






"""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


lowerCAmelCase__    						=			logging.get_logger(__name__)


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

# See all MVP models at https://huggingface.co/models?filter=mvp
lowerCAmelCase__    						=			{
    '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',
    },
}

lowerCAmelCase__    						=			{
    'RUCAIBox/mvp': 1_024,
}


class _lowerCAmelCase						(    __UpperCAmelCase       ):
						SCREAMING_SNAKE_CASE_:					str 					=				VOCAB_FILES_NAMES
						SCREAMING_SNAKE_CASE_:					Dict 					=				PRETRAINED_VOCAB_FILES_MAP
						SCREAMING_SNAKE_CASE_:					Any 					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						SCREAMING_SNAKE_CASE_:					Tuple 					=				['input_ids', 'attention_mask']
						SCREAMING_SNAKE_CASE_:					Any 					=				MvpTokenizer







						def __init__(    self   ,				lowerCAmelCase_=None   ,				lowerCAmelCase_=None   ,				lowerCAmelCase_=None   ,				lowerCAmelCase_="replace"   ,				lowerCAmelCase_="<s>"   ,				lowerCAmelCase_="</s>"   ,				lowerCAmelCase_="</s>"   ,				lowerCAmelCase_="<s>"   ,				lowerCAmelCase_="<unk>"   ,				lowerCAmelCase_="<pad>"   ,				lowerCAmelCase_="<mask>"   ,				lowerCAmelCase_=False   ,				lowerCAmelCase_=True   ,				**lowerCAmelCase_   ,				)		->							Dict:
										super().__init__(
										    lowerCAmelCase_   ,				lowerCAmelCase_   ,				tokenizer_file=lowerCAmelCase_   ,				errors=lowerCAmelCase_   ,				bos_token=lowerCAmelCase_   ,				eos_token=lowerCAmelCase_   ,				sep_token=lowerCAmelCase_   ,				cls_token=lowerCAmelCase_   ,				unk_token=lowerCAmelCase_   ,				pad_token=lowerCAmelCase_   ,				mask_token=lowerCAmelCase_   ,				add_prefix_space=lowerCAmelCase_   ,				trim_offsets=lowerCAmelCase_   ,				**lowerCAmelCase_   ,				)

										_SCREAMING_SNAKE_CASE   :		int       		=    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
										if pre_tok_state.get('add_prefix_space'   ,				lowerCAmelCase_							) != add_prefix_space:
														_SCREAMING_SNAKE_CASE   :		Dict       		=    getattr(lowerCAmelCase_   ,				pre_tok_state.pop('type'							)							)
														_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    add_prefix_space
														_SCREAMING_SNAKE_CASE   :		List[str]       		=    pre_tok_class(**lowerCAmelCase_							)

										_SCREAMING_SNAKE_CASE   :		Dict       		=    add_prefix_space

										# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
										_SCREAMING_SNAKE_CASE   :		Any       		=    'post_processor'
										_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    getattr(self.backend_tokenizer   ,				lowerCAmelCase_   ,				lowerCAmelCase_							)
										if tokenizer_component_instance:
														_SCREAMING_SNAKE_CASE   :		Any       		=    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:
																		_SCREAMING_SNAKE_CASE   :		Tuple       		=    tuple(state['sep']							)
														if "cls" in state:
																		_SCREAMING_SNAKE_CASE   :		List[str]       		=    tuple(state['cls']							)

														_SCREAMING_SNAKE_CASE   :		Tuple       		=    False

														if state.get('add_prefix_space'   ,				lowerCAmelCase_							) != add_prefix_space:
																		_SCREAMING_SNAKE_CASE   :		Dict       		=    add_prefix_space
																		_SCREAMING_SNAKE_CASE   :		int       		=    True

														if state.get('trim_offsets'   ,				lowerCAmelCase_							) != trim_offsets:
																		_SCREAMING_SNAKE_CASE   :		Union[str, Any]       		=    trim_offsets
																		_SCREAMING_SNAKE_CASE   :		int       		=    True

														if changes_to_apply:
																		_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    getattr(lowerCAmelCase_   ,				state.pop('type'							)							)
																		_SCREAMING_SNAKE_CASE   :		Dict       		=    component_class(**lowerCAmelCase_							)
																		setattr(self.backend_tokenizer   ,				lowerCAmelCase_   ,				lowerCAmelCase_							)







						@property
						def 			A      (    self							)		->							str:
										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   ,				lowerCAmelCase_							)		->							str:
										_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    AddedToken(lowerCAmelCase_   ,				lstrip=lowerCAmelCase_   ,				rstrip=lowerCAmelCase_							) if isinstance(lowerCAmelCase_   ,				lowerCAmelCase_							) else value
										_SCREAMING_SNAKE_CASE   :		Dict       		=    value







						def 			A      (    self   ,				*lowerCAmelCase_   ,				**lowerCAmelCase_							)		->							BatchEncoding:
										_SCREAMING_SNAKE_CASE   :		int       		=    kwargs.get('is_split_into_words'   ,				lowerCAmelCase_							)

										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(*lowerCAmelCase_   ,				**lowerCAmelCase_							)







						def 			A      (    self   ,				*lowerCAmelCase_   ,				**lowerCAmelCase_							)		->							BatchEncoding:
										_SCREAMING_SNAKE_CASE   :		Any       		=    kwargs.get('is_split_into_words'   ,				lowerCAmelCase_							)

										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(*lowerCAmelCase_   ,				**lowerCAmelCase_							)







						def 			A      (    self   ,				lowerCAmelCase_   ,				lowerCAmelCase_ = None							)		->							Tuple[str]:
										_SCREAMING_SNAKE_CASE   :		List[str]       		=    self._tokenizer.model.save(lowerCAmelCase_   ,				name=lowerCAmelCase_							)
										return tuple(lowerCAmelCase_							)







						def 			A      (    self   ,				lowerCAmelCase_   ,				lowerCAmelCase_=None							)		->							List[Any]:
										_SCREAMING_SNAKE_CASE   :		Optional[Any]       		=    [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   ,				lowerCAmelCase_   ,				lowerCAmelCase_ = None							)		->							List[int]:
										_SCREAMING_SNAKE_CASE   :		Any       		=    [self.sep_token_id]
										_SCREAMING_SNAKE_CASE   :		Optional[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]









"""simple docstring"""
from __future__ import annotations

from collections.abc import Generator





def 				lowercase__		(					):
				_SCREAMING_SNAKE_CASE   :		dict[int, int]       		=    {}
				_SCREAMING_SNAKE_CASE   :		List[Any]       		=    2
				while True:
								_SCREAMING_SNAKE_CASE   :		List[Any]       		=    factor_map.pop(lowerCamelCase,						lowerCamelCase       )
								if factor:
												_SCREAMING_SNAKE_CASE   :		str       		=    factor + prime
												while x in factor_map:
																x += factor
												_SCREAMING_SNAKE_CASE   :		Union[str, Any]       		=    factor
								else:
												_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    prime
												yield prime
								prime += 1





def 				lowercase__		(					lowerCamelCase = 1E10       ):
				_SCREAMING_SNAKE_CASE   :		Dict       		=    sieve()

				_SCREAMING_SNAKE_CASE   :		Dict       		=    1
				while True:
								_SCREAMING_SNAKE_CASE   :		int       		=    next(lowerCamelCase       )
								if (2 * prime * n) > limit:
												return n
								# Ignore the next prime as the reminder will be 2.
								next(lowerCamelCase       )
								n += 2


if __name__ == "__main__":
			print(solution())

