
'''simple docstring'''





import unittest

from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device

from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import PipelineTesterMixin


if is_torch_available():
 import torch

 from transformers.models.trocr.modeling_trocr import TrOCRDecoder, TrOCRForCausalLM


@require_torch
class        UpperCamelCase__     :






 def __init__(	self     :Optional[Any]		, _A     :Optional[int]		, _A     :Optional[Any]=99		, _A     :Optional[int]=13		, _A     :int=16		, _A     :str=7		, _A     :List[Any]=True		, _A     :List[Any]=True		, _A     :Any=True		, _A     :List[str]=False		, _A     :int=True		, _A     :Union[str, Any]=2		, _A     :List[str]=32		, _A     :Optional[Any]=4		, _A     :int=4		, _A     :int=30		, _A     :Dict=0		, _A     :List[str]=1		, _A     :Union[str, Any]=2		, _A     :int=None		, ) ->	Optional[int]:







       '''simple docstring'''



       __A						=	parent
       __A						=	batch_size
       __A						=	decoder_seq_length
       # For common tests
       __A						=	self.decoder_seq_length
       __A						=	is_training
       __A						=	use_attention_mask
       __A						=	use_labels

       __A						=	vocab_size
       __A						=	d_model
       __A						=	d_model
       __A						=	decoder_layers
       __A						=	decoder_layers
       __A						=	decoder_ffn_dim
       __A						=	decoder_attention_heads
       __A						=	decoder_attention_heads
       __A						=	eos_token_id
       __A						=	bos_token_id
       __A						=	pad_token_id
       __A						=	decoder_start_token_id
       __A						=	use_cache
       __A						=	max_position_embeddings

       __A						=	None
       __A						=	decoder_seq_length
       __A						=	2
       __A						=	1






 def 		lowercase_  (	self     :List[str]	) ->	Any:







       '''simple docstring'''



       __A						=	ids_tensor([self.batch_size, self.decoder_seq_length]		, self.vocab_size	)

       __A						=	None
       if self.use_attention_mask:
             __A						=	ids_tensor([self.batch_size, self.decoder_seq_length]		, vocab_size=2	)

       __A						=	None
       if self.use_labels:
             __A						=	ids_tensor([self.batch_size, self.decoder_seq_length]		, self.vocab_size	)

       __A						=	TrOCRConfig(
           vocab_size=self.vocab_size		, d_model=self.d_model		, decoder_layers=self.decoder_layers		, decoder_ffn_dim=self.decoder_ffn_dim		, decoder_attention_heads=self.decoder_attention_heads		, eos_token_id=self.eos_token_id		, bos_token_id=self.bos_token_id		, use_cache=self.use_cache		, pad_token_id=self.pad_token_id		, decoder_start_token_id=self.decoder_start_token_id		, max_position_embeddings=self.max_position_embeddings		, )

       return (config, input_ids, attention_mask, lm_labels)






 def 		lowercase_  (	self     :int		, _A     :Tuple		, _A     :Union[str, Any]		, _A     :Dict		, _A     :Any		, ) ->	int:







       '''simple docstring'''



       __A						=	True
       __A						=	TrOCRDecoder(config=_A	).to(_A	).eval()
       __A						=	input_ids[:2]

       input_ids[input_ids == 0] += 1
       # first forward pass
       __A						=	model(_A		, use_cache=_A	)
       __A						=	model(_A	)
       __A						=	model(_A		, use_cache=_A	)

       self.parent.assertTrue(len(_A	) == len(_A	)	)
       self.parent.assertTrue(len(_A	) == len(_A	) + 1	)

       __A						=	outputs['past_key_values']

       # create hypothetical next token and extent to next_input_ids
       __A						=	ids_tensor((2, 1)		, config.vocab_size - 1	) + 1

       # append to next input_ids and
       __A						=	torch.cat([input_ids, next_tokens]		, dim=-1	)

       __A						=	model(_A	)['last_hidden_state']
       __A						=	model(_A		, past_key_values=_A	)['last_hidden_state']

       # select random slice
       __A						=	ids_tensor((1,)		, output_from_past.shape[-1]	).item()
       __A						=	output_from_no_past[:, next_input_ids.shape[-1] - 1, random_slice_idx].detach()
       __A						=	output_from_past[:, 0, random_slice_idx].detach()

       # test that outputs are equal for slice
       assert torch.allclose(_A		, _A		, atol=1E-3	)






 def 		lowercase_  (	self     :Optional[int]	) ->	Optional[Any]:







       '''simple docstring'''



