

"""simple docstring"""


import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class      __a							(UpperCamelCase_   ,	unittest.TestCase):






     '''simple docstring'''
     _SCREAMING_SNAKE_CASE						:Optional[int]       = RobertaTokenizer
     _SCREAMING_SNAKE_CASE						:List[str]       = RobertaTokenizerFast
     _SCREAMING_SNAKE_CASE						:List[Any]       = True
     _SCREAMING_SNAKE_CASE						:List[str]       = {"""cls_token""": """<s>"""}

     def 					_a			(						self  )  ->      Tuple:


           """simple docstring"""


           super().setUp()

           # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
           SCREAMING_SNAKE_CASE__   :      str      		=	[
               """l""",
               """o""",
               """w""",
               """e""",
               """r""",
               """s""",
               """t""",
               """i""",
               """d""",
               """n""",
               """\u0120""",
               """\u0120l""",
               """\u0120n""",
               """\u0120lo""",
               """\u0120low""",
               """er""",
               """\u0120lowest""",
               """\u0120newer""",
               """\u0120wider""",
               """<unk>""",
           ]
           SCREAMING_SNAKE_CASE__   :      Tuple      		=	dict(zip(_a	,    range(len(_a  )  )  )  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
           SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	{"""unk_token""": """<unk>"""}

           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["""vocab_file"""]  )
           SCREAMING_SNAKE_CASE__   :      int      		=	os.path.join(self.tmpdirname	,    VOCAB_FILES_NAMES["""merges_file"""]  )
           with open(self.vocab_file	,    """w"""	,    encoding="""utf-8"""  ) as fp:
                 fp.write(json.dumps(_a  ) + """\n"""  )
           with open(self.merges_file	,    """w"""	,    encoding="""utf-8"""  ) as fp:
                 fp.write("""\n""".join(_a  )  )

     def 					_a			(						self	,    **_a  )  ->      Union[str, Any]:


           """simple docstring"""


           kwargs.update(self.special_tokens_map  )
           return self.tokenizer_class.from_pretrained(self.tmpdirname	,    **_a  )

     def 					_a			(						self	,    **_a  )  ->      Union[str, Any]:


           """simple docstring"""


           kwargs.update(self.special_tokens_map  )
           return RobertaTokenizerFast.from_pretrained(self.tmpdirname	,    **_a  )

     def 					_a			(						self	,    _a  )  ->      Optional[int]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	"""lower newer"""
           SCREAMING_SNAKE_CASE__   :      Dict      		=	"""lower newer"""
           return input_text, output_text

     def 					_a			(						self  )  ->      List[Any]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Dict      		=	self.tokenizer_class(self.vocab_file	,    self.merges_file	,    **self.special_tokens_map  )
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	"""lower newer"""
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
           SCREAMING_SNAKE_CASE__   :      Any      		=	tokenizer.tokenize(_a  )  # , add_prefix_space=True)
           self.assertListEqual(_a	,    _a  )

           SCREAMING_SNAKE_CASE__   :      int      		=	tokens + [tokenizer.unk_token]
           SCREAMING_SNAKE_CASE__   :      int      		=	[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(_a  )	,    _a  )

     def 					_a			(						self  )  ->      List[str]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	self.get_tokenizer()

           self.assertListEqual(tokenizer.encode("""Hello world!"""	,    add_special_tokens=_a  )	,    [0, 31_414, 232, 328, 2]  )
           self.assertListEqual(
               tokenizer.encode("""Hello world! cécé herlolip 418"""	,    add_special_tokens=_a  )	,    [0, 31_414, 232, 328, 740, 1_140, 12_695, 69, 46_078, 1_588, 2]	,    )

     @slow
     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      Any      		=	self.tokenizer_class.from_pretrained("""roberta-base"""  )

           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	tokenizer.encode("""sequence builders"""	,    add_special_tokens=_a  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	tokenizer.encode("""multi-sequence build"""	,    add_special_tokens=_a  )

           SCREAMING_SNAKE_CASE__   :      Dict      		=	tokenizer.encode(
               """sequence builders"""	,    add_special_tokens=_a	,    add_prefix_space=_a  )
           SCREAMING_SNAKE_CASE__   :      List[str]      		=	tokenizer.encode(
               """sequence builders"""	,    """multi-sequence build"""	,    add_special_tokens=_a	,    add_prefix_space=_a  )

