mkl_sparse_convert_csr doesn't change rows & cols

Hello, I am using mkl_sparse_convert_csr to perform transpose function by calling with SPARSE_OPERATION_TRANSPOSE option.

However, the values of the result matrix is transposed correctly with the row & col left unchanged.

Here is the code.

#include <bits/stdc++.h>
#include <mkl.h>
#include <omp.h>
using namespace std;

namespace {
// Output MKL sparse matrix in CSR format.
void Print(const sparse_matrix_t &mat) {
  sparse_index_base_t index_base;
  MKL_INT rows, cols;
  MKL_INT *rows_start, *rows_end, *col_idx;
  float *values;
  assert(mkl_sparse_s_export_csr(mat, &index_base, &rows, &cols, &rows_start,
                                 &rows_end, &col_idx,
                                 &values) == SPARSE_STATUS_SUCCESS);
  cout << "IndexBase="<< (index_base == SPARSE_INDEX_BASE_ZERO ? 0 : 1)
       << endl;
  cout << "Rows="<< rows << " Cols="<< cols << endl;
  for (int i = 0; i < rows; ++i) {
    cout << "RowsKey="<< i << ":";
    for (int j = rows_start[i]; j < rows_end[i]; ++j) {
      cout << "("<< col_idx[j] << ","<< values[j] << ")";
    }
    cout << endl;
  }
}

} // namespace

int main() {
  // Auto log flush.
  cout.setf(std::ios::unitbuf);
  mkl_set_num_threads(1);

  const MKL_INT n = 4, m = 5;

  // Create matrix a.
  vector<float> values = {1, 2, 2, 1};
  vector<MKL_INT> rows_start = {0, 0, 2, 3};
  vector<MKL_INT> rows_end = {0, 2, 3, 4};
  vector<MKL_INT> col_idx = {0, 2, 2, 3};

  sparse_matrix_t mat_a;
  assert(mkl_sparse_s_create_csr(&mat_a, SPARSE_INDEX_BASE_ZERO, n, m,
                                 rows_start.data(), rows_end.data(),
                                 col_idx.data(),
                                 values.data()) == SPARSE_STATUS_SUCCESS);
  cout << "Matrix A:"<< endl;
  Print(mat_a);

  sparse_matrix_t mat_b;
  assert(mkl_sparse_convert_csr(mat_a, SPARSE_OPERATION_TRANSPOSE, &mat_b) ==
         SPARSE_STATUS_SUCCESS);
  cout << "Matrix B:"<< endl;
  Print(mat_b);

  mkl_sparse_destroy(mat_b);
  mkl_sparse_destroy(mat_a);
  return 0;
}
 

The result is here:

Matrix A:
IndexBase=0
Rows=4 Cols=5
RowsKey=0:
RowsKey=1:(0,1)(2,2)
RowsKey=2:(2,2)
RowsKey=3:(3,1)
Matrix B:
IndexBase=0
Rows=4 Cols=5
RowsKey=0:(1,1)
RowsKey=1:
RowsKey=2:(1,2)(2,2)
RowsKey=3:(3,1)

As you can see, the rows=4 & cols=5 in the matrix B.

Any idea what the problem is? Is there any useful information?

Thank you very much in advance.

Zixi