




"""simple docstring"""







import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
       import torch

if is_vision_available():
       from PIL import Image

       from transformers import PoolFormerImageProcessor







class  UpperCamelCase	(    unittest.TestCase						):
   def __init__(    self  ,__UpperCamelCase  ,__UpperCamelCase=7  ,__UpperCamelCase=3  ,__UpperCamelCase=30  ,__UpperCamelCase=400  ,__UpperCamelCase=True  ,__UpperCamelCase=None  ,__UpperCamelCase=0.9  ,__UpperCamelCase=None  ,__UpperCamelCase=True  ,__UpperCamelCase=[0.5, 0.5, 0.5]  ,__UpperCamelCase=[0.5, 0.5, 0.5]  ,)			->   Tuple:


        '''simple docstring'''


        lowercase_			:       Optional[int]									=			size if size is not None else {'shortest_edge': 30}
        lowercase_			:       Tuple									=			crop_size if crop_size is not None else {'height': 30, 'width': 30}
        lowercase_			:       Any									=			parent
        lowercase_			:       Optional[Any]									=			batch_size
        lowercase_			:       Union[str, Any]									=			num_channels
        lowercase_			:       List[Any]									=			min_resolution
        lowercase_			:       Tuple									=			max_resolution
        lowercase_			:       Any									=			do_resize_and_center_crop
        lowercase_			:       Optional[int]									=			size
        lowercase_			:       List[str]									=			crop_pct
        lowercase_			:       str									=			crop_size
        lowercase_			:       List[Any]									=			do_normalize
        lowercase_			:       Optional[Any]									=			image_mean
        lowercase_			:       int									=			image_std







   def     _UpperCAmelCase     (    self    )			->   str:


        '''simple docstring'''


        return {
            "size": self.size,
            "do_resize_and_center_crop": self.do_resize_and_center_crop,
            "crop_pct": self.crop_pct,
            "crop_size": self.crop_size,
            "do_normalize": self.do_normalize,
            "image_mean": self.image_mean,
            "image_std": self.image_std,
        }







@require_torch
@require_vision
class  UpperCamelCase	(    lowercase_		,   unittest.TestCase						):
   lowercase							=						PoolFormerImageProcessor if is_vision_available() else None
   def     _UpperCAmelCase     (    self    )			->   List[str]:


        '''simple docstring'''


        lowercase_			:       int									=			PoolFormerImageProcessingTester(self    )
   @property
   def     _UpperCAmelCase     (    self    )			->   List[Any]:


        '''simple docstring'''


        return self.image_processor_tester.prepare_image_processor_dict()
   def     _UpperCAmelCase     (    self    )			->   str:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			self.image_processing_class(**self.image_processor_dict    )
        self.assertTrue(hasattr(__UpperCamelCase  ,'do_resize_and_center_crop'    )    )
        self.assertTrue(hasattr(__UpperCamelCase  ,'size'    )    )
        self.assertTrue(hasattr(__UpperCamelCase  ,'crop_pct'    )    )
        self.assertTrue(hasattr(__UpperCamelCase  ,'do_normalize'    )    )
        self.assertTrue(hasattr(__UpperCamelCase  ,'image_mean'    )    )
        self.assertTrue(hasattr(__UpperCamelCase  ,'image_std'    )    )
   def     _UpperCAmelCase     (    self    )			->   int:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			self.image_processing_class.from_dict(self.image_processor_dict    )
        self.assertEqual(image_processor.size  ,{'shortest_edge': 30}    )
        self.assertEqual(image_processor.crop_size  ,{'height': 30, 'width': 30}    )

        lowercase_			:       Union[str, Any]									=			self.image_processing_class.from_dict(self.image_processor_dict  ,size=42  ,crop_size=84    )
        self.assertEqual(image_processor.size  ,{'shortest_edge': 42}    )
        self.assertEqual(image_processor.crop_size  ,{'height': 84, 'width': 84}    )
   def     _UpperCAmelCase     (    self    )			->   Union[str, Any]:


        '''simple docstring'''


        pass
   def     _UpperCAmelCase     (    self    )			->   Optional[int]:


