code: def set_seed(seed: int):
      """
      ### Set random seeds
      """
      random.seed(seed)
      np.random.seed(seed)
      torch.manual_seed(seed)
      torch.cuda.manual_seed_all(seed)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/diffusion/stable_diffusion/util.py
imports: import os
  import random
  from pathlib import Path
  import PIL
  import numpy
  import torch
  from PIL import Image
  from labml import monit
  from labml.logger import inspect
  from labml_nn.diffusion.stable_diffusion.latent_diffusion import LatentDiffusion
  from labml_nn.diffusion.stable_diffusion.model.autoencoder import Encoder, Decoder, Autoencoder
  from labml_nn.diffusion.stable_diffusion.model.clip_embedder import CLIPTextEmbedder
  from labml_nn.diffusion.stable_diffusion.model.unet import UNetModel
label_desc: Use image node_id 1 for calling a global function with example usage: set_seed(seed) without return types