code: def test_error_message_fp8_non_h100(self, device) -> None:
      (k, l, m) = (16, 48, 32)
      x = torch.rand((k, l), device=device).to(torch.float8_e4m3fn)
      y = torch.rand((m, l), device=device).to(torch.float8_e4m3fn).t()
      self.assertRaisesRegex(
          RuntimeError,
          r"torch\.\_scaled\_mm is only supported on devices with compute capability \>\= 9\.0",
          lambda: torch._scaled_mm(x, y, out_dtype=torch.float32),
      )
  
imports: import unittest
  from itertools import product
  from functools import partial
  from typing import Optional
  import torch
  from torch.quantization._quantized_conversions import pack_int4_to_int8, quantized_weight_reorder_for_mixed_dtypes_linear_cutlass
  from torch.testing import make_tensor
  from torch.testing._internal.common_cuda import SM53OrLater, _get_torch_cuda_version
  from torch.testing._internal.common_device_type import dtypes, instantiate_device_type_tests, onlyCUDA, tol, toleranceOverride
  from torch.testing._internal.common_utils import IS_ARM64, IS_JETSON, IS_WINDOWS, parametrize, run_tests, skipIfRocmVersionLessThan, TEST_WITH_ROCM, skipIfRocm, TestCase
label_desc: Use image node_id 9 for calling the TestFP8MatmulCuda obj's underlying member method code with example usage: obj.test_error_message_fp8_non_h100(device) without return types