           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	tokenizer.build_inputs_with_special_tokens(_a  )
           SCREAMING_SNAKE_CASE__   :      int      		=	tokenizer.build_inputs_with_special_tokens(_a	,    _a  )

           assert encoded_sentence == encoded_text_from_decode
           assert encoded_pair == encoded_pair_from_decode

     def 					_a			(						self  )  ->      Any:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__   :      int      		=	self.get_tokenizer()

           SCREAMING_SNAKE_CASE__   :      Any      		=	"""Encode this sequence."""
           SCREAMING_SNAKE_CASE__   :      str      		=	tokenizer.byte_encoder[""" """.encode("""utf-8"""  )[0]]

           # Testing encoder arguments
           SCREAMING_SNAKE_CASE__   :      Dict      		=	tokenizer.encode(_a	,    add_special_tokens=_a	,    add_prefix_space=_a  )
           SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
           self.assertNotEqual(_a	,    _a  )

           SCREAMING_SNAKE_CASE__   :      Dict      		=	tokenizer.encode(_a	,    add_special_tokens=_a	,    add_prefix_space=_a  )
           SCREAMING_SNAKE_CASE__   :      Any      		=	tokenizer.convert_ids_to_tokens(encoded[0]  )[0]
           self.assertEqual(_a	,    _a  )

           tokenizer.add_special_tokens({"""bos_token""": """<s>"""}  )
           SCREAMING_SNAKE_CASE__   :      Dict      		=	tokenizer.encode(_a	,    add_special_tokens=_a  )
           SCREAMING_SNAKE_CASE__   :      List[str]      		=	tokenizer.convert_ids_to_tokens(encoded[1]  )[0]
           self.assertNotEqual(_a	,    _a  )

           # Testing spaces after special tokens
           SCREAMING_SNAKE_CASE__   :      Any      		=	"""<mask>"""
           tokenizer.add_special_tokens(
               {"""mask_token""": AddedToken(_a	,    lstrip=_a	,    rstrip=_a  )}  )  # mask token has a left space
           SCREAMING_SNAKE_CASE__   :      str      		=	tokenizer.convert_tokens_to_ids(_a  )

           SCREAMING_SNAKE_CASE__   :      List[Any]      		=	"""Encode <mask> sequence"""
           SCREAMING_SNAKE_CASE__   :      str      		=	"""Encode <mask>sequence"""

           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	tokenizer.encode(_a  )
           SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	encoded.index(_a  )
           SCREAMING_SNAKE_CASE__   :      str      		=	tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
           self.assertEqual(_a	,    _a  )

           SCREAMING_SNAKE_CASE__   :      Any      		=	tokenizer.encode(_a  )
           SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	encoded.index(_a  )
           SCREAMING_SNAKE_CASE__   :      Tuple      		=	tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]  )[0]
           self.assertNotEqual(_a	,    _a  )

     def 					_a			(						self  )  ->      Union[str, Any]:


           """simple docstring"""


           pass

     def 					_a			(						self  )  ->      Dict:


           """simple docstring"""


           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
                       SCREAMING_SNAKE_CASE__   :      int      		=	self.rust_tokenizer_class.from_pretrained(_a	,    **_a  )
                       SCREAMING_SNAKE_CASE__   :      str      		=	self.tokenizer_class.from_pretrained(_a	,    **_a  )
                       SCREAMING_SNAKE_CASE__   :      str      		=	"""A, <mask> AllenNLP sentence."""
                       SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	tokenizer_r.encode_plus(_a	,    add_special_tokens=_a	,    return_token_type_ids=_a  )
                       SCREAMING_SNAKE_CASE__   :      Tuple      		=	tokenizer_p.encode_plus(_a	,    add_special_tokens=_a	,    return_token_type_ids=_a  )

                       # token_type_ids should put 0 everywhere
                       self.assertEqual(sum(tokens_r["""token_type_ids"""]  )	,    sum(tokens_p["""token_type_ids"""]  )  )

