501 lines
17 KiB
C++
501 lines
17 KiB
C++
#include <cstdio>
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#include <cstdlib>
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#include <stdexcept>
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#include <vector>
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#include <algorithm>
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//#include "/home/fanasina/progr_/ptens0neD/tensor/tens0neD/tens0neD.h"
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#include "tensor/tens0neD/tens0neD.h"
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//#include "include/tens0neD.h"
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//#include "cudatensor.h"
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//#include "/home/fanasina/progr_/ptens0neD/permutation/permutation.h"
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#include "permutation/permutation.h"
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template<typename T>
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void transform(Tensor<T>& Dst, const Tensor<T>& Src, int* perm, int sz) {
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transform(Dst.Dim, Src.Dim, perm, sz);
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dimension dsrc = Src.Dim;
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dimension ddst = Dst.Dim;
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int coor[dsrc.rank];
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int dcoor[ddst.rank], ldst;
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for (int i = 0; i < Src.Dim.size; i++) {
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dsrc.LinearToCoord(coor, i);
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for (int j = 0; j < dsrc.rank; j++) dcoor[j] = coor[perm[j]];
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ldst = ddst.CoordToLinear(dcoor);
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Dst.elements[ldst] = Src.elements[i];
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}
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}
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template void transform<float>(Tensor<float>& Dst, const Tensor<float>& Src, int* perm, int sz);
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template void transform<double>(Tensor<double>& Dst, const Tensor<double>& Src, int* perm, int sz);
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template<typename T>
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Tensor<T>& Tensor<T>::operator=(const Tensor<T>& M) {
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Dim = M.Dim;
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for (int i = 0; i < Dim.size; ++i) elements[i] = M.elements[i];
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return *this;
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}
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template<typename T>
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Tensor<T>& Tensor<T>::operator*=(const T& val) {
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//for (int i = 0; i < rank.size; ++i) elements[i] *= val;
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return *this;
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}
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template<typename T>
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Tensor<T>& operator*(const Tensor<T>& M0, const Tensor<T>& M1) {
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struct dimension d; add(d, M0.Dim, M1.Dim);
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Tensor<T> Mret(d);
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for (int i = 0; i < M0.Dim.size; ++i) Mret.elements[i] = M0.elements[i];
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Mret.Dim += M0.Dim;
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return Mret;
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}
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void subArray(int* dst, int* src, int debDst, int finDst, int debSrc) {
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for (int i = debDst; i < finDst; i++) {
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dst[i] = src[i + debSrc];
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}
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}
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void concatArray(int* dst, int* src0, int* src1, int debDst, int debSrc0, int finSrc0, int debSrc1, int finSrc1) {
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int i = debDst;
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for (int j = debSrc0; j < finSrc0; j++) {
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dst[i++] = src0[j];
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}
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for (int j = debSrc1; j < finSrc1; j++) {
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dst[i++] = src1[j];
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}
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}
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template<typename T>
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void Tensor<T>::initVal(T val) {
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int* coord = new int[Dim.rank];
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T pp, mult = 0.5;
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for (int i = 0; i < Dim.size; i++) {
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Dim.LinearToCoord(coord, i);
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elements[i] = val;
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pp = mult;
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for (int j = 0; j < Dim.rank; j++) {
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elements[i] += (coord[j] + 1) * pp;
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pp *= mult;
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}
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}
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}
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template
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void Tensor<float>::initVal(float val);
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template
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void Tensor<double>::initVal(double val);
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template<typename T>
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void Tensor<T>::print() {
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Dim.print();
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int* coord = new int[Dim.rank];
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int begin = 0, end = Dim.rank - 1;
