code: def sum(self, axis=None, dtype=None, out=None):
      validateaxis(axis)
  
      if axis is not None and axis < 0:
          axis += 2
  
      res_dtype = get_sum_dtype(self.dtype)
      num_rows, num_cols = self.shape
      ret = None
  
      if axis == 0:
          mask = self._data_mask()
          x = (self.data * mask).sum(axis=0)
          if x.shape[0] == num_cols:
              res = x
          else:
              res = np.zeros(num_cols, dtype=x.dtype)
              res[: x.shape[0]] = x
          ret = self._ascontainer(res, dtype=res_dtype)
  
      else:
          row_sums = np.zeros((num_rows, 1), dtype=res_dtype)
          one = np.ones(num_cols, dtype=res_dtype)
          dia_matvec(
              num_rows,
              num_cols,
              len(self.offsets),
              self.data.shape[1],
              self.offsets,
              self.data,
              one,
              row_sums,
          )
  
          row_sums = self._ascontainer(row_sums)
  
          if axis is None:
              return row_sums.sum(dtype=dtype, out=out)
  
          ret = self._ascontainer(row_sums.sum(axis=axis))
  
      if out is not None and out.shape != ret.shape:
          raise ValueError("dimensions do not match")
  
      return ret.sum(axis=(), dtype=dtype, out=out)
  
imports: import numpy
  from ._matrix import spmatrix
  from ._base import issparse, _formats, _spbase, sparray
  from ._data import _data_matrix
  from ._sputils import isshape, upcast_char, getdtype, get_sum_dtype, validateaxis, check_shape
  from ._sparsetools import dia_matvec
label_desc: Use image node_id 6 for calling the _dia_base obj's underlying member method code with example usage: obj.sum(axis, dtype, out) and returns: ret, row_sums