class_docstr: Uses the CLIP transformer encoder for text (from huggingface)
class_docstr_tok: ["Uses","the","CLIP","transformer","encoder","for","text","(","from","huggingface",")"]
code: def freeze(self):
      self.transformer = self.transformer.eval()
      # self.train = disabled_train
      for param in self.parameters():
          param.requires_grad = False
  
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 2 for calling the FrozenCLIPEmbedder obj's underlying member method code with example usage: obj.freeze() without return types