       __A						=	self.prepare_config_and_inputs()
       __A		,					__A		,					__A		,					__A						=	config_and_inputs

       __A						=	{'input_ids': input_ids, 'attention_mask': attention_mask}
       return config, inputs_dict


@require_torch
class        UpperCamelCase__     (			snake_case__					,   snake_case__					,   snake_case__					,   unittest.TestCase):
 UpperCAmelCase__			:			List[Any]   =    (TrOCRDecoder, TrOCRForCausalLM) if is_torch_available() else ()
 UpperCAmelCase__			:			Dict   =    (TrOCRForCausalLM,) if is_torch_available() else ()
 UpperCAmelCase__			:			Union[str, Any]   =    {"""text-generation""": TrOCRForCausalLM} if is_torch_available() else {}
 UpperCAmelCase__			:			List[Any]   =    True
 UpperCAmelCase__			:			Dict   =    False






 def 		lowercase_  (	self     :Any	) ->	List[str]:







       '''simple docstring'''



       __A						=	TrOCRStandaloneDecoderModelTester(self		, is_training=_A	)
       __A						=	ConfigTester(self		, config_class=_A	)






 def 		lowercase_  (	self     :Optional[int]	) ->	Optional[int]:







       '''simple docstring'''



       pass






 def 		lowercase_  (	self     :List[Any]	) ->	Dict:







       '''simple docstring'''



       pass






 def 		lowercase_  (	self     :Any	) ->	Tuple:







       '''simple docstring'''



       pass






 def 		lowercase_  (	self     :Optional[int]	) ->	Optional[int]:







       '''simple docstring'''



       self.config_tester.run_common_tests()






 def 		lowercase_  (	self     :Optional[int]	) ->	Optional[Any]:







       '''simple docstring'''



       __A						=	self.model_tester.prepare_config_and_inputs()
       self.model_tester.create_and_check_decoder_model_past(*_A	)






 def 		lowercase_  (	self     :Union[str, Any]	) ->	Any:







       '''simple docstring'''



       return






 @unittest.skip('The model doesn\'t support left padding'	)  # and it's not used enough to be worth fixing :)
 def 		lowercase_  (	self     :Any	) ->	Union[str, Any]:







       '''simple docstring'''



       pass












import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase__    			=			get_tests_dir("""fixtures/spiece.model""")
@require_sentencepiece
@require_tokenizers
class 			a__    (					snake_case__ ,				unittest.TestCase      ):
						_a							:    Optional[Any]					=    DebertaVaTokenizer
						_a							:    Optional[Any]					=    DebertaVaTokenizerFast
						_a							:    List[str]					=    True
						_a							:    Optional[Any]					=    True






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											super().setUp()

											# We have a SentencePiece fixture for testing
											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			unk_token="<unk>"			)
											tokenizer.save_pretrained(self.tmpdirname			)






						def 				__SCREAMING_SNAKE_CASE(   self		,			_A			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "this is a test"
											__lowerCAmelCase				   =       "this is a test"
											return input_text, output_text






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "<pad>"
											__lowerCAmelCase				   =       0

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






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       list(self.get_tokenizer().get_vocab().keys()			)
											self.assertEqual(vocab_keys[0]		,			"<pad>"			)
											self.assertEqual(vocab_keys[1]		,			"<unk>"			)
											self.assertEqual(vocab_keys[-1]		,			"[PAD]"			)
											self.assertEqual(len(_A			)		,			3_0_0_0_1			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											self.assertEqual(self.get_tokenizer().vocab_size		,			3_0_0_0_0			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       " \tHeLLo!how  \n Are yoU?  "
											__lowerCAmelCase				   =       ["▁hello", "!", "how", "▁are", "▁you", "?"]
											# fmt: on

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			do_lower_case=_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			do_lower_case=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)






						@unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one."			)
						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											pass






						@unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one."			)
						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											pass






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "I was born in 92000, and this is falsé."
											__lowerCAmelCase				   =       ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
											# fmt: on

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "I was born in 92000, and this is falsé."
											__lowerCAmelCase				   =       ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
											# fmt: on

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)
											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)
											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "I was born in 92000, and this is falsé."
											__lowerCAmelCase				   =       ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
											# fmt: on

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "I was born in 92000, and this is falsé."
											__lowerCAmelCase				   =       ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
											# fmt: on

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       " \tHeLLo!how  \n Are yoU?  "
											__lowerCAmelCase				   =       ["▁", "<unk>", "e", "<unk>", "o", "!", "how", "▁", "<unk>", "re", "▁yo", "<unk>", "?"]
											# fmt: on

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			do_lower_case=_A		,			split_by_punct=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)

											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       self.get_tokenizer()
											__lowerCAmelCase				   =       self.get_rust_tokenizer()

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

											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(tokenizer.encode(_A		,			add_special_tokens=_A			)			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(_A		,			add_special_tokens=_A			)			)
											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       tokenizer.encode(_A		,			add_special_tokens=_A			)
											__lowerCAmelCase				   =       rust_tokenizer.encode(_A		,			add_special_tokens=_A			)
											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       self.get_rust_tokenizer()
											__lowerCAmelCase				   =       tokenizer.encode(_A			)
											__lowerCAmelCase				   =       rust_tokenizer.encode(_A			)
											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       "This is a test"
											__lowerCAmelCase				   =       [1_3, 1, 4_3_9_8, 2_5, 2_1, 1_2_8_9]
											__lowerCAmelCase				   =       ["▁", "T", "his", "▁is", "▁a", "▁test"]
											__lowerCAmelCase				   =       ["▁", "<unk>", "his", "▁is", "▁a", "▁test"]

