input: def Transpile(src_dir: str, dst_dir: str, model_filename: str, params_filename: str) -> None:
      """
      Transpile the given inference model from the source directory to the destination directory.
      This function loads an inference program, applies the inference transpiler, and saves the optimized program.
  
      >>> Transpile('/source_path', '/destination_path', 'model.pdmodel', 'params.pdiparams')
      Loading inference_program from  /source_path
      Saving the optimized inference_program to  /destination_path
      """
      place = fluid.CPUPlace()
      exe = fluid.Executor(place)
  
      inference_scope = fluid.core.Scope()
      with fluid.scope_guard(inference_scope):
          print("Loading inference_program from ", src_dir)
          [inference_program, feed_target_names,
           fetch_targets] = fluid.io.load_inference_model(src_dir, exe, model_filename, params_filename)
  
          inference_transpiler_program = inference_program.clone()
          t = fluid.InferenceTranspiler()
          t.transpile(inference_transpiler_program, place)
  
          print("Saving the optimized inference_program to ", dst_dir)
          if not os.path.isdir(dst_dir):
              os.makedirs(dst_dir)
          model_path = os.path.join(dst_dir, model_filename)
          with open(model_path, "wb") as f:
              f.write(inference_transpiler_program.desc.serialize_to_string())
          fluid.io.save_persistables(exe, dst_dir, inference_transpiler_program, params_filename)
output:     place = fluid.CPUPlace()
      exe = fluid.Executor(place)
  
      inference_scope = fluid.core.Scope()
      with fluid.scope_guard(inference_scope):
          print("Loading inference_program from ", src_dir)
          [inference_program, feed_target_names,
           fetch_targets] = fluid.io.load_inference_model(src_dir, exe, model_filename, params_filename)
  
          inference_transpiler_program = inference_program.clone()
          t = fluid.InferenceTranspiler()
          t.transpile(inference_transpiler_program, place)
  
          print("Saving the optimized inference_program to ", dst_dir)
          if not os.path.isdir(dst_dir):
              os.makedirs(dst_dir)
          model_path = os.path.join(dst_dir, model_filename)
          with open(model_path, "wb") as f:
              f.write(inference_transpiler_program.desc.serialize_to_string())
          fluid.io.save_persistables(exe, dst_dir, inference_transpiler_program, params_filename)