
import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE           =  """▁"""

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

@require_sentencepiece
@require_tokenizers
class 	lowerCamelCase_    ( __a						,unittest.TestCase						):






						'''simple docstring'''
						a__   =  BigBirdTokenizer
						a__   =  BigBirdTokenizerFast
						a__   =  True
						a__   =  True







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[Any] )      ->				int:
									super().setUp()

									A							:					Union[str, Any]              =						self.tokenizer_class(a_	,	keep_accents=a_ )
									tokenizer.save_pretrained(self.tmpdirname )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			Any )      ->				Union[str, Any]:
									A							:					Any              =						"""<s>"""
									A							:					List[Any]              =						1

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







						def 			SCREAMING_SNAKE_CASE__		(	self      :			List[str] )      ->				Dict:
									A							:					Tuple              =						list(self.get_tokenizer().get_vocab().keys() )

									self.assertEqual(vocab_keys[0]	,	"<unk>" )
									self.assertEqual(vocab_keys[1]	,	"<s>" )
									self.assertEqual(vocab_keys[-1]	,	"[MASK]" )
									self.assertEqual(len(a_ )	,	10_04 )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			int )      ->				Optional[int]:
									self.assertEqual(self.get_tokenizer().vocab_size	,	10_00 )







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



									if not self.test_rust_tokenizer:
												return

									A							:					Optional[int]              =						self.get_tokenizer()
									A							:					Any              =						self.get_rust_tokenizer()

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

									A							:					Tuple              =						tokenizer.tokenize(a_ )
									A							:					Tuple              =						rust_tokenizer.tokenize(a_ )
									self.assertListEqual(a_	,	a_ )

									A							:					List[str]              =						tokenizer.encode(a_	,	add_special_tokens=a_ )
									A							:					Optional[Any]              =						rust_tokenizer.encode(a_	,	add_special_tokens=a_ )
									self.assertListEqual(a_	,	a_ )

									A							:					Tuple              =						self.get_rust_tokenizer()
									A							:					Union[str, Any]              =						tokenizer.encode(a_ )
									A							:					Optional[Any]              =						rust_tokenizer.encode(a_ )
									self.assertListEqual(a_	,	a_ )







						def 			SCREAMING_SNAKE_CASE__		(	self      :			str )      ->				Any:
									A							:					int              =						BigBirdTokenizer(a_	,	keep_accents=a_ )

									A							:					int              =						tokenizer.tokenize("This is a test" )
									self.assertListEqual(a_	,	["▁This", "▁is", "▁a", "▁t", "est"] )

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(a_ )	,	[2_85, 46, 10, 1_70, 3_82]	,	)

									A							:					Optional[Any]              =						tokenizer.tokenize("I was born in 92000, and this is falsé." )
									self.assertListEqual(
									    a_	,	[
									        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							:					Union[str, Any]              =						tokenizer.convert_tokens_to_ids(a_ )
									self.assertListEqual(
									    a_	,	[8, 21, 84, 55, 24, 19, 7, 0, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 0, 4]	,	)

									A							:					Optional[Any]              =						tokenizer.convert_ids_to_tokens(a_ )
									self.assertListEqual(
									    a_	,	[
									        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>",
									        ".",
									    ]	,	)







						@cached_property
						def 			SCREAMING_SNAKE_CASE__		(	self      :			str )      ->				int:
									return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base" )







						@slow
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any] )      ->				int:
									A							:					Union[str, Any]              =						"""Hello World!"""
									A							:					List[str]              =						[65, 1_85_36, 22_60, 1_01, 66]

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







						@slow
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Dict )      ->				Optional[Any]:
									A							:					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"""
									)
									# fmt: off
									A							:					Union[str, Any]              =						[65, 8_71, 4_19, 3_58, 9_46, 9_91, 25_21, 4_52, 3_58, 13_57, 3_87, 77_51, 35_36, 1_12, 9_85, 4_56, 1_26, 8_65, 9_38, 54_00, 57_34, 4_58, 13_68, 4_67, 7_86, 24_62, 52_46, 11_59, 6_33, 8_65, 45_19, 4_57, 5_82, 8_52, 25_57, 4_27, 9_16, 5_08, 4_05, 3_43_24, 4_97, 3_91, 4_08, 1_13_42, 12_44, 3_85, 1_00, 9_38, 9_85, 4_56, 5_74, 3_62, 1_25_97, 32_00, 31_29, 11_72, 66]  # noqa: E231
									# fmt: on
									self.assertListEqual(a_	,	self.big_tokenizer.encode(a_ ) )







