





import warnings
from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType





class 				a			(      __lowercase			):
				SCREAMING_SNAKE_CASE__     :   int		      =     ['''image_processor''', '''tokenizer''']
				SCREAMING_SNAKE_CASE__     :   Tuple		      =     '''ViltImageProcessor'''
				SCREAMING_SNAKE_CASE__     :   Optional[int]		      =     ('''BertTokenizer''', '''BertTokenizerFast''')






				def __init__(  self			, _lowerCAmelCase=None			, _lowerCAmelCase=None			, **_lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Any           =   None
										if "feature_extractor" in kwargs:
																warnings.warn(
																    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
																    ''' instead.'''			, _lowerCAmelCase			, )
																__SCREAMING_SNAKE_CASE:				Dict           =   kwargs.pop('''feature_extractor'''					)

										__SCREAMING_SNAKE_CASE:				Tuple           =   image_processor if image_processor is not None else feature_extractor
										if image_processor is None:
																raise ValueError('''You need to specify an `image_processor`.'''					)
										if tokenizer is None:
																raise ValueError('''You need to specify a `tokenizer`.'''					)

										super().__init__(_lowerCAmelCase			, _lowerCAmelCase					)
										__SCREAMING_SNAKE_CASE:				int           =   self.image_processor






				def __call__(  self			, _lowerCAmelCase			, _lowerCAmelCase = None			, _lowerCAmelCase = True			, _lowerCAmelCase = False			, _lowerCAmelCase = None			, _lowerCAmelCase = None			, _lowerCAmelCase = 0			, _lowerCAmelCase = None			, _lowerCAmelCase = None			, _lowerCAmelCase = None			, _lowerCAmelCase = False			, _lowerCAmelCase = False			, _lowerCAmelCase = False			, _lowerCAmelCase = False			, _lowerCAmelCase = True			, _lowerCAmelCase = None			, **_lowerCAmelCase			, ):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   self.tokenizer(
										    text=_lowerCAmelCase			, add_special_tokens=_lowerCAmelCase			, padding=_lowerCAmelCase			, truncation=_lowerCAmelCase			, max_length=_lowerCAmelCase			, stride=_lowerCAmelCase			, pad_to_multiple_of=_lowerCAmelCase			, return_token_type_ids=_lowerCAmelCase			, return_attention_mask=_lowerCAmelCase			, return_overflowing_tokens=_lowerCAmelCase			, return_special_tokens_mask=_lowerCAmelCase			, return_offsets_mapping=_lowerCAmelCase			, return_length=_lowerCAmelCase			, verbose=_lowerCAmelCase			, return_tensors=_lowerCAmelCase			, **_lowerCAmelCase			, )
										# add pixel_values + pixel_mask
										__SCREAMING_SNAKE_CASE:				List[Any]           =   self.image_processor(_lowerCAmelCase			, return_tensors=_lowerCAmelCase					)
										encoding.update(_lowerCAmelCase					)

										return encoding






				def 			snake_case_    (  self			, *_lowerCAmelCase			, **_lowerCAmelCase					):

										"""simple docstring"""




										return self.tokenizer.batch_decode(*_lowerCAmelCase			, **_lowerCAmelCase					)






				def 			snake_case_    (  self			, *_lowerCAmelCase			, **_lowerCAmelCase					):

										"""simple docstring"""




										return self.tokenizer.decode(*_lowerCAmelCase			, **_lowerCAmelCase					)






				@property
				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Optional[int]           =   self.tokenizer.model_input_names
										__SCREAMING_SNAKE_CASE:				Tuple           =   self.image_processor.model_input_names
										return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names					)					)






				@property
				def 			snake_case_    (  self					):

										"""simple docstring"""




										warnings.warn(
										    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''			, _lowerCAmelCase			, )
										return self.image_processor_class






				@property
				def 			snake_case_    (  self					):

										"""simple docstring"""




										warnings.warn(
										    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''			, _lowerCAmelCase			, )
										return self.image_processor










def 		lowerCAmelCase  (	UpperCamelCase__   :   list       ,			UpperCamelCase__   :   list       ,			UpperCamelCase__   :   int					)      ->    list:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				Tuple           =   len(UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				Optional[int]           =   [[0] * n for i in range(UpperCamelCase__					)]
						for i in range(UpperCamelCase__					):
												__SCREAMING_SNAKE_CASE:				str           =   y_points[i]

						for i in range(2       ,			UpperCamelCase__					):
												for j in range(UpperCamelCase__       ,			UpperCamelCase__					):
																		__SCREAMING_SNAKE_CASE:				Optional[int]           =   (
																		    (xa - x_points[j - i + 1]) * q[j][i - 1]
																		    - (xa - x_points[j]) * q[j - 1][i - 1]
																		) / (x_points[j] - x_points[j - i + 1])

						return [q[n - 1][n - 1], q]


if __name__ == "__main__":
							import doctest

							doctest.testmod()



