code: def image_embeddings(
      self, images: torch.Tensor, t: torch.Tensor
  ) -> torch.Tensor:
      z_i = self.image_encoder((images + 1) * 127.5, t)
      return z_i / (
          torch.linalg.norm(z_i, dim=-1, keepdim=True) + 1e-12
      )
  
file_path: glide-text2im/glide_text2im/clip/model_creation.py
imports: import os
  from functools import lru_cache
  from typing import Any, Callable, Dict, List, Optional, Tuple
  import attr
  import numpy
  import torch
  import torch.nn
  import yaml
  from glide_text2im.tokenizer.simple_tokenizer import SimpleTokenizer
  from .encoders import ImageEncoder, TextEncoder
label_desc: Use image node_id 3 for calling the CLIPModel obj's underlying member method code with example usage: obj.image_embeddings(images, t) and returns: unknown