class_docstr: Uses the CLIP transformer encoder for text (from Hugging Face)
class_docstr_tok: ["Uses","the","CLIP","transformer","encoder","for","text","(","from","Hugging","Face",")"]
code: def forward(self, text):
      batch_encoding = self.tokenizer(
          text,
          truncation=True,
          max_length=self.max_length,
          return_length=True,
          return_overflowing_tokens=False,
          padding="max_length",
          return_tensors="pt",
      )
      tokens = batch_encoding["input_ids"].to(self.device)
      outputs = self.transformer(input_ids=tokens)
  
      z = outputs.last_hidden_state
      return z
  
imports: import torch
  import torch.nn
  from functools import partial
  import clip
  from einops import rearrange, repeat
  from transformers import CLIPTokenizer, CLIPTextModel
  import kornia
  from ldm.modules.x_transformer import Encoder, TransformerWrapper
label_desc: Use image node_id 3 for calling the FrozenCLIPEmbedder obj's underlying member method code with example usage: obj.forward(text) and returns: z