        '''simple docstring'''


        lowercase_			:       str									=			self.image_processing_class(**self.image_processor_dict    )
        # create random PIL images
        lowercase_			:       Union[str, Any]									=			prepare_image_inputs(self.image_processor_tester  ,equal_resolution=__UpperCamelCase    )
        for image in image_inputs:
             self.assertIsInstance(__UpperCamelCase  ,Image.Image    )

        # Test not batched input
        lowercase_			:       Dict									=			image_processing(image_inputs[0]  ,return_tensors='pt'    ).pixel_values

        self.assertEqual(
            encoded_images.shape  ,(
                1,
                self.image_processor_tester.num_channels,
                self.image_processor_tester.crop_size['height'],
                self.image_processor_tester.crop_size['width'],
            )  ,)

        # Test batched
        lowercase_			:       Union[str, Any]									=			image_processing(__UpperCamelCase  ,return_tensors='pt'    ).pixel_values
        self.assertEqual(
            encoded_images.shape  ,(
                self.image_processor_tester.batch_size,
                self.image_processor_tester.num_channels,
                self.image_processor_tester.crop_size['height'],
                self.image_processor_tester.crop_size['width'],
            )  ,)
   def     _UpperCAmelCase     (    self    )			->   Optional[int]:


        '''simple docstring'''


        lowercase_			:       int									=			self.image_processing_class(**self.image_processor_dict    )
        # create random numpy tensors
        lowercase_			:       Tuple									=			prepare_image_inputs(self.image_processor_tester  ,equal_resolution=__UpperCamelCase  ,numpify=__UpperCamelCase    )
        for image in image_inputs:
             self.assertIsInstance(__UpperCamelCase  ,np.ndarray    )

        # Test not batched input
        lowercase_			:       Tuple									=			image_processing(image_inputs[0]  ,return_tensors='pt'    ).pixel_values
        self.assertEqual(
            encoded_images.shape  ,(
                1,
                self.image_processor_tester.num_channels,
                self.image_processor_tester.crop_size['height'],
                self.image_processor_tester.crop_size['width'],
            )  ,)

        # Test batched
        lowercase_			:       Dict									=			image_processing(__UpperCamelCase  ,return_tensors='pt'    ).pixel_values
        self.assertEqual(
            encoded_images.shape  ,(
                self.image_processor_tester.batch_size,
                self.image_processor_tester.num_channels,
                self.image_processor_tester.crop_size['height'],
                self.image_processor_tester.crop_size['width'],
            )  ,)







   def     _UpperCAmelCase     (    self    )			->   Any:


        '''simple docstring'''


        lowercase_			:       int									=			self.image_processing_class(**self.image_processor_dict    )
        # create random PyTorch tensors
        lowercase_			:       Dict									=			prepare_image_inputs(self.image_processor_tester  ,equal_resolution=__UpperCamelCase  ,torchify=__UpperCamelCase    )
        for image in image_inputs:
             self.assertIsInstance(__UpperCamelCase  ,torch.Tensor    )

        # Test not batched input
        lowercase_			:       Dict									=			image_processing(image_inputs[0]  ,return_tensors='pt'    ).pixel_values
        self.assertEqual(
            encoded_images.shape  ,(
                1,
                self.image_processor_tester.num_channels,
                self.image_processor_tester.crop_size['height'],
                self.image_processor_tester.crop_size['width'],
            )  ,)

        # Test batched
        lowercase_			:       Union[str, Any]									=			image_processing(__UpperCamelCase  ,return_tensors='pt'    ).pixel_values
        self.assertEqual(
            encoded_images.shape  ,(
                self.image_processor_tester.batch_size,
                self.image_processor_tester.num_channels,
                self.image_processor_tester.crop_size['height'],
                self.image_processor_tester.crop_size['width'],
            )  ,)


"""simple docstring"""







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


__SCREAMING_SNAKE_CASE								=get_tests_dir("fixtures/spiece.model")







@require_sentencepiece
@require_tokenizers
class  UpperCamelCase	(    lowercase_		,   unittest.TestCase						):
   lowercase							=						DebertaVaTokenizer
   lowercase							=						DebertaVaTokenizerFast
   lowercase							=						True
   lowercase							=						True
   def     _UpperCAmelCase     (    self    )			->   List[str]:


        '''simple docstring'''


        super().setUp()

