code: def expected(
      A: T.Buffer((32, 8), "float32"), B: T.Buffer((32,), "float32")
  ):
      T.func_attr({"target": T.target("cuda", host="llvm")})
      threadIdx_y = T.launch_thread("threadIdx.y", 32)
      red_buf0 = T.allocate([1], "float32", "local")
      threadIdx_x = T.launch_thread("threadIdx.x", 8)
      red_buf0_1 = T.Buffer((1,), data=red_buf0, scope="local")
      with T.attr(
          T.comm_reducer(lambda x0, y0: x0 + y0, [T.float32(0)]),
          "reduce_scope",
          T.reinterpret("handle", T.uint64(0)),
      ):
          mask = T.decl_buffer([1], "uint32", scope="local")
          t0 = T.decl_buffer([1], "float32", scope="local")
          A_1 = T.Buffer((256,), data=A.data)
          red_buf0_1[0] = A_1[threadIdx_y * 8 + threadIdx_x]
          mask[0] = T.bitwise_and(
              T.tvm_warp_activemask(),
              T.shift_left(
                  T.uint32(255),
                  T.uint32(8) * T.Cast("uint32", threadIdx_y),
              ),
          )
          t0[0] = T.tvm_warp_shuffle_down(
              mask[0], red_buf0_1[0], 4, 32, 32
          )
          red_buf0_1[0] = red_buf0_1[0] + t0[0]
          t0[0] = T.tvm_warp_shuffle_down(
              mask[0], red_buf0_1[0], 2, 32, 32
          )
          red_buf0_1[0] = red_buf0_1[0] + t0[0]
          t0[0] = T.tvm_warp_shuffle_down(
              mask[0], red_buf0_1[0], 1, 32, 32
          )
          red_buf0_1[0] = red_buf0_1[0] + t0[0]
          red_buf0_1[0] = T.tvm_warp_shuffle(
              mask[0], red_buf0_1[0], 8 * threadIdx_y, 32, 32
          )
      if threadIdx_x == 0:
          B_1 = T.Buffer((32,), data=B.data)
          B_1[threadIdx_y] = red_buf0_1[0]
  
imports: import tvm
  import tvm.testing
  from tvm.script import tir
label_desc: Use image node_id 2 for calling the TestMultiGroupMask1 obj's underlying member method code with example usage: obj.expected(A, B) without return types