class_docstr: Uses the CLIP image encoder.
class_docstr_tok: ["Uses","the","CLIP","image","encoder","."]
code: def __init__(
      self,
      model,
      jit=False,
      device="cuda" if torch.cuda.is_available() else "cpu",
      antialias=False,
  ):
      super().__init__()
      self.model, _ = clip.load(name=model, device=device, jit=jit)
  
      self.antialias = antialias
  
      self.register_buffer(
          "mean",
          torch.Tensor([0.48145466, 0.4578275, 0.40821073]),
          persistent=False,
      )
      self.register_buffer(
          "std",
          torch.Tensor([0.26862954, 0.26130258, 0.27577711]),
          persistent=False,
      )
  
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 FrozenClipImageEmbedder object from inherited base classes: nn with example: obj = FrozenClipImageEmbedder(model, jit, device, antialias)