
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase     =			get_tests_dir("""fixtures/test_sentencepiece.model""")
@require_sentencepiece
@require_tokenizers
class 					a	(  __lowerCAmelCase	,      unittest.TestCase       ):
  UpperCamelCase	:				Optional[Any]     						=					XLMRobertaTokenizer
  UpperCamelCase	:				Optional[Any]     						=					XLMRobertaTokenizerFast
  UpperCamelCase	:				int     						=					True
  UpperCamelCase	:				Tuple     						=					True



  def 	lowerCamelCase__       (						self :					int		)     ->					str:


     '''simple docstring'''




     super().setUp()

     # We have a SentencePiece fixture for testing
     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=XLMRobertaTokenizer(_UpperCamelCase       ,		keep_accents=_UpperCamelCase		)
     tokenizer.save_pretrained(self.tmpdirname		)



  def 	lowerCamelCase__       (						self :					List[str]		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[Any]     			="""<pad>"""
     SCREAMING_SNAKE_CASE_: Optional[int]     			=1

     self.assertEqual(self.get_tokenizer()._convert_token_to_id(_UpperCamelCase		)       ,		_UpperCamelCase		)
     self.assertEqual(self.get_tokenizer()._convert_id_to_token(_UpperCamelCase		)       ,		_UpperCamelCase		)



  def 	lowerCamelCase__       (						self :					Tuple		)     ->					List[str]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Union[str, Any]     			=list(self.get_tokenizer().get_vocab().keys()		)

     self.assertEqual(vocab_keys[0]       ,		"""<s>"""		)
     self.assertEqual(vocab_keys[1]       ,		"""<pad>"""		)
     self.assertEqual(vocab_keys[-1]       ,		"""<mask>"""		)
     self.assertEqual(len(_UpperCamelCase		)       ,		1002		)



  def 	lowerCamelCase__       (						self :					Any		)     ->					str:


     '''simple docstring'''




     self.assertEqual(self.get_tokenizer().vocab_size       ,		1002		)



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


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			=XLMRobertaTokenizer(_UpperCamelCase       ,		keep_accents=_UpperCamelCase		)

     SCREAMING_SNAKE_CASE_: Any     			=tokenizer.tokenize("""This is a test"""		)
     self.assertListEqual(_UpperCamelCase       ,		["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]		)

     self.assertListEqual(
         tokenizer.convert_tokens_to_ids(_UpperCamelCase		)       ,		[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]       ,		)

     SCREAMING_SNAKE_CASE_: List[Any]     			=tokenizer.tokenize("""I was born in 92000, and this is falsé."""		)
     self.assertListEqual(
         _UpperCamelCase       ,		[
             SPIECE_UNDERLINE + """I""",
             SPIECE_UNDERLINE + """was""",
             SPIECE_UNDERLINE + """b""",
             """or""",
             """n""",
             SPIECE_UNDERLINE + """in""",
             SPIECE_UNDERLINE + """""",
             """9""",
             """2""",
             """0""",
             """0""",
             """0""",
             """,""",
             SPIECE_UNDERLINE + """and""",
             SPIECE_UNDERLINE + """this""",
             SPIECE_UNDERLINE + """is""",
             SPIECE_UNDERLINE + """f""",
             """al""",
             """s""",
             """é""",
             """.""",
         ]       ,		)
     SCREAMING_SNAKE_CASE_: Optional[Any]     			=tokenizer.convert_tokens_to_ids(_UpperCamelCase		)
     self.assertListEqual(
         _UpperCamelCase       ,		[
             value + tokenizer.fairseq_offset
             for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
         ]       ,		)

     SCREAMING_SNAKE_CASE_: Any     			=tokenizer.convert_ids_to_tokens(_UpperCamelCase		)
     self.assertListEqual(
         _UpperCamelCase       ,		[
             SPIECE_UNDERLINE + """I""",
             SPIECE_UNDERLINE + """was""",
             SPIECE_UNDERLINE + """b""",
             """or""",
             """n""",
             SPIECE_UNDERLINE + """in""",
             SPIECE_UNDERLINE + """""",
             """<unk>""",
             """2""",
             """0""",
             """0""",
             """0""",
             """,""",
             SPIECE_UNDERLINE + """and""",
             SPIECE_UNDERLINE + """this""",
             SPIECE_UNDERLINE + """is""",
             SPIECE_UNDERLINE + """f""",
             """al""",
             """s""",
             """<unk>""",
             """.""",
         ]       ,		)



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


     '''simple docstring'''




     if not self.test_slow_tokenizer:
        # as we don't have a slow version, we can't compare the outputs between slow and fast versions
        return

