

'''simple docstring'''





import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, 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_	= get_tests_dir("fixtures/test_sentencepiece.model")


if is_torch_available():
				from transformers.models.mbart.modeling_mbart import shift_tokens_right

A_	= 250_004
A_	= 250_020


@require_sentencepiece
@require_tokenizers
class  UpperCAmelCase (							UpperCAmelCase__  , unittest.TestCase    ):

		'''simple docstring'''






		SCREAMING_SNAKE_CASE_           =					MBartTokenizer
		SCREAMING_SNAKE_CASE_           =					MBartTokenizerFast
		SCREAMING_SNAKE_CASE_           =					True
		SCREAMING_SNAKE_CASE_           =					True
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							super().setUp()

							# We have a SentencePiece fixture for testing
							lowerCamelCase_  				=      MBartTokenizer(SCREAMING_SNAKE_CASE_   ,			keep_accents=SCREAMING_SNAKE_CASE_		)
							tokenizer.save_pretrained(self.tmpdirname		)
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      MBartTokenizer(SCREAMING_SNAKE_CASE_   ,			keep_accents=SCREAMING_SNAKE_CASE_		)

							lowerCamelCase_  				=      tokenizer.tokenize('This is a test'		)
							self.assertListEqual(SCREAMING_SNAKE_CASE_   ,			['▁This', '▁is', '▁a', '▁t', 'est']		)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_		)   ,			[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,			)

							lowerCamelCase_  				=      tokenizer.tokenize('I was born in 92000, and this is falsé.'		)
							self.assertListEqual(
							    SCREAMING_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',
							        '.',
							    ]   ,			)
							lowerCamelCase_  				=      tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_		)
							self.assertListEqual(
							    SCREAMING_SNAKE_CASE_   ,			[
							        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]
							        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
							    ]   ,			)

							lowerCamelCase_  				=      tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_		)
							self.assertListEqual(
							    SCREAMING_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 			UpperCamelCase(					self		)  ->     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

							lowerCamelCase_  				=      (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart', {})
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
																	lowerCamelCase_  				=      self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_   ,			**SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      self.tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE_   ,			**SCREAMING_SNAKE_CASE_		)

																	lowerCamelCase_  				=      tempfile.mkdtemp()

																	lowerCamelCase_  				=      tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.save_pretrained(SCREAMING_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		)		)
																	lowerCamelCase_  				=      tuple(f for f in tokenizer_r_files if 'tokenizer.json' not in f		)
																	self.assertSequenceEqual(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)

																	# Checks everything loads correctly in the same way
																	lowerCamelCase_  				=      tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.from_pretrained(SCREAMING_SNAKE_CASE_		)

																	# Check special tokens are set accordingly on Rust and Python
																	for key in tokenizer_pp.special_tokens_map:
																						self.assertTrue(hasattr(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)		)
																						# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																						# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																	shutil.rmtree(SCREAMING_SNAKE_CASE_		)

																	# Save tokenizer rust, legacy_format=True
																	lowerCamelCase_  				=      tempfile.mkdtemp()

																	lowerCamelCase_  				=      tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE_   ,			legacy_format=SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.save_pretrained(SCREAMING_SNAKE_CASE_		)

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

																	# Checks everything loads correctly in the same way
																	lowerCamelCase_  				=      tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.from_pretrained(SCREAMING_SNAKE_CASE_		)

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

																	shutil.rmtree(SCREAMING_SNAKE_CASE_		)

																	# Save tokenizer rust, legacy_format=False
																	lowerCamelCase_  				=      tempfile.mkdtemp()

																	lowerCamelCase_  				=      tokenizer_r.save_pretrained(SCREAMING_SNAKE_CASE_   ,			legacy_format=SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.save_pretrained(SCREAMING_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
																	lowerCamelCase_  				=      tokenizer_r.from_pretrained(SCREAMING_SNAKE_CASE_		)
																	lowerCamelCase_  				=      tokenizer_p.from_pretrained(SCREAMING_SNAKE_CASE_		)

