





'''simple docstring'''






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


A   : Dict             =			get_tests_dir('fixtures/test_sentencepiece.model')


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

A   : Any             =			256_047
A   : Tuple             =			256_145







@require_sentencepiece
@require_tokenizers
class 			lowerCamelCase					(						__UpperCAmelCase     ,							unittest.TestCase  ):
					_SCREAMING_SNAKE_CASE							   =    NllbTokenizer
					_SCREAMING_SNAKE_CASE							   =    NllbTokenizerFast
					_SCREAMING_SNAKE_CASE							   =    True
					_SCREAMING_SNAKE_CASE							   =    True
					_SCREAMING_SNAKE_CASE							   =    {}


					def    SCREAMING_SNAKE_CASE_		(					self	:  Optional[Any]       ):





											'''simple docstring'''





											super().setUp()

											# We have a SentencePiece fixture for testing
											_snake_case:   int  					=		NllbTokenizer(__snake_case       ,     keep_accents=__snake_case       )
											tokenizer.save_pretrained(self.tmpdirname       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  Any       ):





											'''simple docstring'''





											_snake_case:   Any  					=		NllbTokenizer(__snake_case       ,     keep_accents=__snake_case       )

											_snake_case:   Union[str, Any]  					=		tokenizer.tokenize('This is a test'       )
											self.assertListEqual(__snake_case       ,     ['▁This', '▁is', '▁a', '▁t', 'est']       )

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(__snake_case       )       ,     [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]       ,     )

											_snake_case:   Optional[Any]  					=		tokenizer.tokenize('I was born in 92000, and this is falsé.'       )
											self.assertListEqual(
											    __snake_case       ,     [
											        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:   List[str]  					=		tokenizer.convert_tokens_to_ids(__snake_case       )
											self.assertListEqual(
											    __snake_case       ,     [
											        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]
											    ]       ,     )

											_snake_case:   str  					=		tokenizer.convert_ids_to_tokens(__snake_case       )
											self.assertListEqual(
											    __snake_case       ,     [
											        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	:  List[Any]       ):





											'''simple docstring'''





											_snake_case:   int  					=		(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:   int  					=		self.rust_tokenizer_class.from_pretrained(__snake_case       ,     **__snake_case       )
																							_snake_case:   Dict  					=		self.tokenizer_class.from_pretrained(__snake_case       ,     **__snake_case       )

																							_snake_case:   List[str]  					=		tempfile.mkdtemp()

																							_snake_case:   Tuple  					=		tokenizer_r.save_pretrained(__snake_case       )
																							_snake_case:   Dict  					=		tokenizer_p.save_pretrained(__snake_case       )

																							# 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:   int  					=		tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f       )
																							self.assertSequenceEqual(__snake_case       ,     __snake_case       )

																							# Checks everything loads correctly in the same way
																							_snake_case:   str  					=		tokenizer_r.from_pretrained(__snake_case       )
																							_snake_case:   Optional[int]  					=		tokenizer_p.from_pretrained(__snake_case       )

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

																							shutil.rmtree(__snake_case       )

																							# Save tokenizer rust, legacy_format=True
																							_snake_case:   int  					=		tempfile.mkdtemp()

																							_snake_case:   Tuple  					=		tokenizer_r.save_pretrained(__snake_case       ,     legacy_format=__snake_case       )
																							_snake_case:   Dict  					=		tokenizer_p.save_pretrained(__snake_case       )

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

																							# Checks everything loads correctly in the same way
																							_snake_case:   List[Any]  					=		tokenizer_r.from_pretrained(__snake_case       )
																							_snake_case:   List[Any]  					=		tokenizer_p.from_pretrained(__snake_case       )

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

																							shutil.rmtree(__snake_case       )

																							# Save tokenizer rust, legacy_format=False
																							_snake_case:   str  					=		tempfile.mkdtemp()

																							_snake_case:   Optional[int]  					=		tokenizer_r.save_pretrained(__snake_case       ,     legacy_format=__snake_case       )
																							_snake_case:   Union[str, Any]  					=		tokenizer_p.save_pretrained(__snake_case       )

																							# 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:   Any  					=		tokenizer_r.from_pretrained(__snake_case       )
																							_snake_case:   int  					=		tokenizer_p.from_pretrained(__snake_case       )

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

																							shutil.rmtree(__snake_case       )


					@require_torch
					def    SCREAMING_SNAKE_CASE_		(					self	:  Union[str, Any]       ):





