Package | Description |
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org.deeplearning4j.nn.conf | |
org.deeplearning4j.nn.transferlearning |
Modifier and Type | Field and Description |
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protected NeuralNetConfiguration.Builder |
ComputationGraphConfiguration.GraphBuilder.globalConfiguration |
Modifier and Type | Method and Description |
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NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.activation(org.nd4j.linalg.activations.Activation activation)
Activation function / neuron non-linearity
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.activation(org.nd4j.linalg.activations.IActivation activationFunction)
Activation function / neuron non-linearity
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.activation(String activationFunction)
Deprecated.
Use
activation(Activation) or
@activation(IActivation) |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.adamMeanDecay(double adamMeanDecay)
Mean decay rate for Adam updater.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.adamVarDecay(double adamVarDecay)
Variance decay rate for Adam updater.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.biasInit(double biasInit)
Constant for bias initialization.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.biasLearningRate(double biasLearningRate)
Bias learning rate.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.clone() |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.convolutionMode(ConvolutionMode convolutionMode) |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.dist(Distribution dist)
Distribution to sample initial weights from.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.dropOut(double dropOut)
Dropout probability.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.epsilon(double epsilon)
Epsilon value for updaters: Adam, RMSProp, Adagrad, Adadelta
Default values:
Adam.DEFAULT_ADAM_EPSILON , RmsProp.DEFAULT_RMSPROP_EPSILON , AdaGrad.DEFAULT_ADAGRAD_EPSILON ,
AdaDelta.DEFAULT_ADADELTA_EPSILON |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.gradientNormalization(GradientNormalization gradientNormalization)
Gradient normalization strategy.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.gradientNormalizationThreshold(double threshold)
Threshold for gradient normalization, only used for GradientNormalization.ClipL2PerLayer,
GradientNormalization.ClipL2PerParamType, and GradientNormalization.ClipElementWiseAbsoluteValue
Not used otherwise. L2 threshold for first two types of clipping, or absolute value threshold for last type of clipping. |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.iterations(int numIterations)
Number of optimization iterations.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.l1(double l1)
L1 regularization coefficient for the weights.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.l1Bias(double l1Bias)
L1 regularization coefficient for the bias.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.l2(double l2)
L2 regularization coefficient for the weights.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.l2Bias(double l2Bias)
L2 regularization coefficient for the bias.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.layer(Layer layer)
Layer class.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.leakyreluAlpha(double leakyreluAlpha)
Deprecated.
Use
activation(IActivation) with leaky relu, setting alpha value directly in constructor. |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.learningRate(double learningRate)
Learning rate.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.learningRateDecayPolicy(LearningRatePolicy policy)
Learning rate decay policy.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.learningRateSchedule(Map<Integer,Double> learningRateSchedule)
Learning rate schedule.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.learningRateScoreBasedDecayRate(double lrScoreBasedDecay)
Rate to decrease learningRate by when the score stops improving.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.lrPolicyDecayRate(double lrPolicyDecayRate)
Set the decay rate for the learning rate decay policy.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.lrPolicyPower(double lrPolicyPower)
Set the power used for learning rate inverse policy.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.lrPolicySteps(double lrPolicySteps)
Set the number of steps used for learning decay rate steps policy.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.maxNumLineSearchIterations(int maxNumLineSearchIterations)
Maximum number of line search iterations.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.miniBatch(boolean miniBatch)
Process input as minibatch vs full dataset.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.minimize(boolean minimize)
Objective function to minimize or maximize cost function
Default set to minimize true.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.momentum(double momentum)
Momentum rate
Used only when Updater is set to
Updater.NESTEROVS |
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.momentumAfter(Map<Integer,Double> momentumAfter)
Momentum schedule.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.optimizationAlgo(OptimizationAlgorithm optimizationAlgo)
Optimization algorithm to use.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.regularization(boolean useRegularization)
Whether to use regularization (l1, l2, dropout, etc
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.rho(double rho)
Ada delta coefficient
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.rmsDecay(double rmsDecay)
Decay rate for RMSProp.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.seed(int seed)
Random number generator seed.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.seed(long seed)
Random number generator seed.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.stepFunction(StepFunction stepFunction)
Step function to apply for back track line search.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.updater(Updater updater)
Gradient updater.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.useDropConnect(boolean useDropConnect)
Use drop connect: multiply the weight by a binomial sampling wrt the dropout probability.
|
NeuralNetConfiguration.Builder |
NeuralNetConfiguration.Builder.weightInit(WeightInit weightInit)
Weight initialization scheme.
|
Modifier and Type | Method and Description |
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Map<Integer,NeuralNetConfiguration.Builder> |
NeuralNetConfiguration.ListBuilder.getLayerwise() |
Constructor and Description |
---|
GraphBuilder(ComputationGraphConfiguration newConf,
NeuralNetConfiguration.Builder globalConfiguration) |
GraphBuilder(NeuralNetConfiguration.Builder globalConfiguration) |
ListBuilder(NeuralNetConfiguration.Builder globalConfig) |
ListBuilder(NeuralNetConfiguration.Builder globalConfig,
Map<Integer,NeuralNetConfiguration.Builder> layerMap) |
Constructor and Description |
---|
ListBuilder(NeuralNetConfiguration.Builder globalConfig,
Map<Integer,NeuralNetConfiguration.Builder> layerMap) |
Modifier and Type | Method and Description |
---|---|
NeuralNetConfiguration.Builder |
FineTuneConfiguration.appliedNeuralNetConfigurationBuilder() |
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