code: def parse_args():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "-m",
          "--pretrained_model_name_or_path",
          type=str,
          default=None,
          required=True,
          help="Path to pretrained model or model identifier from huggingface.co/models.",
      )
      parser.add_argument(
          "-c",
          "--caption",
          type=str,
          default="robotic cat with wings",
          help="Text used to generate images.",
      )
      parser.add_argument(
          "-n",
          "--images_num",
          type=int,
          default=4,
          help="How much images to generate.",
      )
      parser.add_argument(
          "-s",
          "--seed",
          type=int,
          default=42,
          help="Seed for random process.",
      )
      parser.add_argument(
          "-ci",
          "--cuda_id",
          type=int,
          default=0,
          help="cuda_id.",
      )
      args = parser.parse_args()
      return args
  
file_path: diffusers/examples/research_projects/intel_opts/textual_inversion_dfq/text2images.py
imports: import argparse
  import math
  import os
  import torch
  from neural_compressor.utils.pytorch import load
  from PIL import Image
  from transformers import CLIPTextModel, CLIPTokenizer
  from diffusers import AutoencoderKL, StableDiffusionPipeline, UNet2DConditionModel
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args