class_docstr: A modified wrapper for a public python BPE tokenizer. The modifications allow encoding directly into the formats
  required for finetune. Particularly with respect to formatting with multiple inputs.
class_docstr_tok: ["A","modified","wrapper","for","a","public","python","BPE","tokenizer",".","The","modifications","allow","encoding","directly","into","the","formats","required","for","finetune",".","Particularly","with","respect","to","formatting","with","multiple","inputs","."]
code: def _convert_to_embed_idx(self, idx):
      return self.freqs[idx]
  
imports: import os
  import finetune
  from finetune.encoding.input_encoder import BaseEncoder, EncodedOutput
  from finetune.base_models.gpt2.encoder import GPT2Encoder, bytes_to_unicode
  from finetune.base_models.gpt2 import encoder
  from transformers import RobertaTokenizerFast
label_desc: Use image node_id 2 for calling the RoBERTaEncoder obj's underlying member method code with example usage: obj._convert_to_embed_idx(idx) and returns: self