Index (deeplearning4j-parallel-wrapper 1.0.0-M2.1 API)

A B C D E F G H I L M N O P Q R S T U V W Z
All Classes All Packages

A

accumulator - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
accumulator - Variable in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
acquireModel() - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
addInput(INDArray...) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
addInput(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
addInput(INDArray...) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
addInput(INDArray[], INDArray[]) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
addInput(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
addModelHolder(Integer, InplaceParallelInference.ModelHolder) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
addObserver(Observer) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
averageUpdaters - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
averageUpdaters - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
averageUpdaters(boolean) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method enables/disables updaters averaging.
AVERAGING - org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode: Averaging every X epochs will be applied
averagingFrequency - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
averagingFrequency - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
averagingFrequency - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
averagingFrequency(int) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Model averaging frequency.
averagingRequired() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
averagingRequired() - Method in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
averagingRequired() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: This method returns TRUE if this Trainer implementation assumes periodic aver

B

BasicInferenceObservable - Class in org.deeplearning4j.parallelism.inference.observers
BasicInferenceObservable(INDArray...) - Constructor for class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
BasicInferenceObservable(INDArray[], INDArray[]) - Constructor for class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
BasicInferenceObserver - Class in org.deeplearning4j.parallelism.inference.observers
BasicInferenceObserver() - Constructor for class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObserver
BATCHED - org.deeplearning4j.parallelism.inference.InferenceMode: input will be included into the batch if computation device is busy, and executed immediately otherwise
BatchedInferenceObservable - Class in org.deeplearning4j.parallelism.inference.observers
BatchedInferenceObservable() - Constructor for class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
batchLimit - Variable in class org.deeplearning4j.parallelism.ParallelInference
batchLimit(int) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder: This method defines, how many input samples can be batched within given time frame.
broadcastGradients(SharedGradient) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: This method will propagate gradients across all workers
build() - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder: This method builds new ParallelInference instance
build() - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method returns ParallelWrapper instance
Builder(Model) - Constructor for class org.deeplearning4j.parallelism.ParallelInference.Builder
Builder(T) - Constructor for class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Build ParallelWrapper for MultiLayerNetwork

C

checkOutputException() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
cloneListener(TrainingListener) - Static method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
close() - Method in class org.deeplearning4j.parallelism.ParallelWrapper
CommunicativeTrainer - Interface in org.deeplearning4j.parallelism.trainer
configureListeners(String, Collection<TrainingListener>, Collection<TrainingListener>) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
create() - Method in interface org.deeplearning4j.parallelism.main.DataSetIteratorProviderFactory: Create an DataSetIterator
create() - Method in interface org.deeplearning4j.parallelism.main.MultiDataSetProviderFactory: Create an MultiDataSetIterator
create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext: Create a Trainer based on the given parameters
create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext: Create a Trainer based on the given parameters
create(String, int, Model, int, boolean, ParallelWrapper, WorkspaceMode, int) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext: Create a Trainer based on the given parameters
CUSTOM - org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode: This option assumes use of GradientsAccumulator with any MessageHandler

D

DataSetIteratorProviderFactory - Interface in org.deeplearning4j.parallelism.main
debug - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
DEFAULT_BATCH_LIMIT - Static variable in class org.deeplearning4j.parallelism.ParallelInference
DEFAULT_INFERENCE_MODE - Static variable in class org.deeplearning4j.parallelism.ParallelInference
DEFAULT_NUM_WORKERS - Static variable in class org.deeplearning4j.parallelism.ParallelInference
DEFAULT_QUEUE_LIMIT - Static variable in class org.deeplearning4j.parallelism.ParallelInference
DefaultTrainer - Class in org.deeplearning4j.parallelism.trainer
DefaultTrainer() - Constructor for class org.deeplearning4j.parallelism.trainer.DefaultTrainer
DefaultTrainer.DefaultTrainerBuilder - Class in org.deeplearning4j.parallelism.trainer
DefaultTrainerBuilder() - Constructor for class org.deeplearning4j.parallelism.trainer.DefaultTrainer.DefaultTrainerBuilder
DefaultTrainerContext - Class in org.deeplearning4j.parallelism.factory
DefaultTrainerContext() - Constructor for class org.deeplearning4j.parallelism.factory.DefaultTrainerContext

