code: def __init__(
      self,
      config: "PretrainedConfig",
      task: str = "default",
      patching_specs: "List[PatchingSpec]" = None,
  ):
      super().__init__(config, task, patching_specs)
      config.onnx_export = True
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/longformer/configuration_longformer.py
imports: from collections import OrderedDict
  from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
  from ...configuration_utils import PretrainedConfig
  from ...onnx import OnnxConfig
  from ...utils import TensorType, logging
label_desc: Use image node_id 1 to create a new LongformerOnnxConfig object from inherited base classes: OnnxConfig with example: obj = LongformerOnnxConfig(config, task, patching_specs)