											'''simple docstring'''





											if not self.test_seqaseq:
																	return

											_snake_case:   Optional[int]  					=		self.get_tokenizers()
											for tokenizer in tokenizers:
																	with self.subTest(f'''{tokenizer.__class__.__name__}'''       ):
																							# Longer text that will definitely require truncation.
																							_snake_case:   Dict  					=		[
																							    ' 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:   Dict  					=		[
																							    '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:   List[str]  					=		tokenizer.prepare_seqaseq_batch(
																													    src_texts=__snake_case       ,     tgt_texts=__snake_case       ,     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:   int  					=		tokenizer.prepare_seqaseq_batch(
																							    __snake_case       ,     tgt_texts=__snake_case       ,     max_length=3       ,     return_tensors='pt'       )
																							self.assertEqual(batch.input_ids.shape[1]       ,     3       )
																							self.assertEqual(batch.labels.shape[1]       ,     3       )

																							_snake_case:   Union[str, Any]  					=		tokenizer.prepare_seqaseq_batch(
																							    src_texts=__snake_case       ,     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'       ,     __snake_case       )


					@unittest.skip('Unfortunately way too slow to build a BPE with SentencePiece.'       )
					def    SCREAMING_SNAKE_CASE_		(					self	:  Union[str, Any]       ):





											'''simple docstring'''





											pass




					def    SCREAMING_SNAKE_CASE_		(					self	:  str       ):





											'''simple docstring'''





											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
																							_snake_case:   Union[str, Any]  					=		[AddedToken('<special>'       ,     lstrip=__snake_case       )]

																							_snake_case:   Tuple  					=		self.rust_tokenizer_class.from_pretrained(
																							    __snake_case       ,     additional_special_tokens=__snake_case       ,     **__snake_case       )
																							_snake_case:   Optional[int]  					=		tokenizer_r.encode('Hey this is a <special> token'       )

																							_snake_case:   Optional[int]  					=		tokenizer_r.encode('<special>'       ,     add_special_tokens=__snake_case       )[0]

																							self.assertTrue(special_token_id in r_output       )

																							if self.test_slow_tokenizer:
																													_snake_case:   Union[str, Any]  					=		self.rust_tokenizer_class.from_pretrained(
																													    __snake_case       ,     additional_special_tokens=__snake_case       ,     **__snake_case       ,     )
																													_snake_case:   Optional[Any]  					=		self.tokenizer_class.from_pretrained(
																													    __snake_case       ,     additional_special_tokens=__snake_case       ,     **__snake_case       )

																													_snake_case:   Union[str, Any]  					=		tokenizer_p.encode('Hey this is a <special> token'       )

																													_snake_case:   Any  					=		tokenizer_cr.encode('Hey this is a <special> token'       )

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







@require_torch
@require_sentencepiece
@require_tokenizers
class 			lowerCamelCase					(						unittest.TestCase  ):
					_SCREAMING_SNAKE_CASE							   =    "facebook/nllb-200-distilled-600M"
					_SCREAMING_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.",
					]
					_SCREAMING_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.",
					]
					_SCREAMING_SNAKE_CASE							   =    [
					    25_6047,
					    1_6297,
					    13_4408,
					    8165,
					    24_8066,
					    1_4734,
					    950,
					    1135,
					    10_5721,
					    3573,
					    83,
					    2_7352,
					    108,
					    4_9486,
					    2,
					]


					@classmethod
					def    SCREAMING_SNAKE_CASE_		(					cls	:  Optional[Any]       ):





											'''simple docstring'''





											_snake_case:   NllbTokenizer  					=		NllbTokenizer.from_pretrained(
											    cls.checkpoint_name       ,     src_lang='eng_Latn'       ,     tgt_lang='ron_Latn'       )
											_snake_case:   Any  					=		1
											return cls


					def    SCREAMING_SNAKE_CASE_		(					self	:  List[str]       ):





											'''simple docstring'''





											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ace_Arab']       ,     25_60_01       )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ace_Latn']       ,     25_60_02       )
											self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['fra_Latn']       ,     25_60_57       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ):





											'''simple docstring'''





											_snake_case:   Optional[Any]  					=		self.tokenizer.batch_encode_plus(self.src_text       ).input_ids[0]
											self.assertListEqual(self.expected_src_tokens       ,     __snake_case       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ):





											'''simple docstring'''





											self.assertIn(__snake_case       ,     self.tokenizer.all_special_ids       )
											# fmt: off
											_snake_case:   List[Any]  					=		[RO_CODE, 42_54, 9_80_68, 11_29_23, 3_90_72, 39_09, 7_13, 10_27_67, 26, 1_73_14, 3_56_42, 1_46_83, 3_31_18, 20_22, 6_69_87, 2, 25_60_47]
											# fmt: on

											_snake_case:   Union[str, Any]  					=		self.tokenizer.decode(__snake_case       ,     skip_special_tokens=__snake_case       )
											_snake_case:   Union[str, Any]  					=		self.tokenizer.decode(generated_ids[1:]       ,     skip_special_tokens=__snake_case       )
											self.assertEqual(__snake_case       ,     __snake_case       )
											self.assertNotIn(self.tokenizer.eos_token       ,     __snake_case       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  Optional[Any]       ):





