

from __future__ import annotations


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int							):





    """simple docstring"""


    assert (
        c % greatest_common_divisor(_SCREAMING_SNAKE_CASE			, _SCREAMING_SNAKE_CASE							) == 0
    )  # greatest_common_divisor(a,b) function implemented below
    ((SCREAMING_SNAKE_CASE_)				,      (SCREAMING_SNAKE_CASE_)				,      (SCREAMING_SNAKE_CASE_))						=    extended_gcd(_SCREAMING_SNAKE_CASE			, _SCREAMING_SNAKE_CASE							)  # extended_gcd(a,b) function implemented below
    SCREAMING_SNAKE_CASE_						=    c / d
    return (r * x, r * y)


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int = 2							):





    """simple docstring"""


    ((SCREAMING_SNAKE_CASE_)				,      (SCREAMING_SNAKE_CASE_))						=    diophantine(_SCREAMING_SNAKE_CASE			, _SCREAMING_SNAKE_CASE			, _SCREAMING_SNAKE_CASE							)  # Initial value
    SCREAMING_SNAKE_CASE_						=    greatest_common_divisor(_SCREAMING_SNAKE_CASE			, _SCREAMING_SNAKE_CASE							)
    SCREAMING_SNAKE_CASE_						=    a // d
    SCREAMING_SNAKE_CASE_						=    b // d

    for i in range(_SCREAMING_SNAKE_CASE							):
        SCREAMING_SNAKE_CASE_						=    xa + i * q
        SCREAMING_SNAKE_CASE_						=    ya - i * p
        print(_SCREAMING_SNAKE_CASE			, _SCREAMING_SNAKE_CASE							)


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int							):





    """simple docstring"""


    if a < b:
        SCREAMING_SNAKE_CASE_				,      SCREAMING_SNAKE_CASE_						=    b, a

    while a % b != 0:
        SCREAMING_SNAKE_CASE_				,      SCREAMING_SNAKE_CASE_						=    b, a % b

    return b


def        _UpperCAmelCase							(	_SCREAMING_SNAKE_CASE       :		int			, _SCREAMING_SNAKE_CASE       :		int							):





    """simple docstring"""


    assert a >= 0 and b >= 0

    if b == 0:
        SCREAMING_SNAKE_CASE_				,      SCREAMING_SNAKE_CASE_				,      SCREAMING_SNAKE_CASE_						=    a, 1, 0
    else:
        ((SCREAMING_SNAKE_CASE_)				,      (SCREAMING_SNAKE_CASE_)				,      (SCREAMING_SNAKE_CASE_))						=    extended_gcd(_SCREAMING_SNAKE_CASE			, a % b							)
        SCREAMING_SNAKE_CASE_						=    q
        SCREAMING_SNAKE_CASE_						=    p - q * (a // b)

    assert a % d == 0 and b % d == 0
    assert d == a * x + b * y

    return (d, x, y)


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

       testmod(name="diophantine", verbose=True)
       testmod(name="diophantine_all_soln", verbose=True)
       testmod(name="extended_gcd", verbose=True)
       testmod(name="greatest_common_divisor", verbose=True)





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

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


if is_sentencepiece_available():
       from .tokenization_reformer import ReformerTokenizer
else:
       UpperCamelCase__	:   Optional[int]								=     None


UpperCamelCase__	:   Union[str, Any]								=     logging.get_logger(__name__)


UpperCamelCase__	:   Any								=     "▁"

UpperCamelCase__	:   Any								=     {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

UpperCamelCase__	:   List[Any]								=     {
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    },
    "tokenizer_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json"
        )
    },
}

UpperCamelCase__	:   Optional[Any]								=     {
    "google/reformer-crime-and-punishment": 524_288,
}



class    __snake_case	(     lowerCAmelCase__							):
  __lowerCAmelCase  :						int    			=	VOCAB_FILES_NAMES
  __lowerCAmelCase  :						int    			=	PRETRAINED_VOCAB_FILES_MAP
  __lowerCAmelCase  :						Tuple    			=	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  __lowerCAmelCase  :						List[str]    			=	['input_ids', 'attention_mask']
  __lowerCAmelCase  :						Dict    			=	ReformerTokenizer

  def __init__(       self    ,		_A=None    ,		_A=None    ,		_A="</s>"    ,		_A="<unk>"    ,		_A=[]    ,		**_A    ,		):
      super().__init__(
          _A    ,		tokenizer_file=_A    ,		eos_token=_A    ,		unk_token=_A    ,		additional_special_tokens=_A    ,		**_A    ,		)

      SCREAMING_SNAKE_CASE_						=    vocab_file
      SCREAMING_SNAKE_CASE_						=    False if not self.vocab_file else True


  def     lowerCAmelCase__  (       self    ,		_A    ,		_A = None):
      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(_A):
          logger.error(f"""Vocabulary path ({save_directory}) should be a directory""")
          return
      SCREAMING_SNAKE_CASE_						=    os.path.join(
          _A    ,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

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

      return (out_vocab_file,)


