code: def set_clip_encoding(self, text=None, img=None, encoding=None):
      encoding = self.create_clip_encoding(
          text=text, img=img, encoding=encoding
      )
      self.clip_encoding = encoding.to(self.device)
  
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 5 for calling the Imagine obj's underlying member method code with example usage: obj.set_clip_encoding(text, img, encoding) without return types