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

																	shutil.rmtree(SCREAMING_SNAKE_CASE_		)


@require_torch
@require_sentencepiece
@require_tokenizers
class  UpperCAmelCase (							unittest.TestCase    ):

		'''simple docstring'''






		SCREAMING_SNAKE_CASE_           =					'facebook/mbart-large-en-ro'
		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_           =					[82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2, EN_CODE]
		@classmethod
		def 			UpperCamelCase(					cls		)  ->     Optional[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      MBartTokenizer.from_pretrained(
							    cls.checkpoint_name   ,			src_lang='en_XX'   ,			tgt_lang='ro_RO'		)
							lowerCamelCase_  				=      1
							return cls
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']   ,			250001		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']   ,			250004		)
							self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']   ,			250020		)
		def 			UpperCamelCase(					self		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
							self.assertListEqual(self.expected_src_tokens   ,			SCREAMING_SNAKE_CASE_		)
		def 			UpperCamelCase(					self		)  ->     Optional[int]:






							'''simple docstring'''



							self.assertIn(SCREAMING_SNAKE_CASE_   ,			self.tokenizer.all_special_ids		)
							lowerCamelCase_  				=      [RO_CODE, 884, 9019, 96, 9, 916, 86792, 36, 18743, 15596, 5, 2]
							lowerCamelCase_  				=      self.tokenizer.decode(SCREAMING_SNAKE_CASE_   ,			skip_special_tokens=SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      self.tokenizer.decode(generated_ids[1:]   ,			skip_special_tokens=SCREAMING_SNAKE_CASE_		)
							self.assertEqual(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)
							self.assertNotIn(self.tokenizer.eos_token   ,			SCREAMING_SNAKE_CASE_		)
		def 			UpperCamelCase(					self		)  ->     List[Any]:






							'''simple docstring'''



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






							'''simple docstring'''



							self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']		)   ,			[250026, 250001]		)
		def 			UpperCamelCase(					self		)  ->     List[str]:






							'''simple docstring'''



							lowerCamelCase_  				=      tempfile.mkdtemp()
							lowerCamelCase_  				=      self.tokenizer.fairseq_tokens_to_ids
							self.tokenizer.save_pretrained(SCREAMING_SNAKE_CASE_		)
							lowerCamelCase_  				=      MBartTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_		)
							self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,			SCREAMING_SNAKE_CASE_		)
		@require_torch
		def 			UpperCamelCase(					self		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer(self.src_text   ,			text_target=self.tgt_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			return_tensors='pt'		)
							lowerCamelCase_  				=      shift_tokens_right(batch['labels']   ,			self.tokenizer.pad_token_id		)

							# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
							assert batch.input_ids[1][-2:].tolist() == [2, EN_CODE]
							assert batch.decoder_input_ids[1][0].tolist() == RO_CODE
							assert batch.decoder_input_ids[1][-1] == 2
							assert batch.labels[1][-2:].tolist() == [2, RO_CODE]
		@require_torch
		def 			UpperCamelCase(					self		)  ->     Dict:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer(
							    self.src_text   ,			text_target=self.tgt_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_   ,			max_length=len(self.expected_src_tokens		)   ,			return_tensors='pt'   ,			)

							lowerCamelCase_  				=      shift_tokens_right(batch['labels']   ,			self.tokenizer.pad_token_id		)

							self.assertIsInstance(SCREAMING_SNAKE_CASE_   ,			SCREAMING_SNAKE_CASE_		)

