





'''simple docstring'''




import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin


class 			SCREAMING_SNAKE_CASE   (a__ ,		unittest.TestCase							):
					lowerCAmelCase		      =	PhobertTokenizer
					lowerCAmelCase		      =	False


					def 							SCREAMING_SNAKE_CASE  (						self):

										'''simple docstring'''






										super().setUp()

										# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
										__A						:			str								=	['T@@', 'i', 'I', 'R@@', 'r', 'e@@']
										__A						:			Tuple								=	dict(zip(_UpperCAmelCase						,     range(len(_UpperCAmelCase))))
										__A						:			List[Any]								=	['#version: 0.2', 'l à</w>']
										__A						:			Dict								=	{'unk_token': '<unk>'}

										__A						:			int								=	os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES['vocab_file'])
										__A						:			int								=	os.path.join(self.tmpdirname						,     VOCAB_FILES_NAMES['merges_file'])

										with open(self.vocab_file						,     'w'						,     encoding='utf-8') as fp:
															for token in vocab_tokens:
																				fp.write(F'{token} {vocab_tokens[token]}\n')
										with open(self.merges_file						,     'w'						,     encoding='utf-8') as fp:
															fp.write('\n'.join(_UpperCAmelCase))


					def 							SCREAMING_SNAKE_CASE  (						self						,     **_UpperCAmelCase):

										'''simple docstring'''






										kwargs.update(self.special_tokens_map)
										return PhobertTokenizer.from_pretrained(self.tmpdirname						,     **_UpperCAmelCase)


					def 							SCREAMING_SNAKE_CASE  (						self						,     _UpperCAmelCase):

										'''simple docstring'''






										__A						:			List[str]								=	'Tôi là VinAI Research'
										__A						:			Union[str, Any]								=	'T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
										return input_text, output_text


					def 							SCREAMING_SNAKE_CASE  (						self):

										'''simple docstring'''






										__A						:			str								=	PhobertTokenizer(self.vocab_file						,     self.merges_file						,     **self.special_tokens_map)
										__A						:			Optional[Any]								=	'Tôi là VinAI Research'
										__A						:			Union[str, Any]								=	'T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
										__A						:			List[str]								=	tokenizer.tokenize(_UpperCAmelCase)
										print(_UpperCAmelCase)
										self.assertListEqual(_UpperCAmelCase						,     _UpperCAmelCase)

										__A						:			Optional[int]								=	tokens + [tokenizer.unk_token]

										__A						:			Tuple								=	[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase)						,     _UpperCAmelCase)






'''simple docstring'''




import math






def 	_lowerCAmelCase      (  __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 	_lowerCAmelCase      (  __snake_case  :			float = 0.1      )					->					int:
     __A						:			Dict								=	3
     __A						:			int								=	3

     while primes / (2 * j - 1) >= ratio:
          for i in range(j * j + j + 1			,							(j + 2) * (j + 2)			,							j + 1      ):
               primes += is_prime(__snake_case      )
          j += 2
     return j


if __name__ == "__main__":
  import doctest

  doctest.testmod()