FlexibleTrainer

Instance Constructors

new FlexibleTrainer(network: Network[IN, OUT], objective: Objective, expectConverter: (OUT) ⇒ DataVec, trainSet: RDD[(IN, OUT)], testSet: RDD[(IN, OUT)], name: String, param: TrainingParam)(implicit arg0: ClassTag[IN], arg1: ClassTag[OUT])

network
Network
objective
Objective function
expectConverter
Function to convert real output into vector
trainSet
Train set
testSet
Evaluation set
name
Name of trainer
param
Training parameter

Type Members

class LocalSampler extends Iterator[Seq[(IN, EXP)]]

Sampling iterator, from local
Sampling iterator, from local

Definition Classes
Trainer
class RDDSampler extends Iterator[Seq[(IN, EXP)]]

Sampling iterator, from RDD
Sampling iterator, from RDD

Definition Classes
Trainer

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
val batchSampler: Iterator[Seq[(IN, OUT)]]

Sampler for mini-batch
Sampler for mini-batch

Attributes
protected
Definition Classes
Trainer
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
implicit val evidence$1: ClassTag[IN]

class tag of input
class tag of input

Definition Classes
FlexibleTrainer → Trainer
implicit val evidence$2: ClassTag[OUT]

class tag of output
class tag of output

Definition Classes
FlexibleTrainer → Trainer
implicit val evidence$3: ClassTag[OUT]

Class tag of network output
Class tag of network output

Definition Classes
FlexibleTrainer → Trainer
val expectConverter: (OUT) ⇒ DataVec

Function to convert real output into vector
val file: File

Temporary file path of network
Temporary file path of network

Attributes
protected
Definition Classes
Trainer
def finalize(): Unit

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

Definition Classes
AnyRef → Any
final def getMaxEpoch(epoch: Int, patience: Int): Int

Get next maximum epoch.
Get next maximum epoch.
epoch
Current epoch
patience
Current maximum iteration count
returns
maximum epoch

Attributes
protected
Definition Classes
Trainer
def getStatus: (Int, Double, Double)

Definition Classes
Trainer
final def getTrainedNetwork: Network[IN, OUT]

Train using given RDD sequence.
Train using given RDD sequence.

Definition Classes
Trainer
def getValidationErr: (Double, Double)

Calculate validation error of evaluation set
Calculate validation error of evaluation set
returns
Evaluation loss

Attributes
protected
Definition Classes
FlexibleTrainer → Trainer
def hashCode(): Int

Definition Classes
AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val logfile: File

Attributes
protected
Definition Classes
Trainer
val logger: Logger

Logger
Logger

Attributes
protected
Definition Classes
Trainer
val name: String

Name of trainer
Name of trainer

Definition Classes
FlexibleTrainer → Trainer
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
var network: Network[IN, OUT]

Network
Network

Definition Classes
FlexibleTrainer → Trainer
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val objective: Objective

Objective function
Objective function

Definition Classes
FlexibleTrainer → Trainer
val param: TrainingParam

Training parameter
Training parameter

Definition Classes
FlexibleTrainer → Trainer
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val testSet: RDD[(IN, OUT)]

Evaluation set
Evaluation set

Definition Classes
FlexibleTrainer → Trainer
def toString(): String

Definition Classes
AnyRef → Any
val trainSet: RDD[(IN, OUT)]

Train set
Train set

Definition Classes
FlexibleTrainer → Trainer
final def trainSmallBatch(epoch: Int, patience: Int): Unit

Train single small batch
Train single small batch
epoch
current epoch
patience
current max iteration

Attributes
protected
Definition Classes
FlexibleTrainer → Trainer
Annotations
@tailrec()
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
@throws( ... )

Related Doc: package train

class FlexibleTrainer[IN, OUT] extends Trainer[IN, OUT, OUT]

Instance Constructors

new FlexibleTrainer(network: Network[IN, OUT], objective: Objective, expectConverter: (OUT) ⇒ DataVec, trainSet: RDD[(IN, OUT)], testSet: RDD[(IN, OUT)], name: String, param: TrainingParam)(implicit arg0: ClassTag[IN], arg1: ClassTag[OUT])

Type Members

class LocalSampler extends Iterator[Seq[(IN, EXP)]]

class RDDSampler extends Iterator[Seq[(IN, EXP)]]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

val batchSampler: Iterator[Seq[(IN, OUT)]]

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

implicit val evidence$1: ClassTag[IN]

implicit val evidence$2: ClassTag[OUT]

implicit val evidence$3: ClassTag[OUT]

val expectConverter: (OUT) ⇒ DataVec

val file: File

def finalize(): Unit

final def getClass(): Class[_]

final def getMaxEpoch(epoch: Int, patience: Int): Int

def getStatus: (Int, Double, Double)

final def getTrainedNetwork: Network[IN, OUT]

def getValidationErr: (Double, Double)

def hashCode(): Int

final def isInstanceOf[T0]: Boolean

val logfile: File

val logger: Logger

val name: String

final def ne(arg0: AnyRef): Boolean

var network: Network[IN, OUT]

final def notify(): Unit

final def notifyAll(): Unit

val objective: Objective

val param: TrainingParam

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

val testSet: RDD[(IN, OUT)]

def toString(): String

val trainSet: RDD[(IN, OUT)]

final def trainSmallBatch(epoch: Int, patience: Int): Unit

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Trainer[IN, OUT, OUT]

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped