





import shutil
import tempfile
import unittest

from transformers import (
    SPIECE_UNDERLINE,
    AddedToken,
    BatchEncoding,
    NllbTokenizer,
    NllbTokenizerFast,
    is_torch_available,
)
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


_UpperCAmelCase		:       Optional[int]						    =	get_tests_dir("""fixtures/test_sentencepiece.model""")


if is_torch_available():
					from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

_UpperCAmelCase		:       Optional[Any]						    =	25_6047
_UpperCAmelCase		:       List[Any]						    =	25_6145







@require_sentencepiece
@require_tokenizers
class 			lowercase    (	lowerCamelCase__     ,  unittest.TestCase      ):
				__SCREAMING_SNAKE_CASE :			List[str]	      =      NllbTokenizer
				__SCREAMING_SNAKE_CASE :			Tuple	      =      NllbTokenizerFast
				__SCREAMING_SNAKE_CASE :			Optional[Any]	      =      True
				__SCREAMING_SNAKE_CASE :			List[Any]	      =      True
				__SCREAMING_SNAKE_CASE :			str	      =      {}




				def    a							( self	):
											super().setUp()

											# We have a SentencePiece fixture for testing
											snake_case_          =   NllbTokenizer(__lowerCamelCase				,       keep_accents=__lowerCamelCase	)
											tokenizer.save_pretrained(self.tmpdirname	)




				def    a							( self	):
											snake_case_          =   NllbTokenizer(__lowerCamelCase				,       keep_accents=__lowerCamelCase	)

											snake_case_          =   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 [285, 46, 10, 170, 382]]				,       )

											snake_case_          =   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',
											        '.',
											    ]				,       )
											snake_case_          =   tokenizer.convert_tokens_to_ids(__lowerCamelCase	)
											self.assertListEqual(
											    __lowerCamelCase				,       [
											        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]
											    ]				,       )

											snake_case_          =   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    a							( self	):
											snake_case_          =   (self.rust_tokenizer_class, '''hf-internal-testing/tiny-random-nllb''', {})
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
																									snake_case_          =   self.rust_tokenizer_class.from_pretrained(__lowerCamelCase				,       **__lowerCamelCase	)
																									snake_case_          =   self.tokenizer_class.from_pretrained(__lowerCamelCase				,       **__lowerCamelCase	)

																									snake_case_          =   tempfile.mkdtemp()

																									snake_case_          =   tokenizer_r.save_pretrained(__lowerCamelCase	)
																									snake_case_          =   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	)	)
																									snake_case_          =   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
																									snake_case_          =   tokenizer_r.from_pretrained(__lowerCamelCase	)
																									snake_case_          =   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=True
																									snake_case_          =   tempfile.mkdtemp()

																									snake_case_          =   tokenizer_r.save_pretrained(__lowerCamelCase				,       legacy_format=__lowerCamelCase	)
																									snake_case_          =   tokenizer_p.save_pretrained(__lowerCamelCase	)

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

																									# Checks everything loads correctly in the same way
																									snake_case_          =   tokenizer_r.from_pretrained(__lowerCamelCase	)
																									snake_case_          =   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
																									snake_case_          =   tempfile.mkdtemp()

																									snake_case_          =   tokenizer_r.save_pretrained(__lowerCamelCase				,       legacy_format=__lowerCamelCase	)
																									snake_case_          =   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
																									snake_case_          =   tokenizer_r.from_pretrained(__lowerCamelCase	)
																									snake_case_          =   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	)




				@require_torch
				def    a							( self	):






											if not self.test_seqaseq:
																		return

											snake_case_          =   self.get_tokenizers()
											for tokenizer in tokenizers:
																		with self.subTest(F'''{tokenizer.__class__.__name__}'''	):
																									# Longer text that will definitely require truncation.
																									snake_case_          =   [
																									    ''' UN Chief Says There Is No Military Solution in Syria''',
																									    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for'''
																									    ''' Syria is that \'there is no military solution\' to the nearly five-year conflict and more weapons'''
																									    ''' will only worsen the violence and misery for millions of people.''',
																									]
																									snake_case_          =   [
																									    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
																									    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al'''
																									    ''' Rusiei pentru Siria este că "nu există o soluţie militară" la conflictul de aproape cinci ani şi'''
																									    ''' că noi arme nu vor face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
																									]
																									try:
																																snake_case_          =   tokenizer.prepare_seqaseq_batch(
																																    src_texts=__lowerCamelCase				,       tgt_texts=__lowerCamelCase				,       max_length=3				,       max_target_length=10				,       return_tensors='pt'				,       src_lang='eng_Latn'				,       tgt_lang='ron_Latn'				,       )
																									except NotImplementedError:
																																return
																									self.assertEqual(batch.input_ids.shape[1]				,       3	)
																									self.assertEqual(batch.labels.shape[1]				,       10	)
																									# max_target_length will default to max_length if not specified
																									snake_case_          =   tokenizer.prepare_seqaseq_batch(
																									    __lowerCamelCase				,       tgt_texts=__lowerCamelCase				,       max_length=3				,       return_tensors='pt'	)
																									self.assertEqual(batch.input_ids.shape[1]				,       3	)
																									self.assertEqual(batch.labels.shape[1]				,       3	)

