




'''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    :List[str]				       =     get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
@require_tokenizers
class 			a       (	_a			,						unittest.TestCase ):


     """simple docstring"""






     SCREAMING_SNAKE_CASE :				int							     =     XLMRobertaTokenizer
     SCREAMING_SNAKE_CASE :				Optional[Any]							     =     XLMRobertaTokenizerFast
     SCREAMING_SNAKE_CASE :				Dict							     =     True
     SCREAMING_SNAKE_CASE :				Optional[int]							     =     True

     def 				lowerCamelCase__				(       self  :	Dict    )		->							List[Any]:
          super().setUp()

          # We have a SentencePiece fixture for testing
          __UpperCAmelCase			:				Optional[Any]													=    XLMRobertaTokenizer(snake_case							,				keep_accents=snake_case    )
          tokenizer.save_pretrained(self.tmpdirname    )

     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Optional[int]:
          __UpperCAmelCase			:				int													=    '''<pad>'''
          __UpperCAmelCase			:				Optional[int]													=    1

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

     def 				lowerCamelCase__				(       self  :	List[Any]    )		->							Optional[int]:
          __UpperCAmelCase			:				Optional[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(snake_case    )							,				1002    )

     def 				lowerCamelCase__				(       self  :	Union[str, Any]    )		->							Union[str, Any]:
          self.assertEqual(self.get_tokenizer().vocab_size							,				1002    )

     def 				lowerCamelCase__				(       self  :	Dict    )		->							int:
          __UpperCAmelCase			:				Optional[Any]													=    XLMRobertaTokenizer(snake_case							,				keep_accents=snake_case    )

          __UpperCAmelCase			:				Tuple													=    tokenizer.tokenize('''This is a test'''    )
          self.assertListEqual(snake_case							,				['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']    )

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

          __UpperCAmelCase			:				List[Any]													=    tokenizer.tokenize('''I was born in 92000, and this is falsé.'''    )
          self.assertListEqual(
              snake_case							,				[
                  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			:				Tuple													=    tokenizer.convert_tokens_to_ids(snake_case    )
          self.assertListEqual(
              snake_case							,				[
                  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 ^
              ]							,				)

          __UpperCAmelCase			:				Optional[Any]													=    tokenizer.convert_ids_to_tokens(snake_case    )
          self.assertListEqual(
              snake_case							,				[
                  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  :	int    )		->							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

          __UpperCAmelCase			:				Optional[int]													=    (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			:				Any													=    self.rust_tokenizer_class.from_pretrained(snake_case							,				**snake_case    )
                    __UpperCAmelCase			:				Optional[Any]													=    self.tokenizer_class.from_pretrained(snake_case							,				**snake_case    )

                    __UpperCAmelCase			:				Optional[int]													=    tempfile.mkdtemp()

                    __UpperCAmelCase			:				Dict													=    tokenizer_r.save_pretrained(snake_case    )
                    __UpperCAmelCase			:				Union[str, Any]													=    tokenizer_p.save_pretrained(snake_case    )

                    # 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(snake_case							,				snake_case    )

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

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

                    shutil.rmtree(snake_case    )

                    # Save tokenizer rust, legacy_format=True
                    __UpperCAmelCase			:				int													=    tempfile.mkdtemp()

                    __UpperCAmelCase			:				Tuple													=    tokenizer_r.save_pretrained(snake_case							,				legacy_format=snake_case    )
                    __UpperCAmelCase			:				Optional[Any]													=    tokenizer_p.save_pretrained(snake_case    )

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

                    # Checks everything loads correctly in the same way
                    __UpperCAmelCase			:				Any													=    tokenizer_r.from_pretrained(snake_case    )
                    __UpperCAmelCase			:				Optional[Any]													=    tokenizer_p.from_pretrained(snake_case    )

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

                    shutil.rmtree(snake_case    )

                    # Save tokenizer rust, legacy_format=False
                    __UpperCAmelCase			:				List[Any]													=    tempfile.mkdtemp()

                    __UpperCAmelCase			:				Dict													=    tokenizer_r.save_pretrained(snake_case							,				legacy_format=snake_case    )
                    __UpperCAmelCase			:				Any													=    tokenizer_p.save_pretrained(snake_case    )

                    # 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			:				Optional[int]													=    tokenizer_r.from_pretrained(snake_case    )
                    __UpperCAmelCase			:				List[Any]													=    tokenizer_p.from_pretrained(snake_case    )

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

                    shutil.rmtree(snake_case    )

     @cached_property
     def 				lowerCamelCase__				(       self  :	Dict    )		->							List[str]:
          return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''    )

     def 				lowerCamelCase__				(       self  :	int    )		->							Tuple:
          with tempfile.NamedTemporaryFile() as f:
               shutil.copyfile(snake_case							,				f.name    )
               __UpperCAmelCase			:				Optional[int]													=    XLMRobertaTokenizer(f.name							,				keep_accents=snake_case    )
               __UpperCAmelCase			:				Any													=    pickle.dumps(snake_case    )
          pickle.loads(snake_case    )

     def 				lowerCamelCase__				(       self  :	Optional[int]    )		->							Optional[Any]:
          if not self.test_rust_tokenizer:
               return

          __UpperCAmelCase			:				int													=    self.get_tokenizer()
          __UpperCAmelCase			:				Union[str, Any]													=    self.get_rust_tokenizer()

          __UpperCAmelCase			:				str													=    '''I was born in 92000, and this is falsé.'''

          __UpperCAmelCase			:				Optional[Any]													=    tokenizer.tokenize(snake_case    )
          __UpperCAmelCase			:				Tuple													=    rust_tokenizer.tokenize(snake_case    )
          self.assertListEqual(snake_case							,				snake_case    )

          __UpperCAmelCase			:				Dict													=    tokenizer.encode(snake_case							,				add_special_tokens=snake_case    )
          __UpperCAmelCase			:				Tuple													=    rust_tokenizer.encode(snake_case							,				add_special_tokens=snake_case    )
          self.assertListEqual(snake_case							,				snake_case    )

          __UpperCAmelCase			:				Dict													=    self.get_rust_tokenizer()
          __UpperCAmelCase			:				int													=    tokenizer.encode(snake_case    )
          __UpperCAmelCase			:				int													=    rust_tokenizer.encode(snake_case    )
          self.assertListEqual(snake_case							,				snake_case    )

     @slow
     def 				lowerCamelCase__				(       self  :	List[Any]    )		->							List[Any]:
          __UpperCAmelCase			:				Any													=    '''Hello World!'''
          __UpperCAmelCase			:				List[Any]													=    [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(snake_case							,				self.big_tokenizer.encode(snake_case    )    )

     @slow
     def 				lowerCamelCase__				(       self  :	int    )		->							List[str]:
          __UpperCAmelCase			:				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			:				str													=    [
              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(snake_case							,				self.big_tokenizer.encode(snake_case    )    )






     @slow
     def 				lowerCamelCase__				(       self  :	Any    )		->							Dict:
          # fmt: off
          __UpperCAmelCase			:				List[str]													=    {'''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=snake_case							,				model_name='''xlm-roberta-base'''							,				revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''							,				)



'''simple docstring'''



from __future__ import annotations




def 			_a			(		_lowercase      :			list						):





     '''simple docstring'''






     if not nums:
          raise ValueError('''List is empty'''						)
     return sum(_lowercase						) / len(_lowercase						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()