code: def test_matmul_relu_non_tensorizable():
      # expected to do nothing on non-tensorizable workloads
      mod = te.create_prim_func(
          te_workload.matmul_relu(  # dtype doesn't match tensor intrin
              n=128,
              m=128,
              k=128,
          )
      )
      (sch,) = generate_design_space(
          kind="cuda",
          mod=mod,
          target=tvm.target.Target("cuda --arch=sm_70"),
          types=None,
          sch_rules=[
              multi_level_tiling_tensor_core(write_reuse_scope="shared")
          ]
          + get_rules("cuda", ms.schedule_rule.AutoInline),
      )
      tvm.ir.assert_structural_equal(mod, sch.mod["main"])
  
file_path: tvm/tests/python/meta_schedule/test_meta_schedule_schedule_rule_mlt_tc.py
imports: import pytest
  import tvm
  import tvm.testing
  from tvm import meta_schedule
  from tvm import te
  from tvm.meta_schedule.testing import te_workload
  from tvm.meta_schedule.testing.space_generation import check_sketches, generate_design_space, get_rules, print_sketches
  from tvm.script import tir
  from tvm.tir.tensor_intrin.cuda import get_wmma_intrin_group
label_desc: Use image node_id 6 for calling a global function with example usage: test_matmul_relu_non_tensorizable() without return types