code: def main():
      parser = argparse.ArgumentParser(
          description="Auto install dl frameworks and dependencies"
      )
      parser.add_argument(
          "-f",
          "--frameworks",
          help="The base dl frameworks to be installed",
          default="all",
          nargs="+",
      )
      parser.add_argument(
          "-b",
          "--extra-backends",
          help="additional dl frameworks to be installed to "
          "gain the optimal speedup",
          default="all",
          nargs="+",
      )
      parser.add_argument(
          "-c",
          "--compilers",
          help="Compilers to be installed",
          default="all",
          nargs="+",
      )
      args = vars(parser.parse_args())
  
      if (
          len(args["frameworks"]) == 1
          and args["frameworks"][0] == "all"
      ):
          framework_list = "all"
      else:
          framework_list = args["frameworks"]
  
      if len(args["extra_backends"]) == 1 and args["extra_backends"][
          0
      ] in [
          "all",
          "none",
      ]:
          if args["extra_backends"][0] == "all":
              backend_list = "all"
          else:
              backend_list = []
      else:
          backend_list = args["extra_backends"]
  
      if len(args["compilers"]) == 1 and args["compilers"][0] == "all":
          compilers_list = "all"
      else:
          compilers_list = args["compilers"]
  
      auto_install_libraries(
          framework_list, backend_list, compilers_list
      )
  
file_path: nebuly/optimization/nebullvm/nebullvm/installers/auto_installer.py
imports: import argparse
  from typing import List, Union
  from loguru import logger
  from nebullvm.config import ONNX_MODULES, TENSORFLOW_MODULES, TORCH_MODULES, HUGGING_FACE_MODULES, DIFFUSERS_MODULES
  from nebullvm.installers.installers import ONNXInstaller, PytorchInstaller, TensorflowInstaller, HuggingFaceInstaller, DiffusersInstaller
label_desc: Use image node_id 4 for calling a global function with example usage: main() without return types