											__lowerCAmelCase				   =       DebertaVaTokenizer(_A		,			keep_accents=_A			)
											__lowerCAmelCase				   =       DebertaVaTokenizerFast(_A		,			keep_accents=_A			)

											__lowerCAmelCase				   =       tokenizer.encode(_A		,			add_special_tokens=_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       tokenizer.tokenize(_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(_A			)
											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       rust_tokenizer.encode(_A		,			add_special_tokens=_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       rust_tokenizer.tokenize(_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(_A			)
											self.assertListEqual(_A		,			_A			)

											# fmt: off
											__lowerCAmelCase				   =       "I was born in 92000, and this is falsé."
											__lowerCAmelCase				   =       [1_3, 1, 2_3, 3_8_6, 1_9, 5_6_1, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]
											__lowerCAmelCase				   =       ["▁", "I", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", ".", ]
											__lowerCAmelCase				   =       ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
											# fmt: on

											__lowerCAmelCase				   =       tokenizer.encode(_A		,			add_special_tokens=_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       tokenizer.tokenize(_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       tokenizer.convert_ids_to_tokens(_A			)
											self.assertListEqual(_A		,			_A			)

											__lowerCAmelCase				   =       rust_tokenizer.encode(_A		,			add_special_tokens=_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       rust_tokenizer.tokenize(_A			)
											self.assertListEqual(_A		,			_A			)
											__lowerCAmelCase				   =       rust_tokenizer.convert_ids_to_tokens(_A			)
											self.assertListEqual(_A		,			_A			)






						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       DebertaVaTokenizer(_A			)

											__lowerCAmelCase				   =       tokenizer.encode("sequence builders"			)
											__lowerCAmelCase				   =       tokenizer.encode("multi-sequence build"			)

											__lowerCAmelCase				   =       tokenizer.build_inputs_with_special_tokens(_A			)
											__lowerCAmelCase				   =       tokenizer.build_inputs_with_special_tokens(_A		,			_A			)

											self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]		,			_A			)
											self.assertEqual(
											    [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]		,			_A		,			)






						@slow
						def 				__SCREAMING_SNAKE_CASE(   self			):




											"""simple docstring"""



											__lowerCAmelCase				   =       {"input_ids": [[1, 3_9_8_6_7, 3_6, 1_9_3_9_0, 4_8_6, 2_7, 3_5_0_5_2, 8_1_4_3_6, 1_8, 6_0_6_8_5, 1_2_2_5, 7, 3_5_0_5_2, 8_1_4_3_6, 1_8, 9_3_6_7, 1_6_8_9_9, 1_8, 1_5_9_3_7, 5_3, 5_9_4, 7_7_3, 1_8, 1_6_2_8_7, 3_0_4_6_5, 3_6, 1_5_9_3_7, 6, 4_1_1_3_9, 3_8, 3_6_9_7_9, 6_0_7_6_3, 1_9_1, 6, 3_4_1_3_2, 9_9, 6, 5_0_5_3_8, 3_9_0, 4_3_2_3_0, 6, 3_4_1_3_2, 2_7_7_9, 2_0_8_5_0, 1_4, 6_9_9, 1_0_7_2, 1_1_9_4, 3_6, 3_8_2, 1_0_9_0_1, 5_3, 7, 6_9_9, 1_0_7_2, 2_0_8_4, 3_6, 2_0_4_2_2, 6_3_0, 5_3, 1_9, 1_0_5, 3_0_4_9, 1_8_9_6, 1_0_5_3, 1_6_8_9_9, 1_5_0_6, 1_1, 3_7_9_7_8, 4_2_4_3, 7, 1_2_3_7, 3_1_8_6_9, 2_0_0, 1_6_5_6_6, 6_5_4, 6, 3_5_0_5_2, 8_1_4_3_6, 7, 5_5_6_3_0, 1_3_5_9_3, 4, 2], [1, 2_6, 1_5_0_1_1, 1_3, 6_6_7, 8, 1_0_5_3, 1_8, 2_3_6_1_1, 1_2_3_7, 7_2_3_5_6, 1_2_8_2_0, 3_4, 1_0_4_1_3_4, 1_2_0_9, 3_5, 1_3_3_1_3, 6_6_2_7, 2_1, 2_0_2, 3_4_7, 7, 1_6_4, 2_3_9_9, 1_1, 4_6, 4_4_8_5, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 5, 1_2_3_2, 2_8_6_4, 1_5_7_8_5, 1_4_9_5_1, 1_0_5, 5, 8_5_8_1, 1_2_5_0, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "token_type_ids": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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]]}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=_A		,			model_name="microsoft/deberta-v2-xlarge"		,			revision="ad6e42c1532ddf3a15c39246b63f5559d558b670"		,			)




