class_docstr: Base class for ONNX exportable model describing metadata on how to export the model through the ONNX format.
docstr: Generate inputs for ONNX Runtime using the reference model inputs. Override this to run inference with seq2seq
  models which have the encoder and decoder exported as separate ONNX files.
  
  Args:
      reference_model_inputs ([`Mapping[str, Tensor]`):
          Reference inputs for the model.
  
  Returns:
      `Mapping[str, Tensor]`: The mapping holding the kwargs to provide to the model's forward function
docstr_tok: ["Generate","inputs","for","ONNX","Runtime","using","the","reference","model","inputs",".","Override","this","to","run","inference","with","seq2seq","models","which","have","the","encoder","and","decoder","exported","as","separate","ONNX","files",".","Args",":","reference_model_inputs","(","[","`","Mapping","[","str",",","Tensor","]","`",")",":","Reference","inputs","for","the","model",".","Returns",":","`","Mapping","[","str",",","Tensor","]","`",":","The","mapping","holding","the","kwargs","to","provide","to","the","model","'s","forward","function"]
code: def generate_dummy_inputs_onnxruntime(
      self, reference_model_inputs: Mapping[str, Any]
  ) -> Mapping[str, Any]:
      """
      Generate inputs for ONNX Runtime using the reference model inputs. Override this to run inference with seq2seq
      models which have the encoder and decoder exported as separate ONNX files.
  
      Args:
          reference_model_inputs ([`Mapping[str, Tensor]`):
              Reference inputs for the model.
  
      Returns:
          `Mapping[str, Tensor]`: The mapping holding the kwargs to provide to the model's forward function
      """
      return reference_model_inputs
  
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 16 for calling the OnnxConfig obj's underlying member method code with example usage: obj.generate_dummy_inputs_onnxruntime(reference_model_inputs) and returns: reference_model_inputs