code: def check_onnxruntime_requirements(minimum_version: version.Version):
      """
      Checks that ONNX Runtime is installed and if version is recent enough.
  
      Args:
          minimum_version (`packaging.version.Version`):
              The minimum version allowed for the onnxruntime package.
  
      Raises:
          ImportError: If onnxruntime is not installed or too old version is found
      """
      try:
          import onnxruntime
      except ImportError:
          raise ImportError(
              "ONNX Runtime doesn't seem to be currently installed. "
              "Please install ONNX Runtime by running `pip install onnxruntime`"
              " and relaunch the conversion."
          )
  
      ort_version = version.parse(onnxruntime.__version__)
      if ort_version < ORT_QUANTIZE_MINIMUM_VERSION:
          raise ImportError(
              f"We found an older version of ONNX Runtime ({onnxruntime.__version__}) "
              f"but we require the version to be >= {minimum_version} to enable all the conversions options.\n"
              "Please update ONNX Runtime by running `pip install --upgrade onnxruntime`"
          )
  
imports: import copy
  from typing import TYPE_CHECKING, Dict, List, Optional, Tuple, Union
  import torch
  from packaging import version
  from transformers.models.speecht5.modeling_speecht5 import SpeechT5HifiGan
  from transformers.utils import is_tf_available, is_torch_available
  from ...utils import DIFFUSERS_MINIMUM_VERSION, ORT_QUANTIZE_MINIMUM_VERSION, check_if_diffusers_greater, is_diffusers_available, logging
  from ...utils.import_utils import _diffusers_version
  from ..tasks import TasksManager
  from .constants import ONNX_DECODER_NAME, ONNX_DECODER_WITH_PAST_NAME, ONNX_ENCODER_NAME
label_desc: Use image node_id 1 for calling a global function with example usage: check_onnxruntime_requirements(minimum_version) without return types