
from typing import List, Optional, Union

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





class     lowerCamelCase      (       __lowerCamelCase					):
	UpperCamelCase_  :					Any    		=	['image_processor', 'tokenizer']
	UpperCamelCase_  :					List[Any]    		=	'BlipImageProcessor'
	UpperCamelCase_  :					Any    		=	('BertTokenizer', 'BertTokenizerFast')







	def __init__(     self      :Optional[Any]   ,     lowercase      :Dict   ,     lowercase      :List[Any]			)		->      Any:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= False
				super().__init__(lowercase   ,     lowercase			)
				SCREAMING_SNAKE_CASE     						= self.image_processor







	def __call__(     self      :Optional[Any]   ,     lowercase      :ImageInput = None   ,     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      :bool = False   ,     lowercase      :bool = False   ,     lowercase      :bool = False   ,     lowercase      :bool = False   ,     lowercase      :bool = False   ,     lowercase      :bool = True   ,     lowercase      :Optional[Union[str, TensorType]] = None   ,     **lowercase      :Union[str, Any]   ,     )		->      BatchEncoding:







				"""simple docstring"""






				if images is None and text is None:
							raise ValueError('''You have to specify either images or text.'''			)

				# Get only text
				if images is None:
							SCREAMING_SNAKE_CASE     						= self.tokenizer
							SCREAMING_SNAKE_CASE     						= self.tokenizer(
							    text=lowercase   ,     add_special_tokens=lowercase   ,     padding=lowercase   ,     truncation=lowercase   ,     max_length=lowercase   ,     stride=lowercase   ,     pad_to_multiple_of=lowercase   ,     return_attention_mask=lowercase   ,     return_overflowing_tokens=lowercase   ,     return_special_tokens_mask=lowercase   ,     return_offsets_mapping=lowercase   ,     return_token_type_ids=lowercase   ,     return_length=lowercase   ,     verbose=lowercase   ,     return_tensors=lowercase   ,     **lowercase   ,     )
							return text_encoding

				# add pixel_values
				SCREAMING_SNAKE_CASE     						= self.image_processor(lowercase   ,     return_tensors=lowercase			)

				if text is not None:
							SCREAMING_SNAKE_CASE     						= self.tokenizer(
							    text=lowercase   ,     add_special_tokens=lowercase   ,     padding=lowercase   ,     truncation=lowercase   ,     max_length=lowercase   ,     stride=lowercase   ,     pad_to_multiple_of=lowercase   ,     return_attention_mask=lowercase   ,     return_overflowing_tokens=lowercase   ,     return_special_tokens_mask=lowercase   ,     return_offsets_mapping=lowercase   ,     return_token_type_ids=lowercase   ,     return_length=lowercase   ,     verbose=lowercase   ,     return_tensors=lowercase   ,     **lowercase   ,     )
				else:
							SCREAMING_SNAKE_CASE     						= None

				if text_encoding is not None:
							encoding_image_processor.update(lowercase			)

				return encoding_image_processor







	def  snake_case__     (     self      :List[str]   ,     *lowercase      :str   ,     **lowercase      :Dict			)		->      str:







				"""simple docstring"""






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







	def  snake_case__     (     self      :List[Any]   ,     *lowercase      :Any   ,     **lowercase      :List[str]			)		->      Dict:







				"""simple docstring"""






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







	@property
	def  snake_case__     (     self      :Optional[Any]			)		->      int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE     						= self.tokenizer.model_input_names
				SCREAMING_SNAKE_CASE     						= self.image_processor.model_input_names
				return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names			)			)

from __future__ import annotations


def    a      ( a	)     ->float:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= 0.00
			SCREAMING_SNAKE_CASE     						= 0
			for resistor in resistors:
						if resistor <= 0:
									SCREAMING_SNAKE_CASE     						= F"""Resistor at index {index} has a negative or zero value!"""
									raise ValueError(a	)
						first_sum += 1 / float(a	)
						index += 1
			return 1 / first_sum


def    a      ( a	)     ->float:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= 0.00
			SCREAMING_SNAKE_CASE     						= 0
			for resistor in resistors:
						sum_r += resistor
						if resistor < 0:
									SCREAMING_SNAKE_CASE     						= F"""Resistor at index {index} has a negative value!"""
									raise ValueError(a	)
						index += 1
			return sum_r


if __name__ == "__main__":
							import doctest

							doctest.testmod()