code: def _get_csr_submatrix_minor_axis(Ax, Aj, Ap, start, stop):
      """Return a submatrix of the input sparse matrix by slicing minor axis.
  
      Args:
          Ax (cupy.ndarray): data array from input sparse matrix
          Aj (cupy.ndarray): indices array from input sparse matrix
          Ap (cupy.ndarray): indptr array from input sparse matrix
          start (int): starting index of minor axis
          stop (int): ending index of minor axis
  
      Returns:
          Bx (cupy.ndarray): data array of output sparse matrix
          Bj (cupy.ndarray): indices array of output sparse matrix
          Bp (cupy.ndarray): indptr array of output sparse matrix
  
      """
      mask = (start <= Aj) & (Aj < stop)
      mask_sum = cupy.empty(Aj.size + 1, dtype=Aj.dtype)
      mask_sum[0] = 0
      mask_sum[1:] = mask
      cupy.cumsum(mask_sum, out=mask_sum)
      Bp = mask_sum[Ap]
      Bj = Aj[mask] - start
      Bx = Ax[mask]
  
      return Bx, Bj, Bp
  
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 2 for calling a global function with example usage: _get_csr_submatrix_minor_axis(Ax, Aj, Ap, start, stop) and returns: Bx,  Bj,  Bp