code: def post_process_exported_models(
      self,
      path: Path,
      models_and_onnx_configs: Dict[
          str,
          Tuple[
              Union[
                  "PreTrainedModel", "TFPreTrainedModel", "ModelMixin"
              ],
              "OnnxConfig",
          ],
      ],
      onnx_files_subpaths: List[str],
  ):
      (
          models_and_onnx_configs,
          onnx_files_subpaths,
      ) = super().post_process_exported_models(
          path, models_and_onnx_configs, onnx_files_subpaths
      )
      if self.use_past is True and len(models_and_onnx_configs) == 3:
          models_and_onnx_configs[ONNX_DECODER_NAME][
              1
          ]._decoder_onnx_config.is_merged = True
          models_and_onnx_configs[ONNX_DECODER_NAME][
              1
          ]._decoder_onnx_config.use_cache_branch = False
  
          # Past key values won't be generated by default, but added in the input
          models_and_onnx_configs[ONNX_DECODER_NAME][
              1
          ]._decoder_onnx_config.use_past_in_inputs = True
  
          models_and_onnx_configs[ONNX_DECODER_WITH_PAST_NAME][
              1
          ]._decoder_onnx_config.use_cache_branch = True
          models_and_onnx_configs[ONNX_DECODER_WITH_PAST_NAME][
              1
          ]._decoder_onnx_config.is_merged = True
  
      return models_and_onnx_configs, onnx_files_subpaths
  
imports: from collections import OrderedDict
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Tuple, Union
  from transformers.utils import is_tf_available
  from ...onnx import merge_decoders
  from ...utils import DummyAudioInputGenerator, DummyBboxInputGenerator, DummyInputGenerator, DummyPastKeyValuesGenerator, DummySeq2SeqDecoderTextInputGenerator, DummySeq2SeqPastKeyValuesGenerator, DummyTextInputGenerator, DummyVisionInputGenerator, is_diffusers_available, logging
  from .base import ConfigBehavior, OnnxConfig, OnnxConfigWithPast, OnnxSeq2SeqConfigWithPast
  from .constants import ONNX_DECODER_MERGED_NAME, ONNX_DECODER_NAME, ONNX_DECODER_WITH_PAST_NAME
  from .model_patcher import DecoderModelPatcher
label_desc: Use image node_id 8 for calling the EncoderDecoderBaseOnnxConfig obj's underlying member method code with example usage: obj.post_process_exported_models(path, models_and_onnx_configs, onnx_files_subpaths) and returns: models_and_onnx_configs,  onnx_files_subpaths