'''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


a=  get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
@require_tokenizers
class 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						XLMRobertaTokenizer
     SCREAMING_SNAKE_CASE__		   =						XLMRobertaTokenizerFast
     SCREAMING_SNAKE_CASE__		   =						True
     SCREAMING_SNAKE_CASE__		   =						True







     def lowerCAmelCase     (		self    ):
         super().setUp()

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







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[int]		    =  '<pad>'
         __UpperCamelCase	:	Union[str, 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 lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  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 lowerCAmelCase     (		self    ):
         self.assertEqual(self.get_tokenizer().vocab_size     ,			1_0_0_2    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Union[str, Any]		    =  XLMRobertaTokenizer(_lowerCamelCase     ,			keep_accents=_lowerCamelCase    )

         __UpperCamelCase	:	List[Any]		    =  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]]     ,			)

         __UpperCamelCase	:	Any		    =  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',
                 '.',
             ]     ,			)
         __UpperCamelCase	:	str		    =  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 ^
             ]     ,			)

         __UpperCamelCase	:	Tuple		    =  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 lowerCAmelCase     (		self    ):
         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

         __UpperCamelCase	:	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})"""    ):
                 __UpperCamelCase	:	int		    =  self.rust_tokenizer_class.from_pretrained(_lowerCamelCase     ,			**_lowerCamelCase    )
                 __UpperCamelCase	:	int		    =  self.tokenizer_class.from_pretrained(_lowerCamelCase     ,			**_lowerCamelCase    )

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

                 __UpperCamelCase	:	Union[str, Any]		    =  tokenizer_r.save_pretrained(_lowerCamelCase    )
                 __UpperCamelCase	:	List[Any]		    =  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    )    )
                 __UpperCamelCase	:	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
                 __UpperCamelCase	:	Any		    =  tokenizer_r.from_pretrained(_lowerCamelCase    )
                 __UpperCamelCase	:	Optional[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
                 __UpperCamelCase	:	List[Any]		    =  tempfile.mkdtemp()

                 __UpperCamelCase	:	Optional[Any]		    =  tokenizer_r.save_pretrained(_lowerCamelCase     ,			legacy_format=_lowerCamelCase    )
                 __UpperCamelCase	:	Optional[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
                 __UpperCamelCase	:	Union[str, Any]		    =  tokenizer_r.from_pretrained(_lowerCamelCase    )
                 __UpperCamelCase	:	Optional[int]		    =  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
                 __UpperCamelCase	:	List[str]		    =  tempfile.mkdtemp()

                 __UpperCamelCase	:	List[Any]		    =  tokenizer_r.save_pretrained(_lowerCamelCase     ,			legacy_format=_lowerCamelCase    )
                 __UpperCamelCase	:	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
                 __UpperCamelCase	:	Any		    =  tokenizer_r.from_pretrained(_lowerCamelCase    )
                 __UpperCamelCase	:	Optional[int]		    =  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 lowerCAmelCase     (		self    ):
         return XLMRobertaTokenizer.from_pretrained('xlm-roberta-base'    )







     def lowerCAmelCase     (		self    ):
         with tempfile.NamedTemporaryFile() as f:
             shutil.copyfile(_lowerCamelCase     ,			f.name    )
             __UpperCamelCase	:	List[str]		    =  XLMRobertaTokenizer(f.name     ,			keep_accents=_lowerCamelCase    )
             __UpperCamelCase	:	Optional[int]		    =  pickle.dumps(_lowerCamelCase    )
         pickle.loads(_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         if not self.test_rust_tokenizer:
             return

         __UpperCamelCase	:	List[Any]		    =  self.get_tokenizer()
         __UpperCamelCase	:	Tuple		    =  self.get_rust_tokenizer()

         __UpperCamelCase	:	Tuple		    =  'I was born in 92000, and this is falsé.'

         __UpperCamelCase	:	List[str]		    =  tokenizer.tokenize(_lowerCamelCase    )
         __UpperCamelCase	:	int		    =  rust_tokenizer.tokenize(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )

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

         __UpperCamelCase	:	Union[str, Any]		    =  self.get_rust_tokenizer()
         __UpperCamelCase	:	Any		    =  tokenizer.encode(_lowerCamelCase    )
         __UpperCamelCase	:	int		    =  rust_tokenizer.encode(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )







     @slow
     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  'Hello World!'
         __UpperCamelCase	:	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 lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Optional[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'
         )
         __UpperCamelCase	:	List[Any]		    =  [
             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 lowerCAmelCase     (		self    ):
         # fmt: off
         __UpperCamelCase	:	Tuple		    =  {'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'     ,			)




'''simple docstring'''
def  _UpperCamelCase (     _a	:	int			):




    """simple docstring"""



    if bit_count < 0:
        raise ValueError('The given input must be positive'			)

    # get the generated string sequence
    __UpperCamelCase	:	Dict		    =  gray_code_sequence_string(_a			)
    #
    # convert them to integers
    for i in range(len(_a			)			):
        __UpperCamelCase	:	int		    =  int(sequence[i]				,     2			)

    return sequence







def  _UpperCamelCase (     _a	:	int			):




    """simple docstring"""



    if bit_count == 0:
        return ["0"]

    if bit_count == 1:
        return ["0", "1"]

    __UpperCamelCase	:	Dict		    =  1 << bit_count  # defines the length of the sequence
    # 1<< n is equivalent to 2^n

    # recursive answer will generate answer for n-1 bits
    __UpperCamelCase	:	Tuple		    =  gray_code_sequence_string(bit_count - 1			)

    __UpperCamelCase	:	str		    =  []

    # append 0 to first half of the smaller sequence generated
    for i in range(seq_len // 2			):
        __UpperCamelCase	:	Optional[Any]		    =  '0' + smaller_sequence[i]
        sequence.append(_a			)

    # append 1 to second half ... start from the end of the list
    for i in reversed(range(seq_len // 2			)			):
        __UpperCamelCase	:	List[Any]		    =  '1' + smaller_sequence[i]
        sequence.append(_a			)

    return sequence


if __name__ == "__main__":
  import doctest

  doctest.testmod()



