




import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


_A     =			logging.get_logger(__name__)

_A     =			{'''vocab_file''': '''spiece.model'''}

_A     =			{
    '''vocab_file''': {
        '''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model''',
        '''xlnet-large-cased''': '''https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model''',
    }
}

_A     =			{
    '''xlnet-base-cased''': None,
    '''xlnet-large-cased''': None,
}

# Segments (not really needed)
_A     =			0
_A     =			1
_A     =			2
_A     =			3
_A     =			4


class  A		(  __UpperCamelCase     ):
		__snake_case									=   VOCAB_FILES_NAMES
		__snake_case									=   PRETRAINED_VOCAB_FILES_MAP
		__snake_case									=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		__snake_case									=   'left'



		def __init__(     self,	UpperCamelCase__,	UpperCamelCase__=False,	UpperCamelCase__=True,	UpperCamelCase__=False,	UpperCamelCase__="<s>",	UpperCamelCase__="</s>",	UpperCamelCase__="<unk>",	UpperCamelCase__="<sep>",	UpperCamelCase__="<pad>",	UpperCamelCase__="<cls>",	UpperCamelCase__="<mask>",	UpperCamelCase__=["<eop>", "<eod>"],	UpperCamelCase__ = None,	**UpperCamelCase__,	):







								"""simple docstring"""



								lowerCAmelCase_      			=  AddedToken(lowerCAmelCase__,	lstrip=lowerCAmelCase__,	rstrip=lowerCAmelCase__   ) if isinstance(lowerCAmelCase__,	lowerCAmelCase__   ) else mask_token

								lowerCAmelCase_      			=  {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    do_lower_case=lowerCAmelCase__,	remove_space=lowerCAmelCase__,	keep_accents=lowerCAmelCase__,	bos_token=lowerCAmelCase__,	eos_token=lowerCAmelCase__,	unk_token=lowerCAmelCase__,	sep_token=lowerCAmelCase__,	pad_token=lowerCAmelCase__,	cls_token=lowerCAmelCase__,	mask_token=lowerCAmelCase__,	additional_special_tokens=lowerCAmelCase__,	sp_model_kwargs=self.sp_model_kwargs,	**lowerCAmelCase__,	)

								lowerCAmelCase_      			=  3

								lowerCAmelCase_      			=  do_lower_case
								lowerCAmelCase_      			=  remove_space
								lowerCAmelCase_      			=  keep_accents
								lowerCAmelCase_      			=  vocab_file

								lowerCAmelCase_      			=  spm.SentencePieceProcessor(**self.sp_model_kwargs   )
								self.sp_model.Load(lowerCAmelCase__   )



		@property
		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								return len(self.sp_model   )



		def        SCREAMING_SNAKE_CASE__			(     self   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  {self.convert_ids_to_tokens(lowerCAmelCase__   ): i for i in range(self.vocab_size   )}
								vocab.update(self.added_tokens_encoder   )
								return vocab



		def __getstate__(     self   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  self.__dict__.copy()
								lowerCAmelCase_      			=  None
								return state



		def __setstate__(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  d

								# for backward compatibility
								if not hasattr(self,	'''sp_model_kwargs'''   ):
														lowerCAmelCase_      			=  {}

								lowerCAmelCase_      			=  spm.SentencePieceProcessor(**self.sp_model_kwargs   )
								self.sp_model.Load(self.vocab_file   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								if self.remove_space:
														lowerCAmelCase_      			=  ' '.join(inputs.strip().split()   )
								else:
														lowerCAmelCase_      			=  inputs
								lowerCAmelCase_      			=  outputs.replace('''``''',	'''"'''   ).replace('''\'\'''',	'''"'''   )

								if not self.keep_accents:
														lowerCAmelCase_      			=  unicodedata.normalize('''NFKD''',	lowerCAmelCase__   )
														lowerCAmelCase_      			=  ''.join([c for c in outputs if not unicodedata.combining(lowerCAmelCase__   )]   )
								if self.do_lower_case:
														lowerCAmelCase_      			=  outputs.lower()

								return outputs



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  self.preprocess_text(lowerCAmelCase__   )
								lowerCAmelCase_      			=  self.sp_model.encode(lowerCAmelCase__,	out_type=lowerCAmelCase__   )
								lowerCAmelCase_      			=  []
								for piece in pieces:
														if len(lowerCAmelCase__   ) > 1 and piece[-1] == str(''','''   ) and piece[-2].isdigit():
																				lowerCAmelCase_      			=  self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCAmelCase__,	''''''   )   )
																				if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																										if len(cur_pieces[0]   ) == 1:
																																lowerCAmelCase_      			=  cur_pieces[1:]
																										else:
																																lowerCAmelCase_      			=  cur_pieces[0][1:]
																				cur_pieces.append(piece[-1]   )
																				new_pieces.extend(lowerCAmelCase__   )
														else:
																				new_pieces.append(lowerCAmelCase__   )

								return new_pieces



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return self.sp_model.PieceToId(lowerCAmelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								return self.sp_model.IdToPiece(lowerCAmelCase__   )



