code: def __init__(
      self,
      config: "PretrainedConfig",
      task: str = "default",
      patching_specs: List[PatchingSpec] = None,
      use_past: bool = False,
  ):
      super().__init__(config, task=task, patching_specs=patching_specs)
      self.use_past = use_past
  
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 1 to create a new OnnxConfigWithPast object from inherited base classes: OnnxConfig, ABC with example: obj = OnnxConfigWithPast(config, task, patching_specs, use_past)