




'''simple docstring'''


import math
import unittest
def 		snake_case_   (UpperCamelCase	:  int				):





							'''simple docstring'''


							assert isinstance(UpperCamelCase			,						UpperCamelCase				) and (
							    number >= 0
							), "'number' must been an int and positive"

							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(UpperCamelCase				) + 1				)			,						6				):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True

class       A   (		unittest.TestCase   ):







							def        __lowerCAmelCase      (  self	:  Any )      ->							Dict:


														"""simple docstring"""


														self.assertTrue(is_prime(2 ) )
														self.assertTrue(is_prime(3 ) )
														self.assertTrue(is_prime(5 ) )
														self.assertTrue(is_prime(7 ) )
														self.assertTrue(is_prime(11 ) )
														self.assertTrue(is_prime(13 ) )
														self.assertTrue(is_prime(17 ) )
														self.assertTrue(is_prime(19 ) )
														self.assertTrue(is_prime(23 ) )
														self.assertTrue(is_prime(29 ) )







							def        __lowerCAmelCase      (  self	:  int )      ->							Tuple:


														"""simple docstring"""


														with self.assertRaises(lowerCAmelCase_ ):
																					is_prime(-19 )
														self.assertFalse(
														    is_prime(0 )							,      '''Zero doesn\'t have any positive factors, primes must have exactly two.'''							,      )
														self.assertFalse(
														    is_prime(1 )							,      '''One only has 1 positive factor, primes must have exactly two.'''							,      )
														self.assertFalse(is_prime(2 * 2 ) )
														self.assertFalse(is_prime(2 * 3 ) )
														self.assertFalse(is_prime(3 * 3 ) )
														self.assertFalse(is_prime(3 * 5 ) )
														self.assertFalse(is_prime(3 * 5 * 7 ) )


if __name__ == "__main__":
				unittest.main()







'''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_bert import BertTokenizer


_snake_case				:				Any       							=		logging.get_logger(__name__)

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

_snake_case				:				List[str]       							=		{
    'vocab_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/vocab.txt',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/vocab.txt',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt'
        ),
        'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt',
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt'
        ),
        'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt',
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json'
        ),
        'bert-base-multilingual-cased': (
            'https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-cased': (
            'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json'
        ),
    },
}

_snake_case				:				int       							=		{
    'bert-base-uncased': 512,
    'bert-large-uncased': 512,
    'bert-base-cased': 512,
    'bert-large-cased': 512,
    'bert-base-multilingual-uncased': 512,
    'bert-base-multilingual-cased': 512,
    'bert-base-chinese': 512,
    'bert-base-german-cased': 512,
    'bert-large-uncased-whole-word-masking': 512,
    'bert-large-cased-whole-word-masking': 512,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 512,
    'bert-large-cased-whole-word-masking-finetuned-squad': 512,
    'bert-base-cased-finetuned-mrpc': 512,
    'bert-base-german-dbmdz-cased': 512,
    'bert-base-german-dbmdz-uncased': 512,
    'TurkuNLP/bert-base-finnish-cased-v1': 512,
    'TurkuNLP/bert-base-finnish-uncased-v1': 512,
    'wietsedv/bert-base-dutch-cased': 512,
}

_snake_case				:				int       							=		{
    'bert-base-uncased': {'do_lower_case': True},
    'bert-large-uncased': {'do_lower_case': True},
    'bert-base-cased': {'do_lower_case': False},
    'bert-large-cased': {'do_lower_case': False},
    'bert-base-multilingual-uncased': {'do_lower_case': True},
    'bert-base-multilingual-cased': {'do_lower_case': False},
    'bert-base-chinese': {'do_lower_case': False},
    'bert-base-german-cased': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking-finetuned-squad': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking-finetuned-squad': {'do_lower_case': False},
    'bert-base-cased-finetuned-mrpc': {'do_lower_case': False},
    'bert-base-german-dbmdz-cased': {'do_lower_case': False},
    'bert-base-german-dbmdz-uncased': {'do_lower_case': True},
    'TurkuNLP/bert-base-finnish-cased-v1': {'do_lower_case': False},
    'TurkuNLP/bert-base-finnish-uncased-v1': {'do_lower_case': True},
    'wietsedv/bert-base-dutch-cased': {'do_lower_case': False},
}

class       A   (		_a   ):
							lowercase_          =    VOCAB_FILES_NAMES
							lowercase_          =    PRETRAINED_VOCAB_FILES_MAP
							lowercase_          =    PRETRAINED_INIT_CONFIGURATION
							lowercase_          =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowercase_          =    BertTokenizer







							def __init__(  self	:  str							,      lowerCAmelCase_	:  Union[str, Any]=None							,      lowerCAmelCase_	:  str=None							,      lowerCAmelCase_	:  List[Any]=True							,      lowerCAmelCase_	:  Any="[UNK]"							,      lowerCAmelCase_	:  Union[str, Any]="[SEP]"							,      lowerCAmelCase_	:  Tuple="[PAD]"							,      lowerCAmelCase_	:  Tuple="[CLS]"							,      lowerCAmelCase_	:  Optional[int]="[MASK]"							,      lowerCAmelCase_	:  Dict=True							,      lowerCAmelCase_	:  Union[str, Any]=None							,      **lowerCAmelCase_	:  Union[str, Any]							,      )      ->							Union[str, Any]:


														"""simple docstring"""


														super().__init__(
														    lowerCAmelCase_							,      tokenizer_file=lowerCAmelCase_							,      do_lower_case=lowerCAmelCase_							,      unk_token=lowerCAmelCase_							,      sep_token=lowerCAmelCase_							,      pad_token=lowerCAmelCase_							,      cls_token=lowerCAmelCase_							,      mask_token=lowerCAmelCase_							,      tokenize_chinese_chars=lowerCAmelCase_							,      strip_accents=lowerCAmelCase_							,      **lowerCAmelCase_							,      )

														_a     					=    json.loads(self.backend_tokenizer.normalizer.__getstate__() )
														if (
														    normalizer_state.get('''lowercase'''							,      lowerCAmelCase_ ) != do_lower_case
														    or normalizer_state.get('''strip_accents'''							,      lowerCAmelCase_ ) != strip_accents
														    or normalizer_state.get('''handle_chinese_chars'''							,      lowerCAmelCase_ ) != tokenize_chinese_chars
														):
																					_a     					=    getattr(lowerCAmelCase_							,      normalizer_state.pop('''type''' ) )
																					_a     					=    do_lower_case
																					_a     					=    strip_accents
																					_a     					=    tokenize_chinese_chars
																					_a     					=    normalizer_class(**lowerCAmelCase_ )

														_a     					=    do_lower_case







							def        __lowerCAmelCase      (  self	:  str							,      lowerCAmelCase_	:  Dict							,      lowerCAmelCase_	:  int=None )      ->							List[str]:


														"""simple docstring"""


														_a     					=    [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        __lowerCAmelCase      (  self	:  Any							,      lowerCAmelCase_	:  List[int]							,      lowerCAmelCase_	:  Optional[List[int]] = None )      ->							List[int]:


														"""simple docstring"""


														_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 ) * [0] + len(token_ids_a + sep ) * [1]







							def        __lowerCAmelCase      (  self	:  List[Any]							,      lowerCAmelCase_	:  str							,      lowerCAmelCase_	:  Optional[str] = None )      ->							Tuple[str]:


														"""simple docstring"""


														_a     					=    self._tokenizer.model.save(lowerCAmelCase_							,      name=lowerCAmelCase_ )
														return tuple(lowerCAmelCase_ )

