code: def encode_embedding_init_text(self, init_text, nvpt):
      embedding_layer = self.wrapped.roberta.embeddings
      ids = self.wrapped.tokenizer(
          init_text,
          max_length=nvpt,
          return_tensors="pt",
          add_special_tokens=False,
      )["input_ids"]
      embedded = embedding_layer.token_embedding.wrapped(
          ids.to(devices.device)
      ).squeeze(0)
  
      return embedded
  
imports: import torch
  from modules import sd_hijack_clip, devices
label_desc: Use image node_id 3 for calling the FrozenXLMREmbedderWithCustomWords obj's underlying member method code with example usage: obj.encode_embedding_init_text(init_text, nvpt) and returns: embedded