code: def backward_vadd(dtype, ndim, reduce1st, req):
      s, X, in_grad_a, in_grad, c_list = compute_backward_vadd(
          dtype, ndim, reduce1st, req
      )
      for t in c_list:
          axes = [axis for axis in t.op.axis]
          fused = s[t].fuse(*axes)
          s[t].parallel(fused)
      return s, [X, in_grad_a, in_grad]
  
file_path: mxnet/contrib/tvmop/basic/ufunc.py
imports: import tvm
  from ..None import defop, AllTypes, RealTypes
  from ..None import assign_by_req, reduce_axes
label_desc: Use image node_id 5 for calling a global function with example usage: backward_vadd(dtype, ndim, reduce1st, req) and returns: s,  list