class_docstr: Base class for ONNX exportable model describing metadata on how to export the model through the ONNX format.
code: def restore_ops(self):
      for spec in self._patching_specs:
          orig_op = (
              spec.orig_op
              if spec.op_wrapper is None
              else spec.op_wrapper(spec.orig_op)
          )
          setattr(spec.o, spec.name, orig_op)
  
imports: import copy
  import dataclasses
  import warnings
  from abc import ABC, abstractmethod
  from collections import OrderedDict
  from typing import TYPE_CHECKING, Any, Callable, Dict, Iterable, List, Mapping, Optional, Tuple, Union
  import numpy
  from packaging import version
  from ..utils import TensorType, is_torch_available, is_vision_available, logging
  from .utils import ParameterFormat, compute_effective_axis_dimension, compute_serialized_parameters_size
label_desc: Use image node_id 18 for calling the OnnxConfig obj's underlying member method code with example usage: obj.restore_ops() without return types