code: def encode(
      self,
      texts: List[str],
      *,
      padding: Union[str, bool] = False,
      truncation: bool = True,
      add_special_tokens: bool = True,
      return_numpy: bool = False,
  ) -> Any:
      tokenized = self.tokenizer(
          texts,
          padding=padding,
          truncation=truncation,
          add_special_tokens=add_special_tokens,
      )
      if not return_numpy:
          return tokenized
      return np.array(tokenized["input_ids"], np.int64)
  
file_path: carefree-learn/cflearn/models/nlp/tokenizers/clip.py
imports: import numpy
  from typing import Any
  from typing import List
  from typing import Type
  from typing import Union
  from .schema import ITokenizer
label_desc: Use image node_id 2 for calling the ICLIPTokenizer obj's underlying member method code with example usage: obj.encode(texts) and returns: np, tokenized