






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

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


if is_sentencepiece_available():
		from .tokenization_xlm_roberta import XLMRobertaTokenizer
else:
		__UpperCAmelCase										=		None


__UpperCAmelCase										=		logging.get_logger(__name__)

__UpperCAmelCase										=		{'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

__UpperCAmelCase										=		{
    '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'
        ),
    },
    'tokenizer_file': {
        'xlm-roberta-base': 'https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json',
        'xlm-roberta-large': 'https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json',
        'xlm-roberta-large-finetuned-conll02-dutch': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll02-spanish': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-english': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json'
        ),
        'xlm-roberta-large-finetuned-conll03-german': (
            'https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json'
        ),
    },
}

__UpperCAmelCase										=		{
    '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 						lowerCamelCase   (_snake_case    ):







		'''simple docstring'''



		_snake_case					:					List[Any] 		=						VOCAB_FILES_NAMES
		_snake_case					:					Tuple 		=						PRETRAINED_VOCAB_FILES_MAP
		_snake_case					:					List[Any] 		=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_snake_case					:					Any 		=						['''input_ids''', '''attention_mask''']
		_snake_case					:					Dict 		=						XLMRobertaTokenizer



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

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

							UpperCAmelCase_					:   Any   =		vocab_file
							UpperCAmelCase_					:   Tuple   =		False if not self.vocab_file else True



		def       __UpperCAmelCase    (							self       ,	_UpperCamelCase       ,	_UpperCamelCase = None     )			->							List[int]:

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



		def       __UpperCAmelCase    (							self       ,	_UpperCamelCase       ,	_UpperCamelCase = None     )			->							List[int]:
							UpperCAmelCase_					:   int   =		[self.sep_token_id]
							UpperCAmelCase_					:   Any   =		[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       ,	_UpperCamelCase       ,	_UpperCamelCase = 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(_UpperCamelCase     ):
												logger.error(f"Vocabulary path ({save_directory}) should be a directory."     )
												return
							UpperCAmelCase_					:   Optional[Any]   =		os.path.join(
							    _UpperCamelCase       ,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )

							if os.path.abspath(self.vocab_file     ) != os.path.abspath(_UpperCamelCase     ):
												copyfile(self.vocab_file       ,	_UpperCamelCase     )

							return (out_vocab_file,)














from __future__ import annotations




def   lowercase__   (  __snake_case					:							Any  , __snake_case					:							int						):


					'''simple docstring'''


					UpperCAmelCase_					:   Optional[int]   =		0
					UpperCAmelCase_					:   Optional[int]   =		len(__snake_case						) - 1
					while left <= right:
										UpperCAmelCase_					:   Optional[Any]   =		(left + right) // 2
										if left == right:
															if sorted_list[middle] < item:
																				UpperCAmelCase_					:   List[Any]   =		middle + 1
															break
										elif sorted_list[middle] < item:
															UpperCAmelCase_					:   Union[str, Any]   =		middle + 1
										else:
															UpperCAmelCase_					:   Tuple   =		middle - 1
					sorted_list.insert(__snake_case  , __snake_case						)
					return sorted_list




def   lowercase__   (  __snake_case					:							Union[str, Any]  , __snake_case					:							int						):


					'''simple docstring'''


					UpperCAmelCase_					:   str   =		[]
					while left and right:
										if left[0][0] < right[0][0]:
															result.append(left.pop(0						)						)
										else:
															result.append(right.pop(0						)						)
					return result + left + right




def   lowercase__   (  __snake_case					:							Dict						):


					'''simple docstring'''


					UpperCAmelCase_					:   str   =		len(__snake_case						)
					if length <= 1:
										return list_ad
					UpperCAmelCase_					:   List[Any]   =		length // 2
					return merge(sortlist_ad(list_ad[:middle]						)  , sortlist_ad(list_ad[middle:]						)						)




def   lowercase__   (  __snake_case					:							list[int]						):


					'''simple docstring'''


					if len(__snake_case						) <= 1:
										return collection
					UpperCAmelCase_					:   Any   =		[]
					UpperCAmelCase_					:   Union[str, Any]   =		False
					for i in range(0  , len(__snake_case						)  , 2						):
										if i == len(__snake_case						) - 1:
															UpperCAmelCase_					:   Tuple   =		True
										else:
															if collection[i] < collection[i + 1]:
																				two_paired_list.append([collection[i], collection[i + 1]]						)
															else:
																				two_paired_list.append([collection[i + 1], collection[i]]						)
					UpperCAmelCase_					:   Union[str, Any]   =		sortlist_ad(__snake_case						)
					UpperCAmelCase_					:   Any   =		[i[0] for i in sorted_list_ad]
					result.append(sorted_list_ad[-1][1]						)
					if has_last_odd_item:
										UpperCAmelCase_					:   Union[str, Any]   =		collection[-1]
										UpperCAmelCase_					:   List[Any]   =		binary_search_insertion(__snake_case  , __snake_case						)
					UpperCAmelCase_					:   Tuple   =		False
					for i in range(len(__snake_case						) - 1						):
										if result[i] == collection[-1] and has_last_odd_item:
															UpperCAmelCase_					:   List[Any]   =		True
										UpperCAmelCase_					:   Optional[int]   =		sorted_list_ad[i][1]
										# If last_odd_item is inserted before the item's index,
										# you should forward index one more.
										if is_last_odd_item_inserted_before_this_index:
															UpperCAmelCase_					:   List[str]   =		result[: i + 2] + binary_search_insertion(result[i + 2 :]  , __snake_case						)
										else:
															UpperCAmelCase_					:   List[Any]   =		result[: i + 1] + binary_search_insertion(result[i + 1 :]  , __snake_case						)

					return result


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






