
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCamelCase_						     =					logging.get_logger(__name__)

lowerCamelCase_						     =					{'''vocab_file''': '''spiece.model'''}

lowerCamelCase_						     =					{
    '''vocab_file''': {
        '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model''',
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'''
        ),
    }
}

lowerCamelCase_						     =					{
    '''google/bigbird-roberta-base''': 40_96,
    '''google/bigbird-roberta-large''': 40_96,
    '''google/bigbird-base-trivia-itc''': 40_96,
}




class      __A(    __lowerCamelCase			):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__         =      VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__         =      PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__         =      ["""input_ids""", """attention_mask"""]
  SCREAMING_SNAKE_CASE__         =      []







  def __init__(self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_="<unk>"	,      SCREAMING_SNAKE_CASE_="<s>"	,      SCREAMING_SNAKE_CASE_="</s>"	,      SCREAMING_SNAKE_CASE_="<pad>"	,      SCREAMING_SNAKE_CASE_="[SEP]"	,      SCREAMING_SNAKE_CASE_="[MASK]"	,      SCREAMING_SNAKE_CASE_="[CLS]"	,      SCREAMING_SNAKE_CASE_ = None	,      **SCREAMING_SNAKE_CASE_	,      ):
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else bos_token
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else eos_token
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else unk_token
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else pad_token
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else cls_token
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else sep_token

       # Mask token behave like a normal word, i.e. include the space before it
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else mask_token

       UpperCamelCase__				=    {} if sp_model_kwargs is None else sp_model_kwargs

       super().__init__(
           bos_token=SCREAMING_SNAKE_CASE_	,      eos_token=SCREAMING_SNAKE_CASE_	,      unk_token=SCREAMING_SNAKE_CASE_	,      pad_token=SCREAMING_SNAKE_CASE_	,      sep_token=SCREAMING_SNAKE_CASE_	,      mask_token=SCREAMING_SNAKE_CASE_	,      cls_token=SCREAMING_SNAKE_CASE_	,      sp_model_kwargs=self.sp_model_kwargs	,      **SCREAMING_SNAKE_CASE_	,      )

       UpperCamelCase__				=    vocab_file

       UpperCamelCase__				=    spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(SCREAMING_SNAKE_CASE_						)







  @property
  def 	UpperCAmelCase_ (self						):
       return self.sp_model.get_piece_size()







  def 	UpperCAmelCase_ (self						):
       UpperCamelCase__				=    {self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_						): i for i in range(self.vocab_size						)}
       vocab.update(self.added_tokens_encoder						)
       return vocab







  def __getstate__(self						):
       UpperCamelCase__				=    self.__dict__.copy()
       UpperCamelCase__				=    None
       return state







  def __setstate__(self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    d

       # for backward compatibility
       if not hasattr(self	,      """sp_model_kwargs"""						):
            UpperCamelCase__				=    {}

       UpperCamelCase__				=    spm.SentencePieceProcessor(**self.sp_model_kwargs						)
       self.sp_model.Load(self.vocab_file						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       return self.sp_model.encode(SCREAMING_SNAKE_CASE_	,      out_type=SCREAMING_SNAKE_CASE_						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE_						)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE_						)
       return token







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_						):
       UpperCamelCase__				=    []
       UpperCamelCase__				=    """"""
       UpperCamelCase__				=    False
       for token in tokens:
            # make sure that special tokens are not decoded using sentencepiece model
            if token in self.all_special_tokens:
                 if not prev_is_special:
                      out_string += " "
                 out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE_						) + token
                 UpperCamelCase__				=    True
                 UpperCamelCase__				=    []
            else:
                 current_sub_tokens.append(SCREAMING_SNAKE_CASE_						)
                 UpperCamelCase__				=    False
       out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE_						)
       return out_string.strip()







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = False	,      SCREAMING_SNAKE_CASE_ = None	,      SCREAMING_SNAKE_CASE_ = True	,      **SCREAMING_SNAKE_CASE_	,      ):
       UpperCamelCase__				=    kwargs.pop("""use_source_tokenizer"""	,      SCREAMING_SNAKE_CASE_						)

       UpperCamelCase__				=    self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_	,      skip_special_tokens=SCREAMING_SNAKE_CASE_						)

       # To avoid mixing byte-level and unicode for byte-level BPT
       # we need to build string separately for added tokens and byte-level tokens
       # cf. https://github.com/huggingface/transformers/issues/1133
       UpperCamelCase__				=    []
       UpperCamelCase__				=    []
       for token in filtered_tokens:
            if skip_special_tokens and token in self.all_special_ids:
                 continue
            if token in self.added_tokens_encoder:
                 if current_sub_text:
                      sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE_						)						)
                      UpperCamelCase__				=    []
                 sub_texts.append(SCREAMING_SNAKE_CASE_						)
            else:
                 current_sub_text.append(SCREAMING_SNAKE_CASE_						)
       if current_sub_text:
            sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE_						)						)