											'''simple docstring'''





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


					def    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ):





											'''simple docstring'''





											self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']       )       ,     [25_62_03, 3]       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  List[str]       ):





											'''simple docstring'''





											_snake_case:   str  					=		tempfile.mkdtemp()
											_snake_case:   Optional[Any]  					=		self.tokenizer.fairseq_tokens_to_ids
											self.tokenizer.save_pretrained(__snake_case       )
											_snake_case:   int  					=		NllbTokenizer.from_pretrained(__snake_case       )
											self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,     __snake_case       )


					@require_torch
					def    SCREAMING_SNAKE_CASE_		(					self	:  str       ):





											'''simple docstring'''





											_snake_case:   Any  					=		self.tokenizer(
											    self.src_text       ,     text_target=self.tgt_text       ,     padding=__snake_case       ,     truncation=__snake_case       ,     max_length=len(self.expected_src_tokens       )       ,     return_tensors='pt'       ,     )
											_snake_case:   Optional[Any]  					=		shift_tokens_right(
											    batch['labels']       ,     self.tokenizer.pad_token_id       ,     self.tokenizer.lang_code_to_id['ron_Latn']       )

											self.assertIsInstance(__snake_case       ,     __snake_case       )

											self.assertEqual((2, 15)       ,     batch.input_ids.shape       )
											self.assertEqual((2, 15)       ,     batch.attention_mask.shape       )
											_snake_case:   str  					=		batch.input_ids.tolist()[0]
											self.assertListEqual(self.expected_src_tokens       ,     __snake_case       )
											self.assertEqual(__snake_case       ,     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    SCREAMING_SNAKE_CASE_		(					self	:  Optional[int]       ):





											'''simple docstring'''





											_snake_case:   List[Any]  					=		self.tokenizer(self.src_text       ,     padding=__snake_case       ,     truncation=__snake_case       ,     max_length=3       ,     return_tensors='pt'       )
											_snake_case:   Optional[int]  					=		self.tokenizer(
											    text_target=self.tgt_text       ,     padding=__snake_case       ,     truncation=__snake_case       ,     max_length=10       ,     return_tensors='pt'       )
											_snake_case:   List[Any]  					=		targets['input_ids']
											_snake_case:   str  					=		shift_tokens_right(
											    __snake_case       ,     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    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ):





											'''simple docstring'''





											_snake_case:   Any  					=		self.tokenizer._build_translation_inputs(
											    'A test'       ,     return_tensors='pt'       ,     src_lang='eng_Latn'       ,     tgt_lang='fra_Latn'       )

											self.assertEqual(
											    nested_simplify(__snake_case       )       ,     {
											        # A, test, EOS, en_XX
											        'input_ids': [[25_60_47, 70, 73_56, 2]],
											        'attention_mask': [[1, 1, 1, 1]],
											        # ar_AR
											        'forced_bos_token_id': 25_60_57,
											    }       ,     )




					@require_torch
					def    SCREAMING_SNAKE_CASE_		(					self	:  List[str]       ):





											'''simple docstring'''





											_snake_case:   List[str]  					=		True
											_snake_case:   Optional[int]  					=		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_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2, 25_60_47]       )

											_snake_case:   str  					=		False
											_snake_case:   Optional[Any]  					=		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_60_47, 1_62_97, 13_44_08, 2_56_53, 63_70, 2_48, 2_54, 10_39_29, 9_49_95, 1_08, 4_94_86, 2]       )












'''simple docstring'''






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


A   : Tuple             =			'▁'

A   : Optional[Any]             =			get_tests_dir('fixtures/test_sentencepiece.model')







@require_sentencepiece
@require_tokenizers
class 			lowerCamelCase					(						__UpperCAmelCase     ,							unittest.TestCase  ):
					_SCREAMING_SNAKE_CASE							   =    BigBirdTokenizer
					_SCREAMING_SNAKE_CASE							   =    BigBirdTokenizerFast
					_SCREAMING_SNAKE_CASE							   =    True
					_SCREAMING_SNAKE_CASE							   =    True


					def    SCREAMING_SNAKE_CASE_		(					self	:  str       ):





											'''simple docstring'''





											super().setUp()

											_snake_case:   Dict  					=		self.tokenizer_class(__snake_case       ,     keep_accents=__snake_case       )
											tokenizer.save_pretrained(self.tmpdirname       )


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





											'''simple docstring'''





											_snake_case:   List[str]  					=		'<s>'
											_snake_case:   Tuple  					=		1

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


					def    SCREAMING_SNAKE_CASE_		(					self	:  int       ):





											'''simple docstring'''





											_snake_case:   Dict  					=		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(__snake_case       )       ,     10_04       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  int       ):





											'''simple docstring'''





											self.assertEqual(self.get_tokenizer().vocab_size       ,     10_00       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  List[str]       ):





											'''simple docstring'''





											if not self.test_rust_tokenizer:
																	return

											_snake_case:   Optional[int]  					=		self.get_tokenizer()
											_snake_case:   Union[str, Any]  					=		self.get_rust_tokenizer()

											_snake_case:   List[str]  					=		'I was born in 92000, and this is falsé.'

