



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






@require_sentencepiece
@require_tokenizers
class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__			,      unittest.TestCase					):
							__lowerCamelCase	:	Optional[int]    =XLMRobertaTokenizer
							__lowerCamelCase	:	Union[str, Any]    =XLMRobertaTokenizerFast
							__lowerCamelCase	:	Optional[int]    =True
							__lowerCamelCase	:	int    =True





							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											super().setUp()

											# We have a SentencePiece fixture for testing
											__a       =		XLMRobertaTokenizer(__lowercase      ,				keep_accents=__lowercase	)
											tokenizer.save_pretrained(self.tmpdirname	)





							def 						UpperCamelCase_					(   self		:		Union[str, Any]	):

											'''simple docstring'''
											__a       =		"""<pad>"""
											__a       =		1

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





							def 						UpperCamelCase_					(   self		:		Tuple	):

											'''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(__lowercase	)      ,				1002	)





							def 						UpperCamelCase_					(   self		:		int	):

											'''simple docstring'''
											self.assertEqual(self.get_tokenizer().vocab_size      ,				1002	)





							def 						UpperCamelCase_					(   self		:		int	):

											'''simple docstring'''
											__a       =		XLMRobertaTokenizer(__lowercase      ,				keep_accents=__lowercase	)

											__a       =		tokenizer.tokenize("""This is a test"""	)
											self.assertListEqual(__lowercase      ,				["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]	)

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

											__a       =		tokenizer.tokenize("""I was born in 92000, and this is falsé."""	)
											self.assertListEqual(
											    __lowercase      ,				[
											        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(__lowercase	)
											self.assertListEqual(
											    __lowercase      ,				[
											        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       =		tokenizer.convert_ids_to_tokens(__lowercase	)
											self.assertListEqual(
											    __lowercase      ,				[
											        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		:		Tuple	):

											'''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(__lowercase      ,				**__lowercase	)
																			__a       =		self.tokenizer_class.from_pretrained(__lowercase      ,				**__lowercase	)

																			__a       =		tempfile.mkdtemp()

																			__a       =		tokenizer_r.save_pretrained(__lowercase	)
																			__a       =		tokenizer_p.save_pretrained(__lowercase	)

																			# 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(__lowercase      ,				__lowercase	)

																			# Checks everything loads correctly in the same way
																			__a       =		tokenizer_r.from_pretrained(__lowercase	)
																			__a       =		tokenizer_p.from_pretrained(__lowercase	)

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

																			shutil.rmtree(__lowercase	)

																			# Save tokenizer rust, legacy_format=True
																			__a       =		tempfile.mkdtemp()

																			__a       =		tokenizer_r.save_pretrained(__lowercase      ,				legacy_format=__lowercase	)
																			__a       =		tokenizer_p.save_pretrained(__lowercase	)

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

																			# Checks everything loads correctly in the same way
																			__a       =		tokenizer_r.from_pretrained(__lowercase	)
																			__a       =		tokenizer_p.from_pretrained(__lowercase	)

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

																			shutil.rmtree(__lowercase	)

																			# Save tokenizer rust, legacy_format=False
																			__a       =		tempfile.mkdtemp()

																			__a       =		tokenizer_r.save_pretrained(__lowercase      ,				legacy_format=__lowercase	)
																			__a       =		tokenizer_p.save_pretrained(__lowercase	)

																			# 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(__lowercase	)
																			__a       =		tokenizer_p.from_pretrained(__lowercase	)

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

																			shutil.rmtree(__lowercase	)





							@cached_property
							def 						UpperCamelCase_					(   self		:		List[str]	):

											'''simple docstring'''
											return XLMRobertaTokenizer.from_pretrained("""xlm-roberta-base"""	)





							def 						UpperCamelCase_					(   self		:		Optional[Any]	):

											'''simple docstring'''
											with tempfile.NamedTemporaryFile() as f:
															shutil.copyfile(__lowercase      ,				f.name	)
															__a       =		XLMRobertaTokenizer(f.name      ,				keep_accents=__lowercase	)
															__a       =		pickle.dumps(__lowercase	)
											pickle.loads(__lowercase	)





							def 						UpperCamelCase_					(   self		:		str	):

											'''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(__lowercase	)
											__a       =		rust_tokenizer.tokenize(__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)

											__a       =		tokenizer.encode(__lowercase      ,				add_special_tokens=__lowercase	)
											__a       =		rust_tokenizer.encode(__lowercase      ,				add_special_tokens=__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)

											__a       =		self.get_rust_tokenizer()
											__a       =		tokenizer.encode(__lowercase	)
											__a       =		rust_tokenizer.encode(__lowercase	)
											self.assertListEqual(__lowercase      ,				__lowercase	)





							@slow
							def 						UpperCamelCase_					(   self		:		Dict	):

											'''simple docstring'''
											__a       =		"""Hello World!"""
											__a       =		[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(__lowercase      ,				self.big_tokenizer.encode(__lowercase	)	)





							@slow
							def 						UpperCamelCase_					(   self		:		List[str]	):

											'''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,
											    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(__lowercase      ,				self.big_tokenizer.encode(__lowercase	)	)







							@slow
							def 						UpperCamelCase_					(   self		:		Tuple	):

											'''simple docstring'''
											__a       =		{"""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=__lowercase      ,				model_name="""xlm-roberta-base"""      ,				revision="""d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"""      ,				)





def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			list				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				if index == number_of_items:
								return 0
				__a       =		0
				__a       =		0
				__a       =		knapsack(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     index + 1    )
				if weights[index] <= max_weight:
								__a       =		values[index] + knapsack(
								    _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE				,     max_weight - weights[index]				,     index + 1    )
				return max(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
						import doctest

						doctest.testmod()
