





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class 					__snake_case	(  __SCREAMING_SNAKE_CASE			,     unittest.TestCase    ):


    '''simple docstring'''







    lowerCamelCase__    :		Dict				=	BioGptTokenizer
    lowerCamelCase__    :		List[Any]				=	False



    def  lowercase_					(       self     ):





        '''simple docstring'''

        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        SCREAMING_SNAKE_CASE__											=			[
            '''l''',
            '''o''',
            '''w''',
            '''e''',
            '''r''',
            '''s''',
            '''t''',
            '''i''',
            '''d''',
            '''n''',
            '''w</w>''',
            '''r</w>''',
            '''t</w>''',
            '''lo''',
            '''low''',
            '''er</w>''',
            '''low</w>''',
            '''lowest</w>''',
            '''newer</w>''',
            '''wider</w>''',
            '''<unk>''',
        ]
        SCREAMING_SNAKE_CASE__											=			dict(zip(A_   ,				range(len(A_     )     )     )     )
        SCREAMING_SNAKE_CASE__											=			['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

        SCREAMING_SNAKE_CASE__											=			os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''vocab_file''']     )
        SCREAMING_SNAKE_CASE__											=			os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''merges_file''']     )
        with open(self.vocab_file   ,				'''w'''     ) as fp:
            fp.write(json.dumps(A_     )     )
        with open(self.merges_file   ,				'''w'''     ) as fp:
            fp.write('''\n'''.join(A_     )     )



    def  lowercase_					(       self   ,				A_     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			'''lower newer'''
        SCREAMING_SNAKE_CASE__											=			'''lower newer'''
        return input_text, output_text



    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			BioGptTokenizer(self.vocab_file   ,				self.merges_file     )

        SCREAMING_SNAKE_CASE__											=			'''lower'''
        SCREAMING_SNAKE_CASE__											=			['''low''', '''er</w>''']
        SCREAMING_SNAKE_CASE__											=			tokenizer.tokenize(A_     )
        self.assertListEqual(A_   ,				A_     )

        SCREAMING_SNAKE_CASE__											=			tokens + ['''<unk>''']
        SCREAMING_SNAKE_CASE__											=			[14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(A_     )   ,				A_     )




    @slow
    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			BioGptTokenizer.from_pretrained('''microsoft/biogpt'''     )

        SCREAMING_SNAKE_CASE__											=			tokenizer.encode('''sequence builders'''   ,				add_special_tokens=A_     )
        SCREAMING_SNAKE_CASE__											=			tokenizer.encode('''multi-sequence build'''   ,				add_special_tokens=A_     )

        SCREAMING_SNAKE_CASE__											=			tokenizer.build_inputs_with_special_tokens(A_     )
        SCREAMING_SNAKE_CASE__											=			tokenizer.build_inputs_with_special_tokens(A_   ,				A_     )

        self.assertTrue(encoded_sentence == [2] + text     )
        self.assertTrue(encoded_pair == [2] + text + [2] + text_a     )





import itertools
import math

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:int				)  ->     bool:

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

def 	SCREAMING_SNAKE_CASE_							(	)  ->     Dict:
   _A      =       2
   while True:
      if is_prime(_snake_case				):
         yield num
      num += 1

def 	SCREAMING_SNAKE_CASE_							(	_snake_case	:int = 10_001				)  ->     int:
   return next(itertools.islice(prime_generator()	,   nth - 1	,   _snake_case				)				)


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



