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_						(	__UpperCAmelCase						):
   __lowerCAmelCase      =							["""image_processor""", """tokenizer"""]
   __lowerCAmelCase      =							"""BridgeTowerImageProcessor"""
   __lowerCAmelCase      =							("""RobertaTokenizer""", """RobertaTokenizerFast""")







   def __init__(			self		:		List[str]					,					lowerCamelCase_		:		Dict					,					lowerCamelCase_		:		Union[str, Any]							):





    """simple docstring"""


    super().__init__(lowerCamelCase__					,					lowerCamelCase__							)







   def __call__(			self		:		Optional[int]					,					lowerCamelCase_		:		Tuple					,					lowerCamelCase_		:		Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None					,					lowerCamelCase_		:		bool = True					,					lowerCamelCase_		:		Union[bool, str, PaddingStrategy] = False					,					lowerCamelCase_		:		Union[bool, str, TruncationStrategy] = None					,					lowerCamelCase_		:		Optional[int] = None					,					lowerCamelCase_		:		int = 0					,					lowerCamelCase_		:		Optional[int] = None					,					lowerCamelCase_		:		Optional[bool] = None					,					lowerCamelCase_		:		Optional[bool] = None					,					lowerCamelCase_		:		bool = False					,					lowerCamelCase_		:		bool = False					,					lowerCamelCase_		:		bool = False					,					lowerCamelCase_		:		bool = False					,					lowerCamelCase_		:		bool = True					,					lowerCamelCase_		:		Optional[Union[str, TensorType]] = None					,					**lowerCamelCase_		:		Tuple					,					):





    """simple docstring"""


    UpperCamelCase          =	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
    UpperCamelCase          =	self.image_processor(
        lowerCamelCase__					,					return_tensors=lowerCamelCase__					,					do_normalize=lowerCamelCase__					,					do_center_crop=lowerCamelCase__					,					**lowerCamelCase__							)
    encoding.update(lowerCamelCase__							)

    return encoding







   def 		lowerCamelCase_     (			self		:		Union[str, Any]					,					*lowerCamelCase_		:		Optional[int]					,					**lowerCamelCase_		:		Optional[Any]							):





    """simple docstring"""


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







   def 		lowerCamelCase_     (			self		:		List[str]					,					*lowerCamelCase_		:		Union[str, Any]					,					**lowerCamelCase_		:		List[str]							):





    """simple docstring"""


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







   @property
   def 		lowerCamelCase_     (			self		:		int							):





    """simple docstring"""


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

"""simple docstring"""






from PIL import Image



def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				UpperCAmelCase__             =							(2_5_9 * (level + 2_5_5)) / (2_5_5 * (2_5_9 - level))

				def contrast(lowerCamelCase       ) -> int:
								return int(1_2_8 + factor * (c - 1_2_8)       )

				return img.point(lowerCamelCase       )


if __name__ == "__main__":
						# Load image
						with Image.open('image_data/lena.jpg') as img:
												# Change contrast to 170
												lowerCAmelCase__  :  Any						     =	change_contrast(img, 170)
												cont_img.save('image_data/lena_high_contrast.png', format='png')



