

'''simple docstring'''



def 						__lowerCamelCase	(       __snake_case					:		list[int],		__snake_case					:		int	)	->							Any:






						"""simple docstring"""





						A__					:       List[str]     =len(__snake_case	)
						A__					:       Dict     =[[False] * (required_sum + 1) for _ in range(arr_len + 1	)]

						# for each arr value, a sum of zero(0) can be formed by not taking any element
						# hence True/1
						for i in range(arr_len + 1	):
												A__					:       Optional[int]     =True

						# sum is not zero and set is empty then false
						for i in range(1,		required_sum + 1	):
												A__					:       Optional[Any]     =False

						for i in range(1,		arr_len + 1	):
												for j in range(1,		required_sum + 1	):
																		if arr[i - 1] > j:
																								A__					:       Tuple     =subset[i - 1][j]
																		if arr[i - 1] <= j:
																								A__					:       Tuple     =subset[i - 1][j] or subset[i - 1][j - arr[i - 1]]

						return subset[arr_len][required_sum]


if __name__ == "__main__":
		import doctest

		doctest.testmod()




'''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


__snake_case			:     List[str]										=      get_tests_dir('fixtures/test_sentencepiece.model')



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



			'''simple docstring'''






			__snake_case        =	XLMRobertaTokenizer
			__snake_case        =	XLMRobertaTokenizerFast
			__snake_case        =	True
			__snake_case        =	True


			def lowercase__						(				self	:						Any			)      ->		Union[str, Any]:





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

									# We have a SentencePiece fixture for testing
									A__					:       Any     =XLMRobertaTokenizer(lowerCAmelCase_		,      keep_accents=lowerCAmelCase_			)
									tokenizer.save_pretrained(self.tmpdirname			)


			def lowercase__						(				self	:						Optional[Any]			)      ->		Tuple:





									'''simple docstring'''
									A__					:       Union[str, Any]     ="""<pad>"""
									A__					:       Any     =1

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


			def lowercase__						(				self	:						List[Any]			)      ->		Any:





									'''simple docstring'''
									A__					:       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_			)		,      10_02			)


			def lowercase__						(				self	:						Optional[int]			)      ->		Optional[Any]:





									'''simple docstring'''
									self.assertEqual(self.get_tokenizer().vocab_size		,      10_02			)


			def lowercase__						(				self	:						Tuple			)      ->		Any:





									'''simple docstring'''
									A__					:       List[Any]     =XLMRobertaTokenizer(lowerCAmelCase_		,      keep_accents=lowerCAmelCase_			)

									A__					:       Tuple     =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__					:       Optional[int]     =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__					:       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, 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__					:       Union[str, Any]     =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 lowercase__						(				self	:						List[Any]			)      ->		Optional[int]:





									'''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__					:       Dict     =(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__					:       Union[str, Any]     =self.tokenizer_class.from_pretrained(lowerCAmelCase_		,      **lowerCAmelCase_			)

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

																					A__					:       Union[str, Any]     =tokenizer_r.save_pretrained(lowerCAmelCase_			)
																					A__					:       Union[str, 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[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
																					A__					:       Any     =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_			)			)
																											# 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__					:       List[str]     =tempfile.mkdtemp()

																					A__					:       List[str]     =tokenizer_r.save_pretrained(lowerCAmelCase_		,      legacy_format=lowerCAmelCase_			)
																					A__					:       List[Any]     =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__					:       str     =tokenizer_r.from_pretrained(lowerCAmelCase_			)
																					A__					:       List[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__					:       List[str]     =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__					:       Optional[int]     =tokenizer_r.from_pretrained(lowerCAmelCase_			)
																					A__					:       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_			)			)

																					shutil.rmtree(lowerCAmelCase_			)


			@cached_property
			def lowercase__						(				self	:						Optional[Any]			)      ->		List[str]:





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


			def lowercase__						(				self	:						Tuple			)      ->		Tuple:





									'''simple docstring'''
									with tempfile.NamedTemporaryFile() as f:
															shutil.copyfile(lowerCAmelCase_		,      f.name			)
															A__					:       Dict     =XLMRobertaTokenizer(f.name		,      keep_accents=lowerCAmelCase_			)
															A__					:       Optional[Any]     =pickle.dumps(lowerCAmelCase_			)
									pickle.loads(lowerCAmelCase_			)


			def lowercase__						(				self	:						Optional[Any]			)      ->		List[Any]:





									'''simple docstring'''
									if not self.test_rust_tokenizer:
															return

									A__					:       Any     =self.get_tokenizer()
									A__					:       Any     =self.get_rust_tokenizer()

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

									A__					:       List[str]     =tokenizer.tokenize(lowerCAmelCase_			)
									A__					:       int     =rust_tokenizer.tokenize(lowerCAmelCase_			)
									self.assertListEqual(lowerCAmelCase_		,      lowerCAmelCase_			)

									A__					:       str     =tokenizer.encode(lowerCAmelCase_		,      add_special_tokens=lowerCAmelCase_			)
									A__					:       Dict     =rust_tokenizer.encode(lowerCAmelCase_		,      add_special_tokens=lowerCAmelCase_			)
									self.assertListEqual(lowerCAmelCase_		,      lowerCAmelCase_			)

									A__					:       Union[str, Any]     =self.get_rust_tokenizer()
									A__					:       Union[str, Any]     =tokenizer.encode(lowerCAmelCase_			)
									A__					:       Optional[Any]     =rust_tokenizer.encode(lowerCAmelCase_			)
									self.assertListEqual(lowerCAmelCase_		,      lowerCAmelCase_			)


			@slow
			def lowercase__						(				self	:						Dict			)      ->		int:





									'''simple docstring'''
									A__					:       Optional[Any]     ="""Hello World!"""
									A__					:       Optional[Any]     =[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 lowercase__						(				self	:						List[Any]			)      ->		int:





									'''simple docstring'''
									A__					:       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"""
									)
									A__					:       Optional[Any]     =[
									    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 lowercase__						(				self	:						int			)      ->		Optional[Any]:





									'''simple docstring'''
									# fmt: off
									A__					:       List[Any]     ={"""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"""		,      )