        # We have a SentencePiece fixture for testing
        lowercase_			:       Any									=			DebertaVaTokenizer(__UpperCamelCase  ,unk_token='<unk>'    )
        tokenizer.save_pretrained(self.tmpdirname    )
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase    )			->   Any:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			'this is a test'
        lowercase_			:       str									=			'this is a test'
        return input_text, output_text
   def     _UpperCAmelCase     (    self    )			->   Optional[Any]:


        '''simple docstring'''


        lowercase_			:       Optional[int]									=			'<pad>'
        lowercase_			:       str									=			0

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(__UpperCamelCase    )  ,__UpperCamelCase    )
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(__UpperCamelCase    )  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Optional[int]:


        '''simple docstring'''


        lowercase_			:       Union[str, Any]									=			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(__UpperCamelCase    )  ,3_0001    )
   def     _UpperCAmelCase     (    self    )			->   int:


        '''simple docstring'''


        self.assertEqual(self.get_tokenizer().vocab_size  ,3_0000    )
   def     _UpperCAmelCase     (    self    )			->   List[str]:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			' \tHeLLo!how  \n Are yoU?  '
        lowercase_			:       Optional[int]									=			['▁hello', '!', 'how', '▁are', '▁you', '?']
        # fmt: on

        lowercase_			:       int									=			DebertaVaTokenizer(__UpperCamelCase  ,do_lower_case=__UpperCamelCase    )
        lowercase_			:       Optional[int]									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Optional[Any]									=			DebertaVaTokenizerFast(__UpperCamelCase  ,do_lower_case=__UpperCamelCase    )
        lowercase_			:       Dict									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   @unittest.skip('There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'    )
   def     _UpperCAmelCase     (    self    )			->   Union[str, Any]:


        '''simple docstring'''


        pass
   @unittest.skip('There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'    )
   def     _UpperCAmelCase     (    self    )			->   Tuple:


        '''simple docstring'''


        pass
   def     _UpperCAmelCase     (    self    )			->   List[Any]:


        '''simple docstring'''


        lowercase_			:       Any									=			'I was born in 92000, and this is falsé.'
        lowercase_			:       Union[str, Any]									=			['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', '▁', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '▁', '.', ]
        # fmt: on

        lowercase_			:       List[str]									=			DebertaVaTokenizer(__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       Optional[Any]									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Any									=			DebertaVaTokenizerFast(__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       Tuple									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Tuple:


        '''simple docstring'''


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

        lowercase_			:       List[str]									=			DebertaVaTokenizer(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       Dict									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Tuple									=			DebertaVaTokenizerFast(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       Dict									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       str									=			'I was born in 92000, and this is falsé.'
        lowercase_			:       Optional[Any]									=			['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.', ]
        # fmt: on

        lowercase_			:       Union[str, Any]									=			DebertaVaTokenizer(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       Dict									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Tuple									=			DebertaVaTokenizerFast(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       Tuple									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       Tuple									=			'I was born in 92000, and this is falsé.'
        lowercase_			:       Optional[int]									=			['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', '▁', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '▁', '.', ]
        # fmt: on

        lowercase_			:       Optional[int]									=			DebertaVaTokenizer(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       str									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Union[str, Any]									=			DebertaVaTokenizerFast(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       List[Any]									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Optional[Any]:


        '''simple docstring'''


        lowercase_			:       Tuple									=			' \tHeLLo!how  \n Are yoU?  '
        lowercase_			:       List[str]									=			['▁', '<unk>', 'e', '<unk>', 'o', '!', 'how', '▁', '<unk>', 're', '▁yo', '<unk>', '?']
        # fmt: on

        lowercase_			:       str									=			DebertaVaTokenizer(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       int									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Union[str, Any]									=			DebertaVaTokenizerFast(__UpperCamelCase  ,do_lower_case=__UpperCamelCase  ,split_by_punct=__UpperCamelCase    )
        lowercase_			:       List[Any]									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )

        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   List[Any]:


        '''simple docstring'''


        lowercase_			:       Optional[int]									=			self.get_tokenizer()
        lowercase_			:       int									=			self.get_rust_tokenizer()

        lowercase_			:       Dict									=			'I was born in 92000, and this is falsé.'

