docstr: Add the command config options.
docstr_tok: ["Add","the","command","config","options","."]
code: def add_module_config_arg(self):
      """
      Add the command config options.
      """
  
      self.arg_input_group.add_argument(
          "--num_inference_steps",
          type=int,
          default=50,
          help="The number of inference steps.",
      )
  
      self.arg_input_group.add_argument(
          "--guidance_scale",
          type=float,
          default=7.5,
          help="Increase the adherence to the conditional signal which in this case is text as well as overall sample quality.",
      )
  
      self.arg_input_group.add_argument(
          "--seed",
          type=int,
          default=None,
          help="Deep in the diffusion code, there is a random number ‘seed’ which is used as the basis for determining the initial state of the diffusion.  By default, this is random, but you can also specify your own seed.",
      )
  
      self.arg_input_group.add_argument(
          "--display_rate",
          type=int,
          default=10,
          help="During a diffusion run, you can monitor the progress of each image being created with this variable.",
      )
  
      self.arg_config_group.add_argument(
          "--use_gpu",
          type=ast.literal_eval,
          default=True,
          help="whether use GPU or not",
      )
  
      self.arg_config_group.add_argument(
          "--enable_fp16",
          type=ast.literal_eval,
          default=False,
          help="whether use float16 or not",
      )
  
      self.arg_config_group.add_argument(
          "--output_dir",
          type=str,
          default="stable_diffusion_out",
          help="Output directory.",
      )
  
imports: import argparse
  import ast
  import os
  import random
  import sys
  from functools import partial
  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.clip.clip.utils import build_model
  from stable_diffusion.clip.clip.utils import tokenize
  from stable_diffusion.diffusers import AutoencoderKL
  from stable_diffusion.diffusers import DDIMScheduler
  from stable_diffusion.diffusers import LMSDiscreteScheduler
  from stable_diffusion.diffusers import PNDMScheduler
  from stable_diffusion.diffusers import UNet2DConditionModel
  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 5 for calling the StableDiffusion obj's underlying member method code with example usage: obj.add_module_config_arg() without return types