
'''simple docstring'''


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer


__lowercase							:   Union[str, Any]					=     logging.get_logger(__name__)

__lowercase							:   Any					=     {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__lowercase							:   Dict					=     [
    '''small''',
    '''small-base''',
    '''medium''',
    '''medium-base''',
    '''intermediate''',
    '''intermediate-base''',
    '''large''',
    '''large-base''',
    '''xlarge''',
    '''xlarge-base''',
]

__lowercase							:   int					=     {
    '''vocab_file''': {
        '''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve/main/vocab.txt''',
        '''funnel-transformer/small-base''': '''https://huggingface.co/funnel-transformer/small-base/resolve/main/vocab.txt''',
        '''funnel-transformer/medium''': '''https://huggingface.co/funnel-transformer/medium/resolve/main/vocab.txt''',
        '''funnel-transformer/medium-base''': (
            '''https://huggingface.co/funnel-transformer/medium-base/resolve/main/vocab.txt'''
        ),
        '''funnel-transformer/intermediate''': (
            '''https://huggingface.co/funnel-transformer/intermediate/resolve/main/vocab.txt'''
        ),
        '''funnel-transformer/intermediate-base''': (
            '''https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/vocab.txt'''
        ),
        '''funnel-transformer/large''': '''https://huggingface.co/funnel-transformer/large/resolve/main/vocab.txt''',
        '''funnel-transformer/large-base''': '''https://huggingface.co/funnel-transformer/large-base/resolve/main/vocab.txt''',
        '''funnel-transformer/xlarge''': '''https://huggingface.co/funnel-transformer/xlarge/resolve/main/vocab.txt''',
        '''funnel-transformer/xlarge-base''': (
            '''https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve/main/tokenizer.json''',
        '''funnel-transformer/small-base''': (
            '''https://huggingface.co/funnel-transformer/small-base/resolve/main/tokenizer.json'''
        ),
        '''funnel-transformer/medium''': '''https://huggingface.co/funnel-transformer/medium/resolve/main/tokenizer.json''',
        '''funnel-transformer/medium-base''': (
            '''https://huggingface.co/funnel-transformer/medium-base/resolve/main/tokenizer.json'''
        ),
        '''funnel-transformer/intermediate''': (
            '''https://huggingface.co/funnel-transformer/intermediate/resolve/main/tokenizer.json'''
        ),
        '''funnel-transformer/intermediate-base''': (
            '''https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/tokenizer.json'''
        ),
        '''funnel-transformer/large''': '''https://huggingface.co/funnel-transformer/large/resolve/main/tokenizer.json''',
        '''funnel-transformer/large-base''': (
            '''https://huggingface.co/funnel-transformer/large-base/resolve/main/tokenizer.json'''
        ),
        '''funnel-transformer/xlarge''': '''https://huggingface.co/funnel-transformer/xlarge/resolve/main/tokenizer.json''',
        '''funnel-transformer/xlarge-base''': (
            '''https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/tokenizer.json'''
        ),
    },
}
__lowercase							:   Dict					=     {f'funnel-transformer/{name}': 512 for name in _model_names}
__lowercase							:   Optional[int]					=     {f'funnel-transformer/{name}': {'''do_lower_case''': True} for name in _model_names}

class 	__lowercase				(  _lowercase    ):
			lowerCamelCase			:		List[str]	      =			VOCAB_FILES_NAMES
			lowerCamelCase			:		Tuple	      =			PRETRAINED_VOCAB_FILES_MAP
			lowerCamelCase			:		Optional[int]	      =			PRETRAINED_INIT_CONFIGURATION
			lowerCamelCase			:		Tuple	      =			FunnelTokenizer
			lowerCamelCase			:		Any	      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCamelCase			:		int	      =			2

			def __init__(self			,   A=None			,   A=None			,   A=True			,   A="<unk>"			,   A="<sep>"			,   A="<pad>"			,   A="<cls>"			,   A="<mask>"			,   A="<s>"			,   A="</s>"			,   A=True			,   A=True			,   A=None			,   A="##"			,   **A			,   ):
								super().__init__(
								    A			,   tokenizer_file=A			,   do_lower_case=A			,   unk_token=A			,   sep_token=A			,   pad_token=A			,   cls_token=A			,   mask_token=A			,   bos_token=A			,   eos_token=A			,   clean_text=A			,   tokenize_chinese_chars=A			,   strip_accents=A			,   wordpieces_prefix=A			,   **A			,   )

								lowerCamelCase_					:      Optional[Any]     =		json.loads(self.backend_tokenizer.normalizer.__getstate__()      )
								if (
								    normalizer_state.get('''lowercase'''			,   A      ) != do_lower_case
								    or normalizer_state.get('''strip_accents'''			,   A      ) != strip_accents
								    or normalizer_state.get('''handle_chinese_chars'''			,   A      ) != tokenize_chinese_chars
								):
													lowerCamelCase_					:      str     =		getattr(A			,   normalizer_state.pop('''type'''      )      )
													lowerCamelCase_					:      str     =		do_lower_case
													lowerCamelCase_					:      Dict     =		strip_accents
													lowerCamelCase_					:      List[Any]     =		tokenize_chinese_chars
													lowerCamelCase_					:      int     =		normalizer_class(**A      )

								lowerCamelCase_					:      int     =		do_lower_case

			def        UpperCAmelCase__ (self			,   A			,   A=None      ):
								lowerCamelCase_					:      int     =		[self.cls_token_id] + token_ids_a + [self.sep_token_id]

								if token_ids_a:
													output += token_ids_a + [self.sep_token_id]

								return output

			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      int     =		[self.sep_token_id]
								lowerCamelCase_					:      Optional[int]     =		[self.cls_token_id]
								if token_ids_a is None:
													return len(cls      ) * [self.cls_token_type_id] + len(token_ids_a + sep      ) * [0]
								return len(cls      ) * [self.cls_token_type_id] + len(token_ids_a + sep      ) * [0] + len(token_ids_a + sep      ) * [1]






			def        UpperCAmelCase__ (self			,   A			,   A = None      ):
								lowerCamelCase_					:      Tuple     =		self._tokenizer.model.save(A			,   name=A      )
								return tuple(A      )




'''simple docstring'''


import itertools
import math




def lowercase_	(   _lowercase				)     ->							bool:
					'''simple docstring'''

					if 1 < number < 4:
										# 2 and 3 are primes
										return True
					elif number < 2 or number % 2 == 0 or number % 3 == 0:
										# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
										return False

					# All primes number are in format of 6k +/- 1
					for i in range(5			,       int(math.sqrt(_lowercase				) + 1				)			,       6				):
										if number % i == 0 or number % (i + 2) == 0:
															return False
					return True




def lowercase_	(   )     ->							Optional[int]:
					'''simple docstring'''

					lowerCamelCase_					:      Union[str, Any]     =		2
					while True:
										if is_prime(_lowercase				):
															yield num
										num += 1




def lowercase_	(   _lowercase = 10_001				)     ->							int:
					'''simple docstring'''

					return next(itertools.islice(prime_generator()			,       nth - 1			,       _lowercase				)				)


if __name__ == "__main__":
					print(f'{solution() = }')


