





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     :     Dict							=	get_tests_dir("""fixtures/test_sentencepiece.model""")







@require_sentencepiece
@require_tokenizers
class     __lowerCAmelCase	(   UpperCamelCase__						,    unittest.TestCase):
      _lowercase    : Dict            =      XLMRobertaTokenizer
      _lowercase    : Optional[int]            =      XLMRobertaTokenizerFast
      _lowercase    : Dict            =      True
      _lowercase    : str            =      True







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



        '''simple docstring'''




        super().setUp()

        # We have a SentencePiece fixture for testing
        a__     : List[str]  =XLMRobertaTokenizer(lowerCAmelCase__		,				keep_accents=lowerCAmelCase__							)
        tokenizer.save_pretrained(self.tmpdirname							)







      def        _lowercase  (   self							)       ->						Dict:



        '''simple docstring'''




        a__     : Any  ="<pad>"
        a__     : Any  =1

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







      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        a__     : 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(lowerCAmelCase__							)		,				1_0_0_2							)







      def        _lowercase  (   self							)       ->						str:



        '''simple docstring'''




        self.assertEqual(self.get_tokenizer().vocab_size		,				1_0_0_2							)







      def        _lowercase  (   self							)       ->						Dict:



        '''simple docstring'''




        a__     : Tuple  =XLMRobertaTokenizer(lowerCAmelCase__		,				keep_accents=lowerCAmelCase__							)

        a__     : str  =tokenizer.tokenize("This is a test"							)
        self.assertListEqual(lowerCAmelCase__		,				["▁This", "▁is", "▁a", "▁t", "est"]							)

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(lowerCAmelCase__							)		,				[value + tokenizer.fairseq_offset for value in [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]		,				)

        a__     : Dict  =tokenizer.tokenize("I was born in 92000, and this is falsé."							)
        self.assertListEqual(
            lowerCAmelCase__		,				[
                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",
                ".",
            ]		,				)
        a__     : Union[str, Any]  =tokenizer.convert_tokens_to_ids(lowerCAmelCase__							)
        self.assertListEqual(
            lowerCAmelCase__		,				[
                value + tokenizer.fairseq_offset
                for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
                #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
            ]		,				)

        a__     : Optional[int]  =tokenizer.convert_ids_to_tokens(lowerCAmelCase__							)
        self.assertListEqual(
            lowerCAmelCase__		,				[
                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        _lowercase  (   self							)       ->						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

        a__     : List[str]  =(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})'''							):
            a__     : Optional[Any]  =self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__		,				**lowerCAmelCase__							)
            a__     : Any  =self.tokenizer_class.from_pretrained(lowerCAmelCase__		,				**lowerCAmelCase__							)

            a__     : List[Any]  =tempfile.mkdtemp()

            a__     : str  =tokenizer_r.save_pretrained(lowerCAmelCase__							)
            a__     : List[str]  =tokenizer_p.save_pretrained(lowerCAmelCase__							)

            # 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							)							)
            a__     : Any  =tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f							)
            self.assertSequenceEqual(lowerCAmelCase__		,				lowerCAmelCase__							)

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

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

            shutil.rmtree(lowerCAmelCase__							)

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

            a__     : Any  =tokenizer_r.save_pretrained(lowerCAmelCase__		,				legacy_format=lowerCAmelCase__							)
            a__     : Any  =tokenizer_p.save_pretrained(lowerCAmelCase__							)

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

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

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

            shutil.rmtree(lowerCAmelCase__							)

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

            a__     : Union[str, Any]  =tokenizer_r.save_pretrained(lowerCAmelCase__		,				legacy_format=lowerCAmelCase__							)
            a__     : Optional[int]  =tokenizer_p.save_pretrained(lowerCAmelCase__							)

            # 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
            a__     : Union[str, Any]  =tokenizer_r.from_pretrained(lowerCAmelCase__							)
            a__     : Union[str, Any]  =tokenizer_p.from_pretrained(lowerCAmelCase__							)

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

            shutil.rmtree(lowerCAmelCase__							)







      @cached_property
      def        _lowercase  (   self							)       ->						List[str]:



        '''simple docstring'''




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







      def        _lowercase  (   self							)       ->						Dict:



        '''simple docstring'''




        with tempfile.NamedTemporaryFile() as f:
          shutil.copyfile(lowerCAmelCase__		,				f.name							)
          a__     : List[Any]  =XLMRobertaTokenizer(f.name		,				keep_accents=lowerCAmelCase__							)
          a__     : Optional[Any]  =pickle.dumps(lowerCAmelCase__							)
        pickle.loads(lowerCAmelCase__							)







      def        _lowercase  (   self							)       ->						Tuple:



        '''simple docstring'''




        if not self.test_rust_tokenizer:
          return

        a__     : Dict  =self.get_tokenizer()
        a__     : Tuple  =self.get_rust_tokenizer()

        a__     : Tuple  ="I was born in 92000, and this is falsé."

