func maxEigenvalue(m *linalg.Matrix) float64 {
inVec := make(linalg.Vector, m.Rows)
for i := range inVec {
inVec[i] = rand.NormFloat64()
}
inMat := linalg.NewMatrixColumn(inVec)
for i := 0; i < npPowerIterations; i++ {
inMat = m.MulFast(inMat)
vec := linalg.Vector(inMat.Data)
vec.Scale(1 / vec.Mag())
}
outVec := linalg.Vector(m.MulFast(inMat).Data)
return outVec.Mag()
}
func rbmEnergy(r *RBM, input, output []bool) float64 {
inputVec := make(linalg.Vector, len(input))
for i, x := range input {
if x {
inputVec[i] = 1
}
}
outputVec := make(linalg.Vector, len(output))
for i, x := range output {
if x {
outputVec[i] = 1
}
}
energy := inputVec.Dot(r.VisibleBiases)
energy += outputVec.Dot(r.HiddenBiases)
inputCol := linalg.NewMatrixColumn(inputVec)
energy += outputVec.Dot(linalg.Vector(r.Weights.Mul(inputCol).Data))
return -energy
}