																									snake_case_          =   tokenizer.prepare_seqaseq_batch(
																									    src_texts=__lowerCamelCase				,       max_length=3				,       max_target_length=10				,       return_tensors='pt'	)
																									self.assertEqual(batch_encoder_only.input_ids.shape[1]				,       3	)
																									self.assertEqual(batch_encoder_only.attention_mask.shape[1]				,       3	)
																									self.assertNotIn('decoder_input_ids'				,       __lowerCamelCase	)




				@unittest.skip('Unfortunately way too slow to build a BPE with SentencePiece.'	)
				def    a							( self	):
											pass




				def    a							( self	):






											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
																									snake_case_          =   [AddedToken('<special>'				,       lstrip=__lowerCamelCase	)]

																									snake_case_          =   self.rust_tokenizer_class.from_pretrained(
																									    __lowerCamelCase				,       additional_special_tokens=__lowerCamelCase				,       **__lowerCamelCase	)
																									snake_case_          =   tokenizer_r.encode('Hey this is a <special> token'	)

																									snake_case_          =   tokenizer_r.encode('<special>'				,       add_special_tokens=__lowerCamelCase	)[0]

																									self.assertTrue(special_token_id in r_output	)

																									if self.test_slow_tokenizer:
																																snake_case_          =   self.rust_tokenizer_class.from_pretrained(
																																    __lowerCamelCase				,       additional_special_tokens=__lowerCamelCase				,       **__lowerCamelCase				,       )
																																snake_case_          =   self.tokenizer_class.from_pretrained(
																																    __lowerCamelCase				,       additional_special_tokens=__lowerCamelCase				,       **__lowerCamelCase	)

																																snake_case_          =   tokenizer_p.encode('Hey this is a <special> token'	)

																																snake_case_          =   tokenizer_cr.encode('Hey this is a <special> token'	)

																																self.assertEqual(__lowerCamelCase				,       __lowerCamelCase	)
																																self.assertEqual(__lowerCamelCase				,       __lowerCamelCase	)
																																self.assertTrue(special_token_id in p_output	)
																																self.assertTrue(special_token_id in cr_output	)







@require_torch
@require_sentencepiece
@require_tokenizers
class 			lowercase    (	unittest.TestCase      ):
				__SCREAMING_SNAKE_CASE :			Any	      =      '''facebook/nllb-200-distilled-600M'''
				__SCREAMING_SNAKE_CASE :			str	      =      [
				    ''' UN Chief Says There Is No Military Solution in Syria''',
				    ''' Secretary-General Ban Ki-moon says his response to Russia\'s stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.''',
				]
				__SCREAMING_SNAKE_CASE :			Union[str, Any]	      =      [
				    '''Şeful ONU declară că nu există o soluţie militară în Siria''',
				    '''Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei'''
				    ''' pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor'''
				    ''' face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.''',
				]
				__SCREAMING_SNAKE_CASE :			int	      =      [
				    256_047,
				    16_297,
				    134_408,
				    8_165,
				    248_066,
				    14_734,
				    950,
				    1_135,
				    105_721,
				    3_573,
				    83,
				    27_352,
				    108,
				    49_486,
				    2,
				]




				@classmethod
				def    a							( cls	):
											snake_case_          =   NllbTokenizer.from_pretrained(
											    cls.checkpoint_name				,       src_lang='eng_Latn'				,       tgt_lang='ron_Latn'	)
											snake_case_          =   1
											return cls




				def    a							( self	):
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ace_Arab']				,       25_6001	)
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ace_Latn']				,       25_6002	)
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['fra_Latn']				,       25_6057	)




				def    a							( self	):
											snake_case_          =   self.tokenizer.batch_encode_plus(self.src_text	).input_ids[0]
											self.assertListEqual(self.expected_src_tokens				,       __lowerCamelCase	)




				def    a							( self	):
											self.assertIn(__lowerCamelCase				,       self.tokenizer.all_special_ids	)
											# fmt: off
											snake_case_          =   [RO_CODE, 4254, 9_8068, 11_2923, 3_9072, 3909, 713, 10_2767, 26, 1_7314, 3_5642, 1_4683, 3_3118, 2022, 6_6987, 2, 25_6047]
											# fmt: on

											snake_case_          =   self.tokenizer.decode(__lowerCamelCase				,       skip_special_tokens=__lowerCamelCase	)
											snake_case_          =   self.tokenizer.decode(generated_ids[1:]				,       skip_special_tokens=__lowerCamelCase	)
											self.assertEqual(__lowerCamelCase				,       __lowerCamelCase	)
											self.assertNotIn(self.tokenizer.eos_token				,       __lowerCamelCase	)




