code: def _save_dataset(input_data: DataManager, path: Path):
      path.mkdir(exist_ok=True)
      for i, x in enumerate(input_data):
          torch.save(x, path / f"input_{i}.pt")
  
imports: import json
  from pathlib import Path
  from tempfile import TemporaryDirectory
  from typing import Callable, Dict
  import numpy
  from loguru import logger
  from nebullvm.operations.optimizations.compressors.base import Compressor
  from nebullvm.optional_modules.torch import torch, Module
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.pytorch import save_with_torch_fx, load_with_torch_fx
  from nebullvm.tools.venv import run_in_different_venv
label_desc: Use image node_id 3 for calling a global function with example usage: _save_dataset(input_data, path) without return types