


from transformers import (
    DPRContextEncoderTokenizer,
    DPRContextEncoderTokenizerFast,
    DPRQuestionEncoderTokenizer,
    DPRQuestionEncoderTokenizerFast,
    DPRReaderOutput,
    DPRReaderTokenizer,
    DPRReaderTokenizerFast,
)
from transformers.testing_utils import require_tokenizers, slow
from transformers.tokenization_utils_base import BatchEncoding

from ..bert.test_tokenization_bert import BertTokenizationTest







@require_tokenizers
class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = DPRContextEncoderTokenizer
 SCREAMING_SNAKE_CASE__   = DPRContextEncoderTokenizerFast
 SCREAMING_SNAKE_CASE__   = True







@require_tokenizers
class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = DPRQuestionEncoderTokenizer
 SCREAMING_SNAKE_CASE__   = DPRQuestionEncoderTokenizerFast
 SCREAMING_SNAKE_CASE__   = True







@require_tokenizers
class 	_snake_case						(   _snake_case							):
 SCREAMING_SNAKE_CASE__   = DPRReaderTokenizer
 SCREAMING_SNAKE_CASE__   = DPRReaderTokenizerFast
 SCREAMING_SNAKE_CASE__   = True




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Optional[int]											= self.tokenizer_class.from_pretrained('''bert-base-uncased'''					)

       a		:str											= tokenizer.encode('''question sequence'''      ,						add_special_tokens=_lowerCamelCase					)
       a		:int											= tokenizer.encode('''title sequence'''      ,						add_special_tokens=_lowerCamelCase					)
       a		:Optional[Any]											= tokenizer.encode('''text sequence ''' * 4      ,						add_special_tokens=_lowerCamelCase					)
       a		:Any											= [[101] + text_a + [102] + text_a + [102] + text_a]
       a		:Optional[int]											= BatchEncoding({'''input_ids''': input_ids}					)

       a		:List[str]											= [[0] * len(input_ids[0]					)]
       a		:int											= [[0] * len(input_ids[0]					)]
       a		:List[str]											= [0]
       a		:int											= DPRReaderOutput(_lowerCamelCase      ,						_lowerCamelCase      ,						_lowerCamelCase					)

       a							,       a		:Union[str, Any]											= 8, 9
       a		:List[Any]											= 10
       a		:str											= 10
       a		:List[str]											= tokenizer.decode_best_spans(_lowerCamelCase      ,						_lowerCamelCase					)
       self.assertEqual(predicted_spans[0].start_index      ,						_lowerCamelCase					)
       self.assertEqual(predicted_spans[0].end_index      ,						_lowerCamelCase					)
       self.assertEqual(predicted_spans[0].doc_id      ,						0					)




 @slow
 def  SCREAMING_SNAKE_CASE__       (	self					):
       a		:Union[str, Any]											= self.tokenizer_class.from_pretrained('''bert-base-uncased'''					)

       a		:Union[str, Any]											= tokenizer.encode('''question sequence'''      ,						add_special_tokens=_lowerCamelCase					)
       a		:Any											= tokenizer.encode('''title sequence'''      ,						add_special_tokens=_lowerCamelCase					)
       a		:List[str]											= tokenizer.encode('''text sequence'''      ,						add_special_tokens=_lowerCamelCase					)
       a		:Optional[int]											= [101] + text_a + [102] + text_a + [102] + text_a
       a		:str											= tokenizer(questions=['''question sequence''']      ,						titles=['''title sequence''']      ,						texts=['''text sequence''']					)
       self.assertIn('''input_ids'''      ,						_lowerCamelCase					)
       self.assertIn('''attention_mask'''      ,						_lowerCamelCase					)
       self.assertListEqual(encoded_input['''input_ids'''][0]      ,						_lowerCamelCase					)









import warnings

from ...utils import logging
from .image_processing_convnext import ConvNextImageProcessor


snake_case       :					Tuple        =  logging.get_logger(__name__)







class 	_snake_case						(   _snake_case							):




 def __init__(	self      ,						*_lowerCamelCase      ,						**_lowerCamelCase					):
       warnings.warn(
           '''The class ConvNextFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
           ''' Please use ConvNextImageProcessor instead.'''      ,						_lowerCamelCase      ,						)
       super().__init__(*_lowerCamelCase      ,						**_lowerCamelCase					)





