




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   :						Any				=			get_tests_dir('''fixtures/test_sentencepiece.model''')


@require_sentencepiece
@require_tokenizers
class    lowerCamelCase (		_UpperCamelCase				,unittest.TestCase						):






			'''simple docstring'''





			UpperCamelCase__								=XLMRobertaTokenizer
			UpperCamelCase__								=XLMRobertaTokenizerFast
			UpperCamelCase__								=True
			UpperCamelCase__								=True

			def 							UpperCAmelCase__       ( self			:   Optional[int]  )						->   List[str]:
								super().setUp()

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

			def 							UpperCAmelCase__       ( self			:   Union[str, Any]  )						->   Tuple:
								__magic_name__							:	Any    							=							'''<pad>'''
								__magic_name__							:	Optional[int]    							=							1

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

			def 							UpperCAmelCase__       ( self			:   Dict  )						->   List[str]:
								__magic_name__							:	Dict    							=							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(_UpperCAmelCase  )       ,						1002  )

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

			def 							UpperCAmelCase__       ( self			:   Optional[int]  )						->   List[str]:
								__magic_name__							:	Any    							=							XLMRobertaTokenizer(_UpperCAmelCase       ,						keep_accents=_UpperCAmelCase  )

								__magic_name__							:	Any    							=							tokenizer.tokenize('''This is a test'''  )
								self.assertListEqual(_UpperCAmelCase       ,						['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']  )

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

								__magic_name__							:	Dict    							=							tokenizer.tokenize('''I was born in 92000, and this is falsé.'''  )
								self.assertListEqual(
								    _UpperCAmelCase       ,						[
								        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''',
								        '''.''',
								    ]       ,						)
								__magic_name__							:	Dict    							=							tokenizer.convert_tokens_to_ids(_UpperCAmelCase  )
								self.assertListEqual(
								    _UpperCAmelCase       ,						[
								        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 ^
								    ]       ,						)

								__magic_name__							:	Dict    							=							tokenizer.convert_ids_to_tokens(_UpperCAmelCase  )
								self.assertListEqual(
								    _UpperCAmelCase       ,						[
								        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			:   int  )						->   Any:
								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

								__magic_name__							:	Tuple    							=							(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})'''  ):
																		__magic_name__							:	Any    							=							self.rust_tokenizer_class.from_pretrained(_UpperCAmelCase       ,						**_UpperCAmelCase  )
																		__magic_name__							:	Optional[int]    							=							self.tokenizer_class.from_pretrained(_UpperCAmelCase       ,						**_UpperCAmelCase  )

																		__magic_name__							:	Union[str, Any]    							=							tempfile.mkdtemp()

																		__magic_name__							:	Optional[int]    							=							tokenizer_r.save_pretrained(_UpperCAmelCase  )
																		__magic_name__							:	Tuple    							=							tokenizer_p.save_pretrained(_UpperCAmelCase  )

																		# 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  )  )
																		__magic_name__							:	Tuple    							=							tuple(f for f in tokenizer_r_files if '''tokenizer.json''' not in f  )
																		self.assertSequenceEqual(_UpperCAmelCase       ,						_UpperCAmelCase  )

																		# Checks everything loads correctly in the same way
																		__magic_name__							:	Tuple    							=							tokenizer_r.from_pretrained(_UpperCAmelCase  )
																		__magic_name__							:	Union[str, Any]    							=							tokenizer_p.from_pretrained(_UpperCAmelCase  )

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

																		shutil.rmtree(_UpperCAmelCase  )

																		# Save tokenizer rust, legacy_format=True
																		__magic_name__							:	Tuple    							=							tempfile.mkdtemp()

																		__magic_name__							:	Dict    							=							tokenizer_r.save_pretrained(_UpperCAmelCase       ,						legacy_format=_UpperCAmelCase  )
																		__magic_name__							:	Any    							=							tokenizer_p.save_pretrained(_UpperCAmelCase  )

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

																		# Checks everything loads correctly in the same way
																		__magic_name__							:	int    							=							tokenizer_r.from_pretrained(_UpperCAmelCase  )
																		__magic_name__							:	int    							=							tokenizer_p.from_pretrained(_UpperCAmelCase  )

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

																		shutil.rmtree(_UpperCAmelCase  )

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

																		__magic_name__							:	Union[str, Any]    							=							tokenizer_r.save_pretrained(_UpperCAmelCase       ,						legacy_format=_UpperCAmelCase  )
																		__magic_name__							:	int    							=							tokenizer_p.save_pretrained(_UpperCAmelCase  )

																		# 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
																		__magic_name__							:	List[Any]    							=							tokenizer_r.from_pretrained(_UpperCAmelCase  )
																		__magic_name__							:	List[str]    							=							tokenizer_p.from_pretrained(_UpperCAmelCase  )

