


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

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
		from .tokenization_mbart import MBartTokenizer
else:
		lowerCAmelCase__    :str       =				None


lowerCAmelCase__    :str       =				logging.get_logger(__name__)


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

lowerCAmelCase__    :int       =				{
    '''vocab_file''': {
        '''facebook/mbart-large-en-ro''': (
            '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'''
        ),
        '''facebook/mbart-large-cc25''': (
            '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''facebook/mbart-large-en-ro''': '''https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json''',
        '''facebook/mbart-large-cc25''': '''https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json''',
    },
}

lowerCAmelCase__    :int       =				{
    '''facebook/mbart-large-en-ro''': 1_0_2_4,
    '''facebook/mbart-large-cc25''': 1_0_2_4,
}

# fmt: off
lowerCAmelCase__    :str       =				['''ar_AR''', '''cs_CZ''', '''de_DE''', '''en_XX''', '''es_XX''', '''et_EE''', '''fi_FI''', '''fr_XX''', '''gu_IN''', '''hi_IN''', '''it_IT''', '''ja_XX''', '''kk_KZ''', '''ko_KR''', '''lt_LT''', '''lv_LV''', '''my_MM''', '''ne_NP''', '''nl_XX''', '''ro_RO''', '''ru_RU''', '''si_LK''', '''tr_TR''', '''vi_VN''', '''zh_CN''']

class 						__a (							UpperCAmelCase     ):
		_a      :    List[str]           =      VOCAB_FILES_NAMES
		_a      :    Tuple           =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_a      :    Union[str, Any]           =      PRETRAINED_VOCAB_FILES_MAP
		_a      :    int           =      ['input_ids', 'attention_mask']
		_a      :    Optional[Any]           =      MBartTokenizer

		_a      :    List[int]           =      []
		_a      :    List[int]           =      []
		def __init__(     self     ,       _SCREAMING_SNAKE_CASE=None     ,       _SCREAMING_SNAKE_CASE=None     ,       _SCREAMING_SNAKE_CASE="<s>"     ,       _SCREAMING_SNAKE_CASE="</s>"     ,       _SCREAMING_SNAKE_CASE="</s>"     ,       _SCREAMING_SNAKE_CASE="<s>"     ,       _SCREAMING_SNAKE_CASE="<unk>"     ,       _SCREAMING_SNAKE_CASE="<pad>"     ,       _SCREAMING_SNAKE_CASE="<mask>"     ,       _SCREAMING_SNAKE_CASE=None     ,       _SCREAMING_SNAKE_CASE=None     ,       _SCREAMING_SNAKE_CASE=None     ,       **_SCREAMING_SNAKE_CASE     ,       )					->			str:




									"""simple docstring"""





									_UpperCAmelCase											=     AddedToken(_SCREAMING_SNAKE_CASE     ,       lstrip=_SCREAMING_SNAKE_CASE     ,       rstrip=_SCREAMING_SNAKE_CASE		) if isinstance(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE		) else mask_token

									super().__init__(
									    vocab_file=_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     ,       mask_token=_SCREAMING_SNAKE_CASE     ,       src_lang=_SCREAMING_SNAKE_CASE     ,       tgt_lang=_SCREAMING_SNAKE_CASE     ,       additional_special_tokens=_SCREAMING_SNAKE_CASE     ,       **_SCREAMING_SNAKE_CASE     ,       )

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

									_UpperCAmelCase											=     FAIRSEQ_LANGUAGE_CODES.copy()

									if additional_special_tokens is not None:
																# Only add those special tokens if they are not already there.
																_additional_special_tokens.extend(
																    [t for t in additional_special_tokens if t not in _additional_special_tokens]		)

									self.add_special_tokens({'additional_special_tokens': _additional_special_tokens}		)
									_UpperCAmelCase											=     {
									    lang_code: self.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		) for lang_code in FAIRSEQ_LANGUAGE_CODES
									}

									_UpperCAmelCase											=     src_lang if src_lang is not None else 'en_XX'
									_UpperCAmelCase											=     self.convert_tokens_to_ids(self._src_lang		)
									_UpperCAmelCase											=     tgt_lang
									self.set_src_lang_special_tokens(self._src_lang		)
		@property
		def       UpperCAmelCase__							(     self		)					->			str:




