public CliquePotentialFunction getCliquePotentialFunction(double[] x) { double[] rawScales = separateLopScales(x); double[] scales = ArrayMath.softmax(rawScales); double[][][] learnedLopExpertWeights2D = lopExpertWeights2D; if (backpropTraining) { learnedLopExpertWeights2D = separateLopExpertWeights2D(x); } double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales); return new LinearCliquePotentialFunction(combinedWeights2D); }
double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales);
public CliquePotentialFunction getCliquePotentialFunction(double[] x) { double[] rawScales = separateLopScales(x); double[] scales = ArrayMath.softmax(rawScales); double[][][] learnedLopExpertWeights2D = lopExpertWeights2D; if (backpropTraining) { learnedLopExpertWeights2D = separateLopExpertWeights2D(x); } double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales); return new LinearCliquePotentialFunction(combinedWeights2D); }
public CliquePotentialFunction getCliquePotentialFunction(double[] x) { double[] rawScales = separateLopScales(x); double[] scales = ArrayMath.softmax(rawScales); double[][][] learnedLopExpertWeights2D = lopExpertWeights2D; if (backpropTraining) { learnedLopExpertWeights2D = separateLopExpertWeights2D(x); } double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales); return new LinearCliquePotentialFunction(combinedWeights2D); }
double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales);
double[][] combinedWeights2D = combineAndScaleLopWeights2D(numLopExpert, learnedLopExpertWeights2D, scales);