class_docstr: Constructs a Ernie-M tokenizer. It uses the `sentencepiece` tools to cut the words to sub-words.
  
  Args:
      sentencepiece_model_file (`str`):
          The file path of sentencepiece model.
      vocab_file (`str`, *optional*):
          The file path of the vocabulary.
      do_lower_case (`str`, *optional*, defaults to `True`):
          Whether or not to lowercase the input when tokenizing.
      unk_token (`str`, *optional*, defaults to `"[UNK]"`):
          A special token representing the `unknown (out-of-vocabulary)` token. An unknown token is set to be
          `unk_token` inorder to be converted to an ID.
      sep_token (`str`, *optional*, defaults to `"[SEP]"`):
          A special token separating two different sentences in the same input.
      pad_token (`str`, *optional*, defaults to `"[PAD]"`):
          A special token used to make arrays of tokens the same size for batching purposes.
      cls_token (`str`, *optional*, defaults to `"[CLS]"`):
          A special token used for sequence classification. It is the last token of the sequence when built with
          special tokens.
      mask_token (`str`, *optional*, defaults to `"[MASK]"`):
          A special token representing a masked token. This is the token used in the masked language modeling task
          which the model tries to predict the original unmasked ones.
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docstr: Converts a sequence of tokens (strings for sub-words) in a single string.
docstr_tok: ["Converts","a","sequence","of","tokens","(","strings","for","sub-words",")","in","a","single","string","."]
code: def convert_tokens_to_string(self, tokens):
      """Converts a sequence of tokens (strings for sub-words) in a single string."""
      out_string = (
          "".join(tokens).replace(SPIECE_UNDERLINE, " ").strip()
      )
      return out_string
  
imports: import io
  import os
  import unicodedata
  from typing import Any, Dict, List, Optional, Tuple
  import sentencepiece
  from ...tokenization_utils import PreTrainedTokenizer
  from ...utils import logging
label_desc: Use image node_id 9 for calling the ErnieMTokenizer obj's underlying member method code with example usage: obj.convert_tokens_to_string(tokens) and returns: out_string