





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_big_bird import BigBirdTokenizer
else:
     UpperCAmelCase	:	int		     =       None

UpperCAmelCase	:	List[str]		     =       logging.get_logger(__name__)
UpperCAmelCase	:	List[Any]		     =       {"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCAmelCase	:	Union[str, Any]		     =       {
    """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"""
        ),
    },
    """tokenizer_file""": {
        """google/bigbird-roberta-base""": (
            """https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"""
        ),
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"""
        ),
    },
}

UpperCAmelCase	:	Dict		     =       {
    """google/bigbird-roberta-base""": 4096,
    """google/bigbird-roberta-large""": 4096,
    """google/bigbird-base-trivia-itc""": 4096,
}


UpperCAmelCase	:	Union[str, Any]		     =       """▁"""







class 				__lowerCAmelCase       (    UpperCamelCase__):
      _lowercase				:					Union[str, Any]						=			VOCAB_FILES_NAMES
      _lowercase				:					Any						=			PRETRAINED_VOCAB_FILES_MAP
      _lowercase				:					Dict						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase				:					Tuple						=			BigBirdTokenizer
      _lowercase				:					Any						=			["""input_ids""", """attention_mask"""]
      _lowercase				:					List[int]						=			[]







      def __init__(    self		,      lowerCAmelCase__=None		,      lowerCAmelCase__=None		,      lowerCAmelCase__="<unk>"		,      lowerCAmelCase__="<s>"		,      lowerCAmelCase__="</s>"		,      lowerCAmelCase__="<pad>"		,      lowerCAmelCase__="[SEP]"		,      lowerCAmelCase__="[MASK]"		,      lowerCAmelCase__="[CLS]"		,      **lowerCAmelCase__		,      )   ->						int:



        '''simple docstring'''




        a__	:					List[Any]										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else bos_token
        a__	:					Optional[Any]										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else eos_token
        a__	:					Any										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else unk_token
        a__	:					int										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else pad_token
        a__	:					List[Any]										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else cls_token
        a__	:					Optional[Any]										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else sep_token

        # Mask token behave like a normal word, i.e. include the space before it
        a__	:					Optional[Any]										=AddedToken(lowerCAmelCase__		,      lstrip=lowerCAmelCase__		,      rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__		,      lowerCAmelCase__							) else mask_token

        super().__init__(
            lowerCAmelCase__		,      tokenizer_file=lowerCAmelCase__		,      bos_token=lowerCAmelCase__		,      eos_token=lowerCAmelCase__		,      unk_token=lowerCAmelCase__		,      sep_token=lowerCAmelCase__		,      pad_token=lowerCAmelCase__		,      cls_token=lowerCAmelCase__		,      mask_token=lowerCAmelCase__		,      **lowerCAmelCase__		,      )

        a__	:					Tuple										=vocab_file
        a__	:					str										=False if not self.vocab_file else True







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						List[int]:



        '''simple docstring'''




        a__	:					str										=[self.sep_token_id]
        a__	:					Union[str, Any]										=[self.cls_token_id]
        if token_ids_a is None:
          return cls + token_ids_a + sep
        return cls + token_ids_a + sep + token_ids_a + sep







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None		,      lowerCAmelCase__ = False							)   ->						List[int]:



        '''simple docstring'''




        if already_has_special_tokens:
          if token_ids_a is not None:
            raise ValueError(
                "You should not supply a second sequence if the provided sequence of "
                "ids is already formatted with special tokens for the model."							)
          return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						List[int]:



        '''simple docstring'''




        a__	:					Union[str, Any]										=[self.sep_token_id]
        a__	:					List[Any]										=[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]







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						Tuple[str]:



        '''simple docstring'''




        if not self.can_save_slow_tokenizer:
          raise ValueError(
              "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
              "tokenizer."							)

        if not os.path.isdir(lowerCAmelCase__							):
          logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
          return
        a__	:					Optional[int]										=os.path.join(
            lowerCAmelCase__		,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

        if os.path.abspath(self.vocab_file							) != os.path.abspath(lowerCAmelCase__							):
          copyfile(self.vocab_file		,      lowerCAmelCase__							)

        return (out_vocab_file,)













from __future__ import annotations
def      _A       (		SCREAMING_SNAKE_CASE     :   list						):





  """simple docstring"""



  if len(SCREAMING_SNAKE_CASE						) == 0:
    return []
  a__					,							a__	:					int										=min(SCREAMING_SNAKE_CASE						), max(SCREAMING_SNAKE_CASE						)
  a__	:					Optional[int]										=int(max_value - min_value						) + 1
  a__	:					list[list]										=[[] for _ in range(SCREAMING_SNAKE_CASE						)]

  for i in my_list:
    buckets[int(i - min_value						)].append(SCREAMING_SNAKE_CASE						)

  return [v for bucket in buckets for v in sorted(SCREAMING_SNAKE_CASE						)]


if __name__ == "__main__":
     from doctest import testmod

     testmod()
     assert bucket_sort([4, 5, 3, 2, 1]) == [1, 2, 3, 4, 5]
     assert bucket_sort([0, 1, -10, 15, 2, -2]) == [-10, -2, 0, 1, 2, 15]






