code: def check_module_version(
      module: ModuleType,
      min_version: str = None,
      max_version: str = None,
  ) -> bool:
      installed_version = module.__version__
  
      if min_version is not None:
          if version.parse(installed_version) < version.parse(
              min_version
          ):
              return False
  
      if max_version is not None:
          if version.parse(installed_version) > version.parse(
              max_version
          ):
              return False
  
      return True
  
imports: import os
  import subprocess
  import sys
  import uuid
  from pathlib import Path
  from types import ModuleType
  from typing import Tuple, Any, List, Dict, Union, Iterable, Sequence, Optional, Callable
  import numpy
  from loguru import logger
  from packaging import version
  from nebullvm.core.models import DeepLearningFramework, Device, ModelParams, DeviceType
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch
  from nebullvm.tools.data import DataManager
  from nebullvm.tools.onnx import extract_info_from_np_data, get_output_info_onnx
  from nebullvm.tools.pytorch import extract_info_from_torch_data, get_output_info_torch
  from nebullvm.tools.tf import extract_info_from_tf_data, get_output_info_tf
label_desc: Use image node_id 10 for calling a global function with example usage: check_module_version(module, min_version, max_version) and returns: True, False, False