code: def create_text_encoding(self, text):
      tokenized_text = tokenize(text).to(self.device)
      with torch.no_grad():
          text_encoding = self.perceptor.encode_text(
              tokenized_text
          ).detach()
      return text_encoding
  
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 3 for calling the Imagine obj's underlying member method code with example usage: obj.create_text_encoding(text) and returns: text_encoding