code: def test_autocast_fused_layer_norm(
      self, dtype, elementwise_affine, memory_efficient
  ):
      bf16_fwd_thresholds = dict(rtol=1.6e-2, atol=3e-4)
      bf16_bwd_thresholds = dict(rtol=1.6e-2, atol=3e-3)
      batch_size = 16
      normalized_shape = [32, 16]
      native = torch.nn.LayerNorm(
          normalized_shape=normalized_shape,
          elementwise_affine=elementwise_affine,
      ).to(device="cuda", dtype=dtype)
      fused = FusedLayerNorm(
          normalized_shape=normalized_shape,
          elementwise_affine=elementwise_affine,
          memory_efficient=memory_efficient,
      ).cuda()
      native_x, fused_x = _prep_inputs(
          batch_size, normalized_shape, dtype
      )
  
      expected = native(native_x)
      with torch.cuda.amp.autocast(dtype=dtype):
          actual = fused(fused_x)
      tols = (
          {"rtol": None, "atol": None}
          if dtype == torch.half
          else bf16_fwd_thresholds
      )
      # original tests used torch.testing.assert_allclose, which disables dtype checking by default.
      # link to issue here: https://github.com/pytorch/pytorch/issues/61844
      torch.testing.assert_close(
          actual, expected, **tols, check_dtype=False
      )
  
      g_native = torch.rand_like(expected)
      with torch.no_grad():
          g_fused = g_native.clone()
      expected.backward(g_native)
      actual.backward(g_fused)
  
      if dtype != torch.half:
          tols = bf16_bwd_thresholds
      elif memory_efficient:
          tols = {"rtol": 1e-3, "atol": 1e-4}
      else:
          tols = {"rtol": None, "atol": None}
      torch.testing.assert_close(
          native_x.grad, fused_x.grad, **tols, check_dtype=False
      )
  
imports: import torch
  from apex.normalization import FusedLayerNorm
  from apex.normalization import FusedRMSNorm
  from apex.normalization import MixedFusedLayerNorm
  from apex.normalization import MixedFusedRMSNorm
  from torch.testing._internal import common_utils
  from torch.testing._internal.common_device_type import instantiate_device_type_tests
  from itertools import product
label_desc: Use image node_id 13 for calling the TestFusedLayerNorm obj's underlying member method code with example usage: obj.test_autocast_fused_layer_norm(dtype, elementwise_affine, memory_efficient) without return types