code: def convert(
      model: str,
      output: str,
      input_shape: List[int],
      net_path: str,
      net_name: str,
  ):
      x = torch.randn(*input_shape)  # pylint: disable=no-member
      load_package(net_path, net_name)
      model = torch.load(model)
      print("Pytorch model loaded")
      _ = model(x)
      model.eval()
  
      # Export the model
      torch.onnx.export(
          model,
          x,
          output,
          input_names=["input"],
          output_names=["output"],
          do_constant_folding=True,  # whether to execute constant folding for optimization
      )
      print("Model exported to ONNX")
  
imports: from os import path
  from typing import List
  import torch
  from absl import flags, app
  from .utils import reset_flag, load_package
label_desc: Use image node_id 1 for calling a global function with example usage: convert(model, output, input_shape, net_path, net_name) without return types