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

																		shutil.rmtree(_UpperCAmelCase  )

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

			def 							UpperCAmelCase__       ( self			:   int  )						->   str:
								with tempfile.NamedTemporaryFile() as f:
													shutil.copyfile(_UpperCAmelCase       ,						f.name  )
													__magic_name__							:	int    							=							XLMRobertaTokenizer(f.name       ,						keep_accents=_UpperCAmelCase  )
													__magic_name__							:	List[Any]    							=							pickle.dumps(_UpperCAmelCase  )
								pickle.loads(_UpperCAmelCase  )

			def 							UpperCAmelCase__       ( self			:   Tuple  )						->   Tuple:
								if not self.test_rust_tokenizer:
													return

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

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

								__magic_name__							:	Optional[int]    							=							tokenizer.tokenize(_UpperCAmelCase  )
								__magic_name__							:	str    							=							rust_tokenizer.tokenize(_UpperCAmelCase  )
								self.assertListEqual(_UpperCAmelCase       ,						_UpperCAmelCase  )

								__magic_name__							:	str    							=							tokenizer.encode(_UpperCAmelCase       ,						add_special_tokens=_UpperCAmelCase  )
								__magic_name__							:	Tuple    							=							rust_tokenizer.encode(_UpperCAmelCase       ,						add_special_tokens=_UpperCAmelCase  )
								self.assertListEqual(_UpperCAmelCase       ,						_UpperCAmelCase  )

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

			@slow
			def 							UpperCAmelCase__       ( self			:   Any  )						->   str:
								__magic_name__							:	Dict    							=							'''Hello World!'''
								__magic_name__							:	str    							=							[0, 35378, 6661, 38, 2]
								# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
								# xlmr.eval()
								# xlmr.encode(symbols)

								self.assertListEqual(_UpperCAmelCase       ,						self.big_tokenizer.encode(_UpperCAmelCase  )  )

			@slow
			def 							UpperCAmelCase__       ( self			:   Optional[Any]  )						->   int:
								__magic_name__							:	Optional[int]    							=							(
								    '''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'''
								)
								__magic_name__							:	Optional[Any]    							=							[
								    0,
								    3293,
								    83,
								    10,
								    4552,
								    4989,
								    7986,
								    678,
								    10,
								    5915,
								    111,
								    179459,
								    124850,
								    4,
								    6044,
								    237,
								    12,
								    6,
								    5,
								    6,
								    4,
								    6780,
								    705,
								    15,
								    1388,
								    44,
								    378,
								    10114,
								    711,
								    152,
								    20,
								    6,
								    5,
								    22376,
								    642,
								    1221,
								    15190,
								    34153,
								    450,
								    5608,
								    959,
								    1119,
								    57702,
								    136,
								    186,
								    47,
								    1098,
								    29367,
								    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,
								    50901,
								    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(_UpperCAmelCase       ,						self.big_tokenizer.encode(_UpperCAmelCase  )  )


			@slow
			def 							UpperCAmelCase__       ( self			:   Dict  )						->   Optional[Any]:
								# fmt: off
								__magic_name__							:	List[str]    							=							{'''input_ids''': [[0, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 5428, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 12399, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 122009, 115774, 23, 805, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [0, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 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, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 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=_UpperCAmelCase       ,						model_name='''xlm-roberta-base'''       ,						revision='''d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'''       ,						)









import functools







def 		lowercase__   (		__A:	list[int]							,__A:	list[int]				):





					'''simple docstring'''






					if not isinstance(__A							,__A				) or not all(isinstance(__A							,__A				) for day in days				):
										raise ValueError('''The parameter days should be a list of integers'''				)

					if len(__A				) != 3 or not all(isinstance(__A							,__A				) for cost in costs				):
										raise ValueError('''The parameter costs should be a list of three integers'''				)

					if len(__A				) == 0:
										return 0

					if min(__A				) <= 0:
										raise ValueError('''All days elements should be greater than 0'''				)

					if max(__A				) >= 3_6_6:
										raise ValueError('''All days elements should be less than 366'''				)

					__magic_name__							:	Tuple    							=							set(__A				)

					@functools.cache
					def dynamic_programming(__A:	int				) -> int:
										if index > 3_6_5:
															return 0

										if index not in days_set:
															return dynamic_programming(index + 1				)

										return min(
										    costs[0] + dynamic_programming(index + 1				)							,costs[1] + dynamic_programming(index + 7				)							,costs[2] + dynamic_programming(index + 3_0				)							,)

					return dynamic_programming(1				)


if __name__ == "__main__":
	import doctest

	doctest.testmod()