                       # attention_mask should put 1 everywhere, so sum over length should be 1
                       self.assertEqual(
                           sum(tokens_r["""attention_mask"""]  ) / len(tokens_r["""attention_mask"""]  )	,    sum(tokens_p["""attention_mask"""]  ) / len(tokens_p["""attention_mask"""]  )	,    )

                       SCREAMING_SNAKE_CASE__   :      Dict      		=	tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]  )
                       SCREAMING_SNAKE_CASE__   :      str      		=	tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]  )

                       # Rust correctly handles the space before the mask while python doesnt
                       self.assertSequenceEqual(tokens_p["""input_ids"""]	,    [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]  )
                       self.assertSequenceEqual(tokens_r["""input_ids"""]	,    [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]  )

                       self.assertSequenceEqual(
                           _a	,    ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]  )
                       self.assertSequenceEqual(
                           _a	,    ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]  )

     def 					_a			(						self  )  ->      Tuple:


           """simple docstring"""


           for trim_offsets, add_prefix_space in itertools.product([True, False]	,    repeat=2  ):
                 SCREAMING_SNAKE_CASE__   :      str      		=	self.rust_tokenizer_class.from_pretrained(
                     self.tmpdirname	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )

                 SCREAMING_SNAKE_CASE__   :      int      		=	json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()  )
                 SCREAMING_SNAKE_CASE__   :      Any      		=	json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()  )

                 self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]	,    _a  )

                 self.assertEqual(post_processor_state["""add_prefix_space"""]	,    _a  )
                 self.assertEqual(post_processor_state["""trim_offsets"""]	,    _a  )





     def 					_a			(						self  )  ->      int:


           """simple docstring"""


           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
                       SCREAMING_SNAKE_CASE__   :      str      		=	"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                       SCREAMING_SNAKE_CASE__   :      List[Any]      		=	f'''{text_of_1_token} {text_of_1_token}'''

                       SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (0, len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (len(_a  ) + 1, len(_a  ) + 1 + len(_a  ))	,    )

                       SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      int      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (0, len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (len(_a  ) + 1, len(_a  ) + 1 + len(_a  ))	,    )

                       SCREAMING_SNAKE_CASE__   :      int      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      Any      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (0, len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (len(_a  ), len(_a  ) + 1 + len(_a  ))	,    )

                       SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      List[Any]      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (0, len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (len(_a  ), len(_a  ) + 1 + len(_a  ))	,    )

                       SCREAMING_SNAKE_CASE__   :      List[str]      		=	f''' {text}'''

                       # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
                       #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
                       # )
                       # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
                       # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
                       # self.assertEqual(
                       #     encoding.offset_mapping[1],
                       #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
                       # )

                       SCREAMING_SNAKE_CASE__   :      Any      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      str      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (1, 1 + len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (1 + len(_a  ) + 1, 1 + len(_a  ) + 1 + len(_a  ))	,    )

                       SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      Optional[int]      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (0, 1 + len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (1 + len(_a  ), 1 + len(_a  ) + 1 + len(_a  ))	,    )

                       SCREAMING_SNAKE_CASE__   :      Union[str, Any]      		=	self.rust_tokenizer_class.from_pretrained(
                           _a	,    use_fast=_a	,    add_prefix_space=_a	,    trim_offsets=_a  )
                       SCREAMING_SNAKE_CASE__   :      str      		=	tokenizer_r(_a	,    return_offsets_mapping=_a	,    add_special_tokens=_a  )
                       self.assertEqual(encoding.offset_mapping[0]	,    (0, 1 + len(_a  ))  )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,    (1 + len(_a  ), 1 + len(_a  ) + 1 + len(_a  ))	,    )







"""simple docstring"""


from math import sqrt




def  _lowercase					(    __lowerCAmelCase							)       ->				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(sqrt(__lowerCAmelCase							) + 1							)  ,					6							):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True




def  _lowercase					(    __lowerCAmelCase = 1_0001							)       ->				int:
      SCREAMING_SNAKE_CASE__   :      Dict      		=	0
      SCREAMING_SNAKE_CASE__   :      Tuple      		=	1
      while count != nth and number < 3:
            number += 1
            if is_prime(__lowerCAmelCase							):
                  count += 1
      while count != nth:
            number += 2
            if is_prime(__lowerCAmelCase							):
                  count += 1
      return number


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




