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fix: fix coo to csr tranfer bug

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kradchen
2025-03-27 09:07:31 +08:00
parent 4b878976bb
commit 4f1ac5ac9b
1 changed files with 29 additions and 18 deletions
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47
src/transmissionReconstruction/reconstruction/solvingEquationSystem/TVAL/TVAL.cpp
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@@ -15,9 +15,7 @@
#include <Eigen/Sparse> #include <Eigen/Sparse>
#include <Spectra/GenEigsSolver.h> #include <Spectra/GenEigsSolver.h>
#include <Spectra/MatOp/SparseGenMatProd.h> #include <Spectra/MatOp/SparseGenMatProd.h>
#include <Eigen/Core>
#include <Eigen/SparseCore>
#include <Eigen/Eigenvalues>
namespace Recon namespace Recon
{ {
@@ -86,34 +84,47 @@ namespace Recon
int * xIdxs = new int[M.getRowVector().getDataSize()]; int * xIdxs = new int[M.getRowVector().getDataSize()];
std::copy(M.getRowVector().getData(),M.getRowVector().getData()+M.getRowVector().getDataSize(),xIdxs); std::copy(M.getRowVector().getData(),M.getRowVector().getData()+M.getRowVector().getDataSize(),xIdxs);
Aurora::Matrix values = M.getValVector(); Aurora::Matrix values = M.getValVector();
size_t cols = M.getM(), rows = M.getN(); size_t rows = M.getM(), cols = M.getN();
int nz = std::max(M.getColVector().getDataSize(),std::max(M.getRowVector().getDataSize(),M.getValVector().getDataSize())); int nz = std::max(M.getColVector().getDataSize(),std::max(M.getRowVector().getDataSize(),M.getValVector().getDataSize()));
sparse_matrix_t A; sparse_matrix_t A;
sparse_matrix_t csrA; sparse_matrix_t csrA;
mkl_sparse_s_create_coo(&A, sparse_index_base_t::SPARSE_INDEX_BASE_ZERO, rows, cols, nz, yIdxs, xIdxs,values.getData());
mkl_sparse_convert_csr(A, sparse_operation_t::SPARSE_OPERATION_NON_TRANSPOSE, &csrA); mkl_sparse_s_create_coo(&A, sparse_index_base_t::SPARSE_INDEX_BASE_ZERO, rows,cols, nz, xIdxs,yIdxs,values.getData());
int n_rows,n_cols; // csr transpose means csc, 行列互换
int *rows_start,*rows_end,*col_indx; mkl_sparse_convert_csr(A, sparse_operation_t::SPARSE_OPERATION_TRANSPOSE, &csrA);
float * csrValues;
//export csc matrix , row->col, col->row
int nRows = 0;
int nCols = 0;
int *cscColStart,*cscColEnd,*cscRowIdx;
float * cscValues;
sparse_index_base_t index; sparse_index_base_t index;
mkl_sparse_s_export_csr(csrA, &index, &n_rows, &n_cols, &rows_start, &rows_end, &col_indx, &csrValues); mkl_sparse_s_export_csr(csrA, &index, &nCols, &nRows, &cscColStart, &cscColEnd, &cscRowIdx, &cscValues);
//free A & temp input index
mkl_sparse_destroy(A); mkl_sparse_destroy(A);
delete [] xIdxs; delete [] xIdxs;
delete [] yIdxs; delete [] yIdxs;
int *row_idx = new int[n_rows+1]; // add last unit to cols
std::copy(rows_start,rows_start+n_rows,row_idx); int *cscColIdx = new int[nCols+1];
row_idx[n_rows] = rows_end[n_rows-1]; std::copy(cscColStart,cscColEnd+nCols,cscColIdx);
cscColIdx[nCols] = nz;
// prepare other input
float* bData = b.getData(); float* bData = b.getData();
// std::copy(b.getData(),b.getData()+b.getDataSize(),bData);
size_t bDims[3]={(size_t)b.getDimSize(0),(size_t)b.getDimSize(1),(size_t)b.getDimSize(2)}; size_t bDims[3]={(size_t)b.getDimSize(0),(size_t)b.getDimSize(1),(size_t)b.getDimSize(2)};
size_t rdims[3] = {(size_t)dims[0], (size_t)dims[1], (size_t)dims[2]}; size_t rdims[3] = {(size_t)dims[0], (size_t)dims[1], (size_t)dims[2]};
bool pagelocked = false; bool pagelocked = false;
auto result = TVALGPU( col_indx, row_idx, csrValues, M.getM(), M.getN(), nz, bData, bDims, rdims, opt, device, false);
//call TVAL
auto result = TVALGPU( cscRowIdx,cscColIdx, cscValues, M.getM(), M.getN(), nz, bData, bDims, rdims, opt, device, false);
// free csrA, cscColStart, cscColEnd, cscRowIdx, cscValues will free with it
mkl_sparse_destroy(csrA); mkl_sparse_destroy(csrA);
delete [] row_idx; //free cscColIdx
//delete [] bData; delete [] cscColIdx;
return Aurora::Matrix::fromRawData(result.data, result.dims[0],result.dims[1],result.dims[2]); return Aurora::Matrix::fromRawData(result.data, result.dims[0],result.dims[1],result.dims[2]);
// return Aurora::Matrix();
} }
} }