code: def test_fliplr_invalid(self, device, dtype):
      x = torch.randn(42).to(dtype)
      with self.assertRaisesRegex(
          RuntimeError, "Input must be >= 2-d."
      ):
          torch.fliplr(x)
      with self.assertRaisesRegex(
          RuntimeError, "Input must be >= 2-d."
      ):
          torch.fliplr(torch.tensor(42, device=device, dtype=dtype))
  
imports: import torch
  import numpy
  from itertools import product, combinations, permutations, chain
  from functools import partial
  import random
  import warnings
  import unittest
  from torch import nan
  from torch.testing import make_tensor
  from torch.testing._internal.common_utils import TestCase, run_tests, skipIfTorchDynamo, torch_to_numpy_dtype_dict, IS_JETSON
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, onlyCPU, onlyCUDA, dtypes, onlyNativeDeviceTypes, dtypesIfCUDA, largeTensorTest
  from torch.testing._internal.common_dtype import all_types_and_complex_and, all_types, all_types_and
label_desc: Use image node_id 20 for calling the TestShapeOps obj's underlying member method code with example usage: obj.test_fliplr_invalid(device, dtype) without return types