

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


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

@require_sentencepiece
@require_tokenizers
class 				__UpperCamelCase				(					__lowerCAmelCase  ,						unittest.TestCase			):
	_lowercase  :   Dict       				=  XLMRobertaTokenizer
	_lowercase  :   List[str]       				=  XLMRobertaTokenizerFast
	_lowercase  :   Union[str, Any]       				=  True
	_lowercase  :   Tuple       				=  True







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						super().setUp()

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







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    """<pad>"""
						__magic_name__							=    1

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







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						__magic_name__							=    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      )  , 10_02      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						self.assertEqual(self.get_tokenizer().vocab_size  , 10_02      )







	def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    XLMRobertaTokenizer(_UpperCamelCase  , keep_accents=_UpperCamelCase      )

						__magic_name__							=    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 [2_85, 46, 10, 1_70, 3_82]]  , )

						__magic_name__							=    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__							=    tokenizer.convert_tokens_to_ids(_UpperCamelCase      )
						self.assertListEqual(
						    _UpperCamelCase  , [
						        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 ^
						    ]  , )

						__magic_name__							=    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 	_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

						__magic_name__							=    (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__							=    self.rust_tokenizer_class.from_pretrained(_UpperCamelCase  , **_UpperCamelCase      )
																__magic_name__							=    self.tokenizer_class.from_pretrained(_UpperCamelCase  , **_UpperCamelCase      )

																__magic_name__							=    tempfile.mkdtemp()

																__magic_name__							=    tokenizer_r.save_pretrained(_UpperCamelCase      )
																__magic_name__							=    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(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__							=    tokenizer_r.from_pretrained(_UpperCamelCase      )
																__magic_name__							=    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__							=    tempfile.mkdtemp()

																__magic_name__							=    tokenizer_r.save_pretrained(_UpperCamelCase  , legacy_format=_UpperCamelCase      )
																__magic_name__							=    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__							=    tokenizer_r.from_pretrained(_UpperCamelCase      )
																__magic_name__							=    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__							=    tempfile.mkdtemp()

																__magic_name__							=    tokenizer_r.save_pretrained(_UpperCamelCase  , legacy_format=_UpperCamelCase      )
																__magic_name__							=    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__							=    tokenizer_r.from_pretrained(_UpperCamelCase      )
																__magic_name__							=    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 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

						'''simple docstring'''





						return XLMRobertaTokenizer.from_pretrained('xlm-roberta-base'      )







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						with tempfile.NamedTemporaryFile() as f:
											shutil.copyfile(_UpperCamelCase  , f.name      )
											__magic_name__							=    XLMRobertaTokenizer(f.name  , keep_accents=_UpperCamelCase      )
											__magic_name__							=    pickle.dumps(_UpperCamelCase      )
						pickle.loads(_UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: int      ):

						'''simple docstring'''





						if not self.test_rust_tokenizer:
											return

						__magic_name__							=    self.get_tokenizer()
						__magic_name__							=    self.get_rust_tokenizer()

						__magic_name__							=    """I was born in 92000, and this is falsé."""

						__magic_name__							=    tokenizer.tokenize(_UpperCamelCase      )
						__magic_name__							=    rust_tokenizer.tokenize(_UpperCamelCase      )
						self.assertListEqual(_UpperCamelCase  , _UpperCamelCase      )

						__magic_name__							=    tokenizer.encode(_UpperCamelCase  , add_special_tokens=_UpperCamelCase      )
						__magic_name__							=    rust_tokenizer.encode(_UpperCamelCase  , add_special_tokens=_UpperCamelCase      )
						self.assertListEqual(_UpperCamelCase  , _UpperCamelCase      )

						__magic_name__							=    self.get_rust_tokenizer()
						__magic_name__							=    tokenizer.encode(_UpperCamelCase      )
						__magic_name__							=    rust_tokenizer.encode(_UpperCamelCase      )
						self.assertListEqual(_UpperCamelCase  , _UpperCamelCase      )







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[Any]      ):

						'''simple docstring'''





						__magic_name__							=    """Hello World!"""
						__magic_name__							=    [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(_UpperCamelCase  , self.big_tokenizer.encode(_UpperCamelCase      )      )







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: Optional[int]      ):

						'''simple docstring'''





						__magic_name__							=    (
						    """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__							=    [
						    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(_UpperCamelCase  , self.big_tokenizer.encode(_UpperCamelCase      )      )







	@slow
	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple      ):

						'''simple docstring'''





						__magic_name__							=    {"""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=_UpperCamelCase  , model_name='xlm-roberta-base'  , revision='d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3'  , )







import requests
from bsa import BeautifulSoup




def 					_lowercase     (				a_				:					str = "https://www.worldometers.info/coronavirus"				)				->	dict:




					'''simple docstring'''







					__magic_name__							=    BeautifulSoup(requests.get(a_				).text					,'html.parser'				)
					__magic_name__							=    soup.findAll('h1'				)
					__magic_name__							=    soup.findAll('div'					,{'class': 'maincounter-number'}				)
					keys += soup.findAll('span'					,{'class': 'panel-title'}				)
					values += soup.findAll('div'					,{'class': 'number-table-main'}				)
					return {key.text.strip(): value.text.strip() for key, value in zip(a_					,a_				)}


if __name__ == "__main__":
						print("\033[1m" + "COVID-19 Status of the World" + "\033[0m\n")
						for key, value in world_covidaa_stats().items():
												print(f'''{key}\n{value}\n''')




