code: def test_amp_batch_norm_backward(self):
      device = "cuda"
      grad_out = torch.randn(
          (1, 2, 16, 16), dtype=torch.float16, device=device
      )
      x = torch.randn(
          (1, 2, 16, 16), dtype=torch.float16, device=device
      )
      weight = torch.randn((2,), dtype=torch.float32, device=device)
      rmean = torch.randn((2,), dtype=torch.float32, device=device)
      rvar = torch.randn((2,), dtype=torch.float32, device=device)
      mean = torch.randn((0,), dtype=torch.float32, device=device)
  
      ref = torch.ops.aten.native_batch_norm_backward(
          grad_out,
          x,
          weight,
          rmean,
          rvar,
          mean,
          mean,
          False,
          1e-05,
          [True, True, True],
      )
      res = torch._decomp.decompositions.native_batch_norm_backward(
          grad_out,
          x,
          weight,
          rmean,
          rvar,
          mean,
          mean,
          False,
          1e-05,
          [True, True, True],
      )
      for a, b in zip(ref, res):
          self.assertEqual(a.stride(), b.stride())
          self.assertEqual(a.dtype, b.dtype)
  
imports: from collections import defaultdict
  from torch import Tensor
  import torch.autograd
  from torch._decomp import core_aten_decompositions, decomposition_table
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils._pytree import tree_map, tree_flatten, tree_unflatten
  from torch.utils import _pytree
  from torch.testing import make_tensor
  from torch.testing._internal.common_cuda import tf32_off
  from torch.testing._internal.common_utils import unMarkDynamoStrictTest
  from torch.testing._internal.common_utils import is_iterable_of_tensors, IS_WINDOWS, TestCase, skipIfCrossRef, suppress_warnings, TEST_WITH_ASAN, TEST_WITH_SLOW, run_tests, skipIfTorchDynamo
  from torch.testing._internal.common_modules import module_db, modules
  from torch.testing._internal.common_device_type import onlyNativeDeviceTypes, ops, instantiate_device_type_tests, onlyCPU, onlyCUDA
  from torch.testing._internal.common_methods_invocations import op_db, skip, skipOps, xfail
  from torch._dispatch.python import enable_python_dispatcher
  from torch._ops import DispatchKey
  import itertools
  import functools
  from functools import partial
  import unittest
label_desc: Use image node_id 3 for calling the DecompOneOffTests obj's underlying member method code with example usage: obj.test_amp_batch_norm_backward() without return types