        a__     : int  =tokenizer.tokenize(lowerCAmelCase__							)
        a__     : List[Any]  =rust_tokenizer.tokenize(lowerCAmelCase__							)
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)

        a__     : Optional[int]  =tokenizer.encode(lowerCAmelCase__		,				add_special_tokens=lowerCAmelCase__							)
        a__     : int  =rust_tokenizer.encode(lowerCAmelCase__		,				add_special_tokens=lowerCAmelCase__							)
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)

        a__     : Tuple  =self.get_rust_tokenizer()
        a__     : List[Any]  =tokenizer.encode(lowerCAmelCase__							)
        a__     : List[Any]  =rust_tokenizer.encode(lowerCAmelCase__							)
        self.assertListEqual(lowerCAmelCase__		,				lowerCAmelCase__							)







      @slow
      def        _lowercase  (   self							)       ->						int:



        '''simple docstring'''




        a__     : List[str]  ="Hello World!"
        a__     : Optional[int]  =[0, 3_5_3_7_8, 6_6_6_1, 3_8, 2]
        # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
        # xlmr.eval()
        # xlmr.encode(symbols)

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







      @slow
      def        _lowercase  (   self							)       ->						Optional[int]:



        '''simple docstring'''




        a__     : List[str]  =(
            "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"
        )
        a__     : List[str]  =[
            0,
            3_2_9_3,
            8_3,
            1_0,
            4_5_5_2,
            4_9_8_9,
            7_9_8_6,
            6_7_8,
            1_0,
            5_9_1_5,
            1_1_1,
            1_7_9_4_5_9,
            1_2_4_8_5_0,
            4,
            6_0_4_4,
            2_3_7,
            1_2,
            6,
            5,
            6,
            4,
            6_7_8_0,
            7_0_5,
            1_5,
            1_3_8_8,
            4_4,
            3_7_8,
            1_0_1_1_4,
            7_1_1,
            1_5_2,
            2_0,
            6,
            5,
            2_2_3_7_6,
            6_4_2,
            1_2_2_1,
            1_5_1_9_0,
            3_4_1_5_3,
            4_5_0,
            5_6_0_8,
            9_5_9,
            1_1_1_9,
            5_7_7_0_2,
            1_3_6,
            1_8_6,
            4_7,
            1_0_9_8,
            2_9_3_6_7,
            4_7,
            # 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,
            6_0_4_4,
            2_3_7,
            6_2_8_4,
            5_0_9_0_1,
            5_2_8,
            3_1,
            9_0,
            3_4,
            9_2_7,
            2,
        ]
        # xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
        # xlmr.eval()
        # xlmr.encode(symbols)

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







      @slow
      def        _lowercase  (   self							)       ->						Optional[int]:



        '''simple docstring'''




        a__     : Dict  ={"input_ids": [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 5_4_2_8, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 1_2_3_9_9, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 2_7_8_9, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 8_0_5, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 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, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 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=lowerCAmelCase__		,				model_name="xlm-roberta-base"		,				revision="d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"		,				)













UpperCAmelCase     :     Dict							=	[0, 2, 4, 6, 8]
UpperCAmelCase     :     Tuple							=	[1, 3, 5, 7, 9]
def 					_A	(		SCREAMING_SNAKE_CASE					:       int	,	SCREAMING_SNAKE_CASE					:       int	,	SCREAMING_SNAKE_CASE					:       list[int]	,	SCREAMING_SNAKE_CASE					:       int						):





  """simple docstring"""



  if remaining_length == 0:
    if digits[0] == 0 or digits[-1] == 0:
      return 0

    for i in range(length // 2 - 1	,	-1	,	-1						):
      remainder += digits[i] + digits[length - i - 1]

      if remainder % 2 == 0:
        return 0

      remainder //= 10

    return 1

  if remaining_length == 1:
    if remainder % 2 == 0:
      return 0

    a__     : str  =0
    for digit in range(10						):
      a__     : int  =digit
      result += reversible_numbers(
          0	,	(remainder + 2 * digit) // 10	,	SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE						)
    return result

  a__     : List[str]  =0
  for digita in range(10						):
    a__     : Optional[int]  =digita

    if (remainder + digita) % 2 == 0:
      a__     : Dict  =ODD_DIGITS
    else:
      a__     : Any  =EVEN_DIGITS

    for digita in other_parity_digits:
      a__     : Union[str, Any]  =digita
      result += reversible_numbers(
          remaining_length - 2	,	(remainder + digita + digita) // 10	,	SCREAMING_SNAKE_CASE	,	SCREAMING_SNAKE_CASE	,	)
  return result
def 					_A	(		SCREAMING_SNAKE_CASE					:       int = 9						):





  """simple docstring"""



  a__     : List[str]  =0
  for length in range(1	,	max_power + 1						):
    result += reversible_numbers(SCREAMING_SNAKE_CASE	,	0	,	[0] * length	,	SCREAMING_SNAKE_CASE						)
  return result


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






