





"""simple docstring"""





import os
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


SCREAMING_SNAKE_CASE__					=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__					=   "▁"

SCREAMING_SNAKE_CASE__					=   {"vocab_file": "sentencepiece.bpe.model"}

SCREAMING_SNAKE_CASE__					=   {
    "vocab_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
        ),
    }
}

SCREAMING_SNAKE_CASE__					=   {
    "xlm-roberta-base": 512,
    "xlm-roberta-large": 512,
    "xlm-roberta-large-finetuned-conll02-dutch": 512,
    "xlm-roberta-large-finetuned-conll02-spanish": 512,
    "xlm-roberta-large-finetuned-conll03-english": 512,
    "xlm-roberta-large-finetuned-conll03-german": 512,
}

class 		lowercase					(					_UpperCAmelCase					):
      _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']





      def __init__(       self      ,						lowercase      ,						lowercase="<s>"      ,						lowercase="</s>"      ,						lowercase="</s>"      ,						lowercase="<s>"      ,						lowercase="<unk>"      ,						lowercase="<pad>"      ,						lowercase="<mask>"      ,						lowercase = None      ,						**lowercase      ,						)		->     None:
            # Mask token behave like a normal word, i.e. include the space before it
            lowerCAmelCase  						=       AddedToken(lowercase      ,						lstrip=lowercase      ,						rstrip=lowercase ) if isinstance(lowercase      ,						lowercase ) else mask_token

            lowerCAmelCase  						=       {} if sp_model_kwargs is None else sp_model_kwargs

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

            lowerCAmelCase  						=       spm.SentencePieceProcessor(**self.sp_model_kwargs )
            self.sp_model.Load(str(lowercase ) )
            lowerCAmelCase  						=       vocab_file

            # Original fairseq vocab and spm vocab must be "aligned":
            # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
            # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
            # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
            # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

            # Mimic fairseq token-to-id alignment for the first 4 token
            lowerCAmelCase  						=       {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

            # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
            lowerCAmelCase  						=       1

            lowerCAmelCase  						=       len(self.sp_model ) + self.fairseq_offset
            lowerCAmelCase  						=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}





      def __getstate__(       self )		->     Optional[Any]:
            lowerCAmelCase  						=       self.__dict__.copy()
            lowerCAmelCase  						=       None
            lowerCAmelCase  						=       self.sp_model.serialized_model_proto()
            return state





      def __setstate__(       self      ,						lowercase )		->     int:
            lowerCAmelCase  						=       d

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

            lowerCAmelCase  						=       spm.SentencePieceProcessor(**self.sp_model_kwargs )
            self.sp_model.LoadFromSerializedProto(self.sp_model_proto )





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = None )		->     List[int]:

            if token_ids_a is None:
                  return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
            lowerCAmelCase  						=       [self.cls_token_id]
            lowerCAmelCase  						=       [self.sep_token_id]
            return cls + token_ids_a + sep + sep + token_ids_a + sep





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = None      ,						lowercase = False )		->     List[int]:

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

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





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = None )		->     List[int]:
            lowerCAmelCase  						=       [self.sep_token_id]
            lowerCAmelCase  						=       [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 + sep + token_ids_a + sep ) * [0]





      @property
      def     _snake_case			(       self )		->     Optional[Any]:
            return len(self.sp_model ) + self.fairseq_offset + 1  # Add the <mask> token





      def     _snake_case			(       self )		->     str:
            lowerCAmelCase  						=       {self.convert_ids_to_tokens(lowercase ): i for i in range(self.vocab_size )}
            vocab.update(self.added_tokens_encoder )
            return vocab





      def     _snake_case			(       self      ,						lowercase )		->     List[str]:
            return self.sp_model.encode(lowercase      ,						out_type=lowercase )





      def     _snake_case			(       self      ,						lowercase )		->     Tuple:
            if token in self.fairseq_tokens_to_ids:
                  return self.fairseq_tokens_to_ids[token]
            lowerCAmelCase  						=       self.sp_model.PieceToId(lowercase )

            # Need to return unknown token if the SP model returned 0
            return spm_id + self.fairseq_offset if spm_id else self.unk_token_id





      def     _snake_case			(       self      ,						lowercase )		->     List[str]:
            if index in self.fairseq_ids_to_tokens:
                  return self.fairseq_ids_to_tokens[index]
            return self.sp_model.IdToPiece(index - self.fairseq_offset )





      def     _snake_case			(       self      ,						lowercase )		->     List[Any]:
            lowerCAmelCase  						=       """""".join(lowercase ).replace(lowercase      ,						""" """ ).strip()
            return out_string





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = None )		->     Tuple[str]:
            if not os.path.isdir(lowercase ):
                  logger.error(f'Vocabulary path ({save_directory}) should be a directory' )
                  return
            lowerCAmelCase  						=       os.path.join(
                lowercase      ,						(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

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

            return (out_vocab_file,)











'''simple docstring'''


def 				__lowerCamelCase				(   A__    )       ->	list:






   """simple docstring"""
   UpperCamelCase					=  len(A__    )
   for i in range(1    ,						A__    ):
      UpperCamelCase					=  collection[i]
      UpperCamelCase					=  0
      UpperCamelCase					=  i - 1

      while low <= high:
         UpperCamelCase					=  (low + high) // 2
         if val < collection[mid]:
            UpperCamelCase					=  mid - 1
         else:
            UpperCamelCase					=  mid + 1
      for j in range(A__    ,						A__    ,						-1    ):
         UpperCamelCase					=  collection[j - 1]
      UpperCamelCase					=  val
   return collection


if __name__ == "__main__":
   _lowerCamelCase	:       int      	=	input("Enter numbers separated by a comma:\n").strip()
   _lowerCamelCase	:       Union[str, Any]      	=	[int(item) for item in user_input.split(",")]
   print(binary_insertion_sort(unsorted))

