




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

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


if is_sentencepiece_available():
      from .tokenization_xglm import XGLMTokenizer
else:
      __SCREAMING_SNAKE_CASE      :				Optional[Any]				      =None


__SCREAMING_SNAKE_CASE      :				int				      =logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE      :				Union[str, Any]				      ={'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

__SCREAMING_SNAKE_CASE      :				Optional[Any]				      ={
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json''',
    },
}

__SCREAMING_SNAKE_CASE      :				List[Any]				      ={
    '''facebook/xglm-564M''': 2_048,
}






class      A     (						__lowerCAmelCase						):
     """simple docstring"""

     _snake_case       =VOCAB_FILES_NAMES
     _snake_case       =PRETRAINED_VOCAB_FILES_MAP
     _snake_case       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _snake_case       =['''input_ids''', '''attention_mask''']
     _snake_case       =XGLMTokenizer




     def __init__(      self					:				Any		,					A__					:				Optional[int]=None		,					A__					:				Optional[int]=None		,					A__					:				Tuple="<s>"		,					A__					:				Dict="</s>"		,					A__					:				Dict="</s>"		,					A__					:				Optional[int]="<s>"		,					A__					:				Optional[Any]="<unk>"		,					A__					:				str="<pad>"		,					**A__					:				Optional[Any]		,					)			->    Tuple:
           lowerCamelCase__ 					=			7
           lowerCamelCase__ 					=			[F"""<madeupword{i}>""" for i in range(self.num_madeup_words     )]

           lowerCamelCase__ 					=			kwargs.get('additional_special_tokens'		,					[]     )
           kwargs["additional_special_tokens"] += [
               word for word in madeup_words if word not in kwargs["additional_special_tokens"]
           ]

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

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




     def 	__snake_case				(      self					:				List[str]		,					A__					:				Dict		,					A__					:				Any = None     )			->    List[int]:




           if token_ids_a is None:
                 return [self.sep_token_id] + token_ids_a
           lowerCamelCase__ 					=			[self.sep_token_id]
           return sep + token_ids_a + sep + sep + token_ids_a




     def 	__snake_case				(      self					:				int		,					A__					:				int		,					A__					:				Optional[Any] = None     )			->    List[int]:
           lowerCamelCase__ 					=			[self.sep_token_id]

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




     def 	__snake_case				(      self					:				Tuple		,					A__					:				Optional[int]		,					A__					:				Union[str, Any] = None     )			->    Tuple[str]:




           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(__SCREAMING_SNAKE_CASE     ):
                 logger.error(F"""Vocabulary path ({save_directory}) should be a directory."""     )
                 return
           lowerCamelCase__ 					=			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     ):
                 copyfile(self.vocab_file		,					__SCREAMING_SNAKE_CASE     )

           return (out_vocab_file,)





def      lowerCAmelCase_     (					lowerCamelCase:    Optional[int]  )   ->     Union[str, Any]:


      '''simple docstring'''




      lowerCamelCase__ 					=			[7_01, 3_01, 1_32, 57, 23, 10, 4, 1]
      for gap in gaps:
            for i in range(lowerCamelCase       ,			len(lowerCamelCase  )  ):
                  lowerCamelCase__ 					=			collection[i]
                  lowerCamelCase__ 					=			i
                  while j >= gap and collection[j - gap] > insert_value:
                        lowerCamelCase__ 					=			collection[j - gap]
                        j -= gap
                  if j != i:
                        lowerCamelCase__ 					=			insert_value
      return collection


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

      testmod()
      __SCREAMING_SNAKE_CASE      :				List[Any]				      =input("""Enter numbers separated by a comma:\n""").strip()
      __SCREAMING_SNAKE_CASE      :				Dict				      =[int(item) for item in user_input.split(""",""")]
      print(shell_sort(unsorted))