											_snake_case:   str  					=		tokenizer.tokenize(__snake_case       )
											_snake_case:   Dict  					=		rust_tokenizer.tokenize(__snake_case       )
											self.assertListEqual(__snake_case       ,     __snake_case       )

											_snake_case:   Union[str, Any]  					=		tokenizer.encode(__snake_case       ,     add_special_tokens=__snake_case       )
											_snake_case:   List[Any]  					=		rust_tokenizer.encode(__snake_case       ,     add_special_tokens=__snake_case       )
											self.assertListEqual(__snake_case       ,     __snake_case       )

											_snake_case:   Optional[int]  					=		self.get_rust_tokenizer()
											_snake_case:   int  					=		tokenizer.encode(__snake_case       )
											_snake_case:   Tuple  					=		rust_tokenizer.encode(__snake_case       )
											self.assertListEqual(__snake_case       ,     __snake_case       )


					def    SCREAMING_SNAKE_CASE_		(					self	:  str       ):





											'''simple docstring'''





											_snake_case:   Tuple  					=		BigBirdTokenizer(__snake_case       ,     keep_accents=__snake_case       )

											_snake_case:   Optional[int]  					=		tokenizer.tokenize('This is a test'       )
											self.assertListEqual(__snake_case       ,     ['▁This', '▁is', '▁a', '▁t', 'est']       )

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

											_snake_case:   Any  					=		tokenizer.tokenize('I was born in 92000, and this is falsé.'       )
											self.assertListEqual(
											    __snake_case       ,     [
											        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:   List[Any]  					=		tokenizer.convert_tokens_to_ids(__snake_case       )
											self.assertListEqual(
											    __snake_case       ,     [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]       ,     )

											_snake_case:   Optional[Any]  					=		tokenizer.convert_ids_to_tokens(__snake_case       )
											self.assertListEqual(
											    __snake_case       ,     [
											        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	:  Optional[int]       ):





											'''simple docstring'''





											return BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base'       )


					@slow
					def    SCREAMING_SNAKE_CASE_		(					self	:  Dict       ):





											'''simple docstring'''





											_snake_case:   Dict  					=		'Hello World!'
											_snake_case:   Optional[int]  					=		[65, 1_85_36, 22_60, 1_01, 66]

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


					@slow
					def    SCREAMING_SNAKE_CASE_		(					self	:  Union[str, Any]       ):





											'''simple docstring'''





											_snake_case:   str  					=		(
											    '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
											_snake_case:   str  					=		[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(__snake_case       ,     self.big_tokenizer.encode(__snake_case       )       )


					@require_torch
					@slow
					def    SCREAMING_SNAKE_CASE_		(					self	:  Optional[int]       ):





											'''simple docstring'''





											import torch

											from transformers import BigBirdConfig, BigBirdModel

											# Build sequence
											_snake_case:   Tuple  					=		list(self.big_tokenizer.get_vocab().keys()       )[:10]
											_snake_case:   Union[str, Any]  					=		' '.join(__snake_case       )
											_snake_case:   Optional[Any]  					=		self.big_tokenizer.encode_plus(__snake_case       ,     return_tensors='pt'       ,     return_token_type_ids=__snake_case       )
											_snake_case:   int  					=		self.big_tokenizer.batch_encode_plus(
											    [sequence + ' ' + sequence]       ,     return_tensors='pt'       ,     return_token_type_ids=__snake_case       )

											_snake_case:   int  					=		BigBirdConfig(attention_type='original_full'       )
											_snake_case:   int  					=		BigBirdModel(__snake_case       )

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

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


					@slow
					def    SCREAMING_SNAKE_CASE_		(					self	:  List[Any]       ):





											'''simple docstring'''





											_snake_case:   Tuple  					=		BigBirdTokenizer.from_pretrained('google/bigbird-roberta-base'       )
											_snake_case:   Optional[Any]  					=		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	:  int       ):





											'''simple docstring'''





											_snake_case:   Dict  					=		{'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=__snake_case       ,     model_name='google/bigbird-roberta-base'       ,     revision='215c99f1600e06f83acce68422f2035b2b5c3510'       ,     )





