code: def _parameterized_class_attrs_and_values():
      input_values = []
      input_values.extend(
          itertools.product(
              (opset for opset in onnx_test_common.FX_TESTED_OPSETS),
              (
                  pytorch_test_common.TorchModelType.TORCH_NN_MODULE,
                  pytorch_test_common.TorchModelType.TORCH_EXPORT_EXPORTEDPROGRAM,
              ),
          )
      )
      return {
          "attrs": ["opset_version", "model_type"],
          "input_values": input_values,
      }
  
imports: from __future__ import annotations
  import copy
  import itertools
  from typing import Any, Callable, Collection, Mapping, Optional, Tuple, Type, Union
  import onnx_test_common
  import parameterized
  import pytest
  import pytorch_test_common
  import torch
  from onnx_test_common import skip, skip_slow, xfail
  from torch.onnx._internal.diagnostics import _rules
  from torch.testing._internal import common_device_type, common_methods_invocations, common_utils
  from torch.testing._internal.opinfo import core
label_desc: Use image node_id 6 for calling a global function with example usage: _parameterized_class_attrs_and_values() and returns: dict