code: def export(
      model,
      xml_path="model.xml",
      precision="fp32",
      logging=True,
      **kwargs,
  ):
      """
      Function to export pytorch model into openvino and save it to local.
      Any instance of torch.nn.Module including Lightning Module is acceptable.
  
      :param model: Model instance of torch.nn.module to be exported.
      :param xml_path: The path to save openvino model file.
      :param precision: Global precision of model, supported type: 'fp32', 'fp16',
                        defaults to 'fp32'.
      :param logging: whether to log detailed information of model conversion. default: True.
      :param **kwargs: will be passed to model optimizer function.
      """
      # export a model with dynamic axes to enable IR to accept different batches and resolutions
      with TemporaryDirectory() as folder:
          folder = Path(folder)
          pb_path = str(folder)
          model.save(str(folder))
          convert_pb_to_xml(
              pb_path,
              xml_path,
              precision=precision,
              logging=logging,
              **kwargs,
          )
  
imports: from tempfile import TemporaryDirectory
  from ..core.utils import convert_pb_to_xml
  from pathlib import Path
label_desc: Use image node_id 1 for calling a global function with example usage: export(model, xml_path, precision, logging) without return types