code: def test_python_wrapper(self):
      f, args = self._generate(device="cuda")
      compiled = torch.compile(f, dynamic=True)
      result, code = run_and_get_cpp_code(compiled, *args)
  
      FileCheck().check(
          "pool1 = empty_strided(((4*s0*s1) + (align(4*(s0*s0))), ), (1, )"
      ).check_next(
          "buf0 = alloc_from_pool(pool1, 0, torch.float32, (s0, s0), (s0, 1))"
      ).check(
          "buf1 = alloc_from_pool(pool1, align((4*s0) + (4*s0*((-1) + s0))),"
      ).run(
          code
      )
      self.assertTrue(same(f(*args), result))
  
file_path: pytorch/test/inductor/test_memory_planning.py
imports: import sys
  from torch.testing._internal.common_utils import IS_CI, IS_WINDOWS, skipIfRocm
  import unittest
  from typing import List
  import torch
  from test_torchinductor import run_and_get_cpp_code
  from torch._C import FileCheck
  from torch._dynamo.test_case import run_tests, TestCase
  from torch._dynamo.utils import same
  from torch._inductor import config
  from torch.utils._triton import has_triton
label_desc: Use image node_id 2 for calling the TestMemoryPlanning obj's underlying member method code with example usage: obj.test_python_wrapper() without return types