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//int beginInv = Dim.rank - 1, endInv = 0;
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int (*iter)(int) = incr;
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//int (*iterInv)(int) = decr;
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bool (*cond)(int, int) = isLessEqThan;
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//bool (*condInv)(int, int) = isGreatEqThan;
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if (Dim.endian == false) {
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begin = Dim.rank - 1; end = 0;
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//beginInv = 0; endInv = Dim.rank - 1;
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iter = decr; cond = isGreatEqThan;
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//iterInv = incr; condInv = isLessEqThan;
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}
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for (int i = 0; i < Dim.size; i++) {
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Dim.LinearToCoord(coord, i);
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//if (coord[Dim.rank - 1] == 0) {
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if (coord[begin] == 0) {
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for (int j = begin; cond(j, end); j = iter(j)) {
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//for (int j = Dim.rank - 1; j >= 0; j--) {
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if (coord[j] == 0) {
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printf("(");
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}
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else break;
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}
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}
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//printf(" ");for (int j = 0; j < Dim.rank; j++) printf("[%d]", coord[j]); printf(" ");
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//printf(" "); for (int j = beginInv; condInv(j, endInv); j = iterInv(j)) printf("[%d]", coord[j]); printf(" ");
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//printf(" "); for (int k = beginInv; condInv(k, endInv); k = iterInv(k)) { printf("[%d]", coord[k]); } printf(" ");
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printf(" %.6f ", elements[i]);
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//if (coord[Dim.rank - 1] == Dim.dim[Dim.rank - 1] - 1) {
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if (coord[begin] == Dim.dim[begin] - 1) {
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for (int j = begin; cond(j, end); j = iter(j)) {
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//for (int j = Dim.rank - 1; j >= 0; j--) {
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if (coord[j] == Dim.dim[j] - 1) {
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printf(")");
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}
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else break;
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}
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}
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}
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printf("\n");
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}
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template
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void Tensor<float>::print();
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template
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void Tensor<double>::print();
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template<typename T>
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void tensorProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1) {
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add(M.Dim, M0.Dim, M1.Dim);
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M.initTensor();
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int* coord = new int[M.Dim.rank];
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int* coord0 = new int[M0.Dim.rank], lin0;
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int* coord1 = new int[M1.Dim.rank], lin1;
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for (int i = 0; i < M.Dim.size; i++) {
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M.Dim.LinearToCoord(coord, i);
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subArray(coord0, coord, 0, M0.Dim.rank, 0);
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subArray(coord1, coord, 0, M1.Dim.rank, M0.Dim.rank);
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lin0 = (M0.Dim).CoordToLinear(coord0);
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lin1 = (M1.Dim).CoordToLinear(coord1);
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M.elements[i] = M0.elements[lin0] * M1.elements[lin1];
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}
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}
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template
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void tensorProd<double>(Tensor<double>& M, const Tensor<double>& M1, const Tensor<double>& M0);
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template
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void tensorProd<float>(Tensor<float>& M, const Tensor<float>& M1, const Tensor<float>& M0);
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bool checkMatchProdTensor(const dimension& d0, const dimension& d1, int nestingDepth) {
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if (d0.rank <= nestingDepth || d1.rank <= nestingDepth) return false;
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for (int i = 0; i < nestingDepth;i++) {
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if (d1.dim[i] != d0.dim[d0.rank - nestingDepth + i]) return false;
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}
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return true;
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}
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bool checkMatchProdTensorReverse(const dimension& d0, const dimension& d1, int nestingDepth) {
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if (d0.rank <= nestingDepth || d1.rank <= nestingDepth) return false;
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for (int i = 0; i < nestingDepth;i++) {
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if (d1.dim[i] != d0.dim[d0.rank - 1 - i]) return false;
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}
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return true;
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}
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void extractDimNestingDepth(dimension& dM, const dimension& d0, const dimension& d1, int nestingDepth) {
