Uses of Interface
org.nd4j.autodiff.listeners.Listener

Packages that use Listener

Package	Description
org.nd4j.autodiff.listeners
org.nd4j.autodiff.listeners.checkpoint
org.nd4j.autodiff.listeners.debugging
org.nd4j.autodiff.listeners.impl
org.nd4j.autodiff.listeners.profiler
org.nd4j.autodiff.samediff
org.nd4j.autodiff.samediff.config
org.nd4j.autodiff.samediff.internal
org.nd4j.autodiff.validation
org.nd4j.autodiff.validation.listeners

Uses of Listener in org.nd4j.autodiff.listeners

Classes in org.nd4j.autodiff.listeners that implement Listener

Modifier and Type	Class and Description
class	BaseEvaluationListener
class	BaseListener

Uses of Listener in org.nd4j.autodiff.listeners.checkpoint

Classes in org.nd4j.autodiff.listeners.checkpoint that implement Listener

Modifier and Type	Class and Description
class	CheckpointListener

Uses of Listener in org.nd4j.autodiff.listeners.debugging

Classes in org.nd4j.autodiff.listeners.debugging that implement Listener

Modifier and Type	Class and Description
class	ArraySavingListener
class	ExecDebuggingListener
class	OpBenchmarkListener

Uses of Listener in org.nd4j.autodiff.listeners.impl

Classes in org.nd4j.autodiff.listeners.impl that implement Listener

Modifier and Type	Class and Description
class	HistoryListener
class	ScoreListener
class	UIListener

Uses of Listener in org.nd4j.autodiff.listeners.profiler

Classes in org.nd4j.autodiff.listeners.profiler that implement Listener

Modifier and Type	Class and Description
class	ProfilingListener

Uses of Listener in org.nd4j.autodiff.samediff

Methods in org.nd4j.autodiff.samediff that return types with arguments of type Listener

Modifier and Type	Method and Description
List<Listener>	SameDiff.getListeners() Gets the current SameDiff-wide listeners.

Methods in org.nd4j.autodiff.samediff with parameters of type Listener

Modifier and Type	Method and Description
void	SameDiff.addListeners(Listener... listeners) Add SameDiff-wide Listener instances.
void	SameDiff.evaluate(@NonNull DataSetIterator iterator, @NonNull Map<String,IEvaluation> variableEvals, Listener... listeners) Evaluation for multiple-output networks. See SameDiff.evaluate(MultiDataSetIterator, Map, Map, Listener[]).
void	SameDiff.evaluate(MultiDataSetIterator iterator, Map<String,List<IEvaluation>> variableEvals, Map<String,Integer> predictionLabelMapping, Listener... listeners) Perform evaluation using classes such as Evaluation for classifier outputs and RegressionEvaluation for regression outputs. Example: classifier evaluation Predictions variable name: "softmaxOutput" Evaluations to perform: Evaluation Data: single input, single output MultiDataSets Code:
void	SameDiff.evaluateMultiple(DataSetIterator iterator, Map<String,List<IEvaluation>> variableEvals, Listener... listeners) Evaluation for multiple output networks - one or more.
History	SameDiff.fit(@NonNull DataSetIterator iter, int numEpochs, DataSetIterator validationIter, int validationFrequency, Listener... listeners) Fit the SameDiff instance based on DataSetIterator for the specified number of epochs. This method can only be used for singe input, single output SameDiff instances as DataSet only supports a single input and a single output. Note that a TrainingConfig must be set via SameDiff.setTrainingConfig(TrainingConfig) before training can be performed.
History	SameDiff.fit(@NonNull DataSetIterator iter, int numEpochs, Listener... listeners) See SameDiff.fit(DataSetIterator, int, DataSetIterator, int, Listener...), does not preform validation.
History	SameDiff.fit(@NonNull DataSet dataSet, Listener... listeners) Fit the SameDiff instance based on a single DataSet (i.e., a single minibatch for one iteration). This method can only be used for singe input, single output SameDiff instances as DataSet only supports a single input and a single output. Note that a TrainingConfig must be set via SameDiff.setTrainingConfig(TrainingConfig) before training can be performed.
protected History	SameDiff.fit(@NonNull MultiDataSetIterator iter, int numEpochs, boolean incrementEpochCount, MultiDataSetIterator validationData, int validationFrequency, Listener... listeners)
History	SameDiff.fit(@NonNull MultiDataSetIterator iter, int numEpochs, Listener... listeners) See SameDiff.fit(MultiDataSetIterator, int, MultiDataSetIterator, int, Listener...), does not preform validation.
History	SameDiff.fit(@NonNull MultiDataSetIterator iter, int numEpochs, MultiDataSetIterator validationIter, int validationFrequency, Listener... listeners) Fit the SameDiff instance based on MultiDataSetIterator for the specified number of epochs. This method can both singe input, single output and multi-input, multi-output SameDiff instances Note that a TrainingConfig must be set via SameDiff.setTrainingConfig(TrainingConfig) before training can be performed.
History	SameDiff.fit(@NonNull MultiDataSet dataSet, Listener... listeners) Fit the SameDiff instance based on a single MultiDataSet (i.e., a single minibatch for one iteration). Note that a TrainingConfig must be set via SameDiff.setTrainingConfig(TrainingConfig) before training can be performed.
void	SameDiff.setListeners(Listener... listeners) Set the current SameDiff-wide Listener instances.