     SCREAMING_SNAKE_CASE_: Tuple     			=(self.rust_tokenizer_class, """hf-internal-testing/tiny-xlm-roberta""", {})
     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
        with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
           SCREAMING_SNAKE_CASE_: Dict     			=self.rust_tokenizer_class.from_pretrained(_UpperCamelCase       ,		**_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Optional[Any]     			=self.tokenizer_class.from_pretrained(_UpperCamelCase       ,		**_UpperCamelCase		)

           SCREAMING_SNAKE_CASE_: str     			=tempfile.mkdtemp()

           SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer_r.save_pretrained(_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer_p.save_pretrained(_UpperCamelCase		)

           # Checks it save with the same files + the tokenizer.json file for the fast one
           self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files		)		)
           SCREAMING_SNAKE_CASE_: Optional[int]     			=tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f		)
           self.assertSequenceEqual(_UpperCamelCase       ,		_UpperCamelCase		)

           # Checks everything loads correctly in the same way
           SCREAMING_SNAKE_CASE_: str     			=tokenizer_r.from_pretrained(_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Union[str, Any]     			=tokenizer_p.from_pretrained(_UpperCamelCase		)

           # Check special tokens are set accordingly on Rust and Python
           for key in tokenizer_pp.special_tokens_map:
              self.assertTrue(hasattr(_UpperCamelCase       ,		_UpperCamelCase		)		)
              # self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
              # self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

           shutil.rmtree(_UpperCamelCase		)

           # Save tokenizer rust, legacy_format=True
           SCREAMING_SNAKE_CASE_: Union[str, Any]     			=tempfile.mkdtemp()

           SCREAMING_SNAKE_CASE_: Dict     			=tokenizer_r.save_pretrained(_UpperCamelCase       ,		legacy_format=_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Union[str, Any]     			=tokenizer_p.save_pretrained(_UpperCamelCase		)

           # Checks it save with the same files
           self.assertSequenceEqual(_UpperCamelCase       ,		_UpperCamelCase		)

           # Checks everything loads correctly in the same way
           SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer_r.from_pretrained(_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Union[str, Any]     			=tokenizer_p.from_pretrained(_UpperCamelCase		)

           # Check special tokens are set accordingly on Rust and Python
           for key in tokenizer_pp.special_tokens_map:
              self.assertTrue(hasattr(_UpperCamelCase       ,		_UpperCamelCase		)		)

           shutil.rmtree(_UpperCamelCase		)

           # Save tokenizer rust, legacy_format=False
           SCREAMING_SNAKE_CASE_: Dict     			=tempfile.mkdtemp()

           SCREAMING_SNAKE_CASE_: Union[str, Any]     			=tokenizer_r.save_pretrained(_UpperCamelCase       ,		legacy_format=_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Any     			=tokenizer_p.save_pretrained(_UpperCamelCase		)

           # Checks it saved the tokenizer.json file
           self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files		)		)

           # Checks everything loads correctly in the same way
           SCREAMING_SNAKE_CASE_: List[str]     			=tokenizer_r.from_pretrained(_UpperCamelCase		)
           SCREAMING_SNAKE_CASE_: Dict     			=tokenizer_p.from_pretrained(_UpperCamelCase		)

           # Check special tokens are set accordingly on Rust and Python
           for key in tokenizer_pp.special_tokens_map:
              self.assertTrue(hasattr(_UpperCamelCase       ,		_UpperCamelCase		)		)

           shutil.rmtree(_UpperCamelCase		)



  @cached_property
  def 	lowerCamelCase__       (						self :					List[str]		)     ->					Optional[Any]:


     '''simple docstring'''




     return XLMRobertaTokenizer.from_pretrained("""xlm-roberta-base"""		)



  def 	lowerCamelCase__       (						self :					int		)     ->					int:


     '''simple docstring'''




     with tempfile.NamedTemporaryFile() as f:
        shutil.copyfile(_UpperCamelCase       ,		f.name		)
        SCREAMING_SNAKE_CASE_: Tuple     			=XLMRobertaTokenizer(f.name       ,		keep_accents=_UpperCamelCase		)
        SCREAMING_SNAKE_CASE_: List[Any]     			=pickle.dumps(_UpperCamelCase		)
     pickle.loads(_UpperCamelCase		)



  def 	lowerCamelCase__       (						self :					int		)     ->					Any:


     '''simple docstring'''




     if not self.test_rust_tokenizer:
        return

     SCREAMING_SNAKE_CASE_: Tuple     			=self.get_tokenizer()
     SCREAMING_SNAKE_CASE_: int     			=self.get_rust_tokenizer()

     SCREAMING_SNAKE_CASE_: List[Any]     			="""I was born in 92000, and this is falsé."""

