code: def save_with_torch_fx(model: torch.nn.Module, path: Path):
      traced_model = torch.fx.symbolic_trace(model)
      traced_model.to_folder(path, FX_MODULE_NAME)
  
file_path: nebuly/optimization/nebullvm/nebullvm/tools/pytorch.py
imports: from pathlib import Path
  from typing import List, Tuple, Optional, Dict, Union, Sequence
  from loguru import logger
  from nebullvm.core.models import Device, DataType, DeviceType, InputInfo
  from nebullvm.optional_modules.torch import torch, DataLoader
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.diffusers import get_default_dynamic_info
label_desc: Use image node_id 1 for calling a global function with example usage: save_with_torch_fx(model, path) without return types