									"""simple docstring"""





									return self._src_lang
		@src_lang.setter
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE		)					->			None:




									"""simple docstring"""





									_UpperCAmelCase											=     new_src_lang
									self.set_src_lang_special_tokens(self._src_lang		)
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE = None		)					->			List[int]:




									"""simple docstring"""





									if token_ids_a is None:
																return self.prefix_tokens + token_ids_a + self.suffix_tokens
									# We don't expect to process pairs, but leave the pair logic for API consistency
									return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE = None		)					->			List[int]:




									"""simple docstring"""





									_UpperCAmelCase											=     [self.sep_token_id]
									_UpperCAmelCase											=     [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]
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       **_SCREAMING_SNAKE_CASE		)					->			int:




									"""simple docstring"""





									if src_lang is None or tgt_lang is None:
																raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model'		)
									_UpperCAmelCase											=     src_lang
									_UpperCAmelCase											=     self(_SCREAMING_SNAKE_CASE     ,       add_special_tokens=_SCREAMING_SNAKE_CASE     ,       return_tensors=_SCREAMING_SNAKE_CASE     ,       **_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     self.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     tgt_lang_id
									return inputs
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE = "en_XX"     ,       _SCREAMING_SNAKE_CASE = None     ,       _SCREAMING_SNAKE_CASE = "ro_RO"     ,       **_SCREAMING_SNAKE_CASE     ,       )					->			BatchEncoding:




									"""simple docstring"""





									_UpperCAmelCase											=     src_lang
									_UpperCAmelCase											=     tgt_lang
									return super().prepare_seqaseq_batch(_SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE     ,       **_SCREAMING_SNAKE_CASE		)
		def       UpperCAmelCase__							(     self		)					->			Dict:




									"""simple docstring"""





									return self.set_src_lang_special_tokens(self.src_lang		)
		def       UpperCAmelCase__							(     self		)					->			List[Any]:




									"""simple docstring"""





									return self.set_tgt_lang_special_tokens(self.tgt_lang		)
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE		)					->			None:




									"""simple docstring"""





									_UpperCAmelCase											=     self.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     []
									_UpperCAmelCase											=     [self.eos_token_id, self.cur_lang_code]

									_UpperCAmelCase											=     self.convert_ids_to_tokens(self.prefix_tokens		)
									_UpperCAmelCase											=     self.convert_ids_to_tokens(self.suffix_tokens		)

									_UpperCAmelCase											=     processors.TemplateProcessing(
									    single=prefix_tokens_str + ['$A'] + suffix_tokens_str     ,       pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str     ,       special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str     ,       self.prefix_tokens + self.suffix_tokens		)		)     ,       )
		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE		)					->			None:




									"""simple docstring"""





									_UpperCAmelCase											=     self.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase											=     []
									_UpperCAmelCase											=     [self.eos_token_id, self.cur_lang_code]

									_UpperCAmelCase											=     self.convert_ids_to_tokens(self.prefix_tokens		)
									_UpperCAmelCase											=     self.convert_ids_to_tokens(self.suffix_tokens		)

									_UpperCAmelCase											=     processors.TemplateProcessing(
									    single=prefix_tokens_str + ['$A'] + suffix_tokens_str     ,       pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str     ,       special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str     ,       self.prefix_tokens + self.suffix_tokens		)		)     ,       )






		def       UpperCAmelCase__							(     self     ,       _SCREAMING_SNAKE_CASE     ,       _SCREAMING_SNAKE_CASE = None		)					->			Tuple[str]:




									"""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(_SCREAMING_SNAKE_CASE		):
																logger.error(f'''Vocabulary path ({save_directory}) should be a directory.'''		)
																return
									_UpperCAmelCase											=     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__					(     a__:						Optional[int]			)    ->						Optional[int]:


							'''simple docstring'''





							_UpperCAmelCase											=     len(a__			)
							for i in range(length - 1			):
														_UpperCAmelCase											=     i
														for k in range(i + 1     ,    a__			):
																					if collection[k] < collection[least]:
																												_UpperCAmelCase											=     k
														if least != i:
																					_UpperCAmelCase						,			_UpperCAmelCase											=     (collection[i], collection[least])
							return collection


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