





"""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 						__snake_case   (						SCREAMING_SNAKE_CASE__				,				unittest.TestCase	):





 """simple docstring"""


 _lowerCamelCase								=	XLMRobertaTokenizer
 _lowerCamelCase								=	XLMRobertaTokenizerFast
 _lowerCamelCase								=	True
 _lowerCamelCase								=	True

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     super().setUp()

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

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		str							=	'''<pad>'''
     __A       :		Tuple							=	1

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

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Optional[int]							=	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    )   ,		1002    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     self.assertEqual(self.get_tokenizer().vocab_size   ,		1002    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Union[str, Any]							=	XLMRobertaTokenizer(__lowerCamelCase   ,		keep_accents=__lowerCamelCase    )

     __A       :		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]]   ,		)

     __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       :		List[Any]							=	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 ^
         ]   ,		)

     __A       :		Dict							=	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    UpperCamelCase__(       self    ):



     '''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       :		Optional[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})"""    ):
             __A       :		List[str]							=	self.rust_tokenizer_class.from_pretrained(__lowerCamelCase   ,		**__lowerCamelCase    )
             __A       :		Dict							=	self.tokenizer_class.from_pretrained(__lowerCamelCase   ,		**__lowerCamelCase    )

             __A       :		Optional[Any]							=	tempfile.mkdtemp()

             __A       :		Optional[int]							=	tokenizer_r.save_pretrained(__lowerCamelCase    )
             __A       :		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    )    )
             __A       :		List[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       :		Union[str, Any]							=	tokenizer_r.from_pretrained(__lowerCamelCase    )
             __A       :		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    )    )
                 # 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       :		Dict							=	tokenizer_r.save_pretrained(__lowerCamelCase   ,		legacy_format=__lowerCamelCase    )
             __A       :		int							=	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       :		Dict							=	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       :		int							=	tempfile.mkdtemp()

             __A       :		Dict							=	tokenizer_r.save_pretrained(__lowerCamelCase   ,		legacy_format=__lowerCamelCase    )
             __A       :		List[Any]							=	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       :		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    UpperCamelCase__(       self    ):



     '''simple docstring'''




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

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     with tempfile.NamedTemporaryFile() as f:
         shutil.copyfile(__lowerCamelCase   ,		f.name    )
         __A       :		List[str]							=	XLMRobertaTokenizer(f.name   ,		keep_accents=__lowerCamelCase    )
         __A       :		Any							=	pickle.dumps(__lowerCamelCase    )
     pickle.loads(__lowerCamelCase    )

 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     if not self.test_rust_tokenizer:
         return

     __A       :		Optional[Any]							=	self.get_tokenizer()
     __A       :		str							=	self.get_rust_tokenizer()

     __A       :		Optional[Any]							=	'''I was born in 92000, and this is falsé.'''

     __A       :		str							=	tokenizer.tokenize(__lowerCamelCase    )
     __A       :		Dict							=	rust_tokenizer.tokenize(__lowerCamelCase    )
     self.assertListEqual(__lowerCamelCase   ,		__lowerCamelCase    )

     __A       :		List[Any]							=	tokenizer.encode(__lowerCamelCase   ,		add_special_tokens=__lowerCamelCase    )
     __A       :		Any							=	rust_tokenizer.encode(__lowerCamelCase   ,		add_special_tokens=__lowerCamelCase    )
     self.assertListEqual(__lowerCamelCase   ,		__lowerCamelCase    )

     __A       :		Optional[int]							=	self.get_rust_tokenizer()
     __A       :		Any							=	tokenizer.encode(__lowerCamelCase    )
     __A       :		Optional[int]							=	rust_tokenizer.encode(__lowerCamelCase    )
     self.assertListEqual(__lowerCamelCase   ,		__lowerCamelCase    )

 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		List[str]							=	'''Hello World!'''
     __A       :		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(__lowerCamelCase   ,		self.big_tokenizer.encode(__lowerCamelCase    )    )

 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Dict							=	(
         '''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       :		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(__lowerCamelCase   ,		self.big_tokenizer.encode(__lowerCamelCase    )    )







 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		List[Any]							=	{'''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=__lowerCamelCase   ,		model_name='''xlm-roberta-base'''   ,		revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''   ,		)











"""simple docstring"""



import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


a_					=     logging.get_logger(__name__)






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 def __init__(       self   ,		*__lowerCamelCase   ,		**__lowerCamelCase    ):



     '''simple docstring'''




     warnings.warn(
         '''The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
         ''' Please use PoolFormerImageProcessor instead.'''   ,		__lowerCamelCase   ,		)
     super().__init__(*__lowerCamelCase   ,		**__lowerCamelCase    )




