code: def main():
      """
      ### CLI
      """
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "--prompt",
          type=str,
          nargs="?",
          default="a painting of a cute monkey playing guitar",
          help="the prompt to render",
      )
  
      parser.add_argument(
          "--orig-img",
          type=str,
          nargs="?",
          help="path to the input image",
      )
  
      parser.add_argument(
          "--batch_size",
          type=int,
          default=4,
          help="batch size",
      )
      parser.add_argument(
          "--steps",
          type=int,
          default=50,
          help="number of sampling steps",
      )
  
      parser.add_argument(
          "--scale",
          type=float,
          default=5.0,
          help="unconditional guidance scale: "
          "eps = eps(x, empty) + scale * (eps(x, cond) - eps(x, empty))",
      )
  
      parser.add_argument(
          "--strength",
          type=float,
          default=0.75,
          help="strength for noise: "
          " 1.0 corresponds to full destruction of information in init image",
      )
  
      opt = parser.parse_args()
      set_seed(42)
  
      in_paint = InPaint(
          checkpoint_path=lab.get_data_path()
          / "stable-diffusion"
          / "sd-v1-4.ckpt",
          ddim_steps=opt.steps,
      )
  
      with monit.section("Generate"):
          in_paint(
              dest_path="outputs",
              orig_img=opt.orig_img,
              strength=opt.strength,
              batch_size=opt.batch_size,
              prompt=opt.prompt,
              uncond_scale=opt.scale,
          )
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/diffusion/stable_diffusion/scripts/in_paint.py
imports: import argparse
  from pathlib import Path
  from typing import Optional
  import torch
  from labml import lab, monit
  from labml_nn.diffusion.stable_diffusion.latent_diffusion import LatentDiffusion
  from labml_nn.diffusion.stable_diffusion.sampler import DiffusionSampler
  from labml_nn.diffusion.stable_diffusion.sampler.ddim import DDIMSampler
  from labml_nn.diffusion.stable_diffusion.util import load_model, save_images, load_img, set_seed
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types