							self.assertEqual((2, 14)   ,			batch.input_ids.shape		)
							self.assertEqual((2, 14)   ,			batch.attention_mask.shape		)
							lowerCamelCase_  				=      batch.input_ids.tolist()[0]
							self.assertListEqual(self.expected_src_tokens   ,			SCREAMING_SNAKE_CASE_		)
							self.assertEqual(2   ,			batch.decoder_input_ids[0, -1]		)  # EOS
							# Test that special tokens are reset
							self.assertEqual(self.tokenizer.prefix_tokens   ,			[]		)
							self.assertEqual(self.tokenizer.suffix_tokens   ,			[self.tokenizer.eos_token_id, EN_CODE]		)
		def 			UpperCamelCase(					self		)  ->     Optional[Any]:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer(self.src_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_   ,			max_length=3   ,			return_tensors='pt'		)
							lowerCamelCase_  				=      self.tokenizer(
							    text_target=self.tgt_text   ,			padding=SCREAMING_SNAKE_CASE_   ,			truncation=SCREAMING_SNAKE_CASE_   ,			max_length=10   ,			return_tensors='pt'		)
							lowerCamelCase_  				=      targets['input_ids']
							lowerCamelCase_  				=      shift_tokens_right(SCREAMING_SNAKE_CASE_   ,			self.tokenizer.pad_token_id		)

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






		@require_torch
		def 			UpperCamelCase(					self		)  ->     Any:






							'''simple docstring'''



							lowerCamelCase_  				=      self.tokenizer._build_translation_inputs(
							    'A test'   ,			return_tensors='pt'   ,			src_lang='en_XX'   ,			tgt_lang='ar_AR'		)

							self.assertEqual(
							    nested_simplify(SCREAMING_SNAKE_CASE_		)   ,			{
							        # A, test, EOS, en_XX
							        'input_ids': [[62, 3034, 2, 250004]],
							        'attention_mask': [[1, 1, 1, 1]],
							        # ar_AR
							        'forced_bos_token_id': 250001,
							    }   ,			)





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


_lowercase											=    """▁"""

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


@require_sentencepiece
@require_tokenizers
class 			lowercase_		(      A  ,      unittest.TestCase       ):
       __lowerCamelCase				       =						BigBirdTokenizer
       __lowerCamelCase				       =						BigBirdTokenizerFast
       __lowerCamelCase				       =						True
       __lowerCamelCase				       =						True


       def 	_snake_case				(    self				)						->    Tuple:
              super().setUp()

              SCREAMING_SNAKE_CASE_							:				str		=self.tokenizer_class(__A						,       keep_accents=__A				)
              tokenizer.save_pretrained(self.tmpdirname				)


       def 	_snake_case				(    self				)						->    List[Any]:
              SCREAMING_SNAKE_CASE_							:				str		='''<s>'''
              SCREAMING_SNAKE_CASE_							:				Union[str, 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 	_snake_case				(    self				)						->    Any:
              SCREAMING_SNAKE_CASE_							:				str		=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				)						,       1_004				)


       def 	_snake_case				(    self				)						->    Optional[Any]:
              self.assertEqual(self.get_tokenizer().vocab_size						,       1_000				)


       def 	_snake_case				(    self				)						->    str:
              if not self.test_rust_tokenizer:
                     return

              SCREAMING_SNAKE_CASE_							:				Dict		=self.get_tokenizer()
              SCREAMING_SNAKE_CASE_							:				List[Any]		=self.get_rust_tokenizer()

              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		='''I was born in 92000, and this is falsé.'''

              SCREAMING_SNAKE_CASE_							:				List[Any]		=tokenizer.tokenize(__A				)
              SCREAMING_SNAKE_CASE_							:				Optional[int]		=rust_tokenizer.tokenize(__A				)
              self.assertListEqual(__A						,       __A				)

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

              SCREAMING_SNAKE_CASE_							:				Dict		=self.get_rust_tokenizer()
              SCREAMING_SNAKE_CASE_							:				int		=tokenizer.encode(__A				)
              SCREAMING_SNAKE_CASE_							:				Dict		=rust_tokenizer.encode(__A				)
              self.assertListEqual(__A						,       __A				)


       def 	_snake_case				(    self				)						->    str:
              SCREAMING_SNAKE_CASE_							:				Optional[Any]		=BigBirdTokenizer(__A						,       keep_accents=__A				)

              SCREAMING_SNAKE_CASE_							:				str		=tokenizer.tokenize('''This is a test'''				)
              self.assertListEqual(__A						,       ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']				)

              self.assertListEqual(
                  tokenizer.convert_tokens_to_ids(__A				)						,       [285, 46, 10, 170, 382]						,       )

