRef
final def eq(arg0: AnyRef): Boolean

Definition Classes
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def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
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Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
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def getHyperParameter(): String

Get hyper parameter from config table.
def hashCode(): Int

Definition Classes
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final def isInstanceOf[T0]: Boolean

Definition Classes
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final def ne(arg0: AnyRef): Boolean

Definition Classes
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final def notify(): Unit

Definition Classes
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final def notifyAll(): Unit

Definition Classes
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def save(path: String, overWrite: Boolean = false): OptimMethod.this.type

save OptimMethod
save OptimMethod
path
path
overWrite
whether to overwrite
returns
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
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.
final def wait(): Unit

Definition Classes
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Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
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Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Deprecated Value Members

def clearHistory(state: Table): Table

Clear the history information in the state
Clear the history information in the state
state
returns

Annotations
@deprecated
Deprecated
(Since version 0.2.0) Please use clearHistory() instead
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
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
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

trait OptimMethod[T] extends Serializable

Abstract Value Members

abstract def clearHistory(): Unit

abstract def getLearningRate(): Double

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

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

Concrete Value Members

final def !=(arg0: AnyRef): Boolean

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: AnyRef): Boolean

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): OptimMethod[T]

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def getHyperParameter(): String

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def save(path: String, overWrite: Boolean = false): OptimMethod.this.type

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

def toString(): String

def updateHyperParameter(): Unit

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Deprecated Value Members

def clearHistory(state: Table): Table

def getHyperParameter(config: Table): String

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

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

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped