


'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase_ :     Tuple								=      logging.get_logger(__name__)


UpperCAmelCase_ :     Dict								=      '▁'

UpperCAmelCase_ :     Tuple								=      {'vocab_file': 'spiece.model'}

UpperCAmelCase_ :     Tuple								=      {
    'vocab_file': {
        'google/reformer-crime-and-punishment': (
            'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
        )
    }
}

UpperCAmelCase_ :     Union[str, Any]								=      {
    'google/reformer-crime-and-punishment': 5_2_4_2_8_8,
}

class 						_lowerCamelCase					(    snake_case_				):




 '''simple docstring'''
 __lowercase				:		Tuple    							=						VOCAB_FILES_NAMES
 __lowercase				:		Tuple    							=						PRETRAINED_VOCAB_FILES_MAP
 __lowercase				:		Optional[Any]    							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowercase				:		str    							=						['''input_ids''', '''attention_mask''']


 def __init__(      self      ,      __lowercase      ,      __lowercase="</s>"      ,      __lowercase="<unk>"      ,      __lowercase=[]      ,      __lowercase = None      ,      **__lowercase      ,      ):

  """simple docstring"""







  __A  :		Any       =			{} if sp_model_kwargs is None else sp_model_kwargs

  super().__init__(
      eos_token=__lowercase      ,      unk_token=__lowercase      ,      additional_special_tokens=__lowercase      ,      sp_model_kwargs=self.sp_model_kwargs      ,      **__lowercase      ,      )

  __A  :		Optional[Any]       =			vocab_file
  __A  :		Dict       =			spm.SentencePieceProcessor(**self.sp_model_kwargs						)
  self.sp_model.Load(__lowercase						)


 @property
 def  snake_case__   (      self						):

  """simple docstring"""







  return self.sp_model.get_piece_size()


 def  snake_case__   (      self						):

  """simple docstring"""







  __A  :		Dict       =			{self.convert_ids_to_tokens(__lowercase						): i for i in range(self.vocab_size						)}
  vocab.update(self.added_tokens_encoder						)
  return vocab


 def __getstate__(      self						):

  """simple docstring"""







  __A  :		Tuple       =			self.__dict__.copy()
  __A  :		Union[str, Any]       =			None
  return state


 def __setstate__(      self      ,      __lowercase						):

  """simple docstring"""







  __A  :		Optional[Any]       =			d

  # for backward compatibility
  if not hasattr(self      ,      'sp_model_kwargs'						):
   __A  :		str       =			{}

  __A  :		Optional[int]       =			spm.SentencePieceProcessor(**self.sp_model_kwargs						)
  self.sp_model.Load(self.vocab_file						)


 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  return self.sp_model.encode(__lowercase      ,      out_type=__lowercase						)


 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  return self.sp_model.piece_to_id(__lowercase						)


 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  if index < self.sp_model.get_piece_size():
   __A  :		List[Any]       =			self.sp_model.IdToPiece(__lowercase						)
  return token


 def  snake_case__   (      self      ,      __lowercase						):

  """simple docstring"""







  __A  :		Optional[int]       =			[]
  __A  :		List[str]       =			''
  for token in tokens:
   # make sure that special tokens are not decoded using sentencepiece model
   if token in self.all_special_tokens:
    out_string += self.sp_model.decode(__lowercase						) + token
    __A  :		List[str]       =			[]
   else:
    current_sub_tokens.append(__lowercase						)
  out_string += self.sp_model.decode(__lowercase						)
  return out_string.strip()







 def  snake_case__   (      self      ,      __lowercase      ,      __lowercase = None						):

  """simple docstring"""







  if not os.path.isdir(__lowercase						):
   logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
   return
  __A  :		Tuple       =			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:
    __A  :		Optional[int]       =			self.sp_model.serialized_model_proto()
    fi.write(__lowercase						)

  return (out_vocab_file,)










'''simple docstring'''
from __future__ import annotations


def 			_lowercase       (				UpperCamelCase__       :					list,				UpperCamelCase__       :					int,				UpperCamelCase__       :					int,				UpperCamelCase__       :					int			):
 __A  :		Dict       =			[]
 __A     ,__A  :		Dict       =			input_list[low:mid], input_list[mid : high + 1]
 while left and right:
  result.append((left if left[0] <= right[0] else right).pop(0			)			)
 __A  :		Optional[Any]       =			result + left + right
 return input_list


def 			_lowercase       (				UpperCamelCase__       :					list			):
 if len(UpperCamelCase__			) <= 1:
  return input_list
 __A  :		Any       =			list(UpperCamelCase__			)

 # iteration for two-way merging
 __A  :		Dict       =			2
 while p <= len(UpperCamelCase__			):
  # getting low, high and middle value for merge-sort of single list
  for i in range(0,				len(UpperCamelCase__			),				UpperCamelCase__			):
   __A  :		Union[str, Any]       =			i
   __A  :		Tuple       =			i + p - 1
   __A  :		Union[str, Any]       =			(low + high + 1) // 2
   __A  :		Tuple       =			merge(UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__			)
  # final merge of last two parts
  if p * 2 >= len(UpperCamelCase__			):
   __A  :		Optional[int]       =			i
   __A  :		str       =			merge(UpperCamelCase__,				0,				UpperCamelCase__,				len(UpperCamelCase__			) - 1			)
   break
  p *= 2

 return input_list


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






