code: def test2():
      mem = ContiguousMemoryAllocator(512, torch.half, "cpu")
      a1 = mem.allocate_tensor(64).mul_(0.0).add_(1.0)
      a2 = mem.allocate_tensor(64).mul_(0.0).add_(2.0)
      a3 = mem.allocate_tensor(64).mul_(0.0).add_(3.0)
      a4 = mem.allocate_tensor(64).mul_(0.0).add_(4.0)
      a5 = mem.allocate_tensor(64).mul_(0.0).add_(5.0)
      a6 = mem.allocate_tensor(64).mul_(0.0).add_(6.0)
      a7 = mem.allocate_tensor(64).mul_(0.0).add_(7.0)
      a8 = mem.allocate_tensor(64).mul_(0.0).add_(8.0)
      mem.release_tensor(a2)
      mem.release_tensor(a4)
      mem.release_tensor(a6)
      mem.release_tensor(a8)
      mem.print_allocation(resolution=100)
  
      a9 = mem.allocate_tensor(128).mul_(0.0).add_(9.0)
      a10 = mem.allocate_tensor(64).mul_(0.0).add_(10.0)
      a11 = mem.allocate_tensor(64).mul_(0.0).add_(11.0)
      mem.release_tensor(a1)
      mem.release_tensor(a5)
      mem.print_allocation(resolution=100)
      a12 = mem.allocate_tensor(128).mul_(0.0).add_(12.0)
      mem.print_allocation(resolution=100)
      print(f"a7:{a7}")
      print(f"a9:{a9}")
      print(f"a10:{a10}")
      print(f"a11:{a11}")
      print(f"a12:{a12}")
      assert (
          a7.norm() + a9.norm() + a10.norm() + a11.norm() + a12.norm()
      ) == 460.75, "TestFailed"
  
label_desc: Use image node_id 2 for calling a global function with example usage: test2() without return types