code: def convert_onnx(m, save_path):
      m.eval()
      x = torch.rand(1, 3, 288, 288, requires_grad=True)
  
      # export the model
      torch.onnx.export(
          m,  # model being run
          x,  # model input (or a tuple for multiple inputs)
          save_path,  # where to save the model (can be a file or file-like object)
          export_params=True,
          opset_version=11,
      )
  
imports: from typing import Union, List
  import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 3 for calling a global function with example usage: convert_onnx(m, save_path) without return types