






"""simple docstring"""



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

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


if is_sentencepiece_available():
 from .tokenization_deberta_va import DebertaVaTokenizer
else:
 _lowerCAmelCase     :     Optional[Any]            =	None

_lowerCAmelCase     :     List[str]            =	logging.get_logger(__name__)

_lowerCAmelCase     :     Optional[Any]            =	{"""vocab_file""": """spm.model""", """tokenizer_file""": """tokenizer.json"""}

_lowerCAmelCase     :     int            =	{
    """vocab_file""": {
        """microsoft/deberta-v2-xlarge""": """https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model""",
        """microsoft/deberta-v2-xxlarge""": """https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model""",
        """microsoft/deberta-v2-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model"""
        ),
        """microsoft/deberta-v2-xxlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model"""
        ),
    }
}

_lowerCAmelCase     :     int            =	{
    """microsoft/deberta-v2-xlarge""": 512,
    """microsoft/deberta-v2-xxlarge""": 512,
    """microsoft/deberta-v2-xlarge-mnli""": 512,
    """microsoft/deberta-v2-xxlarge-mnli""": 512,
}

_lowerCAmelCase     :     Dict            =	{
    """microsoft/deberta-v2-xlarge""": {"""do_lower_case""": False},
    """microsoft/deberta-v2-xxlarge""": {"""do_lower_case""": False},
    """microsoft/deberta-v2-xlarge-mnli""": {"""do_lower_case""": False},
    """microsoft/deberta-v2-xxlarge-mnli""": {"""do_lower_case""": False},
}




class        lowerCAmelCase__       (  __magic_name__					):
   SCREAMING_SNAKE_CASE_					      =VOCAB_FILES_NAMES
   SCREAMING_SNAKE_CASE_					      =PRETRAINED_VOCAB_FILES_MAP
   SCREAMING_SNAKE_CASE_					      =PRETRAINED_INIT_CONFIGURATION
   SCREAMING_SNAKE_CASE_					      =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   SCREAMING_SNAKE_CASE_					      =DebertaVaTokenizer
   def __init__(						self	:     int				,       snake_case__	:     List[str]=None				,       snake_case__	:     Dict=None				,       snake_case__	:     str=False				,       snake_case__	:     Optional[Any]=False				,       snake_case__	:     Optional[Any]="[CLS]"				,       snake_case__	:     Optional[int]="[SEP]"				,       snake_case__	:     int="[UNK]"				,       snake_case__	:     Union[str, Any]="[SEP]"				,       snake_case__	:     Optional[int]="[PAD]"				,       snake_case__	:     Any="[CLS]"				,       snake_case__	:     int="[MASK]"				,       **snake_case__	:     List[str]				,       ):


        '''simple docstring'''
        super().__init__(
            snake_case__				,       tokenizer_file=snake_case__				,       do_lower_case=snake_case__				,       bos_token=snake_case__				,       eos_token=snake_case__				,       unk_token=snake_case__				,       sep_token=snake_case__				,       pad_token=snake_case__				,       cls_token=snake_case__				,       mask_token=snake_case__				,       split_by_punct=snake_case__				,       **snake_case__				,       )

        UpperCAmelCase__		:  List[Any]				=				do_lower_case
        UpperCAmelCase__		:  Any				=				split_by_punct
        UpperCAmelCase__		:  List[str]				=				vocab_file
        UpperCAmelCase__		:  Optional[Any]				=				False if not self.vocab_file else True
   def 	__a				(						self	:     str				,       snake_case__	:     List[str]				,       snake_case__	:     Optional[Any]=None				):


        '''simple docstring'''

        if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        UpperCAmelCase__		:  str				=				[self.cls_token_id]
        UpperCAmelCase__		:  str				=				[self.sep_token_id]
        return cls + token_ids_a + sep + token_ids_a + sep
   def 	__a				(						self	:     Union[str, Any]				,       snake_case__	:     Tuple				,       snake_case__	:     Optional[Any]=None				,       snake_case__	:     Dict=False				):


