Feedforward Closedloop Learning
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Public Member Functions | |
def | __init__ (self, "int" num_of_inputs, "int *" num_of_neurons_per_layer_array) |
"void" | doStep (self, *args) |
"double" | getOutput (self, "int" index) |
"void" | setLearningRate (self, "double" learningRate) |
"void" | setLearningRateDiscountFactor (self, "double" _learningRateDiscountFactor) |
"void" | setDecay (self, "double" decay) |
"void" | setMomentum (self, "double" momentum) |
"void" | setActivationFunction (self, "Neuron::ActivationFunction" _activationFunction) |
"void" | initWeights (self, *args) |
"void" | seedRandom (self, "int" s) |
"void" | setBias (self, "double" _bias) |
"int" | getNumLayers (self) |
"Layer *" | getLayer (self, "int" i) |
"Layer *" | getOutputLayer (self) |
"int" | getNumInputs (self) |
"Layer **" | getLayers (self) |
"bool" | saveModel (self, "char const *" name) |
"bool" | loadModel (self, "char const *" name) |
Properties | |
thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") | |
Proxy of C++ FeedforwardClosedloopLearning class.
def feedforward_closedloop_learning.FeedforwardClosedloopLearning.__init__ | ( | self, | |
"int" | num_of_inputs, | ||
"int *" | num_of_neurons_per_layer_array | ||
) |
__init__(FeedforwardClosedloopLearning self, int num_of_inputs, int * num_of_neurons_per_layer_array) -> FeedforwardClosedloopLearning Parameters ---------- num_of_inputs: int num_of_neurons_per_layer_array: int *
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.doStep | ( | self, | |
* | args | ||
) |
doStep(FeedforwardClosedloopLearning self, double * input, double * error) Parameters ---------- input: double * error: double * doStep(FeedforwardClosedloopLearning self, double * input, double * error) Parameters ---------- input: double * error: double *
Reimplemented in feedforward_closedloop_learning.FeedforwardClosedloopLearningWithFilterbank.
"Layer *" feedforward_closedloop_learning.FeedforwardClosedloopLearning.getLayer | ( | self, | |
"int" | i | ||
) |
getLayer(FeedforwardClosedloopLearning self, int i) -> Layer Parameters ---------- i: int
"Layer **" feedforward_closedloop_learning.FeedforwardClosedloopLearning.getLayers | ( | self | ) |
getLayers(FeedforwardClosedloopLearning self) -> Layer **
"int" feedforward_closedloop_learning.FeedforwardClosedloopLearning.getNumInputs | ( | self | ) |
getNumInputs(FeedforwardClosedloopLearning self) -> int
"int" feedforward_closedloop_learning.FeedforwardClosedloopLearning.getNumLayers | ( | self | ) |
getNumLayers(FeedforwardClosedloopLearning self) -> int
"double" feedforward_closedloop_learning.FeedforwardClosedloopLearning.getOutput | ( | self, | |
"int" | index | ||
) |
getOutput(FeedforwardClosedloopLearning self, int index) -> double Parameters ---------- index: int
"Layer *" feedforward_closedloop_learning.FeedforwardClosedloopLearning.getOutputLayer | ( | self | ) |
getOutputLayer(FeedforwardClosedloopLearning self) -> Layer
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.initWeights | ( | self, | |
* | args | ||
) |
initWeights(FeedforwardClosedloopLearning self, double max=0.001, int initBias=1, Neuron::WeightInitMethod weightInitMethod=MAX_OUTPUT_RANDOM) Parameters ---------- max: double initBias: int weightInitMethod: enum Neuron::WeightInitMethod
"bool" feedforward_closedloop_learning.FeedforwardClosedloopLearning.loadModel | ( | self, | |
"char const *" | name | ||
) |
loadModel(FeedforwardClosedloopLearning self, char const * name) -> bool Parameters ---------- name: char const *
"bool" feedforward_closedloop_learning.FeedforwardClosedloopLearning.saveModel | ( | self, | |
"char const *" | name | ||
) |
saveModel(FeedforwardClosedloopLearning self, char const * name) -> bool Parameters ---------- name: char const *
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.seedRandom | ( | self, | |
"int" | s | ||
) |
seedRandom(FeedforwardClosedloopLearning self, int s) Parameters ---------- s: int
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.setActivationFunction | ( | self, | |
"Neuron::ActivationFunction" | _activationFunction | ||
) |
setActivationFunction(FeedforwardClosedloopLearning self, Neuron::ActivationFunction _activationFunction) Parameters ---------- _activationFunction: enum Neuron::ActivationFunction
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.setBias | ( | self, | |
"double" | _bias | ||
) |
setBias(FeedforwardClosedloopLearning self, double _bias) Parameters ---------- _bias: double
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.setDecay | ( | self, | |
"double" | decay | ||
) |
setDecay(FeedforwardClosedloopLearning self, double decay) Parameters ---------- decay: double
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.setLearningRate | ( | self, | |
"double" | learningRate | ||
) |
setLearningRate(FeedforwardClosedloopLearning self, double learningRate) Parameters ---------- learningRate: double
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.setLearningRateDiscountFactor | ( | self, | |
"double" | _learningRateDiscountFactor | ||
) |
setLearningRateDiscountFactor(FeedforwardClosedloopLearning self, double _learningRateDiscountFactor) Parameters ---------- _learningRateDiscountFactor: double
"void" feedforward_closedloop_learning.FeedforwardClosedloopLearning.setMomentum | ( | self, | |
"double" | momentum | ||
) |
setMomentum(FeedforwardClosedloopLearning self, double momentum) Parameters ---------- momentum: double