code: def fake_diffusion(steps):
      images = []
      for _ in range(steps):
          time.sleep(1)
          image = np.random.random((600, 600, 3))
          images.append(image)
          yield image, gr.Image(visible=False)
  
      time.sleep(1)
      image = "https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg"
      images.append(image)
      gif_path = create_gif(images)
  
      yield image, gr.Image(value=gif_path, visible=True)
  
file_path: gradio/demo/fake_diffusion_with_gif/run.py
imports: import gradio
  import numpy
  import time
  import os
  from PIL import Image
  import requests
  from io import BytesIO
label_desc: Use image node_id 2 for calling a global function with example usage: fake_diffusion(steps) without return types