Package org.nd4j.autodiff.samediff

Class TrainingConfig

java.lang.Object

org.nd4j.autodiff.samediff.TrainingConfig

public class TrainingConfig
extends Object

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	TrainingConfig.Builder

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	TrainingConfig(IUpdater updater, List<Regularization> regularization, boolean minimize, List<String> dataSetFeatureMapping, List<String> dataSetLabelMapping, List<String> dataSetFeatureMaskMapping, List<String> dataSetLabelMaskMapping, List<String> lossVariables, Map<String,List<IEvaluation>> trainEvaluations, Map<String,Integer> trainEvaluationLabels, Map<String,List<IEvaluation>> validationEvaluations, Map<String,Integer> validationEvaluationLabels, DataType initialLossDataType)
	TrainingConfig(IUpdater updater, List<Regularization> regularization, boolean minimize, List<String> dataSetFeatureMapping, List<String> dataSetLabelMapping, List<String> dataSetFeatureMaskMapping, List<String> dataSetLabelMaskMapping, List<String> lossVariables, DataType initialLossDataType)	Create a training configuration suitable for training both single input/output and multi input/output networks. See also the TrainingConfig.Builder for creating a TrainingConfig
	TrainingConfig(IUpdater updater, List<Regularization> regularization, String dataSetFeatureMapping, String dataSetLabelMapping)	Create a training configuration suitable for training a single input, single output network. See also the TrainingConfig.Builder for creating a TrainingConfig

Method Summary

Modifier and Type	Method	Description
static TrainingConfig.Builder	builder()
static TrainingConfig	fromJson(@NonNull String json)
void	incrementEpochCount()	Increment the epoch count by 1
void	incrementIterationCount()	Increment the iteration count by 1
int	labelIdx(String s)	Get the index of the label array that the specified variable is associated with
static void	removeInstances(List<?> list, Class<?> remove)	Remove any instances of the specified type from the list.
static void	removeInstancesWithWarning(List<?> list, Class<?> remove, String warning)
String	toJson()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

TrainingConfig

public TrainingConfig(IUpdater updater,
                      List<Regularization> regularization,
                      String dataSetFeatureMapping,
                      String dataSetLabelMapping)

Create a training configuration suitable for training a single input, single output network.
See also the TrainingConfig.Builder for creating a TrainingConfig

Parameters:

updater - The updater configuration to use

dataSetFeatureMapping - The name of the placeholder/variable that should be set using the feature INDArray from the DataSet (or the first/only feature from a MultiDataSet). For example, if the network input placeholder was called "input" then this should be set to "input"

dataSetLabelMapping - The name of the placeholder/variable that should be set using the label INDArray from the DataSet (or the first/only feature from a MultiDataSet). For example, if the network input placeholder was called "input" then this should be set to "input"

TrainingConfig

public TrainingConfig(IUpdater updater,
                      List<Regularization> regularization,
                      boolean minimize,
                      List<String> dataSetFeatureMapping,
                      List<String> dataSetLabelMapping,
                      List<String> dataSetFeatureMaskMapping,
                      List<String> dataSetLabelMaskMapping,
                      List<String> lossVariables,
                      DataType initialLossDataType)

Create a training configuration suitable for training both single input/output and multi input/output networks.
See also the TrainingConfig.Builder for creating a TrainingConfig

Parameters:

updater - The updater configuration to use

regularization - Regularization for all trainable parameters;\

minimize - Set to true if the loss function should be minimized (usually true). False to maximize

dataSetFeatureMapping - The name of the placeholders/variables that should be set using the feature INDArray(s) from the DataSet or MultiDataSet. For example, if the network had 2 inputs called "input1" and "input2" and the MultiDataSet features should be mapped with MultiDataSet.getFeatures(0)->"input1" and MultiDataSet.getFeatures(1)->"input2", then this should be set to List<>("input1", "input2").

dataSetLabelMapping - As per dataSetFeatureMapping, but for the DataSet/MultiDataSet labels

dataSetFeatureMaskMapping - May be null. If non-null, the variables that the MultiDataSet feature mask arrays should be associated with.

dataSetLabelMaskMapping - May be null. If non-null, the variables that the MultiDataSet label mask arrays should be associated with.

TrainingConfig

protected TrainingConfig(IUpdater updater,
                         List<Regularization> regularization,
                         boolean minimize,
                         List<String> dataSetFeatureMapping,
                         List<String> dataSetLabelMapping,
                         List<String> dataSetFeatureMaskMapping,
                         List<String> dataSetLabelMaskMapping,
                         List<String> lossVariables,
                         Map<String,List<IEvaluation>> trainEvaluations,
                         Map<String,Integer> trainEvaluationLabels,
                         Map<String,List<IEvaluation>> validationEvaluations,
                         Map<String,Integer> validationEvaluationLabels,
                         DataType initialLossDataType)

Method Detail

incrementIterationCount

public void incrementIterationCount()

Increment the iteration count by 1

incrementEpochCount

public void incrementEpochCount()

Increment the epoch count by 1

builder

public static TrainingConfig.Builder builder()

labelIdx

public int labelIdx(String s)

Get the index of the label array that the specified variable is associated with

Parameters:

s - Name of the variable

Returns:

The index of the label variable, or -1 if not found

removeInstances

public static void removeInstances(List<?> list,
                                   Class<?> remove)

Remove any instances of the specified type from the list. This includes any subtypes.

Parameters:

list - List. May be null

remove - Type of objects to remove

removeInstancesWithWarning

public static void removeInstancesWithWarning(List<?> list,
                                              Class<?> remove,
                                              String warning)

toJson

public String toJson()

fromJson

public static TrainingConfig fromJson(@NonNull
                                      @NonNull String json)