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  ''.join(lowerCAmelCase__   ).replace(lowerCAmelCase__,	''' '''   ).strip()
								return out_string



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = False,	UpperCamelCase__ = None,	UpperCamelCase__ = True,	**UpperCamelCase__,	):







								"""simple docstring"""



								lowerCAmelCase_      			=  kwargs.pop('''use_source_tokenizer''',	lowerCAmelCase__   )

								lowerCAmelCase_      			=  self.convert_ids_to_tokens(lowerCAmelCase__,	skip_special_tokens=lowerCAmelCase__   )

								# To avoid mixing byte-level and unicode for byte-level BPT
								# we need to build string separately for added tokens and byte-level tokens
								# cf. https://github.com/huggingface/transformers/issues/1133
								lowerCAmelCase_      			=  []
								lowerCAmelCase_      			=  []
								for token in filtered_tokens:
														if skip_special_tokens and token in self.all_special_ids:
																				continue
														if token in self.added_tokens_encoder:
																				if current_sub_text:
																										sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase__   )   )
																										lowerCAmelCase_      			=  []
																				sub_texts.append(lowerCAmelCase__   )
														else:
																				current_sub_text.append(lowerCAmelCase__   )
								if current_sub_text:
														sub_texts.append(self.convert_tokens_to_string(lowerCAmelCase__   )   )

								# Mimic the behavior of the Rust tokenizer:
								# By default, there are no spaces between special tokens
								lowerCAmelCase_      			=  ''.join(lowerCAmelCase__   )

								lowerCAmelCase_      			=  (
								    clean_up_tokenization_spaces
								    if clean_up_tokenization_spaces is not None
								    else self.clean_up_tokenization_spaces
								)
								if clean_up_tokenization_spaces:
														lowerCAmelCase_      			=  self.clean_up_tokenization(lowerCAmelCase__   )
														return clean_text
								else:
														return text



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  [self.sep_token_id]
								lowerCAmelCase_      			=  [self.cls_token_id]
								if token_ids_a is None:
														return token_ids_a + sep + cls
								return token_ids_a + sep + token_ids_a + sep + cls



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None,	UpperCamelCase__ = False   ):







								"""simple docstring"""



								if already_has_special_tokens:
														return super().get_special_tokens_mask(
														    token_ids_a=lowerCAmelCase__,	token_ids_a=lowerCAmelCase__,	already_has_special_tokens=lowerCAmelCase__   )

								if token_ids_a is not None:
														return ([0] * len(lowerCAmelCase__   )) + [1] + ([0] * len(lowerCAmelCase__   )) + [1, 1]
								return ([0] * len(lowerCAmelCase__   )) + [1, 1]



		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								lowerCAmelCase_      			=  [self.sep_token_id]
								lowerCAmelCase_      			=  [2]

								if token_ids_a is None:
														return len(token_ids_a + sep   ) * [0] + cls_segment_id
								return len(token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1] + cls_segment_id







		def        SCREAMING_SNAKE_CASE__			(     self,	UpperCamelCase__,	UpperCamelCase__ = None   ):







								"""simple docstring"""



								if not os.path.isdir(lowerCAmelCase__   ):
														logger.error(f"Vocabulary path ({save_directory}) should be a directory"   )
														return
								lowerCAmelCase_      			=  os.path.join(
								    lowerCAmelCase__,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )

								if os.path.abspath(self.vocab_file   ) != os.path.abspath(lowerCAmelCase__   ) and os.path.isfile(self.vocab_file   ):
														copyfile(self.vocab_file,	lowerCAmelCase__   )
								elif not os.path.isfile(self.vocab_file   ):
														with open(lowerCAmelCase__,	'''wb'''   ) as fi:
																				lowerCAmelCase_      			=  self.sp_model.serialized_model_proto()
																				fi.write(lowerCAmelCase__   )

								return (out_vocab_file,)








import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
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


__lowerCAmelCase		       =							get_tests_dir('''fixtures/test_sentencepiece_no_bos.model''')





@require_sentencepiece
@require_tokenizers
class   __a			(    __UpperCamelCase       ,       unittest.TestCase      ):
 __lowercase :							int        = PegasusTokenizer
 __lowercase :							Any        = PegasusTokenizerFast
 __lowercase :							Optional[int]        = True
 __lowercase :							Tuple        = True
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Any:




        '''simple docstring'''
        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase__:   List[str]  			=   PegasusTokenizer(lowerCAmelCase__ )
        tokenizer.save_pretrained(self.tmpdirname )
 @cached_property
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Union[str, Any]:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained('google/pegasus-large' )
 def 		SCREAMING_SNAKE_CASE__   (   self				, **lowerCAmelCase__ )					->				PegasusTokenizer:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained(self.tmpdirname				, **lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self				, lowerCAmelCase__ )					->				List[str]:




        '''simple docstring'''
        return ("This is a test", "This is a test")
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Tuple:




        '''simple docstring'''
        lowercase__:   Optional[Any]  			=   '</s>'
        lowercase__:   Union[str, Any]  			=   1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase__ )				, lowerCAmelCase__ )
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase__ )				, lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				List[str]:




        '''simple docstring'''
        lowercase__:   Tuple  			=   list(self.get_tokenizer().get_vocab().keys() )

        self.assertEqual(vocab_keys[0]				, '<pad>' )
        self.assertEqual(vocab_keys[1]				, '</s>' )
        self.assertEqual(vocab_keys[-1]				, 'v' )
        self.assertEqual(len(lowerCAmelCase__ )				, 1_103 )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Any:




        '''simple docstring'''
        self.assertEqual(self.get_tokenizer().vocab_size				, 1_103 )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				List[str]:




        '''simple docstring'''
        lowercase__:   Dict  			=   self.rust_tokenizer_class.from_pretrained(self.tmpdirname )
        lowercase__:   Optional[int]  			=   self.tokenizer_class.from_pretrained(self.tmpdirname )
        lowercase__:   Optional[Any]  			=   (
            'Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'
            ' </s> <pad> <pad> <pad>'
        )
        lowercase__:   Dict  			=   rust_tokenizer([raw_input_str]				, return_tensors=lowerCAmelCase__				, add_special_tokens=lowerCAmelCase__ ).input_ids[0]
        lowercase__:   Tuple  			=   py_tokenizer([raw_input_str]				, return_tensors=lowerCAmelCase__				, add_special_tokens=lowerCAmelCase__ ).input_ids[0]
        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				List[Any]:




        '''simple docstring'''
        lowercase__:   int  			=   self._large_tokenizer
        # <mask_1> masks whole sentence while <mask_2> masks single word
        lowercase__:   Any  			=   '<mask_1> To ensure a <mask_2> flow of bank resolutions.'
        lowercase__:   Union[str, Any]  			=   [2, 413, 615, 114, 3, 1_971, 113, 1_679, 10_710, 107, 1]
        lowercase__:   int  			=   tokenizer([raw_input_str]				, return_tensors=lowerCAmelCase__ ).input_ids[0]
        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Dict:




        '''simple docstring'''
        lowercase__:   Optional[int]  			=   self._large_tokenizer
        # The tracebacks for the following asserts are **better** without messages or self.assertEqual
        assert tokenizer.vocab_size == 96_103
        assert tokenizer.pad_token_id == 0
        assert tokenizer.eos_token_id == 1
        assert tokenizer.offset == 103
        assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
        assert tokenizer.unk_token == "<unk>"
        assert tokenizer.model_max_length == 1_024
        lowercase__:   int  			=   'To ensure a smooth flow of bank resolutions.'
        lowercase__:   Any  			=   [413, 615, 114, 2_291, 1_971, 113, 1_679, 10_710, 107, 1]
        lowercase__:   str  			=   tokenizer([raw_input_str]				, return_tensors=lowerCAmelCase__ ).input_ids[0]
        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
        assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3] ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]
 @require_torch
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Dict:




        '''simple docstring'''
        lowercase__:   Any  			=   ['This is going to be way too long.' * 150, 'short example']
        lowercase__:   Tuple  			=   ['not super long but more than 5 tokens', 'tiny']
        lowercase__:   Dict  			=   self._large_tokenizer(lowerCAmelCase__				, padding=lowerCAmelCase__				, truncation=lowerCAmelCase__				, return_tensors='pt' )
        lowercase__:   Any  			=   self._large_tokenizer(
            text_target=lowerCAmelCase__				, max_length=5				, padding=lowerCAmelCase__				, truncation=lowerCAmelCase__				, return_tensors='pt' )

        assert batch.input_ids.shape == (2, 1_024)
        assert batch.attention_mask.shape == (2, 1_024)
        assert targets["input_ids"].shape == (2, 5)
        assert len(lowerCAmelCase__ ) == 2  # input_ids, attention_mask.
 @slow
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				List[Any]:




