code: def test_reference_masked(self, device, dtype, op):
      op_name = op.name.rsplit(".", 1)[-1]
      ref_op = reference_functions[op_name]
      sample_inputs = op.sample_inputs(device, dtype)
      for sample_input in sample_inputs:
          t_inp, t_args, t_kwargs = (
              sample_input.input,
              sample_input.args,
              sample_input.kwargs,
          )
          if op_name in {"var", "std"} and not (
              t_inp.dtype.is_floating_point or t_inp.dtype.is_complex
          ):
              # torch.var/torch.std does not support integer inputs
              continue
          actual = op.op(t_inp, *t_args, **t_kwargs)
          expected = ref_op(t_inp, *t_args, **t_kwargs)
          if t_kwargs.get("mask") is None:
              outmask = None
          else:
              outmask = torch.masked._output_mask(
                  op.op, t_inp, *t_args, **t_kwargs
              )
          self.assertEqualMasked(actual, expected, outmask)
  
imports: import itertools
  import torch
  from typing import List, Any
  from functools import wraps
  import unittest
  from torch.testing._internal.common_utils import skipIfTorchDynamo
  from torch.testing._internal.common_utils import TestCase, parametrize, suppress_warnings, _TestParametrizer, run_tests
  from torch.testing._internal.common_methods_invocations import op_db, SampleInput
  from torch.testing._internal.common_device_type import instantiate_device_type_tests, ops, onlyNativeDeviceTypes, precisionOverride
label_desc: Use image node_id 2 for calling the TestMasked obj's underlying member method code with example usage: obj.test_reference_masked(device, dtype, op) without return types