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int len0 = d0.rank - nestingDepth;
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int len1 = d1.rank - nestingDepth;
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int* tsub0 = new int[len0];
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int* tsub1 = new int[len1];
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int* tDk1 = new int[nestingDepth];
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int* tDk0 = new int[nestingDepth];
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subArray(tsub0, d0.dim, 0, len0, 0);
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subArray(tsub1, d1.dim, 0, len1, nestingDepth);
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subArray(tDk1, d1.dim, 0, nestingDepth, 0);
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subArray(tDk0, d0.dim, 0, nestingDepth, len0);
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dimension dSub0(len0, tsub0);
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dimension dSub1(len1, tsub1);
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dimension dM1(nestingDepth, tDk1);
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dimension dM0(nestingDepth, tDk0);
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min(dM, dM0, dM1);
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//max(dM, dM0, dM1);
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}
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// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xl = y0,x{l+1}=y1, x{n}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
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// M[x0,x1,x3..xl x{l+1}...xn] X M[xn,x{n-1},x{n-2}...xl y{l+1} ..ym] = M[x0,x1..xly{l+1}...y{n+m-2l}] (deep = l > 0)
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//M[[i][j]]=sum_{[k]}M0[[i][k]]*M[[k][j]]
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template<typename T>
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void tensorContractnProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth) {
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if (!checkMatchProdTensor(M0.Dim, M1.Dim, nestingDepth)) {
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printf("Deep = %d\n", nestingDepth);
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//throw std::check_ProdTensor(" Failed imbrication order in Multiplication matrix ");
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//throw std::invalid_argument(" Failed imbrication order in Multiplication matrix ");
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}
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int len0 = M0.Dim.rank - nestingDepth;
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int len1 = M1.Dim.rank - nestingDepth;
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int* tsub0 = new int[len0];
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int* tsub1 = new int[len1];
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int* tDk1 = new int[nestingDepth];
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int* tDk0 = new int[nestingDepth];
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subArray(tsub0, M0.Dim.dim, 0, len0, 0);
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subArray(tsub1, M1.Dim.dim, 0, len1, nestingDepth);
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subArray(tDk1, M1.Dim.dim, 0, nestingDepth, 0);
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subArray(tDk0, M0.Dim.dim, 0, nestingDepth, len0);
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dimension dSub0(len0, tsub0);
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dimension dSub1(len1, tsub1);
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dimension dM1(nestingDepth, tDk1);
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dimension dM0(nestingDepth, tDk0);
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dimension dM;
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min(dM, dM0, dM1);
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//max(dM, dM0, dM1);
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add(M.Dim, dSub0, dSub1);
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M.initTensor();
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int* coord = new int[M.Dim.rank];
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int* coord0 = new int[len0], lin0;
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int* coord1 = new int[len1], lin1;
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int* coordM0 = new int[M0.Dim.rank];
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int* coordM1 = new int[M1.Dim.rank];
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int* Koord = new int[nestingDepth];
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for (int i = 0; i < M.Dim.size; i++) {
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M.Dim.LinearToCoord(coord, i);
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subArray(coord0, coord, 0, len0, 0);
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subArray(coord1, coord, 0, len1, len0);
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M.elements[i] = 0;
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for (int k = 0; k < dM.size; k++) {
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dM.LinearToCoord(Koord, k);
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concatArray(coordM0, coord0, Koord, 0, 0, len0, 0, nestingDepth);
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concatArray(coordM1, Koord, coord1, 0, 0, nestingDepth, 0, len1);
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lin0 = (M0.Dim).CoordToLinear(coordM0);
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lin1 = (M1.Dim).CoordToLinear(coordM1);
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M.elements[i] += M0.elements[lin0] * M1.elements[lin1];
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}
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}
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}
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template
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void tensorContractnProd<float>(Tensor<float>& M, const Tensor<float>& M0, const Tensor<float>& M1, int nestingDepth);
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template
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void tensorContractnProd<double>(Tensor<double>& M, const Tensor<double>& M0, const Tensor<double>& M1, int nestingDepth);
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void reverseDim(dimension& d, const dimension& d0) {
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d.rank = d0.rank;
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d.size = d0.size;
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if (d.dim != NULL) free(d.dim);
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d.dim = (int*)malloc(d.rank * sizeof(int));
