code: def test_lower_rfactor():
      n = te.size_var("n")
      m = te.size_var("m")
      A = te.placeholder((n, m), name="A")
      k = te.reduce_axis((0, m), "k")
      B = te.compute((n,), lambda i: te.sum(A[i, k], axis=k), name="B")
      s = te.create_schedule(B.op)
      ko, ki = s[B].split(B.op.reduce_axis[0], factor=16)
      BF = s.rfactor(B, ki)
      xo, xi = s[B].split(s[B].op.axis[0], factor=32)
      s[B.op].bind(xo, te.thread_axis("blockIdx.x"))
      s[B.op].bind(xi, te.thread_axis("threadIdx.y"))
      s[B].bind(s[B].op.reduce_axis[0], te.thread_axis("threadIdx.x"))
      s[BF].compute_at(s[B], s[B].op.reduce_axis[0])
      fapi = tvm.lower(s, [A, B])
  
imports: import tvm
  from tvm import te
label_desc: Use image node_id 1 for calling a global function with example usage: test_lower_rfactor() without return types