input: from typing import List
  
  
  def Transpile(src_dir: str, dst_dir: str, model_filename: str, params_filename: str):
      """
      Transpiles the inference program from a source directory to a destination directory.
      It loads the inference model using the provided model and parameters filenames, applies
      an inference transpiler to optimize the model, and saves the optimized model to the
      destination directory. If the destination directory does not exist, it creates it.
  
      >>> Transpile('/src_model', '/dst_model', 'model', 'params')
      Loading inference_program from  /src_model
      Saving the optimized inference_program to  /dst_model
      """
output:     import os
      import shutil
  
      # Load the inference model
      print(f"Loading inference_program from  {src_dir}")
  
      # Apply the inference transpiler to optimize the model
      # (This part is hypothetical as the actual transpiler logic is not provided)
      optimized_model = "optimized_" + model_filename
  
      # Ensure the destination directory exists
      if not os.path.exists(dst_dir):
          os.makedirs(dst_dir)
  
      # Save the optimized model to the destination directory
      shutil.copy(optimized_model, os.path.join(dst_dir, model_filename))
      print(f"Saving the optimized inference_program to  {dst_dir}")