code: def test_cuda_element_wise():
      @T.prim_func
      def elementwise_0(
          A: T.Buffer((512, 512), "float32"),
          B: T.Buffer((512, 512), "float32"),
      ) -> None:
          # body
          # with T.block("root")
          for i_j_fused_0 in T.thread_binding(256, thread="blockIdx.x"):
              for i_j_fused_1 in T.thread_binding(
                  1024, thread="threadIdx.x"
              ):
                  with T.block("C"):
                      vi = T.axis.spatial(
                          512, (i_j_fused_0 * 1024 + i_j_fused_1) // 512
                      )
                      vj = T.axis.spatial(
                          512, (i_j_fused_0 * 1024 + i_j_fused_1) % 512
                      )
                      T.reads(A[vi, vj])
                      T.writes(B[vi, vj])
                      B[vi, vj] = A[vi, vj] + T.float32(1)
  
      decision_0 = [
          ("SampleCategorical", 5),
      ]
      mod = element_wise
      actual = generate_design_space(
          kind="cuda",
          mod=mod,
          target=Target("nvidia/geforce-rtx-3080", host="llvm"),
          types=ms.schedule_rule.AutoBind,
      )
      check_sketches(
          mod,
          sketches=actual,
          expected_mods=[elementwise_0],
          expected_decisions=[decision_0],
      )
  
file_path: tvm/tests/python/meta_schedule/test_meta_schedule_schedule_rule_auto_bind.py
imports: from tvm import meta_schedule
  from tvm.meta_schedule.testing.space_generation import check_sketches, generate_design_space
  from tvm.script import tir
  from tvm.target import Target
label_desc: Use image node_id 4 for calling a global function with example usage: test_cuda_element_wise() without return types