     SCREAMING_SNAKE_CASE_: List[Any]     			=tokenizer.tokenize(_UpperCamelCase		)
     SCREAMING_SNAKE_CASE_: Tuple     			=rust_tokenizer.tokenize(_UpperCamelCase		)
     self.assertListEqual(_UpperCamelCase       ,		_UpperCamelCase		)

     SCREAMING_SNAKE_CASE_: Optional[int]     			=tokenizer.encode(_UpperCamelCase       ,		add_special_tokens=_UpperCamelCase		)
     SCREAMING_SNAKE_CASE_: List[Any]     			=rust_tokenizer.encode(_UpperCamelCase       ,		add_special_tokens=_UpperCamelCase		)
     self.assertListEqual(_UpperCamelCase       ,		_UpperCamelCase		)

     SCREAMING_SNAKE_CASE_: str     			=self.get_rust_tokenizer()
     SCREAMING_SNAKE_CASE_: Any     			=tokenizer.encode(_UpperCamelCase		)
     SCREAMING_SNAKE_CASE_: Any     			=rust_tokenizer.encode(_UpperCamelCase		)
     self.assertListEqual(_UpperCamelCase       ,		_UpperCamelCase		)



  @slow
  def 	lowerCamelCase__       (						self :					Optional[Any]		)     ->					List[str]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Optional[int]     			="""Hello World!"""
     SCREAMING_SNAKE_CASE_: Tuple     			=[0, 3_5378, 6661, 38, 2]
     # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
     # xlmr.eval()
     # xlmr.encode(symbols)

     self.assertListEqual(_UpperCamelCase       ,		self.big_tokenizer.encode(_UpperCamelCase		)		)



  @slow
  def 	lowerCamelCase__       (						self :					Optional[int]		)     ->					List[Any]:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Any     			=(
         """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
         """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
     )
     SCREAMING_SNAKE_CASE_: Optional[int]     			=[
         0,
         3293,
         83,
         10,
         4552,
         4989,
         7986,
         678,
         10,
         5915,
         111,
         17_9459,
         12_4850,
         4,
         6044,
         237,
         12,
         6,
         5,
         6,
         4,
         6780,
         705,
         15,
         1388,
         44,
         378,
         1_0114,
         711,
         152,
         20,
         6,
         5,
         2_2376,
         642,
         1221,
         1_5190,
         3_4153,
         450,
         5608,
         959,
         1119,
         5_7702,
         136,
         186,
         47,
         1098,
         2_9367,
         47,
         # 4426, # What fairseq tokenizes from "<unk>": "_<"
         # 3678, # What fairseq tokenizes from "<unk>": "unk"
         # 2740, # What fairseq tokenizes from "<unk>": ">"
         3,  # What we tokenize from "<unk>": "<unk>"
         6,  # Residue from the tokenization: an extra sentencepiece underline
         4,
         6044,
         237,
         6284,
         5_0901,
         528,
         31,
         90,
         34,
         927,
         2,
     ]
     # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
     # xlmr.eval()
     # xlmr.encode(symbols)

     self.assertListEqual(_UpperCamelCase       ,		self.big_tokenizer.encode(_UpperCamelCase		)		)





  @slow
  def 	lowerCamelCase__       (						self :					Tuple		)     ->					Dict:


     '''simple docstring'''




     SCREAMING_SNAKE_CASE_: Tuple     			={"""input_ids""": [[0, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [0, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
     # fmt: on

     self.tokenizer_integration_test_util(
         expected_encoding=_UpperCamelCase       ,		model_name="""xlm-roberta-base"""       ,		revision="""d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"""       ,		)








"""simple docstring"""
def      __magic_name__				(							lowercase ):
   return str(lowercase ) == str(lowercase )[::-1]





def      __magic_name__				(							lowercase ):
   return int(lowercase ) + int(str(lowercase )[::-1] )





def      __magic_name__				(							lowercase = 1_0000 ):
   SCREAMING_SNAKE_CASE_: List[str]     			=[]
   for num in range(1							,			lowercase ):
      SCREAMING_SNAKE_CASE_: List[Any]     			=0
      SCREAMING_SNAKE_CASE_: int     			=num
      while iterations < 50:
         SCREAMING_SNAKE_CASE_: Optional[Any]     			=sum_reverse(lowercase )
         iterations += 1
         if is_palindrome(lowercase ):
            break
      else:
         lychrel_nums.append(lowercase )
   return len(lowercase )


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



