






import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer


SCREAMING_SNAKE_CASE__				     =			logging.get_logger(__name__)


SCREAMING_SNAKE_CASE__				     =			{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all MVP models at https://huggingface.co/models?filter=mvp
SCREAMING_SNAKE_CASE__				     =			{
    '''vocab_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json''',
    },
    '''added_tokens.json''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json''',
    },
    '''merges_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/tokenizer.json''',
    },
}

SCREAMING_SNAKE_CASE__				     =			{
    '''RUCAIBox/mvp''': 1024,
}






class 			_UpperCamelCase(       __lowerCamelCase		):
		__SCREAMING_SNAKE_CASE  :       Optional[Any]							=							VOCAB_FILES_NAMES
		__SCREAMING_SNAKE_CASE  :       str							=							PRETRAINED_VOCAB_FILES_MAP
		__SCREAMING_SNAKE_CASE  :       Union[str, Any]							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		__SCREAMING_SNAKE_CASE  :       List[Any]							=							['''input_ids''', '''attention_mask''']
		__SCREAMING_SNAKE_CASE  :       Optional[int]							=							MvpTokenizer

		def __init__(					self		:    List[Any]    ,       SCREAMING_SNAKE_CASE__		:    Union[str, Any]=None    ,       SCREAMING_SNAKE_CASE__		:    Any=None    ,       SCREAMING_SNAKE_CASE__		:    Any=None    ,       SCREAMING_SNAKE_CASE__		:    int="replace"    ,       SCREAMING_SNAKE_CASE__		:    List[str]="<s>"    ,       SCREAMING_SNAKE_CASE__		:    Optional[Any]="</s>"    ,       SCREAMING_SNAKE_CASE__		:    Union[str, Any]="</s>"    ,       SCREAMING_SNAKE_CASE__		:    Dict="<s>"    ,       SCREAMING_SNAKE_CASE__		:    Optional[int]="<unk>"    ,       SCREAMING_SNAKE_CASE__		:    Dict="<pad>"    ,       SCREAMING_SNAKE_CASE__		:    List[str]="<mask>"    ,       SCREAMING_SNAKE_CASE__		:    Union[str, Any]=False    ,       SCREAMING_SNAKE_CASE__		:    str=True    ,       **SCREAMING_SNAKE_CASE__		:    str    ,       ):



					'''simple docstring'''



					super().__init__(
					    SCREAMING_SNAKE_CASE__    ,       SCREAMING_SNAKE_CASE__    ,       tokenizer_file=SCREAMING_SNAKE_CASE__    ,       errors=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__    ,       mask_token=SCREAMING_SNAKE_CASE__    ,       add_prefix_space=SCREAMING_SNAKE_CASE__    ,       trim_offsets=SCREAMING_SNAKE_CASE__    ,       **SCREAMING_SNAKE_CASE__    ,       )

					__a						:  Dict									=     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()    )
					if pre_tok_state.get('add_prefix_space'    ,       SCREAMING_SNAKE_CASE__    ) != add_prefix_space:
								__a						:  Dict									=     getattr(SCREAMING_SNAKE_CASE__    ,       pre_tok_state.pop('type'    )    )
								__a						:  Optional[Any]									=     add_prefix_space
								__a						:  Any									=     pre_tok_class(**SCREAMING_SNAKE_CASE__    )

					__a						:  Union[str, Any]									=     add_prefix_space

					# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
					__a						:  List[Any]									=     'post_processor'
					__a						:  Dict									=     getattr(self.backend_tokenizer    ,       SCREAMING_SNAKE_CASE__    ,       SCREAMING_SNAKE_CASE__    )
					if tokenizer_component_instance:
								__a						:  Tuple									=     json.loads(tokenizer_component_instance.__getstate__()    )

								# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
								if "sep" in state:
											__a						:  List[Any]									=     tuple(state['sep']    )
								if "cls" in state:
											__a						:  Tuple									=     tuple(state['cls']    )

								__a						:  List[Any]									=     False

								if state.get('add_prefix_space'    ,       SCREAMING_SNAKE_CASE__    ) != add_prefix_space:
											__a						:  str									=     add_prefix_space
											__a						:  List[str]									=     True

								if state.get('trim_offsets'    ,       SCREAMING_SNAKE_CASE__    ) != trim_offsets:
											__a						:  str									=     trim_offsets
											__a						:  Optional[int]									=     True

								if changes_to_apply:
											__a						:  Optional[Any]									=     getattr(SCREAMING_SNAKE_CASE__    ,       state.pop('type'    )    )
											__a						:  Optional[Any]									=     component_class(**SCREAMING_SNAKE_CASE__    )
											setattr(self.backend_tokenizer    ,       SCREAMING_SNAKE_CASE__    ,       SCREAMING_SNAKE_CASE__    )

