
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_bart import BartTokenizer


SCREAMING_SNAKE_CASE							:Optional[Any]							 =				logging.get_logger(__name__)


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

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE							:Dict							 =				{
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json',
    },
}

SCREAMING_SNAKE_CASE							:Tuple							 =				{
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}





class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	snake_case_					    =     VOCAB_FILES_NAMES
	snake_case_					    =     PRETRAINED_VOCAB_FILES_MAP
	snake_case_					    =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	snake_case_					    =     ["input_ids", "attention_mask"]
	snake_case_					    =     BartTokenizer






	def __init__(       self					: Any							,A					: Optional[Any]=None							,A					: str=None							,A					: Optional[Any]=None							,A					: Tuple="replace"							,A					: List[Any]="<s>"							,A					: Dict="</s>"							,A					: str="</s>"							,A					: Union[str, Any]="<s>"							,A					: List[Any]="<unk>"							,A					: str="<pad>"							,A					: Union[str, Any]="<mask>"							,A					: int=False							,A					: Optional[int]=True							,**A					: Any							,):
					super().__init__(
					    A							,A							,tokenizer_file=A							,errors=A							,bos_token=A							,eos_token=A							,sep_token=A							,cls_token=A							,unk_token=A							,pad_token=A							,mask_token=A							,add_prefix_space=A							,trim_offsets=A							,**A							,)

					__A   			= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
					if pre_tok_state.get("add_prefix_space"							,A ) != add_prefix_space:
									__A   			= getattr(A							,pre_tok_state.pop("type" ) )
									__A   			= add_prefix_space
									__A   			= pre_tok_class(**A )

					__A   			= add_prefix_space

					# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
					__A   			= "post_processor"
					__A   			= getattr(self.backend_tokenizer							,A							,A )
					if tokenizer_component_instance:
									__A   			= 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   			= tuple(state["sep"] )
									if "cls" in state:
													__A   			= tuple(state["cls"] )

									__A   			= False

									if state.get("add_prefix_space"							,A ) != add_prefix_space:
													__A   			= add_prefix_space
													__A   			= True

									if state.get("trim_offsets"							,A ) != trim_offsets:
													__A   			= trim_offsets
													__A   			= True

									if changes_to_apply:
													__A   			= getattr(A							,state.pop("type" ) )
													__A   			= component_class(**A )
													setattr(self.backend_tokenizer							,A							,A )






	@property
	def 				UpperCamelCase_  (       self					: Tuple ):
					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 				UpperCamelCase_  (       self					: str							,A					: Dict ):
					__A   			= AddedToken(A							,lstrip=A							,rstrip=A ) if isinstance(A							,A ) else value
					__A   			= value






	def 				UpperCamelCase_  (       self					: List[str]							,*A					: List[Any]							,**A					: List[str] ):
					__A   			= kwargs.get("is_split_into_words"							,A )

					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(*A							,**A )






	def 				UpperCamelCase_  (       self					: Optional[Any]							,*A					: Tuple							,**A					: Any ):
					__A   			= kwargs.get("is_split_into_words"							,A )

					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(*A							,**A )






	def 				UpperCamelCase_  (       self					: Tuple							,A					: str							,A					: Optional[str] = None ):
					__A   			= self._tokenizer.model.save(A							,name=A )
					return tuple(A )






	def 				UpperCamelCase_  (       self					: Union[str, Any]							,A					: Optional[Any]							,A					: Union[str, Any]=None ):
					__A   			= [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 				UpperCamelCase_  (       self					: int							,A					: List[int]							,A					: Optional[List[int]] = None ):
					__A   			= [self.sep_token_id]
					__A   			= [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			(	a_						)		->	list:







				"""simple docstring"""



				if len(a_						) <= 1:
								return lst

				__A   			= 1

				while i < len(a_						):
								if lst[i - 1] <= lst[i]:
												i += 1
								else:
												__A			,							__A   			= lst[i], lst[i - 1]
												i -= 1
												if i == 0:
																__A   			= 1

				return lst


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