code: def test_inductor_reuse_buffer_after_inplace_collective(self):
      self._init_process_group()
  
      def func(arg: torch.Tensor) -> torch.Tensor:
          # Expect allocation
          buf0 = arg + 42
          ar0 = torch.ops._c10d_functional.all_reduce(
              buf0, "avg", "default"
          )
          ar0 = torch.ops._c10d_functional.wait_tensor(ar0)
          # Expect allocation
          buf1 = torch.mm(arg, ar0)
          # Expect buf0 to be reused
          buf2 = torch.mm(arg, buf1)
          return buf1, buf2
  
      arg = torch.rand(4, 4, device=self.device)
      compiled = torch.compile(func)
      code = run_and_get_triton_code(compiled, arg)
      (
          FileCheck()
          # Expect allocation
          .check("buf0 = empty(")
          .check("torch.ops._c10d_functional.all_reduce_.default(buf0")
          .check("torch.ops._c10d_functional.wait_tensor.default(buf0")
          # Expect allocation
          .check("buf5 = empty(")
          .check("extern_kernels.mm(arg0_1, buf0, out=buf5")
          # Expect buf0 to be reused
          .check("buf6 = buf0; del buf0  # reuse")
          .check("extern_kernels.mm(arg0_1, buf5, out=buf6")
          # Expect no extra copy on return
          .check("return (buf5, buf6, )")
          .run(code)
      )
      out = compiled(arg)
      correct = func(arg)
      assert same(out, correct), f"{out} va {correct}"
  
imports: import unittest
  from typing import List
  import torch
  import torch.distributed
  from torch._C import FileCheck
  from torch._dynamo.utils import same
  from torch._inductor.utils import fresh_inductor_cache, run_and_get_triton_code
  from torch.testing._internal.common_distributed import MultiProcessTestCase, requires_nccl, skip_if_lt_x_gpu
  from torch.testing._internal.common_utils import run_tests
  from torch.utils._triton import has_triton
  import sys
label_desc: Use image node_id 17 for calling the C10DFunctionalNativeTest obj's underlying member method code with example usage: obj.test_inductor_reuse_buffer_after_inplace_collective() and returns: buf1,  buf2