code: def check_onnxruntime_requirements(minimum_version: Version):
      """
      Check onnxruntime is installed and if the installed version match is recent enough
  
      Raises:
          ImportError: If onnxruntime is not installed or too old version is found
      """
      try:
          import onnxruntime
  
          # Parse the version of the installed onnxruntime
          ort_version = parse(onnxruntime.__version__)
  
          # We require 1.4.0 minimum
          if ort_version < ORT_QUANTIZE_MINIMUM_VERSION:
              raise ImportError(
                  f"We found an older version of onnxruntime ({onnxruntime.__version__}) "
                  f"but we require onnxruntime to be >= {minimum_version} to enable all the conversions options.\n"
                  "Please update onnxruntime by running `pip install --upgrade onnxruntime`"
              )
  
      except ImportError:
          raise ImportError(
              "onnxruntime doesn't seem to be currently installed. "
              "Please install the onnxruntime by running `pip install onnxruntime`"
              " and relaunch the conversion."
          )
  
file_path: transformers/src/transformers/onnx/convert.py
imports: import warnings
  from inspect import signature
  from itertools import chain
  from pathlib import Path
  from typing import TYPE_CHECKING, Iterable, List, Tuple, Union
  import numpy
  from packaging.version import Version, parse
  from ..tokenization_utils_base import PreTrainedTokenizerBase
  from ..utils import TensorType, is_tf_available, is_torch_available, logging
  from .config import OnnxConfig
label_desc: Use image node_id 1 for calling a global function with example usage: check_onnxruntime_requirements(minimum_version) without return types