class_docstr: Uses the BERT tokenizr model and add some transformer encoder layers
class_docstr_tok: ["Uses","the","BERT","tokenizr","model","and","add","some","transformer","encoder","layers"]
code: def forward(self, text):
      if self.use_tknz_fn:
          tokens = self.tknz_fn(text)  # .to(self.device)
      else:
          tokens = text
      z = self.transformer(tokens, return_embeddings=True)
      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 2 for calling the BERTEmbedder obj's underlying member method code with example usage: obj.forward(text) and returns: z