



"""simple docstring"""






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


__UpperCAmelCase   :   Dict        =       logging.get_logger(__name__)


__UpperCAmelCase   :   Optional[Any]        =       {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

# See all MVP models at https://huggingface.co/models?filter=mvp
__UpperCAmelCase   :   Optional[int]        =       {
    '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',
    },
}

__UpperCAmelCase   :   Optional[int]        =       {
    'RUCAIBox/mvp': 10_24,
}

class 						__lowerCAmelCase				(UpperCamelCase__	):


					'''simple docstring'''


					a__          =  VOCAB_FILES_NAMES
					a__          =  PRETRAINED_VOCAB_FILES_MAP
					a__          =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					a__          =  ['input_ids', 'attention_mask']
					a__          =  MvpTokenizer







					def __init__(   self     ,							a=None     ,							a=None     ,							a=None     ,							a="replace"     ,							a="<s>"     ,							a="</s>"     ,							a="</s>"     ,							a="<s>"     ,							a="<unk>"     ,							a="<pad>"     ,							a="<mask>"     ,							a=False     ,							a=True     ,							**a     ,							):




										"""simple docstring"""





										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     ,							)

										snake_case_    :Optional[int]										=    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
										if pre_tok_state.get("add_prefix_space"     ,							a ) != add_prefix_space:
															snake_case_    :str										=    getattr(a     ,							pre_tok_state.pop("type" ) )
															snake_case_    :List[str]										=    add_prefix_space
															snake_case_    :List[Any]										=    pre_tok_class(**a )

										snake_case_    :Optional[int]										=    add_prefix_space

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

															snake_case_    :Optional[Any]										=    False

															if state.get("add_prefix_space"     ,							a ) != add_prefix_space:
																				snake_case_    :Union[str, Any]										=    add_prefix_space
																				snake_case_    :str										=    True

															if state.get("trim_offsets"     ,							a ) != trim_offsets:
																				snake_case_    :Tuple										=    trim_offsets
																				snake_case_    :str										=    True

															if changes_to_apply:
																				snake_case_    :Union[str, Any]										=    getattr(a     ,							state.pop("type" ) )
																				snake_case_    :Dict										=    component_class(**a )
																				setattr(self.backend_tokenizer     ,							a     ,							a )







					@property
					def 		_a			(   self ):




										"""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 		_a			(   self     ,							a ):




										"""simple docstring"""





										snake_case_    :List[Any]										=    AddedToken(a     ,							lstrip=a     ,							rstrip=a ) if isinstance(a     ,							a ) else value
										snake_case_    :Dict										=    value







					def 		_a			(   self     ,							*a     ,							**a ):




										"""simple docstring"""





										snake_case_    :List[str]										=    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 		_a			(   self     ,							*a     ,							**a ):




										"""simple docstring"""





										snake_case_    :Tuple										=    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 		_a			(   self     ,							a     ,							a = None ):




										"""simple docstring"""





										snake_case_    :List[str]										=    self._tokenizer.model.save(a     ,							name=a )
										return tuple(a )







					def 		_a			(   self     ,							a     ,							a=None ):




										"""simple docstring"""





										snake_case_    :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 		_a			(   self     ,							a     ,							a = None ):




										"""simple docstring"""





										snake_case_    :List[Any]										=    [self.sep_token_id]
										snake_case_    :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]



'''simple docstring'''
def      UpperCamelCase_				(      A__						):
	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__":
		lowercase__											=input('Enter numbers separated by a comma:\n').strip()
		lowercase__											=[int(item) for item in user_input.split(',')]
		print(gnome_sort(unsorted))
