docstr: Add the command input options.
code: def add_module_input_arg(self):
      """
      Add the command input options.
      """
      self.arg_input_group.add_argument(
          "--text_prompts",
          type=str,
          help='Phrase, sentence, or string of words and phrases describing what the image should look like.  The words will be analyzed by the AI and will guide the diffusion process toward the image(s) you describe. These can include commas and weights to adjust the relative importance of each element.  E.g. "A beautiful painting of a singular lighthouse, shining its light across a tumultuous sea of blood by greg rutkowski and thomas kinkade, Trending on artstation."Notice that this prompt loosely follows a structure: [subject], [prepositional details], [setting], [meta modifiers and artist]; this is a good starting point for your experiments. Developing text prompts takes practice and experience, and is not the subject of this guide.  If you are a beginner to writing text prompts, a good place to start is on a simple AI art app like Night Cafe, starry ai or WOMBO prior to using DD, to get a feel for how text gets translated into images by GAN tools.  These other apps use different technologies, but many of the same principles apply.',
      )
  
      self.arg_input_group.add_argument(
          "--init_image", type=str, help="Initial image."
      )
  
      self.arg_input_group.add_argument(
          "--mask_image", type=str, help="Mask image."
      )
  
      self.arg_input_group.add_argument(
          "--strength",
          type=float,
          help="Control the noise strength added to initial image, value is in the interval [0.0, 1.0]. The closer to 1, the bigger change to the initial image.",
      )
  
      self.arg_input_group.add_argument(
          "--style",
          type=str,
          default=None,
          help="Image style, such as oil paintings, if specified, style will be used to construct prompts.",
      )
      self.arg_input_group.add_argument(
          "--artist",
          type=str,
          default=None,
          help="Artist style, if specified, style will be used to construct prompts.",
      )
  
      self.arg_input_group.add_argument(
          "--batch_size",
          type=int,
          default=1,
          help="This variable sets the number of still images you want SD to create for each prompt.",
      )
  
imports: import argparse
  import ast
  import base64
  import inspect
  import os
  import random
  import sys
  from functools import partial
  from io import BytesIO
  from typing import List
  from typing import Optional
  import numpy
  import paddle
  from docarray import Document
  from docarray import DocumentArray
  from IPython import display
  from PIL import Image
  from stable_diffusion_inpainting.clip.clip.utils import build_model
  from stable_diffusion_inpainting.clip.clip.utils import tokenize
  from stable_diffusion_inpainting.diffusers import AutoencoderKL
  from stable_diffusion_inpainting.diffusers import DDIMScheduler
  from stable_diffusion_inpainting.diffusers import LMSDiscreteScheduler
  from stable_diffusion_inpainting.diffusers import PNDMScheduler
  from stable_diffusion_inpainting.diffusers import UNet2DConditionModel
  from stable_diffusion_inpainting.utils import preprocess
  from stable_diffusion_inpainting.utils import preprocess_mask
  from tqdm.auto import tqdm
  import paddlehub
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 6 for calling the StableDiffusionInpainting obj's underlying member method code with example usage: obj.add_module_input_arg() without return types