code: def _csr_sample_values(
      n_row, n_col, Ap, Aj, Ax, Bi, Bj, not_found_val=0
  ):
      """Populate data array for a set of rows and columns
      Args
          n_row : total number of rows in input array
          n_col : total number of columns in input array
          Ap : indptr array for input sparse matrix
          Aj : indices array for input sparse matrix
          Ax : data array for input sparse matrix
          Bi : array of rows to extract from input sparse matrix
          Bj : array of columns to extract from input sparse matrix
      Returns
          Bx : data array for output sparse matrix
      """
  
      Bi[Bi < 0] += n_row
      Bj[Bj < 0] += n_col
  
      return _csr_sample_values_kern(
          n_row, n_col, Ap, Aj, Ax, Bi, Bj, not_found_val, size=Bi.size
      )
  
imports: import cupy
  from cupy import _core
  from cupyx.scipy.sparse._base import isspmatrix
  from cupyx.scipy.sparse._base import spmatrix
  from cupy.cuda import device
  from cupy.cuda import runtime
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: _csr_sample_values(n_row, n_col, Ap, Aj, Ax, Bi, Bj, not_found_val) and returns: _csr_sample_values_kern