

"""simple docstring"""





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 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					lowercase__				 =       ["image_processor", "tokenizer"]
					lowercase__				 =       "ViltImageProcessor"
					lowercase__				 =       ("BertTokenizer", "BertTokenizerFast")







					def __init__(       self			:				List[Any]   ,lowercase_			:				int=None   ,lowercase_			:				int=None   ,**lowercase_			:				Union[str, Any]		):
						lowerCAmelCase__	:						List[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.'''   ,lowercase_   ,)
							lowerCAmelCase__	:						Optional[Any]  				=	kwargs.pop('''feature_extractor'''		)

						lowerCAmelCase__	:						List[str]  				=	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__(lowercase_   ,lowercase_		)
						lowerCAmelCase__	:						Optional[Any]  				=	self.image_processor







					def __call__(       self			:				Tuple   ,lowercase_			:				Tuple   ,lowercase_			:				Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None   ,lowercase_			:				bool = True   ,lowercase_			:				Union[bool, str, PaddingStrategy] = False   ,lowercase_			:				Union[bool, str, TruncationStrategy] = None   ,lowercase_			:				Optional[int] = None   ,lowercase_			:				int = 0   ,lowercase_			:				Optional[int] = None   ,lowercase_			:				Optional[bool] = None   ,lowercase_			:				Optional[bool] = None   ,lowercase_			:				bool = False   ,lowercase_			:				bool = False   ,lowercase_			:				bool = False   ,lowercase_			:				bool = False   ,lowercase_			:				bool = True   ,lowercase_			:				Optional[Union[str, TensorType]] = None   ,**lowercase_			:				List[str]   ,):
						lowerCAmelCase__	:						List[Any]  				=	self.tokenizer(
						    text=lowercase_   ,add_special_tokens=lowercase_   ,padding=lowercase_   ,truncation=lowercase_   ,max_length=lowercase_   ,stride=lowercase_   ,pad_to_multiple_of=lowercase_   ,return_token_type_ids=lowercase_   ,return_attention_mask=lowercase_   ,return_overflowing_tokens=lowercase_   ,return_special_tokens_mask=lowercase_   ,return_offsets_mapping=lowercase_   ,return_length=lowercase_   ,verbose=lowercase_   ,return_tensors=lowercase_   ,**lowercase_   ,)
						# add pixel_values + pixel_mask
						lowerCAmelCase__	:						Optional[Any]  				=	self.image_processor(lowercase_   ,return_tensors=lowercase_		)
						encoding.update(lowercase_		)

						return encoding







					def        __lowerCAmelCase (       self			:				Tuple   ,*lowercase_			:				Any   ,**lowercase_			:				List[str]		):
						return self.tokenizer.batch_decode(*lowercase_   ,**lowercase_		)







					def        __lowerCAmelCase (       self			:				Tuple   ,*lowercase_			:				str   ,**lowercase_			:				Tuple		):
						return self.tokenizer.decode(*lowercase_   ,**lowercase_		)







					@property
					def        __lowerCAmelCase (       self			:				int		):
						lowerCAmelCase__	:						Tuple  				=	self.tokenizer.model_input_names
						lowerCAmelCase__	:						Optional[Any]  				=	self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)







					@property
					def        __lowerCAmelCase (       self			:				Union[str, Any]		):
						warnings.warn(
						    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''   ,lowercase_   ,)
						return self.image_processor_class







					@property
					def        __lowerCAmelCase (       self			:				int		):
						warnings.warn(
						    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''   ,lowercase_   ,)
						return self.image_processor











"""simple docstring"""




from __future__ import annotations






def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    list[int]    ,       _lowercase						:    int					) ->int:






	'''simple docstring'''






	if len(_lowercase					) < k or k < 0:
		raise ValueError("Invalid Input"					)
	a      :		Optional[Any]	=				sum(array[:k]					)
	for i in range(len(_lowercase					) - k					):
		a      :		Optional[Any]	=				current_sum - array[i] + array[i + k]
		a      :		Union[str, Any]	=				max(_lowercase    ,       _lowercase					)
	return max_sum


if __name__ == "__main__":
		from doctest import testmod
		from random import randint

		testmod()
		a						: Any     	=			[randint(-1000, 1000) for i in range(100)]
		a						: List[str]     	=			randint(0, 110)
		print(F'''The maximum sum of {k} consecutive elements is {max_sum_in_array(array,k)}''')


