public class BatchNormalization extends FeedForwardLayer
Modifier and Type | Class and Description |
---|---|
static class |
BatchNormalization.Builder |
Modifier and Type | Field and Description |
---|---|
protected double |
beta |
protected double |
decay |
protected double |
eps |
protected double |
gamma |
protected boolean |
isMinibatch |
protected boolean |
lockGammaBeta |
nIn, nOut
activationFn, adamMeanDecay, adamVarDecay, biasInit, biasLearningRate, dist, dropOut, epsilon, gradientNormalization, gradientNormalizationThreshold, l1, l1Bias, l2, l2Bias, layerName, learningRate, learningRateSchedule, momentum, momentumSchedule, rho, rmsDecay, updater, weightInit
Modifier and Type | Method and Description |
---|---|
BatchNormalization |
clone() |
double |
getL1ByParam(java.lang.String paramName)
Get the L1 coefficient for the given parameter.
|
double |
getL2ByParam(java.lang.String paramName)
Get the L2 coefficient for the given parameter.
|
double |
getLearningRateByParam(java.lang.String paramName)
Get the (initial) learning rate coefficient for the given parameter.
|
InputType |
getOutputType(int layerIndex,
InputType inputType)
For a given type of input to this layer, what is the type of the output?
|
InputPreProcessor |
getPreProcessorForInputType(InputType inputType)
For the given type of input to this layer, what preprocessor (if any) is required?
Returns null if no preprocessor is required, otherwise returns an appropriate InputPreProcessor
for this layer, such as a CnnToFeedForwardPreProcessor |
Updater |
getUpdaterByParam(java.lang.String paramName)
Get the updater for the given parameter.
|
ParamInitializer |
initializer() |
Layer |
instantiate(NeuralNetConfiguration conf,
java.util.Collection<IterationListener> iterationListeners,
int layerIndex,
org.nd4j.linalg.api.ndarray.INDArray layerParamsView,
boolean initializeParams) |
void |
setNIn(InputType inputType,
boolean override)
Set the nIn value (number of inputs, or input depth for CNNs) based on the given input type
|
resetLayerDefaultConfig
protected double decay
protected double eps
protected boolean isMinibatch
protected double gamma
protected double beta
protected boolean lockGammaBeta
public BatchNormalization clone()
public Layer instantiate(NeuralNetConfiguration conf, java.util.Collection<IterationListener> iterationListeners, int layerIndex, org.nd4j.linalg.api.ndarray.INDArray layerParamsView, boolean initializeParams)
instantiate
in class Layer
public ParamInitializer initializer()
initializer
in class Layer
public InputType getOutputType(int layerIndex, InputType inputType)
Layer
getOutputType
in class FeedForwardLayer
layerIndex
- Index of the layerinputType
- Type of input for the layerpublic void setNIn(InputType inputType, boolean override)
Layer
setNIn
in class FeedForwardLayer
inputType
- Input type for this layeroverride
- If false: only set the nIn value if it's not already set. If true: set it regardless of whether it's
already set or not.public InputPreProcessor getPreProcessorForInputType(InputType inputType)
Layer
InputPreProcessor
for this layer, such as a CnnToFeedForwardPreProcessor
getPreProcessorForInputType
in class FeedForwardLayer
inputType
- InputType to this layerpublic double getL1ByParam(java.lang.String paramName)
Layer
getL1ByParam
in class FeedForwardLayer
paramName
- Parameter namepublic double getL2ByParam(java.lang.String paramName)
Layer
getL2ByParam
in class FeedForwardLayer
paramName
- Parameter namepublic double getLearningRateByParam(java.lang.String paramName)
Layer
getLearningRateByParam
in class FeedForwardLayer
paramName
- Parameter namepublic Updater getUpdaterByParam(java.lang.String paramName)
Layer
getUpdaterByParam
in class Layer
paramName
- Parameter name