        '''simple docstring'''

        if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=snake_case__				,       token_ids_a=snake_case__				,       already_has_special_tokens=snake_case__				)

        if token_ids_a is not None:
             return [1] + ([0] * len(snake_case__				)) + [1] + ([0] * len(snake_case__				)) + [1]
        return [1] + ([0] * len(snake_case__				)) + [1]
   def 	__a				(						self	:     Dict				,       snake_case__	:     Union[str, Any]				,       snake_case__	:     Any=None				):


        '''simple docstring'''
        UpperCAmelCase__		:  Optional[int]				=				[self.sep_token_id]
        UpperCAmelCase__		:  int				=				[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 	__a				(						self	:     str				,       snake_case__	:     str				,       snake_case__	:     Optional[str] = None				):


        '''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(snake_case__				):
             logger.error(f'Vocabulary path ({save_directory}) should be a directory'				)
             return
        UpperCAmelCase__		:  List[Any]				=				os.path.join(
            snake_case__				,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)

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

        return (out_vocab_file,)










"""simple docstring"""



def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list       , snake_case    :      int       , snake_case    :      int							)->						None:






     '''simple docstring'''



     if right <= left:
          return
     UpperCAmelCase__		:  str				=				left
     UpperCAmelCase__		:  List[str]				=				right
     UpperCAmelCase__		:  List[Any]				=				sorting[left]
     while i <= b:
          if sorting[i] < pivot:
               UpperCAmelCase__				,							UpperCAmelCase__		:  List[str]				=				sorting[i], sorting[a]
               a += 1
               i += 1
          elif sorting[i] > pivot:
               UpperCAmelCase__				,							UpperCAmelCase__		:  Optional[int]				=				sorting[i], sorting[b]
               b -= 1
          else:
               i += 1
     quick_sort_apartition(snake_case       , snake_case       , a - 1							)
     quick_sort_apartition(snake_case       , b + 1       , snake_case							)


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list       , snake_case    :      int       , snake_case    :      int							)->						None:






     '''simple docstring'''



     if left < right:
          UpperCAmelCase__		:  int				=				lomuto_partition(snake_case       , snake_case       , snake_case							)
          quick_sort_lomuto_partition(snake_case       , snake_case       , pivot_index - 1							)
          quick_sort_lomuto_partition(snake_case       , pivot_index + 1       , snake_case							)


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list       , snake_case    :      int       , snake_case    :      int							)->						int:






     '''simple docstring'''



     UpperCAmelCase__		:  Union[str, Any]				=				sorting[right]
     UpperCAmelCase__		:  Optional[Any]				=				left
     for i in range(snake_case       , snake_case							):
          if sorting[i] < pivot:
               UpperCAmelCase__				,							UpperCAmelCase__		:  List[Any]				=				sorting[i], sorting[store_index]
               store_index += 1
     UpperCAmelCase__				,							UpperCAmelCase__		:  List[Any]				=				sorting[store_index], sorting[right]
     return store_index


def      SCREAMING_SNAKE_CASE__    (   snake_case    :      list							)->						list:






     '''simple docstring'''



     if len(snake_case							) <= 1:
          return sorting
     return (
         three_way_radix_quicksort([i for i in sorting if i < sorting[0]]							)
         + [i for i in sorting if i == sorting[0]]
         + three_way_radix_quicksort([i for i in sorting if i > sorting[0]]							)
     )


if __name__ == "__main__":
 import doctest

 doctest.testmod(verbose=True)

 _lowerCAmelCase     :     Optional[int]            =	input("""Enter numbers separated by a comma:\n""").strip()
 _lowerCAmelCase     :     str            =	[int(item) for item in user_input.split(""",""")]
 quick_sort_apartition(unsorted, 0, len(unsorted) - 1)
 print(unsorted)