       # Mimic the behavior of the Rust tokenizer:
       # No space before [MASK] and [SEP]
       if spaces_between_special_tokens:
            UpperCamelCase__				=    re.sub(r""" (\[(MASK|SEP)\])"""	,      r"""\1"""	,      """ """.join(SCREAMING_SNAKE_CASE_						)						)
       else:
            UpperCamelCase__				=    """""".join(SCREAMING_SNAKE_CASE_						)

       UpperCamelCase__				=    (
           clean_up_tokenization_spaces
           if clean_up_tokenization_spaces is not None
           else self.clean_up_tokenization_spaces
       )
       if clean_up_tokenization_spaces:
            UpperCamelCase__				=    self.clean_up_tokenization(SCREAMING_SNAKE_CASE_						)
            return clean_text
       else:
            return text







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):
       if not os.path.isdir(SCREAMING_SNAKE_CASE_						):
            logger.error(F"Vocabulary path ({save_directory}) should be a directory"						)
            return
       UpperCamelCase__				=    os.path.join(
           SCREAMING_SNAKE_CASE_	,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]						)

       if os.path.abspath(self.vocab_file						) != os.path.abspath(SCREAMING_SNAKE_CASE_						) and os.path.isfile(self.vocab_file						):
            copyfile(self.vocab_file	,      SCREAMING_SNAKE_CASE_						)
       elif not os.path.isfile(self.vocab_file						):
            with open(SCREAMING_SNAKE_CASE_	,      """wb"""						) as fi:
                 UpperCamelCase__				=    self.sp_model.serialized_model_proto()
                 fi.write(SCREAMING_SNAKE_CASE_						)

       return (out_vocab_file,)







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):
       if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       UpperCamelCase__				=    [self.cls_token_id]
       UpperCamelCase__				=    [self.sep_token_id]
       return cls + token_ids_a + sep + token_ids_a + sep







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None	,      SCREAMING_SNAKE_CASE_ = False						):
       if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=SCREAMING_SNAKE_CASE_	,      token_ids_a=SCREAMING_SNAKE_CASE_	,      already_has_special_tokens=SCREAMING_SNAKE_CASE_						)

       if token_ids_a is None:
            return [1] + ([0] * len(SCREAMING_SNAKE_CASE_						)) + [1]
       return [1] + ([0] * len(SCREAMING_SNAKE_CASE_						)) + [1] + ([0] * len(SCREAMING_SNAKE_CASE_						)) + [1]







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):
       UpperCamelCase__				=    [self.sep_token_id]
       UpperCamelCase__				=    [self.cls_token_id]
       if token_ids_a is None:
            return len(cls + token_ids_a + sep						) * [0]
       return len(cls + token_ids_a + sep						) * [0] + len(token_ids_a + sep						) * [1]







import importlib
import inspect
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase_						     =					'''src/transformers'''


# This is to make sure the transformers module imported is the one in the repo.
lowerCamelCase_						     =					importlib.util.spec_from_file_location(
    '''transformers''',
    os.path.join(PATH_TO_TRANSFORMERS, '''__init__.py'''),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
lowerCamelCase_						     =					spec.loader.load_module()

lowerCamelCase_						     =					transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
lowerCamelCase_						     =					re.compile('''\[(.+?)\]\((https://huggingface\.co/.+?)\)''')


lowerCamelCase_						     =					{
    '''CLIPConfigMixin''',
    '''DecisionTransformerConfigMixin''',
    '''EncoderDecoderConfigMixin''',
    '''RagConfigMixin''',
    '''SpeechEncoderDecoderConfigMixin''',
    '''VisionEncoderDecoderConfigMixin''',
    '''VisionTextDualEncoderConfigMixin''',
}






def 						__magic_name__			(   ):



     '''simple docstring'''




     UpperCamelCase__				=    []

     for config_class in list(CONFIG_MAPPING.values()						):
          UpperCamelCase__				=    False

          # source code of `config_class`
          UpperCamelCase__				=    inspect.getsource(__a						)
          UpperCamelCase__				=    _re_checkpoint.findall(__a						)

          for checkpoint in checkpoints:
               # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
               # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
               UpperCamelCase__		,	UpperCamelCase__				=    checkpoint

               # verify the checkpoint name corresponds to the checkpoint link
               UpperCamelCase__				=    f"https://huggingface.co/{ckpt_name}"
               if ckpt_link == ckpt_link_from_name:
                    UpperCamelCase__				=    True
                    break

          UpperCamelCase__				=    config_class.__name__
          if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
               configs_without_checkpoint.append(__a						)

     if len(__a						) > 0:
          UpperCamelCase__				=    """\n""".join(sorted(__a						)						)
          raise ValueError(f"The following configurations don't contain any valid checkpoint:\n{message}"						)


if __name__ == "__main__":
    check_config_docstrings_have_checkpoints()