E

EarlyStoppingParallelTrainer<T extends org.deeplearning4j.nn.api.Model> - Class in org.deeplearning4j.parallelism
EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, int, int, int) - Constructor for class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, EarlyStoppingListener<T>, int, int, int) - Constructor for class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
EarlyStoppingParallelTrainer(EarlyStoppingConfiguration<T>, T, DataSetIterator, MultiDataSetIterator, EarlyStoppingListener<T>, int, int, int, boolean, boolean) - Constructor for class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
encoderMemory - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
enqueueGradient(SharedGradient) - Method in interface org.deeplearning4j.parallelism.trainer.CommunicativeTrainer
enqueueGradient(SharedGradient) - Method in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer: Deprecated.
esConfig - Variable in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
exception - Variable in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
exception - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
exceptionEncountered - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
executorService - Variable in class org.deeplearning4j.parallelism.ParallelWrapper

F

feedDataSet(DataSet, long) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Train on a DataSet
feedDataSet(DataSet, long) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
feedMultiDataSet(MultiDataSet, long) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
feedMultiDataSet(MultiDataSet, long) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Train on a MultiDataSet
FIFO - org.deeplearning4j.parallelism.inference.LoadBalanceMode: in this mode we'll be picking free node for next request, blocking if we don't have free nodes at the moment
finalizeRound(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
finalizeRound(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
finalizeRound(Model, Model...) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext: This method is called at averagingFrequency
finalizeTraining(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext
finalizeTraining(Model, Model...) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext
finalizeTraining(Model, Model...) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext: This method is called
fit() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
fit(DataSetIterator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: This method takes DataSetIterator, and starts training over it by scheduling DataSets to different executors
fit(MultiDataSetIterator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper
fit(DataSet) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
fit(MultiDataSet) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer

G

getCounter() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
getCurrentModelsFromWorkers() - Method in class org.deeplearning4j.parallelism.InplaceParallelInference
getCurrentModelsFromWorkers() - Method in class org.deeplearning4j.parallelism.ParallelInference: This method returns Models used in workers at this moment PLEASE NOTE: This method is NOT thread safe, and should NOT be used anywhere but tests
getInputBatches() - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable: Get input batches - and their associated input mask arrays, if any
Note that usually the returned list will be of size 1 - however, in the batched case, not all inputs can actually be batched (variable size inputs to fully convolutional net, for example).
getInputBatches() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
getInputBatches() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
getModel() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
getModel() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: THe current model for the trainer
getModelForThisThread() - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
getModelForThread(long) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
getOutput() - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
getOutput() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
getOutput() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
getOutputs() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable: PLEASE NOTE: This method is for tests only
getTermination() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
getUuid() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
getWorkerCounter(int) - Method in class org.deeplearning4j.parallelism.ParallelInference
gradientsAccumulator - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
gradientsAccumulator(GradientsAccumulator) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method allows you to specify GradientsAccumulator instance to be used in this ParallelWrapper instance PLEASE NOTE: This method is applicable only to gradients sharing mechanics.

H

holders - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference

I

incrementIteration() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
inferenceMode - Variable in class org.deeplearning4j.parallelism.ParallelInference
inferenceMode(InferenceMode) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder: This method allows you to define mode that'll be used during inference.
InferenceMode - Enum in org.deeplearning4j.parallelism.inference
InferenceObservable - Interface in org.deeplearning4j.parallelism.inference
init() - Method in class org.deeplearning4j.parallelism.InplaceParallelInference
init() - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
init() - Method in class org.deeplearning4j.parallelism.ParallelInference
init() - Method in class org.deeplearning4j.parallelism.ParallelWrapper
init(Model, Object...) - Method in class org.deeplearning4j.parallelism.factory.DefaultTrainerContext: Initialize the context
init(Model, Object...) - Method in class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext: Initialize the context
init(Model, Object...) - Method in interface org.deeplearning4j.parallelism.factory.TrainerContext: Initialize the context
INPLACE - org.deeplearning4j.parallelism.inference.InferenceMode: Inference will applied in the calling thread instead of workers.
InplaceParallelInference - Class in org.deeplearning4j.parallelism
InplaceParallelInference() - Constructor for class org.deeplearning4j.parallelism.InplaceParallelInference
InplaceParallelInference.ModelHolder - Class in org.deeplearning4j.parallelism
InplaceParallelInference.ModelSelector - Class in org.deeplearning4j.parallelism
isCG - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
isLocked() - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
isMLN - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
isMQ - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
isMQ - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
isRunning() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
isRunning() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer
isStopped - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
iterationsCounter - Variable in class org.deeplearning4j.parallelism.ParallelWrapper