Method parameters in org.nd4j.autodiff.samediff with type arguments of type Listener

Modifier and Type	Method and Description
void	SameDiff.addListeners(Collection<? extends Listener> listeners) See SameDiff.addListeners(Listener...).
protected Map<String,INDArray>	SameDiff.batchOutputHelper(Map<String,INDArray> placeholders, List<Listener> listeners, Operation operation, String... outputs)
protected Map<String,INDArray>	SameDiff.directExecHelper(Map<String,INDArray> placeholders, At at, MultiDataSet batch, Collection<String> requiredActivations, List<Listener> activeListeners, String... outputs) Do inference for the given variables for a single batch, with training information
Map<String,INDArray>	SameDiff.output(Map<String,INDArray> placeholders, List<Listener> listeners, String... outputs) Do inference for the given variables for a single batch.
List<Map<String,INDArray>>	SameDiff.outputBatches(DataSetIterator iterator, List<Listener> listeners, String... outputs) See SameDiff.output(DataSetIterator, List, String...), but without the concatenation of batches.
List<Map<String,INDArray>>	SameDiff.outputBatches(MultiDataSetIterator iterator, List<Listener> listeners, String... outputs) Perform inference. Example: classifier inference Predictions variable name: "softmaxOutput" Evaluations to perform: Evaluation Data: single output MultiDataSets Code:
void	SameDiff.setListeners(Collection<? extends Listener> listeners) See SameDiff.setListeners(Listener...).

Uses of Listener in org.nd4j.autodiff.samediff.config

Methods in org.nd4j.autodiff.samediff.config with parameters of type Listener

Modifier and Type	Method and Description
BatchOutputConfig	BatchOutputConfig.listeners(Listener... listeners) Add listeners for this operation
EvaluationConfig	EvaluationConfig.listeners(Listener... listeners) Add listeners for this operation
FitConfig	FitConfig.listeners(Listener... listeners) Add listeners for this operation
OutputConfig	OutputConfig.listeners(Listener... listeners) Add listeners for this operation

Uses of Listener in org.nd4j.autodiff.samediff.internal

Fields in org.nd4j.autodiff.samediff.internal with type parameters of type Listener

Modifier and Type	Field and Description
protected List<Listener>	TrainingSession.listeners

Method parameters in org.nd4j.autodiff.samediff.internal with type arguments of type Listener

Modifier and Type	Method and Description
abstract T[]	AbstractSession.getOutputs(O op, FrameIter outputFrameIter, Set<AbstractSession.VarId> inputs, Set<AbstractSession.VarId> allIterInputs, Set<String> constAndPhInputs, List<Listener> listeners, At at, MultiDataSet batch, Set<String> allReqVariables) Execute the op - calculate INDArrays, or shape info, etc
INDArray[]	InferenceSession.getOutputs(Pair<SameDiffOp,OpContext> opPair, FrameIter outputFrameIter, Set<AbstractSession.VarId> opInputs, Set<AbstractSession.VarId> allIterInputs, Set<String> constAndPhInputs, List<Listener> listeners, At at, MultiDataSet batch, Set<String> allReqVariables)
INDArray[]	TrainingSession.getOutputs(Pair<SameDiffOp,OpContext> opPair, FrameIter outputFrameIter, Set<AbstractSession.VarId> opInputs, Set<AbstractSession.VarId> allIterInputs, Set<String> constAndPhInputs, List<Listener> listeners, At at, MultiDataSet batch, Set<String> allReqVariables)
Map<String,T>	AbstractSession.output(@NonNull List<String> variables, Map<String,T> placeholderValues, MultiDataSet batch, Collection<String> requiredActivations, List<Listener> listeners, At at) Get the output of the session - i.e., perform inference/forward pass and return the outputs for the specified variables
Loss	TrainingSession.trainingIteration(TrainingConfig config, Map<String,INDArray> placeholders, Set<String> paramsToTrain, Map<String,GradientUpdater> updaters, MultiDataSet batch, List<String> lossVariables, List<Listener> listeners, At at) Perform one iteration of training - i.e., do forward and backward passes, and update the parameters

Uses of Listener in org.nd4j.autodiff.validation

Classes in org.nd4j.autodiff.validation that implement Listener

Modifier and Type	Class and Description
class	ActivationGradientCheckListener

Uses of Listener in org.nd4j.autodiff.validation.listeners

Classes in org.nd4j.autodiff.validation.listeners that implement Listener

Modifier and Type	Class and Description
class	NonInplaceValidationListener