Feedforward Closedloop Learning
|
Public Member Functions | |
def | __init__ (self, "int" _nNeurons, "int" _nInputs) |
"void" | calcOutputs (self) |
"void" | doLearning (self) |
"void" | setError (self, *args) |
"void" | setErrors (self, "double *" _errors) |
"double" | getError (self, "int" i) |
"void" | setBias (self, "double" _bias) |
"void" | setInput (self, "int" inputIndex, "double" input) |
"void" | setInputs (self, "double *" _inputs) |
"void" | setLearningRate (self, "double" _learningRate) |
"void" | setActivationFunction (self, "Neuron::ActivationFunction" _activationFunction) |
"void" | setMomentum (self, "double" _momentum) |
"void" | setDecay (self, "double" _decay) |
"void" | initWeights (self, *args) |
"double" | getOutput (self, "int" index) |
"Neuron *" | getNeuron (self, "int" index) |
"int" | getNneurons (self) |
"int" | getNinputs (self) |
"void" | setConvolution (self, "int" width, "int" height) |
"void" | setMaxDetLayer (self, "int" _m) |
"void" | setNormaliseWeights (self, "Layer::WeightNormalisation" _normaliseWeights) |
"void" | setDebugInfo (self, "int" layerIndex) |
"void" | setStep (self, "long" step) |
"double" | getWeightDistanceFromInitialWeights (self) |
"void" | doNormaliseWeights (self) |
"void" | setUseThreads (self, "int" _useThreads) |
"int" | saveWeightMatrix (self, "char *" filename) |
Properties | |
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") | |
Proxy of C++ Layer class.
def feedforward_closedloop_learning.Layer.__init__ | ( | self, | |
"int" | _nNeurons, | ||
"int" | _nInputs | ||
) |
__init__(Layer self, int _nNeurons, int _nInputs) -> Layer Parameters ---------- _nNeurons: int _nInputs: int
"void" feedforward_closedloop_learning.Layer.calcOutputs | ( | self | ) |
calcOutputs(Layer self)
"void" feedforward_closedloop_learning.Layer.doLearning | ( | self | ) |
doLearning(Layer self)
"void" feedforward_closedloop_learning.Layer.doNormaliseWeights | ( | self | ) |
doNormaliseWeights(Layer self)
"double" feedforward_closedloop_learning.Layer.getError | ( | self, | |
"int" | i | ||
) |
getError(Layer self, int i) -> double Parameters ---------- i: int
"Neuron *" feedforward_closedloop_learning.Layer.getNeuron | ( | self, | |
"int" | index | ||
) |
getNeuron(Layer self, int index) -> Neuron Parameters ---------- index: int
"int" feedforward_closedloop_learning.Layer.getNinputs | ( | self | ) |
getNinputs(Layer self) -> int
"int" feedforward_closedloop_learning.Layer.getNneurons | ( | self | ) |
getNneurons(Layer self) -> int
"double" feedforward_closedloop_learning.Layer.getOutput | ( | self, | |
"int" | index | ||
) |
getOutput(Layer self, int index) -> double Parameters ---------- index: int
"double" feedforward_closedloop_learning.Layer.getWeightDistanceFromInitialWeights | ( | self | ) |
getWeightDistanceFromInitialWeights(Layer self) -> double
"void" feedforward_closedloop_learning.Layer.initWeights | ( | self, | |
* | args | ||
) |
initWeights(Layer self, double _max=1, int initBiasWeight=1, Neuron::WeightInitMethod weightInitMethod=MAX_OUTPUT_RANDOM) Parameters ---------- _max: double initBiasWeight: int weightInitMethod: enum Neuron::WeightInitMethod
"int" feedforward_closedloop_learning.Layer.saveWeightMatrix | ( | self, | |
"char *" | filename | ||
) |
saveWeightMatrix(Layer self, char * filename) -> int Parameters ---------- filename: char *
"void" feedforward_closedloop_learning.Layer.setActivationFunction | ( | self, | |
"Neuron::ActivationFunction" | _activationFunction | ||
) |
setActivationFunction(Layer self, Neuron::ActivationFunction _activationFunction) Parameters ---------- _activationFunction: enum Neuron::ActivationFunction
"void" feedforward_closedloop_learning.Layer.setBias | ( | self, | |
"double" | _bias | ||
) |
setBias(Layer self, double _bias) Parameters ---------- _bias: double
"void" feedforward_closedloop_learning.Layer.setConvolution | ( | self, | |
"int" | width, | ||
"int" | height | ||
) |
setConvolution(Layer self, int width, int height) Parameters ---------- width: int height: int
"void" feedforward_closedloop_learning.Layer.setDebugInfo | ( | self, | |
"int" | layerIndex | ||
) |
setDebugInfo(Layer self, int layerIndex) Parameters ---------- layerIndex: int
"void" feedforward_closedloop_learning.Layer.setDecay | ( | self, | |
"double" | _decay | ||
) |
setDecay(Layer self, double _decay) Parameters ---------- _decay: double
"void" feedforward_closedloop_learning.Layer.setError | ( | self, | |
* | args | ||
) |
setError(Layer self, double _error) Parameters ---------- _error: double setError(Layer self, int i, double _error) Parameters ---------- i: int _error: double
"void" feedforward_closedloop_learning.Layer.setErrors | ( | self, | |
"double *" | _errors | ||
) |
setErrors(Layer self, double * _errors) Parameters ---------- _errors: double *
"void" feedforward_closedloop_learning.Layer.setInput | ( | self, | |
"int" | inputIndex, | ||
"double" | input | ||
) |
setInput(Layer self, int inputIndex, double input) Parameters ---------- inputIndex: int input: double
"void" feedforward_closedloop_learning.Layer.setInputs | ( | self, | |
"double *" | _inputs | ||
) |
setInputs(Layer self, double * _inputs) Parameters ---------- _inputs: double *
"void" feedforward_closedloop_learning.Layer.setLearningRate | ( | self, | |
"double" | _learningRate | ||
) |
setLearningRate(Layer self, double _learningRate) Parameters ---------- _learningRate: double
"void" feedforward_closedloop_learning.Layer.setMaxDetLayer | ( | self, | |
"int" | _m | ||
) |
setMaxDetLayer(Layer self, int _m) Parameters ---------- _m: int
"void" feedforward_closedloop_learning.Layer.setMomentum | ( | self, | |
"double" | _momentum | ||
) |
setMomentum(Layer self, double _momentum) Parameters ---------- _momentum: double
"void" feedforward_closedloop_learning.Layer.setNormaliseWeights | ( | self, | |
"Layer::WeightNormalisation" | _normaliseWeights | ||
) |
setNormaliseWeights(Layer self, Layer::WeightNormalisation _normaliseWeights) Parameters ---------- _normaliseWeights: enum Layer::WeightNormalisation
"void" feedforward_closedloop_learning.Layer.setStep | ( | self, | |
"long" | step | ||
) |
setStep(Layer self, long step) Parameters ---------- step: long
"void" feedforward_closedloop_learning.Layer.setUseThreads | ( | self, | |
"int" | _useThreads | ||
) |
setUseThreads(Layer self, int _useThreads) Parameters ---------- _useThreads: int