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for (int i = 0; i < d.rank; i++) d.dim[i] = d0.dim[d.rank - i - 1];
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}
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template<typename T>
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void reverseTensor(Tensor<T>& M, const Tensor<T>& M0) {
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reverseDim(M.Dim, M0.Dim);
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size_t id;
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int coor[M0.Dim.rank];
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for (size_t i = 0; i < M.Dim.size; i++) {
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M0.Dim.LinearToCoord(coor, i);
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reverseArray(coor, M0.Dim.rank);
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id = M.Dim.CoordToLinear(coor);
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M.elements[id] = M0.elements[i];
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}
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}
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// M[x0,x1,x3..xn] X M[y0,y1,y3..ym] = M[z0,z1...zp] (deep = l > 0) /exists 1<= l<...<l=n / xn = y0,x{n-1}=y1, x{n-l}=yl et zi=xi i<n-l et zj=y{j-(n-l)} j>=n-l alor p=n+m-2l
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// M[x0,x1,x3..xl x{l+1}..xn] X M[xn,x{n-1},..x{l+1}xl y{l+1}..ym] = M[x0,x1..xly{l+1}...y{n+m-2l}] (deep = l > 0)
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//M[[i][j]]=sum_{[k]}M0[[i][k]]*M[[k][j]]
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template<typename T>
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void tensorContractnReverseProd(Tensor<T>& M, const Tensor<T>& M0, const Tensor<T>& M1, int nestingDepth) {
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if (!checkMatchProdTensorReverse(M0.Dim, M1.Dim, nestingDepth)) {
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printf("Failed in Deep = %d\n", nestingDepth);
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//throw std::check_ProdTensor(" Failed imbrication order in Multiplication matrix ");
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//throw std::invalid_argument(" Failed imbrication order in Multiplication matrix ");
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}
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int len0 = M0.Dim.rank - nestingDepth;
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int len1 = M1.Dim.rank - nestingDepth;
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int* tsub0 = new int[len0];
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int* tsub1 = new int[len1];
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int* tDk1 = new int[nestingDepth];
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int* tDk0 = new int[nestingDepth];
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subArray(tsub0, M0.Dim.dim, 0, len0, 0);
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subArray(tsub1, M1.Dim.dim, 0, len1, nestingDepth);
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subArray(tDk1, M1.Dim.dim, 0, nestingDepth, 0);
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subArray(tDk0, M0.Dim.dim, 0, nestingDepth, len0);
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dimension dSub0(len0, tsub0);
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dimension dSub1(len1, tsub1);
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dimension dM1(nestingDepth, tDk1);
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dimension dM0(nestingDepth, tDk0);
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dimension dM;
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bool rev;
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minReverse(dM, dM0, dM1, rev);
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if (rev) reverseArray(dM.dim, dM.rank);
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//max(dM, dM0, dM1);
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add(M.Dim, dSub0, dSub1);
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M.initTensor();
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int* coord = new int[M.Dim.rank];
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int* coord0 = new int[len0], lin0;
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int* coord1 = new int[len1], lin1;
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int* coordM0 = new int[M0.Dim.rank];
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int* coordM1 = new int[M1.Dim.rank];
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int* Koord = new int[nestingDepth];
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for (int i = 0; i < M.Dim.size; i++) {
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M.Dim.LinearToCoord(coord, i);
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subArray(coord0, coord, 0, len0, 0);
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subArray(coord1, coord, 0, len1, len0);
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M.elements[i] = 0;
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for (int k = 0; k < dM.size; k++) {
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dM.LinearToCoord(Koord, k);
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concatArray(coordM0, coord0, Koord, 0, 0, len0, 0, nestingDepth);
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reverseArray(Koord, nestingDepth);
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concatArray(coordM1, Koord, coord1, 0, 0, nestingDepth, 0, len1);
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lin0 = (M0.Dim).CoordToLinear(coordM0);
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lin1 = (M1.Dim).CoordToLinear(coordM1);
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M.elements[i] += M0.elements[lin0] * M1.elements[lin1];
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}
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}
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}
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template
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void tensorContractnReverseProd<float>(Tensor<float>& M, const Tensor<float>& M0, const Tensor<float>& M1, int nestingDepth);
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template
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void tensorContractnReverseProd<double>(Tensor<double>& M, const Tensor<double>& M0, const Tensor<double>& M1, int nestingDepth);
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template<typename T>
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void permuteTensorDef(Tensor<T>& M, const Tensor<T>& M0, permutation p) {
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if (p.size == M0.Dim.rank) {
