code: def generate_gif(self):
      images = []
      for file_name in sorted(os.listdir("./")):
          if (
              file_name.startswith(self.textpath)
              and file_name != f"{self.textpath}.jpg"
          ):
              images.append(imread(os.path.join("./", file_name)))
  
      if self.save_video:
          mimsave(f"{self.textpath}.mp4", images)
          print(
              f"Generated image generation animation at ./{self.textpath}.mp4"
          )
      if self.save_gif:
          mimsave(f"{self.textpath}.gif", images)
          print(
              f"Generated image generation animation at ./{self.textpath}.gif"
          )
  
imports: import os
  import subprocess
  import sys
  import random
  from datetime import datetime
  from pathlib import Path
  import torch
  import torch.nn.functional
  from siren_pytorch import SirenNet, SirenWrapper
  from torch import nn
  from torch.cuda.amp import GradScaler, autocast
  from torch_optimizer import DiffGrad, AdamP
  import numpy
  from PIL import Image
  from imageio import imread, mimsave
  import torchvision.transforms
  from tqdm import trange, tqdm
  from .clip import load, tokenize
label_desc: Use image node_id 12 for calling the Imagine obj's underlying member method code with example usage: obj.generate_gif() without return types