code: def _sum_gpu(itype, otype, ndim, reduce1st_dim, req):
      (
          s,
          a,
          output_placeholder,
          final_output,
          tensor_list,
      ) = _compute_sum(itype, otype, ndim, reduce1st_dim, req)
      num_threads = 64
      for t in tensor_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_threads)
          s[t].bind(bx, block_x)
          s[t].bind(tx, thread_x)
      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 3 for calling a global function with example usage: _sum_gpu(itype, otype, ndim, reduce1st_dim, req) and returns: s,  list