L

lastEtlTime - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
legacyAveraging - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
legacyAveraging - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
listeners - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
loadBalanceMode - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
loadBalanceMode - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
loadBalanceMode - Variable in class org.deeplearning4j.parallelism.ParallelInference.Builder
loadBalanceMode - Variable in class org.deeplearning4j.parallelism.ParallelInference
loadBalanceMode(LoadBalanceMode) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder: This method allows you to specify load balance mode
LoadBalanceMode - Enum in org.deeplearning4j.parallelism.inference
locker - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference

M

main(String[]) - Static method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
map - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
model - Variable in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
model - Variable in class org.deeplearning4j.parallelism.ParallelInference
model - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
model - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
ModelHolder() - Constructor for class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
modelLock - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
modelLock - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
modelParamsSupplier - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
modelParamsSupplier - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
modelParamsSupplier(Supplier<INDArray>) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method attaches supplier that'll probably provide model params update PLEASE NOTE: This method is mostly used in Spark environment as part of fault tolerance logic
ModelSelector() - Constructor for class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
ModelSelector(LoadBalanceMode) - Constructor for class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
MultiDataSetProviderFactory - Interface in org.deeplearning4j.parallelism.main

N

nanos - Variable in class org.deeplearning4j.parallelism.ParallelInference
nullDataSet - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
nullMode - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer

O

ObservablesProvider(long, int, BlockingQueue<InferenceObservable>) - Constructor for class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
onRootModel - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
org.deeplearning4j.parallelism - package org.deeplearning4j.parallelism
org.deeplearning4j.parallelism.factory - package org.deeplearning4j.parallelism.factory
org.deeplearning4j.parallelism.inference - package org.deeplearning4j.parallelism.inference
org.deeplearning4j.parallelism.inference.observers - package org.deeplearning4j.parallelism.inference.observers
org.deeplearning4j.parallelism.main - package org.deeplearning4j.parallelism.main
org.deeplearning4j.parallelism.trainer - package org.deeplearning4j.parallelism.trainer
originalModel - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
output(double[]) - Method in class org.deeplearning4j.parallelism.ParallelInference
output(float[]) - Method in class org.deeplearning4j.parallelism.ParallelInference
output(ModelAdapter<T>, INDArray...) - Method in class org.deeplearning4j.parallelism.ParallelInference: This method does forward pass and returns output provided by OutputAdapter
output(ModelAdapter<T>, INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.ParallelInference: This method does forward pass and returns output provided by OutputAdapter
output(ModelAdapter<T>, INDArray[], INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference: This method does forward pass and returns output provided by OutputAdapter
output(INDArray) - Method in class org.deeplearning4j.parallelism.ParallelInference
output(INDArray...) - Method in class org.deeplearning4j.parallelism.ParallelInference: Generate predictions/output from the netwonk
output(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
output(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelSelector
output(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference
output(INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.ParallelInference: Generate predictions/outputs from the network, optionally using input masks for predictions
output(INDArray, INDArray) - Method in class org.deeplearning4j.parallelism.ParallelInference
output(DataSet) - Method in class org.deeplearning4j.parallelism.ParallelInference

