code: def _sum_cpu(itype, otype, ndim, reduce1st_dim, req):
      (
          s,
          a,
          output_placeholder,
          final_output,
          tensor_list,
      ) = _compute_sum(itype, otype, ndim, reduce1st_dim, req)
      for t in tensor_list:
          axes = [axis for axis in t.op.axis]
          fused = s[t].fuse(*axes)
          s[t].parallel(fused)
      return s, [a, output_placeholder, final_output]
  
imports: import tvm
  from ..None import defop
  from ..utils import reduce_axes, assign_by_req
label_desc: Use image node_id 2 for calling a global function with example usage: _sum_cpu(itype, otype, ndim, reduce1st_dim, req) and returns: s,  list