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M.Dim.rank = M0.Dim.rank;
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M.Dim.size = M0.Dim.size;
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M.Dim.initDim();
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M.initTensor();
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//permuteArray(M.Dim.dim, M0.Dim.dim, p);
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//for (int i = 0; i < p.size; i++) { M.Dim.dim[i] = M0.Dim.dim[p.perm[i]]; }
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p.permute(M.Dim.dim, M0.Dim.dim);
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size_t img;
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int coor[p.size];
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int rooc[p.size];
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for (size_t i = 0; i < M.Dim.size;i++) {
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M0.Dim.LinearToCoord(coor, i);
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p.permute(rooc, coor);
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img = M.Dim.CoordToLinear(rooc);
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if (img >= M.Dim.size) printf(" i: %ld vs img:%ld size: %ld\n", i, img, M.Dim.size);
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M.elements[img] = M0.elements[i];
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}
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}
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}
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template
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void permuteTensorDef(Tensor<float>& M, const Tensor<float>& M0, permutation p);
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template<typename T>
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bool scanPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<T>& Msecond, const Tensor<T>& Mfirst, int contractNest) {
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if (contractNest < Msecond.Dim.rank && contractNest < Mfirst.Dim.rank) {
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std::vector<int> founded;
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int begin = Mfirst.Dim.rank - contractNest, tmp;
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for (int i = 0; i < Msecond.Dim.rank;i++) perm[i] = i;
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for (int i = begin; i < Mfirst.Dim.rank; i++) {
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for (int j = 0; j < Msecond.Dim.rank;j++) {
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if (std::find(founded.begin(), founded.end(), perm[j]) == founded.end()) {// not found
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if (Msecond.Dim.dim[perm[j]] == Mfirst.Dim.dim[i]) {
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founded.push_back(perm[j]);
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tmp = perm[i - begin];
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perm[i - begin] = perm[j];
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perm[j] = tmp;
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}
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}
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}
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}
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return (founded.size() == contractNest);
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}
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return false;
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}
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template
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bool scanPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<float>& Msecond, const Tensor<float>& Mfirst, int contractNest);
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|
|
|
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template<typename T>
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|
bool scanInvPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<T>& Msecond, const Tensor<T>& Mfirst, int contractNest) {
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|
if (contractNest < Msecond.Dim.rank && contractNest < Mfirst.Dim.rank) {
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|
std::vector<int> founded;
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|
int begin = Mfirst.Dim.rank - contractNest, tmp;
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for (int i = 0; i < Msecond.Dim.rank;i++) perm[i] = i;
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|
for (int i = begin; i < Mfirst.Dim.rank; i++) {
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|
for (int j = 0; j < Msecond.Dim.rank;j++) {
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|
if (std::find(founded.begin(), founded.end(), j) == founded.end()) {// not found
|
|
if (Msecond.Dim.dim[j] == Mfirst.Dim.dim[perm[i - begin]]) {
|
|
founded.push_back(j);
|
|
tmp = perm[i - begin];
|
|
perm[i - begin] = j;
|
|
perm[j] = tmp;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
return (founded.size() == contractNest);
|
|
}
|
|
return false;
|
|
}
|
|
template
|
|
bool scanInvPermuteMatchContractTensorfromSrcToDst(int* perm, const Tensor<float>& Msecond, const Tensor<float>& Mfirst, int contractNest);
|
|
|
|
|
|
void LinearTransformCoord(size_t& dst, size_t src, int* inversePerm, size_t Msize, dimension dDst, dimension dSrc) {
|
|
size_t sm = src;
|
|
size_t pp = Msize;
|
|
size_t s = 0;
|
|
size_t p = 1;
|
|
int ret;// = new int[rank];
|
|
int i;
|
|
for (i = 0; i < dSrc.rank; ++i) {
|
|
pp /= dSrc.dim[i];
|
|
ret = sm / pp;
|
|
p = 1;
|
|
for (int j = inversePerm[i] + 1; j < dDst.rank;j++) {
|
|
p *= dDst.dim[j];
|
|
}
|
|
s += ret * p;
|
|
|
|
sm %= pp;
|
|
|
|
}
|
|
dst = s;
|
|
if (s > Msize) printf("I have a problem in LinearTransformCoord: s:%ld siez:%ld \n", s, Msize);
|
|
|
|
}
|
|
|
|
|
|
template<typename T>
|
|
void permuteTensor(Tensor<T>& M, const Tensor<T>& M0, permutation p) {
|
|
if (p.size == M0.Dim.rank) {
|
|
M.Dim.rank = M0.Dim.rank;
|
|
M.Dim.size = M0.Dim.size;
|
|
M.Dim.initDim();
|
|
M.initTensor();
|
|
|
|
if (p.size == M0.Dim.rank) p.permute(M.Dim.dim, M0.Dim.dim);
|
|
else {
|
|
printf("something wrong perm, not the same size as M0.Dim.rank\n");
|
|
exit(1);
|
|
}
|
|
size_t img = 0;
|
|
printf("in permuteTensor:\n");
|
|
M0.Dim.print();
|
|
M.Dim.print();
|
|
setInit se(M.Dim.rank, 0);
|
|
int invP[M.Dim.rank];
|
|
inverseArray(invP, p.perm, M.Dim.rank);
|
|
for (size_t i = 0; i < M.Dim.size;i++) {
|
|
//LinearTransformCoord(img, i, p.perm, M.Dim.size, M.Dim, M0.Dim);
|
|
LinearTransformCoord(img, i, invP, M.Dim.size, M.Dim, M0.Dim);
|
|
M.elements[img] = M0.elements[i];
|
|
}
|
|
}
|
|
}
|
|
|
|
template
|
|
void permuteTensor(Tensor<float>& M, const Tensor<float>& M0, permutation p);
|
|
|