P

ParallelInference - Class in org.deeplearning4j.parallelism
ParallelInference() - Constructor for class org.deeplearning4j.parallelism.ParallelInference
ParallelInference.Builder - Class in org.deeplearning4j.parallelism
ParallelInference.ObservablesProvider - Class in org.deeplearning4j.parallelism
parallelWrapper - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
ParallelWrapper - Class in org.deeplearning4j.parallelism
ParallelWrapper(Model, int, int) - Constructor for class org.deeplearning4j.parallelism.ParallelWrapper
ParallelWrapper.Builder<T extends org.deeplearning4j.nn.api.Model> - Class in org.deeplearning4j.parallelism
ParallelWrapper.TrainingMode - Enum in org.deeplearning4j.parallelism
ParallelWrapperMain - Class in org.deeplearning4j.parallelism.main
ParallelWrapperMain() - Constructor for class org.deeplearning4j.parallelism.main.ParallelWrapperMain
position - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
postInit() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer: This method does post-initialization configuration of Model.
postInit() - Method in class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
prefetchBuffer(int) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Size of prefetch buffer that will be used for background data prefetching.
prefetchSize - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
prefetchSize - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
pretrain() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer

Q

queue - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
queue - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
queueLimit - Variable in class org.deeplearning4j.parallelism.ParallelInference
queueLimit(int) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder: This method defines buffer queue size.
queueMDS - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer

R

releaseModel(Model) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
replicas - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
replicatedModel - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
reportScore - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
reportScore - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
reportScoreAfterAveraging(boolean) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method enables/disables averaged model score reporting
reset() - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
residualPostProcessor - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
residualPostProcessor(ResidualPostProcessor) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Set the residual post processor algorithm.
rootDevice - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
ROUND_ROBIN - org.deeplearning4j.parallelism.inference.LoadBalanceMode: In this mode, `n+1 % nodes` node will be used for next request
run() - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
run() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
runMain(String...) - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain
running - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer

S

selector - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference
SEQUENTIAL - org.deeplearning4j.parallelism.inference.InferenceMode: input will be passed into the model as is
setCounter(int) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
setInput(Observer, INDArray) - Method in class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
setInput(Observer, INDArray...) - Method in class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
setInput(Observer, INDArray[], INDArray[]) - Method in class org.deeplearning4j.parallelism.ParallelInference.ObservablesProvider
setLatestScore(double) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
setListener(EarlyStoppingListener<T>) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
setListeners(Collection<TrainingListener>) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: This method allows you to specify trainingListeners for this model.
setListeners(TrainingListener...) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: This method allows you to specify trainingListeners for this model.
setListeners(StatsStorageRouter, Collection<? extends TrainingListener>) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: Set the listeners, along with a StatsStorageRouter that the results will be shuffled to (in the case of any listeners that implement the RoutingIterationListener interface)
setListeners(StatsStorageRouter, TrainingListener...) - Method in class org.deeplearning4j.parallelism.ParallelWrapper: Set the listeners, along with a StatsStorageRouter that the results will be shuffled to (in the case of any listeners that implement the RoutingIterationListener interface)
setOutputBatches(List<INDArray[]>) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
setOutputBatches(List<INDArray[]>) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
setOutputBatches(List<INDArray[]>) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
setOutputException(Exception) - Method in interface org.deeplearning4j.parallelism.inference.InferenceObservable
setOutputException(Exception) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObservable
setPosition(int) - Method in class org.deeplearning4j.parallelism.inference.observers.BatchedInferenceObservable
setTermination(boolean) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
setTerminationReason(IterationTerminationCondition) - Method in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
setUncaughtExceptionHandler(Thread.UncaughtExceptionHandler) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Set the Thread.UncaughtExceptionHandler for this Trainer
setupIfNeccessary() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
SHARED_GRADIENTS - org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode: Models within ParallelWrapper instance will share gradients updates
shouldStop - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
shouldUpdate - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
shutdown() - Method in class org.deeplearning4j.parallelism.ParallelInference: This method gracefully shuts down ParallelInference instance
shutdown() - Method in class org.deeplearning4j.parallelism.ParallelWrapper: This method causes all threads used for parallel training to stop
shutdown() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
shutdown() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Shutdown this worker
sourceModel - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
start() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Start this trainer
stop() - Method in class org.deeplearning4j.parallelism.main.ParallelWrapperMain: Stop the ParallelWrapper main.
stopFit - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
stopFit() - Method in class org.deeplearning4j.parallelism.ParallelWrapper: Will stop a fit operation from continuing to iterate.
storageRouter - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
SymmetricTrainer - Class in org.deeplearning4j.parallelism.trainer
SymmetricTrainer(Model, String, int, WorkspaceMode, ParallelWrapper, boolean) - Constructor for class org.deeplearning4j.parallelism.trainer.SymmetricTrainer
SymmetricTrainerContext - Class in org.deeplearning4j.parallelism.factory
SymmetricTrainerContext() - Constructor for class org.deeplearning4j.parallelism.factory.SymmetricTrainerContext

