class SGD[T] extends OptimMethod[T]
A plain implementation of SGD
- Alphabetic
- By Inheritance
- SGD
- OptimMethod
- Serializable
- Serializable
- AnyRef
- Any
- Hide All
- Show All
- Public
- All
Instance Constructors
-
new
SGD(learningRate: Double = 1e-3, learningRateDecay: Double = 0.0, weightDecay: Double = 0.0, momentum: Double = 0.0, dampening: Double = Double.MaxValue, nesterov: Boolean = false, learningRateSchedule: LearningRateSchedule = Default(), learningRates: Tensor[T] = null, weightDecays: Tensor[T] = null)(implicit arg0: ClassTag[T], ev: TensorNumeric[T])
- learningRate
learning rate
- learningRateDecay
learning rate decay
- weightDecay
weight decay
- momentum
momentum
- dampening
dampening for momentum
- nesterov
enables Nesterov momentum
- learningRates
1D tensor of individual learning rates
- weightDecays
1D tensor of individual weight decays
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
clearHistory(): Unit
Clear the history information in the OptimMethod state
Clear the history information in the OptimMethod state
- Definition Classes
- SGD → OptimMethod
-
def
clone(): OptimMethod[T]
clone OptimMethod
clone OptimMethod
- Definition Classes
- OptimMethod → AnyRef
- var dampening: Double
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
equals(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
def
finalize(): Unit
- Attributes
- protected[java.lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
def
getHyperParameter(config: Table): String
return an string of current hyperParameter.
return an string of current hyperParameter.
- config
a table contains the hyper parameter.
- Definition Classes
- SGD → OptimMethod
-
def
getHyperParameter(): String
return an string of current hyperParameter.
return an string of current hyperParameter.
- Definition Classes
- SGD → OptimMethod
-
def
getLearningRate(): Double
get learning rate
get learning rate
- Definition Classes
- SGD → OptimMethod
-
def
hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- var learningRate: Double
- var learningRateDecay: Double
- var learningRateSchedule: LearningRateSchedule
- var learningRates: Tensor[T]
-
def
loadFromTable(config: Table): SGD.this.type
load optimMethod parameters from Table
load optimMethod parameters from Table
- Definition Classes
- SGD → OptimMethod
- var momentum: Double
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- var nesterov: Boolean
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
def
optimize(feval: (Tensor[T]) ⇒ (T, Tensor[T]), x: Tensor[T]): (Tensor[T], Array[T])
- feval
a function that takes a single input (X), the point of a evaluation, and returns f(X) and df/dX
- x
the initial point
- returns
the new x 1D tensor and the function list, evaluated before the update
- Definition Classes
- SGD → OptimMethod
-
def
save(path: String, overWrite: Boolean = false): SGD.this.type
save OptimMethod
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
def
toString(): String
- Definition Classes
- AnyRef → Any
-
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.
- Definition Classes
- SGD → OptimMethod
-
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.
- Definition Classes
- SGD → OptimMethod
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @throws( ... )
- var weightDecay: Double
- var weightDecays: Tensor[T]
Deprecated Value Members
-
def
clearHistory(state: Table): Table
Clear the history information in the state
Clear the history information in the state
- Definition Classes
- OptimMethod
- Annotations
- @deprecated
- Deprecated
(Since version 0.2.0) Please use clearHistory() 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
- Definition Classes
- OptimMethod
- Annotations
- @deprecated
- Deprecated
(Since version 0.2.0) Please initialize OptimMethod with parameters when creating it instead of importing table