

"""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 					_lowerCAmelCase  (	UpperCamelCase_     ,unittest.TestCase   ):







 """simple docstring"""







 __UpperCAmelCase	:					str   		=	XLMRobertaTokenizer
 __UpperCAmelCase	:					List[Any]   		=	XLMRobertaTokenizerFast
 __UpperCAmelCase	:					Optional[int]   		=	True
 __UpperCAmelCase	:					str   		=	True


 def 					_lowercase (			self							:			Optional[Any]	):
    super().setUp()

    # We have a SentencePiece fixture for testing
    __lowercase								=						XLMRobertaTokenizer(lowercase_,					keep_accents=lowercase_	)
    tokenizer.save_pretrained(self.tmpdirname	)


 def 					_lowercase (			self							:			int	):
    __lowercase								=						'<pad>'
    __lowercase								=						1

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


 def 					_lowercase (			self							:			Dict	):
    __lowercase								=						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(lowercase_	),					1_0_0_2	)


 def 					_lowercase (			self							:			Dict	):
    self.assertEqual(self.get_tokenizer().vocab_size,					1_0_0_2	)


 def 					_lowercase (			self							:			Optional[int]	):
    __lowercase								=						XLMRobertaTokenizer(lowercase_,					keep_accents=lowercase_	)

    __lowercase								=						tokenizer.tokenize("This is a test"	)
    self.assertListEqual(lowercase_,					["▁This", "▁is", "▁a", "▁t", "est"]	)

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

    __lowercase								=						tokenizer.tokenize("I was born in 92000, and this is falsé."	)
    self.assertListEqual(
        lowercase_,					[
            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",
            ".",
        ],					)
    __lowercase								=						tokenizer.convert_tokens_to_ids(lowercase_	)
    self.assertListEqual(
        lowercase_,					[
            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 ^
        ],					)

    __lowercase								=						tokenizer.convert_ids_to_tokens(lowercase_	)
    self.assertListEqual(
        lowercase_,					[
            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							:			int	):




    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

    __lowercase								=						(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})"""	):
          __lowercase								=						self.rust_tokenizer_class.from_pretrained(lowercase_,					**lowercase_	)
          __lowercase								=						self.tokenizer_class.from_pretrained(lowercase_,					**lowercase_	)

          __lowercase								=						tempfile.mkdtemp()

          __lowercase								=						tokenizer_r.save_pretrained(lowercase_	)
          __lowercase								=						tokenizer_p.save_pretrained(lowercase_	)

          # 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	)	)
          __lowercase								=						tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f	)
          self.assertSequenceEqual(lowercase_,					lowercase_	)

          # Checks everything loads correctly in the same way
          __lowercase								=						tokenizer_r.from_pretrained(lowercase_	)
          __lowercase								=						tokenizer_p.from_pretrained(lowercase_	)

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

          shutil.rmtree(lowercase_	)

          # Save tokenizer rust, legacy_format=True
          __lowercase								=						tempfile.mkdtemp()

          __lowercase								=						tokenizer_r.save_pretrained(lowercase_,					legacy_format=lowercase_	)
          __lowercase								=						tokenizer_p.save_pretrained(lowercase_	)

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

          # Checks everything loads correctly in the same way
          __lowercase								=						tokenizer_r.from_pretrained(lowercase_	)
          __lowercase								=						tokenizer_p.from_pretrained(lowercase_	)

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

          shutil.rmtree(lowercase_	)

          # Save tokenizer rust, legacy_format=False
          __lowercase								=						tempfile.mkdtemp()

          __lowercase								=						tokenizer_r.save_pretrained(lowercase_,					legacy_format=lowercase_	)
          __lowercase								=						tokenizer_p.save_pretrained(lowercase_	)

          # 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
          __lowercase								=						tokenizer_r.from_pretrained(lowercase_	)
          __lowercase								=						tokenizer_p.from_pretrained(lowercase_	)

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

          shutil.rmtree(lowercase_	)