T

targetDeviceId - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
temporaryMemory(Long) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method allows to define amount of temporary memory that will be used for gradients sharing.
terminationReason - Variable in class org.deeplearning4j.parallelism.EarlyStoppingParallelTrainer
threadId - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
thresholdAlgorithm - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
thresholdAlgorithm(ThresholdAlgorithm) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Set the threshold algorithm.
thrownException - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
Trainer - Interface in org.deeplearning4j.parallelism.trainer
trainerContext - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
trainerContext - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
TrainerContext - Interface in org.deeplearning4j.parallelism.factory
trainerContextArgs - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
trainerContextArgs - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
trainerContextArgs(Object...) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Transer context args are for calling a TrainerContext init method when ParallelWrapper starts training
trainerFactory(TrainerContext) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: Specify a TrainerContext for the given ParallelWrapper instance.
trainingMode - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
trainingMode(ParallelWrapper.TrainingMode) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method allows you to specify training mode for this instance of PW.
1) AVERAGING - stands for parameters averaging.

U

update(Observable, Object) - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObserver
updateModel(Model) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
updateModel(Model) - Method in class org.deeplearning4j.parallelism.InplaceParallelInference
updateModel(Model) - Method in class org.deeplearning4j.parallelism.ParallelInference: This method allows to update Model used for inference in runtime, without queue reset
updateModel(Model) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
updateModel(Model) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Update the current Model for the worker
updateModelParams(INDArray) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
updateModelParams(INDArray) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: This method updates replicated model params
updaterParamsSupplier - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
updaterParamsSupplier - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
updaterParamsSupplier(Supplier<INDArray>) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method attaches supplier that'll probably provide updater params update PLEASE NOTE: This method is mostly used in Spark environment as part of fault tolerance logic
updateUpdaterParams(INDArray) - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
updateUpdaterParams(INDArray) - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: This method updates updater params of the replicated model
useMDS - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
uuid - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
uuid - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer

V

valueOf(String) - Static method in enum org.deeplearning4j.parallelism.inference.InferenceMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.parallelism.inference.LoadBalanceMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.deeplearning4j.parallelism.inference.InferenceMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.parallelism.inference.LoadBalanceMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.deeplearning4j.parallelism.ParallelWrapper.TrainingMode: Returns an array containing the constants of this enum type, in the order they are declared.

W

waitTillDone() - Method in class org.deeplearning4j.parallelism.inference.observers.BasicInferenceObserver: FOR DEBUGGING ONLY, TO BE REMOVED BEFORE MERGE
waitTillRunning() - Method in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
waitTillRunning() - Method in interface org.deeplearning4j.parallelism.trainer.Trainer: Block the main thread till the trainer is up and running.
wasAveraged - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
workerCounter - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
workers - Variable in class org.deeplearning4j.parallelism.InplaceParallelInference.ModelHolder
workers - Variable in class org.deeplearning4j.parallelism.ParallelInference
workers - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
workers - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
workers(int) - Method in class org.deeplearning4j.parallelism.ParallelInference.Builder: This method defines, how many model copies will be used for inference.
workers(int) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method allows to configure number of workers that'll be used for parallel training
workspaceMode - Variable in class org.deeplearning4j.parallelism.ParallelWrapper.Builder
workspaceMode - Variable in class org.deeplearning4j.parallelism.ParallelWrapper
workspaceMode - Variable in class org.deeplearning4j.parallelism.trainer.DefaultTrainer
workspaceMode(WorkspaceMode) - Method in class org.deeplearning4j.parallelism.ParallelWrapper.Builder: This method allows to override model's WorkspaceMode configuration option

Z

zoo - Variable in class org.deeplearning4j.parallelism.ParallelWrapper

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