				def    a							( self	):
											snake_case_          =   ['''this is gunna be a long sentence ''' * 20]
											assert isinstance(src_text[0]				,       __lowerCamelCase	)
											snake_case_          =   10
											snake_case_          =   self.tokenizer(__lowerCamelCase				,       max_length=__lowerCamelCase				,       truncation=__lowerCamelCase	).input_ids[0]
											self.assertEqual(ids[-1]				,       2	)
											self.assertEqual(ids[0]				,       __lowerCamelCase	)
											self.assertEqual(len(__lowerCamelCase	)				,       __lowerCamelCase	)




				def    a							( self	):
											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']	)				,       [25_6203, 3]	)




				def    a							( self	):
											snake_case_          =   tempfile.mkdtemp()
											snake_case_          =   self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(__lowerCamelCase	)
											snake_case_          =   NllbTokenizer.from_pretrained(__lowerCamelCase	)
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids				,       __lowerCamelCase	)




				@require_torch
				def    a							( self	):
											snake_case_          =   self.tokenizer(
											    self.src_text				,       text_target=self.tgt_text				,       padding=__lowerCamelCase				,       truncation=__lowerCamelCase				,       max_length=len(self.expected_src_tokens	)				,       return_tensors='pt'				,       )
											snake_case_          =   shift_tokens_right(
											    batch['labels']				,       self.tokenizer.pad_token_id				,       self.tokenizer.lang_code_to_id['ron_Latn']	)

											self.assertIsInstance(__lowerCamelCase				,       __lowerCamelCase	)

											self.assertEqual((2, 15)				,       batch.input_ids.shape	)
											self.assertEqual((2, 15)				,       batch.attention_mask.shape	)
											snake_case_          =   batch.input_ids.tolist()[0]
											self.assertListEqual(self.expected_src_tokens				,       __lowerCamelCase	)
											self.assertEqual(__lowerCamelCase				,       batch.decoder_input_ids[0, 0]	)  # EOS
											# Test that special tokens are reset
											self.assertEqual(self.tokenizer.prefix_tokens				,       [EN_CODE]	)
											self.assertEqual(self.tokenizer.suffix_tokens				,       [self.tokenizer.eos_token_id]	)




				def    a							( self	):
											snake_case_          =   self.tokenizer(self.src_text				,       padding=__lowerCamelCase				,       truncation=__lowerCamelCase				,       max_length=3				,       return_tensors='pt'	)
											snake_case_          =   self.tokenizer(
											    text_target=self.tgt_text				,       padding=__lowerCamelCase				,       truncation=__lowerCamelCase				,       max_length=10				,       return_tensors='pt'	)
											snake_case_          =   targets['''input_ids''']
											snake_case_          =   shift_tokens_right(
											    __lowerCamelCase				,       self.tokenizer.pad_token_id				,       decoder_start_token_id=self.tokenizer.lang_code_to_id[self.tokenizer.tgt_lang]				,       )

											self.assertEqual(batch.input_ids.shape[1]				,       3	)
											self.assertEqual(batch.decoder_input_ids.shape[1]				,       10	)




				@require_torch
				def    a							( self	):
											snake_case_          =   self.tokenizer._build_translation_inputs(
											    'A test'				,       return_tensors='pt'				,       src_lang='eng_Latn'				,       tgt_lang='fra_Latn'	)

											self.assertEqual(
											    nested_simplify(__lowerCamelCase	)				,       {
											        # A, test, EOS, en_XX
											        'input_ids': [[25_6047, 70, 7356, 2]],
											        'attention_mask': [[1, 1, 1, 1]],
											        # ar_AR
											        'forced_bos_token_id': 25_6057,
											    }				,       )




				@require_torch
				def    a							( self	):
											snake_case_          =   True
											snake_case_          =   self.tokenizer(
											    'UN Chief says there is no military solution in Syria'				,       src_lang='eng_Latn'				,       tgt_lang='fra_Latn'	)
											self.assertEqual(
											    inputs.input_ids				,       [1_6297, 13_4408, 2_5653, 6370, 248, 254, 10_3929, 9_4995, 108, 4_9486, 2, 25_6047]	)

											snake_case_          =   False
											snake_case_          =   self.tokenizer(
											    'UN Chief says there is no military solution in Syria'				,       src_lang='eng_Latn'				,       tgt_lang='fra_Latn'	)
											self.assertEqual(
											    inputs.input_ids				,       [25_6047, 1_6297, 13_4408, 2_5653, 6370, 248, 254, 10_3929, 9_4995, 108, 4_9486, 2]	)







import requests

_UpperCAmelCase		:       Union[str, Any]						    =	"""https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""





def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   requests.get(_NEWS_API + bbc_news_api_key				).json()
							# each article in the list is a dict
							for i, article in enumerate(bbc_news_page['articles']       ,							1				):
														print(F'''{i}.) {article["title"]}'''				)


if __name__ == "__main__":
					fetch_bbc_news(bbc_news_api_key="""<Your BBC News API key goes here>""")




