


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


__lowerCAmelCase	: List[str]  				=get_tests_dir('fixtures/test_sentencepiece.model')
@require_sentencepiece
@require_tokenizers
class        _lowercase      (			A__						,			unittest.TestCase       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			str						=		XLMRobertaTokenizer
				SCREAMING_SNAKE_CASE__				:			List[str]						=		XLMRobertaTokenizerFast
				SCREAMING_SNAKE_CASE__				:			str						=		True
				SCREAMING_SNAKE_CASE__				:			int						=		True


				def 		__magic_name__(       self			:List[str]	)		->			List[Any]:
										super().setUp()

										# We have a SentencePiece fixture for testing
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		XLMRobertaTokenizer(lowerCAmelCase__			,			keep_accents=lowerCAmelCase__	)
										tokenizer.save_pretrained(self.tmpdirname	)


				def 		__magic_name__(       self			:int	)		->			str:
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		'''<pad>'''
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		1

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


				def 		__magic_name__(       self			:Optional[Any]	)		->			Optional[Any]:
										__SCREAMING_SNAKE_CASE						:     List[str]					=		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_002	)


				def 		__magic_name__(       self			:int	)		->			str:
										self.assertEqual(self.get_tokenizer().vocab_size			,			1_002	)


				def 		__magic_name__(       self			:Any	)		->			Union[str, Any]:
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		XLMRobertaTokenizer(lowerCAmelCase__			,			keep_accents=lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Optional[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 [285, 46, 10, 170, 382]]			,			)

										__SCREAMING_SNAKE_CASE						:     Union[str, 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''',
										        '''.''',
										    ]			,			)
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		tokenizer.convert_tokens_to_ids(lowerCAmelCase__	)
										self.assertListEqual(
										    lowerCAmelCase__			,			[
										        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						:     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 		__magic_name__(       self			:Optional[Any]	)		->			Optional[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

										__SCREAMING_SNAKE_CASE						:     List[Any]					=		(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						:     Tuple					=		self.rust_tokenizer_class.from_pretrained(lowerCAmelCase__			,			**lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     str					=		self.tokenizer_class.from_pretrained(lowerCAmelCase__			,			**lowerCAmelCase__	)

																						__SCREAMING_SNAKE_CASE						:     int					=		tempfile.mkdtemp()

																						__SCREAMING_SNAKE_CASE						:     Tuple					=		tokenizer_r.save_pretrained(lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Dict					=		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	)	)
																						__SCREAMING_SNAKE_CASE						:     List[str]					=		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
																						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		tokenizer_r.from_pretrained(lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     str					=		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
																						__SCREAMING_SNAKE_CASE						:     List[str]					=		tempfile.mkdtemp()

																						__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		tokenizer_r.save_pretrained(lowerCAmelCase__			,			legacy_format=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     List[str]					=		tokenizer_p.save_pretrained(lowerCAmelCase__	)

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

																						# Checks everything loads correctly in the same way
																						__SCREAMING_SNAKE_CASE						:     Any					=		tokenizer_r.from_pretrained(lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     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
																						__SCREAMING_SNAKE_CASE						:     List[str]					=		tempfile.mkdtemp()

																						__SCREAMING_SNAKE_CASE						:     List[Any]					=		tokenizer_r.save_pretrained(lowerCAmelCase__			,			legacy_format=lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     str					=		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
																						__SCREAMING_SNAKE_CASE						:     Tuple					=		tokenizer_r.from_pretrained(lowerCAmelCase__	)
																						__SCREAMING_SNAKE_CASE						:     Dict					=		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 		__magic_name__(       self			:List[str]	)		->			Union[str, Any]:
										return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''	)


				def 		__magic_name__(       self			:Union[str, Any]	)		->			Tuple:
										with tempfile.NamedTemporaryFile() as f:
																shutil.copyfile(lowerCAmelCase__			,			f.name	)
																__SCREAMING_SNAKE_CASE						:     Tuple					=		XLMRobertaTokenizer(f.name			,			keep_accents=lowerCAmelCase__	)
																__SCREAMING_SNAKE_CASE						:     Tuple					=		pickle.dumps(lowerCAmelCase__	)
										pickle.loads(lowerCAmelCase__	)


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

										__SCREAMING_SNAKE_CASE						:     int					=		self.get_tokenizer()
										__SCREAMING_SNAKE_CASE						:     Any					=		self.get_rust_tokenizer()

										__SCREAMING_SNAKE_CASE						:     int					=		'''I was born in 92000, and this is falsé.'''

										__SCREAMING_SNAKE_CASE						:     str					=		tokenizer.tokenize(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     List[str]					=		rust_tokenizer.tokenize(lowerCAmelCase__	)
										self.assertListEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		tokenizer.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     List[str]					=		rust_tokenizer.encode(lowerCAmelCase__			,			add_special_tokens=lowerCAmelCase__	)
										self.assertListEqual(lowerCAmelCase__			,			lowerCAmelCase__	)

										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		self.get_rust_tokenizer()
										__SCREAMING_SNAKE_CASE						:     str					=		tokenizer.encode(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Any					=		rust_tokenizer.encode(lowerCAmelCase__	)
										self.assertListEqual(lowerCAmelCase__			,			lowerCAmelCase__	)


				@slow
				def 		__magic_name__(       self			:Optional[int]	)		->			int:
										__SCREAMING_SNAKE_CASE						:     Tuple					=		'''Hello World!'''
										__SCREAMING_SNAKE_CASE						:     Optional[int]					=		[0, 35_378, 6_661, 38, 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 		__magic_name__(       self			:Dict	)		->			int:
										__SCREAMING_SNAKE_CASE						:     List[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						:     Any					=		[
										    0,
										    3_293,
										    83,
										    10,
										    4_552,
										    4_989,
										    7_986,
										    678,
										    10,
										    5_915,
										    111,
										    179_459,
										    124_850,
										    4,
										    6_044,
										    237,
										    12,
										    6,
										    5,
										    6,
										    4,
										    6_780,
										    705,
										    15,
										    1_388,
										    44,
										    378,
										    10_114,
										    711,
										    152,
										    20,
										    6,
										    5,
										    22_376,
										    642,
										    1_221,
										    15_190,
										    34_153,
										    450,
										    5_608,
										    959,
										    1_119,
										    57_702,
										    136,
										    186,
										    47,
										    1_098,
										    29_367,
										    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,
										    6_044,
										    237,
										    6_284,
										    50_901,
										    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(lowerCAmelCase__			,			self.big_tokenizer.encode(lowerCAmelCase__	)	)



				@slow
				def 		__magic_name__(       self			:Dict	)		->			List[Any]:
										# fmt: off
										__SCREAMING_SNAKE_CASE						:     Tuple					=		{'''input_ids''': [[0, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 5_428, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 12_399, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 2_789, 1_328, 4_589, 42, 122_009, 115_774, 23, 805, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [0, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 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, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 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'''			,			)




from ..utils import DummyObject, requires_backends
class        _lowercase      (			metaclass=A__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			Optional[int]						=		['''keras_nlp''']


				def __init__(       self			:Tuple			,			*lowerCAmelCase__			:Optional[Any]			,			**lowerCAmelCase__			:Dict	)		->			Dict:
										requires_backends(self			,			['''keras_nlp''']	)
