
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase  :					Optional[int]													=       logging.get_logger(__name__)

lowercase  :					List[Any]													=       {
    'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}




class  lowerCamelCase__							(				__lowercase):




	'''simple docstring'''




	_A								=     'vit_msn'







	def __init__(					self		:Optional[int]     ,   a		:Any=7_6_8     ,   a		:str=1_2     ,   a		:Dict=1_2     ,   a		:Optional[int]=3_0_7_2     ,   a		:Optional[int]="gelu"     ,   a		:List[str]=0.0     ,   a		:Any=0.0     ,   a		:Optional[int]=0.02     ,   a		:Union[str, Any]=1E-0_6     ,   a		:Dict=2_2_4     ,   a		:Tuple=1_6     ,   a		:List[str]=3     ,   a		:Optional[int]=True     ,   **a		:Union[str, Any]     ,   )		-> List[Any]:
								super().__init__(**a						)

								__UpperCamelCase	:   Optional[int]			   =					hidden_size
								__UpperCamelCase	:   Union[str, Any]			   =					num_hidden_layers
								__UpperCamelCase	:   str			   =					num_attention_heads
								__UpperCamelCase	:   Optional[int]			   =					intermediate_size
								__UpperCamelCase	:   Tuple			   =					hidden_act
								__UpperCamelCase	:   int			   =					hidden_dropout_prob
								__UpperCamelCase	:   str			   =					attention_probs_dropout_prob
								__UpperCamelCase	:   List[Any]			   =					initializer_range
								__UpperCamelCase	:   Tuple			   =					layer_norm_eps
								__UpperCamelCase	:   str			   =					image_size
								__UpperCamelCase	:   Union[str, Any]			   =					patch_size
								__UpperCamelCase	:   Optional[Any]			   =					num_channels
								__UpperCamelCase	:   List[Any]			   =					qkv_bias

from PIL import Image




def 	_SCREAMING_SNAKE_CASE					(		_lowerCamelCase :			Image						,  _lowerCamelCase :			int)					->    Image:






							'''simple docstring'''





							__UpperCamelCase	:   str			   =					(259 * (level + 255)) / (255 * (259 - level))

							def contrast(_lowerCamelCase :			int) -> int:
														return int(128 + factor * (c - 128))

							return img.point(_lowerCamelCase)


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