



'''simple docstring'''




import copy
import random

from transformers import CLIPTokenizer

class 			UpperCamelCase_ (							__magic_name__			):





	def __init__(  self		,		*A		,		**A    )			->			Dict:
								super().__init__(*A		,		**A    )
								UpperCAmelCase     :		int							     =		{}





	def  _lowercase(  self		,		A		,		*A		,		**A    )			->			int:
								UpperCAmelCase     :		List[Any]							     =		super().add_tokens(A		,		*A		,		**A    )
								if num_added_tokens == 0:
															raise ValueError(
															    f'''The tokenizer already contains the token {placeholder_token}. Please pass a different'''
															    """ `placeholder_token` that is not already in the tokenizer."""    )





	def  _lowercase(  self		,		A		,		*A		,		A=1		,		**A    )			->			List[str]:
								UpperCAmelCase     :		int							     =		[]
								if num_vec_per_token == 1:
															self.try_adding_tokens(A		,		*A		,		**A    )
															output.append(A    )
								else:
															UpperCAmelCase     :		Optional[Any]							     =		[]
															for i in range(A    ):
																						UpperCAmelCase     :		Tuple							     =		placeholder_token + f'''_{i}'''
																						self.try_adding_tokens(A		,		*A		,		**A    )
																						output.append(A    )
        # handle cases where there is a new placeholder token that contains the current placeholder token but is larger
								for token in self.token_map:
															if token in placeholder_token:
																						raise ValueError(
																						    f'''The tokenizer already has placeholder token {token} that can get confused with'''
																						    f''' {placeholder_token}keep placeholder tokens independent'''    )
								UpperCAmelCase     :		Tuple							     =		output





	def  _lowercase(  self		,		A		,		A=False		,		A=1.0    )			->			Dict:
								if isinstance(A		,		A    ):
															UpperCAmelCase     :		List[Any]							     =		[]
															for i in range(len(A    )    ):
																						output.append(self.replace_placeholder_tokens_in_text(text[i]		,		vector_shuffle=A    )    )
															return output
								for placeholder_token in self.token_map:
															if placeholder_token in text:
																						UpperCAmelCase     :		Any							     =		self.token_map[placeholder_token]
																						UpperCAmelCase     :		Dict							     =		tokens[: 1 + int(len(A    ) * prop_tokens_to_load    )]
																						if vector_shuffle:
																													UpperCAmelCase     :		str							     =		copy.copy(A    )
																													random.shuffle(A    )
																						UpperCAmelCase     :		List[Any]							     =		text.replace(A		,		""" """.join(A    )    )
								return text





	def __call__(  self		,		A		,		*A		,		A=False		,		A=1.0		,		**A    )			->			str:
								return super().__call__(
								    self.replace_placeholder_tokens_in_text(
								        A		,		vector_shuffle=A		,		prop_tokens_to_load=A    )		,		*A		,		**A		,		)






	def  _lowercase(  self		,		A		,		*A		,		A=False		,		A=1.0		,		**A    )			->			Union[str, Any]:
								return super().encode(
								    self.replace_placeholder_tokens_in_text(
								        A		,		vector_shuffle=A		,		prop_tokens_to_load=A    )		,		*A		,		**A		,		)






'''simple docstring'''




from PIL import Image



def       __lowerCamelCase  (					_lowercase	,				_lowercase		)      ->			Image:

							def brightness(_lowercase		) -> float:
														return 1_2_8 + level + (c - 1_2_8)

							if not -255.0 <= level <= 255.0:
														raise ValueError("""level must be between -255.0 (black) and 255.0 (white)"""		)
							return img.point(_lowercase		)


if __name__ == "__main__":
							# Load image
							with Image.open("""image_data/lena.jpg""") as img:
														# Change brightness to 100
														a   :			Optional[Any]					  =    change_brightness(img, 1_0_0)
														brigt_img.save("""image_data/lena_brightness.png""", format="""png""")

