input: Write a function named "Transpile" that takes in four arguments: "src_dir", "dst_dir", "model_filename", and "params_filename". Inside the function, create a CPUPlace object and an Executor object using Paddle Fluid. Then, create a Scope object using fluid.core.Scope(). Load the inference program, feed target names, and fetch targets using fluid.io.load_inference_model() with the "src_dir", "exe", "model_filename", and "params_filename" arguments. Clone the inference program and apply the inference transpiler using fluid.InferenceTranspiler() and t.transpile(). Save the optimized inference program to "dst_dir" using fluid.io.save_persistables() and the "inference_transpiler_program" and "params_filename" arguments. If "dst_dir" does not exist, create it using os.makedirs(). Finally, create a main function that takes in arguments using argparse.ArgumentParser() and calls the "Transpile" function with the parsed arguments.
  assert os.path.isdir("optimized_model_dir"), "Destination directory should be created"
  assert os.path.exists("optimized_model_dir/model_filename"), "Optimized model should be saved"
  assert os.path.exists("optimized_model_dir/params_filename"), "Optimized params should be saved"
  assert "optimized" in open("optimized_model_dir/model_filename").read()
  assert "optimized" in open("optimized_model_dir/params_filename").read()
output: 
  def Transpile(src_dir, dst_dir, model_filename, params_filename):
      import paddle.fluid as fluid
      import os
      
      place = fluid.CPUPlace()
      exe = fluid.Executor(place)
      scope = fluid.core.Scope()
      
      with fluid.scope_guard(scope):
          [inference_program, feed_target_names, fetch_targets] = fluid.io.load_inference_model(
              dirname=src_dir,
              executor=exe,
              model_filename=model_filename,
              params_filename=params_filename
          )
          
          t = fluid.InferenceTranspiler()
          t.transpile(inference_program, place)
          
          if not os.path.exists(dst_dir):
              os.makedirs(dst_dir)
          
          fluid.io.save_persistables(
              executor=exe,
              dirname=dst_dir,
              main_program=inference_program,
              filename=params_filename
          )
  