        lowercase_			:       Any									=			tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )
        lowercase_			:       Union[str, Any]									=			rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Optional[int]									=			tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )
        lowercase_			:       str									=			rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Optional[int]									=			self.get_rust_tokenizer()
        lowercase_			:       Optional[Any]									=			tokenizer.encode(__UpperCamelCase    )
        lowercase_			:       Dict									=			rust_tokenizer.encode(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       Optional[int]									=			'This is a test'
        lowercase_			:       Any									=			[13, 1, 4398, 25, 21, 1289]
        lowercase_			:       Union[str, Any]									=			['▁', 'T', 'his', '▁is', '▁a', '▁test']
        lowercase_			:       str									=			['▁', '<unk>', 'his', '▁is', '▁a', '▁test']

        lowercase_			:       Optional[int]									=			DebertaVaTokenizer(__UpperCamelCase  ,keep_accents=__UpperCamelCase    )
        lowercase_			:       str									=			DebertaVaTokenizerFast(__UpperCamelCase  ,keep_accents=__UpperCamelCase    )

        lowercase_			:       Optional[int]									=			tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       List[Any]									=			tokenizer.tokenize(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       Any									=			tokenizer.convert_ids_to_tokens(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       str									=			rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       Optional[int]									=			rust_tokenizer.tokenize(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       str									=			rust_tokenizer.convert_ids_to_tokens(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        # fmt: off
        lowercase_			:       List[Any]									=			'I was born in 92000, and this is falsé.'
        lowercase_			:       int									=			[13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
        lowercase_			:       List[str]									=			['▁', 'I', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.', ]
        lowercase_			:       List[str]									=			['▁', '<unk>', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.', ]
        # fmt: on

        lowercase_			:       List[str]									=			tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       List[str]									=			tokenizer.tokenize(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       List[Any]									=			tokenizer.convert_ids_to_tokens(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )

        lowercase_			:       Tuple									=			rust_tokenizer.encode(__UpperCamelCase  ,add_special_tokens=__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       Optional[int]									=			rust_tokenizer.tokenize(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
        lowercase_			:       Dict									=			rust_tokenizer.convert_ids_to_tokens(__UpperCamelCase    )
        self.assertListEqual(__UpperCamelCase  ,__UpperCamelCase    )
   def     _UpperCAmelCase     (    self    )			->   Dict:


        '''simple docstring'''


        lowercase_			:       Dict									=			DebertaVaTokenizer(__UpperCamelCase    )

        lowercase_			:       int									=			tokenizer.encode('sequence builders'    )
        lowercase_			:       Tuple									=			tokenizer.encode('multi-sequence build'    )

        lowercase_			:       Dict									=			tokenizer.build_inputs_with_special_tokens(__UpperCamelCase    )
        lowercase_			:       Optional[int]									=			tokenizer.build_inputs_with_special_tokens(__UpperCamelCase  ,__UpperCamelCase    )

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







   @slow
   def     _UpperCAmelCase     (    self    )			->   List[str]:


        '''simple docstring'''


        lowercase_			:       List[Any]									=			{'input_ids': [[1, 3_9867, 36, 1_9390, 486, 27, 3_5052, 8_1436, 18, 6_0685, 1225, 7, 3_5052, 8_1436, 18, 9367, 1_6899, 18, 1_5937, 53, 594, 773, 18, 1_6287, 3_0465, 36, 1_5937, 6, 4_1139, 38, 3_6979, 6_0763, 191, 6, 3_4132, 99, 6, 5_0538, 390, 4_3230, 6, 3_4132, 2779, 2_0850, 14, 699, 1072, 1194, 36, 382, 1_0901, 53, 7, 699, 1072, 2084, 36, 2_0422, 630, 53, 19, 105, 3049, 1896, 1053, 1_6899, 1506, 11, 3_7978, 4243, 7, 1237, 3_1869, 200, 1_6566, 654, 6, 3_5052, 8_1436, 7, 5_5630, 1_3593, 4, 2], [1, 26, 1_5011, 13, 667, 8, 1053, 18, 2_3611, 1237, 7_2356, 1_2820, 34, 10_4134, 1209, 35, 1_3313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 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, 1232, 2864, 1_5785, 1_4951, 105, 5, 8581, 1250, 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=__UpperCamelCase  ,model_name='microsoft/deberta-v2-xlarge'  ,revision='ad6e42c1532ddf3a15c39246b63f5559d558b670'  ,)