		@property
		def    __lowerCAmelCase  (					self		:    Dict    ):



					'''simple docstring'''



					if self._mask_token is None:
								if self.verbose:
											logger.error('Using mask_token, but it is not set yet.'    )
								return None
					return str(self._mask_token    )

		@mask_token.setter
		def    __lowerCAmelCase  (					self		:    Dict    ,       SCREAMING_SNAKE_CASE__		:    Tuple    ):



					'''simple docstring'''



					__a						:  Optional[Any]									=     AddedToken(SCREAMING_SNAKE_CASE__    ,       lstrip=SCREAMING_SNAKE_CASE__    ,       rstrip=SCREAMING_SNAKE_CASE__    ) if isinstance(SCREAMING_SNAKE_CASE__    ,       SCREAMING_SNAKE_CASE__    ) else value
					__a						:  Dict									=     value

		def    __lowerCAmelCase  (					self		:    Optional[int]    ,       *SCREAMING_SNAKE_CASE__		:    Optional[int]    ,       **SCREAMING_SNAKE_CASE__		:    List[str]    ):



					'''simple docstring'''



					__a						:  Union[str, Any]									=     kwargs.get('is_split_into_words'    ,       SCREAMING_SNAKE_CASE__    )

					if is_split_into_words and not self.add_prefix_space:
								raise ValueError(
								    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
								    'to use it with pretokenized inputs.'    )

					return super()._batch_encode_plus(*SCREAMING_SNAKE_CASE__    ,       **SCREAMING_SNAKE_CASE__    )

		def    __lowerCAmelCase  (					self		:    int    ,       *SCREAMING_SNAKE_CASE__		:    Dict    ,       **SCREAMING_SNAKE_CASE__		:    Tuple    ):



					'''simple docstring'''



					__a						:  Dict									=     kwargs.get('is_split_into_words'    ,       SCREAMING_SNAKE_CASE__    )

					if is_split_into_words and not self.add_prefix_space:
								raise ValueError(
								    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
								    'to use it with pretokenized inputs.'    )

					return super()._encode_plus(*SCREAMING_SNAKE_CASE__    ,       **SCREAMING_SNAKE_CASE__    )

		def    __lowerCAmelCase  (					self		:    str    ,       SCREAMING_SNAKE_CASE__		:    str    ,       SCREAMING_SNAKE_CASE__		:    Optional[str] = None    ):



					'''simple docstring'''



					__a						:  int									=     self._tokenizer.model.save(SCREAMING_SNAKE_CASE__    ,       name=SCREAMING_SNAKE_CASE__    )
					return tuple(SCREAMING_SNAKE_CASE__    )

		def    __lowerCAmelCase  (					self		:    int    ,       SCREAMING_SNAKE_CASE__		:    Any    ,       SCREAMING_SNAKE_CASE__		:    Tuple=None    ):



					'''simple docstring'''



					__a						:  int									=     [self.bos_token_id] + token_ids_a + [self.eos_token_id]
					if token_ids_a is None:
								return output

					return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]



		def    __lowerCAmelCase  (					self		:    Dict    ,       SCREAMING_SNAKE_CASE__		:    List[int]    ,       SCREAMING_SNAKE_CASE__		:    Optional[List[int]] = None    ):



					'''simple docstring'''



					__a						:  Tuple									=     [self.sep_token_id]
					__a						:  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 + sep + token_ids_a + sep    ) * [0]









from __future__ import annotations




def    a__    (		snake_case__					:							list[int]     ):
  if len(snake_case__     ) == 0:
    return array

  _UpperCAmelCase,_UpperCAmelCase		:							List[str]							=     min(snake_case__     ), max(snake_case__     )

  # Compute the variables
  _UpperCAmelCase		:							Tuple							=     _max - _min + 1
  _UpperCAmelCase,_UpperCAmelCase		:							Union[str, Any]							=     [0] * holes_range, [0] * holes_range

  # Make the sorting.
  for i in array:
    _UpperCAmelCase		:							Optional[int]							=     i - _min
    _UpperCAmelCase		:							Any							=     i
    holes_repeat[index] += 1

  # Makes the array back by replacing the numbers.
  _UpperCAmelCase		:							List[Any]							=     0
  for i in range(snake_case__     ):
    while holes_repeat[i] > 0:
      _UpperCAmelCase		:							Optional[Any]							=     holes[i]
      index += 1
      holes_repeat[i] -= 1

    # Returns the sorted array.
  return array


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 SCREAMING_SNAKE_CASE__					:     Dict       =     input('Enter numbers separated by comma:\n')
 SCREAMING_SNAKE_CASE__					:     Optional[int]       =     [int(x) for x in user_input.split(',')]
 print(pigeon_sort(unsorted))





