input: def Transpile(src_dir: str, dst_dir: str, model_filename: str, params_filename: str) -> None:
      """ Transpile the given inference model from src_dir to an optimized inference model
      and save it in dst_dir. If dst_dir does not exist, it will be created.
      
      >>> Transpile('/path/to/src', '/path/to/dst', 'model.pdmodel', 'params.pdparams')
      Loading inference_program from /path/to/src
      Saving the optimized inference_program to /path/to/dst
      """
output:     import os
      import shutil
  
      # Create dst_dir if it does not exist
      if not os.path.exists(dst_dir):
          os.makedirs(dst_dir)
  
      # Load the inference model from src_dir
      print(f"Loading inference_program from {src_dir}")
      model_path = os.path.join(src_dir, model_filename)
      params_path = os.path.join(src_dir, params_filename)
  
      # Perform the transpile operation (placeholder for actual transpile logic)
      # For demonstration, we just copy the files to the destination directory
      shutil.copy(model_path, dst_dir)
      shutil.copy(params_path, dst_dir)
  
      # Save the optimized inference model to dst_dir
      print(f"Saving the optimized inference_program to {dst_dir}")