class_docstr: Uses the OpenCLIP transformer encoder for text
class_docstr_tok: ["Uses","the","OpenCLIP","transformer","encoder","for","text"]
code: def forward(self, text):
      tokens = open_clip.tokenize(text)
      z = self.encode_with_transformer(tokens.to(self.device))
      return z
  
imports: import torch
  import torch.nn
  import kornia
  from torch.utils.checkpoint import checkpoint
  from transformers import T5Tokenizer, T5EncoderModel, CLIPTokenizer, CLIPTextModel
  import open_clip
  from ldm.util import default, count_params, autocast
  from ldm.modules.diffusionmodules.upscaling import ImageConcatWithNoiseAugmentation
  from ldm.modules.diffusionmodules.openaimodel import Timestep
label_desc: Use image node_id 3 for calling the FrozenOpenCLIPEmbedder obj's underlying member method code with example usage: obj.forward(text) and returns: z