code: def backward_vadd_gpu(dtype, ndim, reduce1st, req):
      s, X, in_grad_a, in_grad, c_list = compute_backward_vadd(
          dtype, ndim, reduce1st, req
      )
      num_thread = 64
      for t in c_list:
          block_x = tvm.te.thread_axis("blockIdx.x")
          thread_x = tvm.te.thread_axis("threadIdx.x")
          axes = [axis for axis in t.op.axis]
          fused = s[t].fuse(*axes)
          bx, tx = s[t].split(fused, factor=num_thread)
          s[t].bind(bx, block_x)
          s[t].bind(tx, thread_x)
      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 6 for calling a global function with example usage: backward_vadd_gpu(dtype, ndim, reduce1st, req) and returns: s,  list