Feature/tensors performance #497
@ -308,6 +308,14 @@ internal fun DoubleTensorAlgebra.svdPowerMethodHelper(
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val res = ArrayList<Triple<Double, DoubleTensor, DoubleTensor>>(0)
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val (matrixU, matrixS, matrixV) = USV
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val matrixUStart = matrixU.bufferStart
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val matrixSStart = matrixS.bufferStart
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val matrixVStart = matrixV.bufferStart
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val matrixUBuffer = matrixU.mutableBuffer
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val matrixSBuffer = matrixS.mutableBuffer
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val matrixVBuffer = matrixV.mutableBuffer
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for (k in 0 until min(n, m)) {
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var a = matrix.copy()
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for ((singularValue, u, v) in res.slice(0 until k)) {
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@ -341,13 +349,13 @@ internal fun DoubleTensorAlgebra.svdPowerMethodHelper(
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val uBuffer = res.map { it.second }.flatMap { it.mutableBuffer.array().toList() }.toDoubleArray()
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val vBuffer = res.map { it.third }.flatMap { it.mutableBuffer.array().toList() }.toDoubleArray()
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for (i in uBuffer.indices) {
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matrixU.mutableBuffer.array()[matrixU.bufferStart + i] = uBuffer[i]
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matrixUBuffer[matrixUStart + i] = uBuffer[i]
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}
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for (i in s.indices) {
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matrixS.mutableBuffer.array()[matrixS.bufferStart + i] = s[i]
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matrixSBuffer[matrixSStart + i] = s[i]
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}
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for (i in vBuffer.indices) {
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matrixV.mutableBuffer.array()[matrixV.bufferStart + i] = vBuffer[i]
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matrixVBuffer[matrixVStart + i] = vBuffer[i]
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}
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}
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