						@require_torch
						@slow
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any] )      ->				int:
									import torch

									from transformers import BigBirdConfig, BigBirdModel

									# Build sequence
									A							:					int              =						list(self.big_tokenizer.get_vocab().keys() )[:10]
									A							:					List[Any]              =						""" """.join(a_ )
									A							:					Dict              =						self.big_tokenizer.encode_plus(a_	,	return_tensors="pt"	,	return_token_type_ids=a_ )
									A							:					List[str]              =						self.big_tokenizer.batch_encode_plus(
									    [sequence + " " + sequence]	,	return_tensors="pt"	,	return_token_type_ids=a_ )

									A							:					Any              =						BigBirdConfig(attention_type="original_full" )
									A							:					str              =						BigBirdModel(a_ )

									assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

									with torch.no_grad():
												model(**a_ )
												model(**a_ )







						@slow
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Optional[Any] )      ->				List[Any]:
									A							:					Optional[Any]              =						BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base" )
									A							:					Optional[int]              =						tokenizer.decode(tokenizer("Paris is the [MASK]." ).input_ids )

									self.assertTrue(decoded_text == "[CLS] Paris is the[MASK].[SEP]" )







						@slow
						def 			SCREAMING_SNAKE_CASE__		(	self      :			Union[str, Any] )      ->				Tuple:
									A							:					Any              =						{"""input_ids""": [[65, 3_92_86, 4_58, 3_63_35, 20_01, 4_56, 1_30_73, 1_32_66, 4_55, 1_13, 77_46, 17_41, 1_11_57, 3_91, 1_30_73, 1_32_66, 4_55, 1_13, 39_67, 3_54_12, 1_13, 49_36, 1_09, 38_70, 23_77, 1_13, 3_00_84, 4_57_20, 4_58, 1_34, 1_74_96, 1_12, 5_03, 1_16_72, 1_13, 1_18, 1_12, 56_65, 1_33_47, 3_86_87, 1_12, 14_96, 3_13_89, 1_12, 32_68, 4_72_64, 1_34, 9_62, 1_12, 1_63_77, 80_35, 2_31_30, 4_30, 1_21_69, 1_55_18, 2_85_92, 4_58, 1_46, 4_16_97, 1_09, 3_91, 1_21_69, 1_55_18, 1_66_89, 4_58, 1_46, 4_13_58, 1_09, 4_52, 7_26, 40_34, 1_11, 7_63, 3_54_12, 50_82, 3_88, 19_03, 1_11, 90_51, 3_91, 28_70, 4_89_18, 19_00, 11_23, 5_50, 9_98, 1_12, 95_86, 1_59_85, 4_55, 3_91, 4_10, 2_29_55, 3_76_36, 1_14, 66], [65, 4_48, 1_74_96, 4_19, 36_63, 3_85, 7_63, 1_13, 2_75_33, 28_70, 32_83, 1_30_43, 16_39, 2_47_13, 5_23, 6_56, 2_40_13, 1_85_50, 25_21, 5_17, 2_70_14, 2_12_44, 4_20, 12_12, 14_65, 3_91, 9_27, 48_33, 3_88, 5_78, 1_17_86, 1_14, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 4_84, 21_69, 76_87, 2_19_32, 1_81_46, 7_26, 3_63, 1_70_32, 33_91, 1_14, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=a_	,	model_name="google/bigbird-roberta-base"	,	revision="215c99f1600e06f83acce68422f2035b2b5c3510"	,	)




from collections.abc import Sequence




def 	UpperCAmelCase   (						_lowerCamelCase = None    ):
			if nums is None or not nums:
						raise ValueError("Input sequence should not be empty"    )

			A							:					Dict              =						nums[0]
			for i in range(1 ,    len(_lowerCamelCase    )    ):
						A							:					Tuple              =						nums[i]
						A							:					List[Any]              =						max(_lowerCamelCase ,    ans + num ,    _lowerCamelCase    )

			return ans


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							# Try on a sample input from the user
							__SCREAMING_SNAKE_CASE           =  int(input("""Enter number of elements : """).strip())
							__SCREAMING_SNAKE_CASE           =  list(map(int, input("""\nEnter the numbers : """).strip().split()))[:n]
							print(max_subsequence_sum(array))