 @cached_property
 def 					_lowercase (			self							:			int	):
    return XLMRobertaTokenizer.from_pretrained("xlm-roberta-base"	)


 def 					_lowercase (			self							:			Optional[int]	):




    with tempfile.NamedTemporaryFile() as f:
       shutil.copyfile(lowercase_,					f.name	)
       __lowercase								=						XLMRobertaTokenizer(f.name,					keep_accents=lowercase_	)
       __lowercase								=						pickle.dumps(lowercase_	)
    pickle.loads(lowercase_	)


 def 					_lowercase (			self							:			List[Any]	):




    if not self.test_rust_tokenizer:
       return

    __lowercase								=						self.get_tokenizer()
    __lowercase								=						self.get_rust_tokenizer()

    __lowercase								=						'I was born in 92000, and this is falsé.'

    __lowercase								=						tokenizer.tokenize(lowercase_	)
    __lowercase								=						rust_tokenizer.tokenize(lowercase_	)
    self.assertListEqual(lowercase_,					lowercase_	)

    __lowercase								=						tokenizer.encode(lowercase_,					add_special_tokens=lowercase_	)
    __lowercase								=						rust_tokenizer.encode(lowercase_,					add_special_tokens=lowercase_	)
    self.assertListEqual(lowercase_,					lowercase_	)

    __lowercase								=						self.get_rust_tokenizer()
    __lowercase								=						tokenizer.encode(lowercase_	)
    __lowercase								=						rust_tokenizer.encode(lowercase_	)
    self.assertListEqual(lowercase_,					lowercase_	)


 @slow
 def 					_lowercase (			self							:			str	):
    __lowercase								=						'Hello World!'
    __lowercase								=						[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(lowercase_,					self.big_tokenizer.encode(lowercase_	)	)


 @slow
 def 					_lowercase (			self							:			Tuple	):
    __lowercase								=						(
        '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'
    )
    __lowercase								=						[
        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(lowercase_,					self.big_tokenizer.encode(lowercase_	)	)



 @slow
 def 					_lowercase (			self							:			Any	):
    __lowercase								=						{'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=lowercase_,					model_name="xlm-roberta-base",					revision="d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3",					)








def 	a_      (    SCREAMING_SNAKE_CASE__					:      str		,			SCREAMING_SNAKE_CASE__					:      str     ):
       '''simple docstring'''





       assert x is not None
       assert y is not None

       _lowerCamelCase       :		Dict		=len(SCREAMING_SNAKE_CASE__     )
       _lowerCamelCase       :		Optional[Any]		=len(SCREAMING_SNAKE_CASE__     )

       # declaring the array for storing the dp values
       _lowerCamelCase       :		Optional[int]		=[[0] * (n + 1) for _ in range(m + 1     )]  # noqa: E741

       for i in range(1		,			m + 1     ):
              for j in range(1		,			n + 1     ):
                     _lowerCamelCase       :		int		=1 if x[i - 1] == y[j - 1] else 0

                     _lowerCamelCase       :		Union[str, Any]		=max(l[i - 1][j]		,			l[i][j - 1]		,			l[i - 1][j - 1] + match     )

       _lowerCamelCase       :		Optional[int]		=''
       _lowerCamelCase	,     _lowerCamelCase       :		Dict		=m, n
       while i > 0 and j > 0:
              _lowerCamelCase       :		int		=1 if x[i - 1] == y[j - 1] else 0

              if l[i][j] == l[i - 1][j - 1] + match:
                     if match == 1:
                            _lowerCamelCase       :		Union[str, Any]		=x[i - 1] + seq
                     i -= 1
                     j -= 1
              elif l[i][j] == l[i - 1][j]:
                     i -= 1
              else:
                     j -= 1

       return l[m][n], seq


if __name__ == "__main__":
 lowerCamelCase											=       'AGGTAB'
 lowerCamelCase											=       'GXTXAYB'
 lowerCamelCase											=       4
 lowerCamelCase											=       'GTAB'

 lowerCamelCase					,				lowerCamelCase											=       longest_common_subsequence(a, b)
 print('len =', ln, ', sub-sequence =', subseq)
 import doctest

 doctest.testmod()


