



from PIL import Image



def    _lowerCAmelCase    (_lowerCAmelCase   ,	_lowerCAmelCase):
					UpperCamelCase_		  =   (2_59 * (level + 2_55)) / (2_55 * (2_59 - level))

					def contrast(_lowerCAmelCase) -> int:
										return int(1_28 + factor * (c - 1_28))

					return img.point(_lowerCAmelCase)


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





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


UpperCAmelCase   :							str							 =logging.get_logger(__name__)

UpperCAmelCase   :							Tuple							 ={
    """google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
    # See all PEGASUS models at https://huggingface.co/models?filter=pegasus
}


class       _lowercase   (a_      ):
				'''simple docstring'''







				lowercase__   						=						"""pegasus"""
				lowercase__   						=						["""past_key_values"""]
				lowercase__   						=						{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}

				def __init__( self     , snake_case__=5_0265     , snake_case__=1024     , snake_case__=12     , snake_case__=4096     , snake_case__=16     , snake_case__=12     , snake_case__=4096     , snake_case__=16     , snake_case__=0.0     , snake_case__=0.0     , snake_case__=True     , snake_case__=True     , snake_case__="gelu"     , snake_case__=1024     , snake_case__=0.1     , snake_case__=0.0     , snake_case__=0.0     , snake_case__=0.02     , snake_case__=0     , snake_case__=False     , snake_case__=0     , snake_case__=1     , snake_case__=1     , **snake_case__     , ):

									'''simple docstring'''


									UpperCamelCase_		  =   vocab_size
									UpperCamelCase_		  =   max_position_embeddings
									UpperCamelCase_		  =   d_model
									UpperCamelCase_		  =   encoder_ffn_dim
									UpperCamelCase_		  =   encoder_layers
									UpperCamelCase_		  =   encoder_attention_heads
									UpperCamelCase_		  =   decoder_ffn_dim
									UpperCamelCase_		  =   decoder_layers
									UpperCamelCase_		  =   decoder_attention_heads
									UpperCamelCase_		  =   dropout
									UpperCamelCase_		  =   attention_dropout
									UpperCamelCase_		  =   activation_dropout
									UpperCamelCase_		  =   activation_function
									UpperCamelCase_		  =   init_std
									UpperCamelCase_		  =   encoder_layerdrop
									UpperCamelCase_		  =   decoder_layerdrop
									UpperCamelCase_		  =   use_cache
									UpperCamelCase_		  =   encoder_layers
									UpperCamelCase_		  =   scale_embedding  # scale factor will be sqrt(d_model) if True
									super().__init__(
									    pad_token_id=snake_case__     , eos_token_id=snake_case__     , is_encoder_decoder=snake_case__     , decoder_start_token_id=snake_case__     , forced_eos_token_id=snake_case__     , **snake_case__     , )

				@property
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									return self.encoder_attention_heads

				@property
				def       _lowerCamelCase					( self    ):

									'''simple docstring'''


									return self.d_model