        '''simple docstring'''
        # fmt: off
        lowercase__:   List[str]  			=   {'input_ids': [[38_979, 143, 18_485, 606, 130, 26_669, 87_686, 121, 54_189, 1_129, 111, 26_669, 87_686, 121, 9_114, 14_787, 121, 13_249, 158, 592, 956, 121, 14_621, 31_576, 143, 62_613, 108, 9_688, 930, 43_430, 11_562, 62_613, 304, 108, 11_443, 897, 108, 9_314, 17_415, 63_399, 108, 11_443, 7_614, 18_316, 118, 4_284, 7_148, 12_430, 143, 1_400, 25_703, 158, 111, 4_284, 7_148, 11_772, 143, 21_297, 1_064, 158, 122, 204, 3_506, 1_754, 1_133, 14_787, 1_581, 115, 33_224, 4_482, 111, 1_355, 110, 29_173, 317, 50_833, 108, 20_147, 94_665, 111, 77_198, 107, 1], [110, 62_613, 117, 638, 112, 1_133, 121, 20_098, 1_355, 79_050, 13_872, 135, 1_596, 53_541, 1_352, 141, 13_039, 5_542, 124, 302, 518, 111, 268, 2_956, 115, 149, 4_427, 107, 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], [139, 1_235, 2_799, 18_289, 17_780, 204, 109, 9_474, 1_296, 107, 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]], '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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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=lowerCAmelCase__				, model_name='google/bigbird-pegasus-large-arxiv'				, revision='ba85d0851d708441f91440d509690f1ab6353415'				, )





@require_sentencepiece
@require_tokenizers
class   __a			(    __UpperCamelCase       ,       unittest.TestCase      ):
 __lowercase :							int        = PegasusTokenizer
 __lowercase :							Any        = PegasusTokenizerFast
 __lowercase :							Any        = True
 __lowercase :							Dict        = True
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Union[str, Any]:




        '''simple docstring'''
        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase__:   Union[str, Any]  			=   PegasusTokenizer(lowerCAmelCase__				, offset=0				, mask_token_sent=lowerCAmelCase__				, mask_token='[MASK]' )
        tokenizer.save_pretrained(self.tmpdirname )
 @cached_property
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				str:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained('google/bigbird-pegasus-large-arxiv' )
 def 		SCREAMING_SNAKE_CASE__   (   self				, **lowerCAmelCase__ )					->				PegasusTokenizer:




        '''simple docstring'''
        return PegasusTokenizer.from_pretrained(self.tmpdirname				, **lowerCAmelCase__ )
 def 		SCREAMING_SNAKE_CASE__   (   self				, lowerCAmelCase__ )					->				Optional[int]:




        '''simple docstring'''
        return ("This is a test", "This is a test")
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				List[str]:




        '''simple docstring'''
        lowercase__:   str  			=   self.rust_tokenizer_class.from_pretrained(self.tmpdirname )
        lowercase__:   str  			=   self.tokenizer_class.from_pretrained(self.tmpdirname )
        lowercase__:   Tuple  			=   (
            'Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'
            ' <pad> <pad> <pad>'
        )
        lowercase__:   List[Any]  			=   rust_tokenizer([raw_input_str]				, return_tensors=lowerCAmelCase__				, add_special_tokens=lowerCAmelCase__ ).input_ids[0]
        lowercase__:   Any  			=   py_tokenizer([raw_input_str]				, return_tensors=lowerCAmelCase__				, add_special_tokens=lowerCAmelCase__ ).input_ids[0]
        self.assertListEqual(lowerCAmelCase__				, lowerCAmelCase__ )
 @require_torch
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				int:




        '''simple docstring'''
        lowercase__:   List[Any]  			=   ['This is going to be way too long.' * 1_000, 'short example']
        lowercase__:   str  			=   ['not super long but more than 5 tokens', 'tiny']
        lowercase__:   Tuple  			=   self._large_tokenizer(lowerCAmelCase__				, padding=lowerCAmelCase__				, truncation=lowerCAmelCase__				, return_tensors='pt' )
        lowercase__:   Dict  			=   self._large_tokenizer(
            text_target=lowerCAmelCase__				, max_length=5				, padding=lowerCAmelCase__				, truncation=lowerCAmelCase__				, return_tensors='pt' )

        assert batch.input_ids.shape == (2, 4_096)
        assert batch.attention_mask.shape == (2, 4_096)
        assert targets["input_ids"].shape == (2, 5)
        assert len(lowerCAmelCase__ ) == 2  # input_ids, attention_mask.
 def 		SCREAMING_SNAKE_CASE__   (   self )					->				Tuple:




        '''simple docstring'''
        lowercase__:   str  			=   (
            'This is an example string that is used to test the original TF implementation against the HF'
            ' implementation'
        )

        lowercase__:   Optional[int]  			=   self._large_tokenizer(lowerCAmelCase__ ).input_ids

        self.assertListEqual(
            lowerCAmelCase__				, [182, 117, 142, 587, 4_211, 120, 117, 263, 112, 804, 109, 856, 25_016, 3_137, 464, 109, 26_955, 3_137, 1]				, )