              SCREAMING_SNAKE_CASE_							:				List[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''',
                      '''.''',
                  ]						,       )
              SCREAMING_SNAKE_CASE_							:				Dict		=tokenizer.convert_tokens_to_ids(__A				)
              self.assertListEqual(
                  __A						,       [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]						,       )

              SCREAMING_SNAKE_CASE_							:				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 	_snake_case				(    self				)						->    Union[str, Any]:
              return BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''				)


       @slow
       def 	_snake_case				(    self				)						->    Any:
              SCREAMING_SNAKE_CASE_							:				str		='''Hello World!'''
              SCREAMING_SNAKE_CASE_							:				Dict		=[65, 18_536, 2_260, 101, 66]

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


       @slow
       def 	_snake_case				(    self				)						->    Optional[int]:
              SCREAMING_SNAKE_CASE_							:				Union[str, 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
              SCREAMING_SNAKE_CASE_							:				List[Any]		=[65, 871, 419, 358, 946, 991, 2_521, 452, 358, 1_357, 387, 7_751, 3_536, 112, 985, 456, 126, 865, 938, 5_400, 5_734, 458, 1_368, 467, 786, 2_462, 5_246, 1_159, 633, 865, 4_519, 457, 582, 852, 2_557, 427, 916, 508, 405, 34_324, 497, 391, 408, 11_342, 1_244, 385, 100, 938, 985, 456, 574, 362, 12_597, 3_200, 3_129, 1_172, 66]  # noqa: E231
              # fmt: on
              self.assertListEqual(__A						,       self.big_tokenizer.encode(__A				)				)


       @require_torch
       @slow
       def 	_snake_case				(    self				)						->    int:
              import torch

              from transformers import BigBirdConfig, BigBirdModel

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

              SCREAMING_SNAKE_CASE_							:				Union[str, Any]		=BigBirdConfig(attention_type='''original_full'''				)
              SCREAMING_SNAKE_CASE_							:				Tuple		=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 	_snake_case				(    self				)						->    Tuple:
              SCREAMING_SNAKE_CASE_							:				Any		=BigBirdTokenizer.from_pretrained('''google/bigbird-roberta-base'''				)
              SCREAMING_SNAKE_CASE_							:				List[Any]		=tokenizer.decode(tokenizer('''Paris is the [MASK].'''				).input_ids				)

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





       @slow
       def 	_snake_case				(    self				)						->    Any:
              # fmt: off
              SCREAMING_SNAKE_CASE_							:				Optional[int]		={'''input_ids''': [[65, 39_286, 458, 36_335, 2_001, 456, 13_073, 13_266, 455, 113, 7_746, 1_741, 11_157, 391, 13_073, 13_266, 455, 113, 3_967, 35_412, 113, 4_936, 109, 3_870, 2_377, 113, 30_084, 45_720, 458, 134, 17_496, 112, 503, 11_672, 113, 118, 112, 5_665, 13_347, 38_687, 112, 1_496, 31_389, 112, 3_268, 47_264, 134, 962, 112, 16_377, 8_035, 23_130, 430, 12_169, 15_518, 28_592, 458, 146, 41_697, 109, 391, 12_169, 15_518, 16_689, 458, 146, 41_358, 109, 452, 726, 4_034, 111, 763, 35_412, 5_082, 388, 1_903, 111, 9_051, 391, 2_870, 48_918, 1_900, 1_123, 550, 998, 112, 9_586, 15_985, 455, 391, 410, 22_955, 37_636, 114, 66], [65, 448, 17_496, 419, 3_663, 385, 763, 113, 27_533, 2_870, 3_283, 13_043, 1_639, 24_713, 523, 656, 24_013, 18_550, 2_521, 517, 27_014, 21_244, 420, 1_212, 1_465, 391, 927, 4_833, 388, 578, 11_786, 114, 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, 484, 2_169, 7_687, 21_932, 18_146, 726, 363, 17_032, 3_391, 114, 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'''						,       )
