






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__    :   int    		=       get_tests_dir("""fixtures/test_sentencepiece.model""")







@require_sentencepiece
@require_tokenizers
class 					lowerCamelCase_  (						a_			,    unittest.TestCase  ):
							SCREAMING_SNAKE_CASE_      =      XLMRobertaTokenizer
							SCREAMING_SNAKE_CASE_      =      XLMRobertaTokenizerFast
							SCREAMING_SNAKE_CASE_      =      True
							SCREAMING_SNAKE_CASE_      =      True
							def 			SCREAMING_SNAKE_CASE_			(    self		:       str       ):





								'''simple docstring'''



								super().setUp()

								# We have a SentencePiece fixture for testing
								a												=      XLMRobertaTokenizer(__lowerCamelCase				,keep_accents=__lowerCamelCase       )
								tokenizer.save_pretrained(self.tmpdirname       )
							def 			SCREAMING_SNAKE_CASE_			(    self		:       int       ):





								'''simple docstring'''



								a												=      '''<pad>'''
								a												=      1

								self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCamelCase       )				,__lowerCamelCase       )
								self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCamelCase       )				,__lowerCamelCase       )
							def 			SCREAMING_SNAKE_CASE_			(    self		:       Optional[int]       ):





								'''simple docstring'''



								a												=      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       )				,10_02       )
							def 			SCREAMING_SNAKE_CASE_			(    self		:       Tuple       ):





								'''simple docstring'''



								self.assertEqual(self.get_tokenizer().vocab_size				,10_02       )
							def 			SCREAMING_SNAKE_CASE_			(    self		:       List[str]       ):





								'''simple docstring'''



								a												=      XLMRobertaTokenizer(__lowerCamelCase				,keep_accents=__lowerCamelCase       )

								a												=      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_85, 46, 10, 1_70, 3_82]]				,)

								a												=      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												=      tokenizer.convert_tokens_to_ids(__lowerCamelCase       )
								self.assertListEqual(
								    __lowerCamelCase				,[
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
								    ]				,)

								a												=      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 			SCREAMING_SNAKE_CASE_			(    self		:       Union[str, Any]       ):





								'''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												=      (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												=      self.rust_tokenizer_class.from_pretrained(__lowerCamelCase				,**__lowerCamelCase       )
										a												=      self.tokenizer_class.from_pretrained(__lowerCamelCase				,**__lowerCamelCase       )

										a												=      tempfile.mkdtemp()

										a												=      tokenizer_r.save_pretrained(__lowerCamelCase       )
										a												=      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												=      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												=      tokenizer_r.from_pretrained(__lowerCamelCase       )
										a												=      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												=      tempfile.mkdtemp()

										a												=      tokenizer_r.save_pretrained(__lowerCamelCase				,legacy_format=__lowerCamelCase       )
										a												=      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												=      tokenizer_r.from_pretrained(__lowerCamelCase       )
										a												=      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												=      tempfile.mkdtemp()

										a												=      tokenizer_r.save_pretrained(__lowerCamelCase				,legacy_format=__lowerCamelCase       )
										a												=      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												=      tokenizer_r.from_pretrained(__lowerCamelCase       )
										a												=      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 			SCREAMING_SNAKE_CASE_			(    self		:       Dict       ):





								'''simple docstring'''



								return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''       )
							def 			SCREAMING_SNAKE_CASE_			(    self		:       Any       ):





								'''simple docstring'''



								with tempfile.NamedTemporaryFile() as f:
									shutil.copyfile(__lowerCamelCase				,f.name       )
									a												=      XLMRobertaTokenizer(f.name				,keep_accents=__lowerCamelCase       )
									a												=      pickle.dumps(__lowerCamelCase       )
								pickle.loads(__lowerCamelCase       )
							def 			SCREAMING_SNAKE_CASE_			(    self		:       Dict       ):





								'''simple docstring'''



								if not self.test_rust_tokenizer:
									return

								a												=      self.get_tokenizer()
								a												=      self.get_rust_tokenizer()

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

								a												=      tokenizer.tokenize(__lowerCamelCase       )
								a												=      rust_tokenizer.tokenize(__lowerCamelCase       )
								self.assertListEqual(__lowerCamelCase				,__lowerCamelCase       )

								a												=      tokenizer.encode(__lowerCamelCase				,add_special_tokens=__lowerCamelCase       )
								a												=      rust_tokenizer.encode(__lowerCamelCase				,add_special_tokens=__lowerCamelCase       )
								self.assertListEqual(__lowerCamelCase				,__lowerCamelCase       )

								a												=      self.get_rust_tokenizer()
								a												=      tokenizer.encode(__lowerCamelCase       )
								a												=      rust_tokenizer.encode(__lowerCamelCase       )
								self.assertListEqual(__lowerCamelCase				,__lowerCamelCase       )
							@slow
							def 			SCREAMING_SNAKE_CASE_			(    self		:       Any       ):





								'''simple docstring'''



								a												=      '''Hello World!'''
								a												=      [0, 3_53_78, 66_61, 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 			SCREAMING_SNAKE_CASE_			(    self		:       Optional[int]       ):





								'''simple docstring'''



								a												=      (
								    '''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												=      [
								    0,
								    32_93,
								    83,
								    10,
								    45_52,
								    49_89,
								    79_86,
								    6_78,
								    10,
								    59_15,
								    1_11,
								    17_94_59,
								    12_48_50,
								    4,
								    60_44,
								    2_37,
								    12,
								    6,
								    5,
								    6,
								    4,
								    67_80,
								    7_05,
								    15,
								    13_88,
								    44,
								    3_78,
								    1_01_14,
								    7_11,
								    1_52,
								    20,
								    6,
								    5,
								    2_23_76,
								    6_42,
								    12_21,
								    1_51_90,
								    3_41_53,
								    4_50,
								    56_08,
								    9_59,
								    11_19,
								    5_77_02,
								    1_36,
								    1_86,
								    47,
								    10_98,
								    2_93_67,
								    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,
								    60_44,
								    2_37,
								    62_84,
								    5_09_01,
								    5_28,
								    31,
								    90,
								    34,
								    9_27,
								    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 			SCREAMING_SNAKE_CASE_			(    self		:       Union[str, Any]       ):





								'''simple docstring'''



								a												=      {'''input_ids''': [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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'''				,)









import random
from typing import Any






def 	__lowerCamelCase						(							lowerCamelCase__		:						list      ):





			'''simple docstring'''




			for _ in range(len(lowerCamelCase__      )      ):
						lowerCamelCase    		=  random.randint(0  ,							len(lowerCamelCase__      ) - 1      )
						lowerCamelCase    		=  random.randint(0  ,							len(lowerCamelCase__      ) - 1      )
						lowerCamelCase		,		lowerCamelCase    		=  data[b], data[a]
			return data


if __name__ == "__main__":
		UpperCAmelCase   :    str     =		[0, 1, 2, 3, 4, 5, 6, 7]
		UpperCAmelCase   :    Union[str, Any]     =		["python", "says", "hello", "!"]
		print("Fisher-Yates Shuffle:")
		print("List", integers, strings)
		print("FY Shuffle", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))

