class_docstr: Uses the CLIP transformer encoder for text.
class_docstr_tok: ["Uses","the","CLIP","transformer","encoder","for","text","."]
code: def __init__(
      self,
      version="ViT-L/14",
      device="cuda",
      max_length=77,
      n_repeat=1,
      normalize=True,
  ):
      super().__init__()
      self.model, _ = clip.load(version, jit=False, device="cpu")
      self.device = device
      self.max_length = max_length
      self.n_repeat = n_repeat
      self.normalize = normalize
  
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 1 to create a new FrozenCLIPTextEmbedder object from inherited base classes: nn with example: obj = FrozenCLIPTextEmbedder(version, device, max_length, n_repeat, normalize)