code: def _make_loops(
      loop_vars: List[Var], extents: List[int]
  ) -> List[For]:
      assert len(loop_vars) == len(extents)
      return [
          For(
              loop_var=loop_var,
              min=0,
              extent=extent,
              kind=ForKind.SERIAL,
              body=Evaluate(0),
          )
          for loop_var, extent in zip(loop_vars, extents)
      ]
  
imports: from typing import List
  import pytest
  import tvm
  import tvm.testing
  from tvm.meta_schedule.testing import te_workload
  from tvm.script import tir
  from tvm.te import create_prim_func
  from tvm.tir import Evaluate, For, ForKind, IndexMap, Schedule, Var, decl_buffer, floordiv, floormod
  from tvm.tir.analysis import expr_deep_equal
  from tvm.tir.function import TensorIntrin
  from tvm.tir.schedule.analysis import TensorizeInfo, get_auto_tensorize_mapping_info, get_tensorize_loop_mapping, is_output_block, suggest_index_map
  from tvm.tir.stmt_functor import pre_order_visit
  from tvm.tir.tensor_intrin.cuda import WMMA_SYNC_16x16x16_f16f16f16_INTRIN, WMMA_SYNC_16x16x16_f16f16f32_INTRIN
  from tvm.tir.tensor_intrin.x86 import dot_product_16x4_u8i8i32_desc
label_desc: Use image node_id 2 for calling a global function with example usage: _make_loops(loop_vars, extents) and returns: unknown