
import copy
import os
from typing import TYPE_CHECKING, List, Union


if TYPE_CHECKING:
    pass

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


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

__lowerCAmelCase			:     Tuple           =   {
    'kakaobrain/align-base': 'https://huggingface.co/kakaobrain/align-base/resolve/main/config.json',
}




class        UpperCAmelCase_			( _a     ):


  '''simple docstring'''







  a__           =		"""align_text_model"""
  def __init__( self			: Dict			,							UpperCamelCase__			: Any=3_0522			,							UpperCamelCase__			: Tuple=768			,							UpperCamelCase__			: Any=12			,							UpperCamelCase__			: Union[str, Any]=12			,							UpperCamelCase__			: List[Any]=3072			,							UpperCamelCase__			: Dict="gelu"			,							UpperCamelCase__			: Optional[int]=0.1			,							UpperCamelCase__			: str=0.1			,							UpperCamelCase__			: List[str]=512			,							UpperCamelCase__			: str=2			,							UpperCamelCase__			: Optional[Any]=0.02			,							UpperCamelCase__			: Optional[Any]=1E-12			,							UpperCamelCase__			: List[Any]=0			,							UpperCamelCase__			: Union[str, Any]="absolute"			,							UpperCamelCase__			: List[Any]=True			,							**UpperCamelCase__			: List[Any]			,							)			->	Tuple:







    """simple docstring"""






    super().__init__(**snake_case_    )

    __magic_name__				     =       vocab_size
    __magic_name__				     =       hidden_size
    __magic_name__				     =       num_hidden_layers
    __magic_name__				     =       num_attention_heads
    __magic_name__				     =       hidden_act
    __magic_name__				     =       intermediate_size
    __magic_name__				     =       hidden_dropout_prob
    __magic_name__				     =       attention_probs_dropout_prob
    __magic_name__				     =       max_position_embeddings
    __magic_name__				     =       type_vocab_size
    __magic_name__				     =       initializer_range
    __magic_name__				     =       layer_norm_eps
    __magic_name__				     =       position_embedding_type
    __magic_name__				     =       use_cache
    __magic_name__				     =       pad_token_id





  @classmethod
  def 							_lowercase							( cls			: Union[str, Any]			,							UpperCamelCase__			: Union[str, os.PathLike]			,							**UpperCamelCase__			: Optional[int]    )			->	Optional[int]:







    """simple docstring"""






    cls._set_token_in_kwargs(snake_case_    )

    __magic_name__				     =       cls.get_config_dict(snake_case_			,							**snake_case_    )

    # get the text config dict if we are loading from AlignConfig
    if config_dict.get("""model_type"""    ) == "align":
      __magic_name__				     =       config_dict["""text_config"""]

    if "model_type" in config_dict and hasattr(cls			,							"""model_type"""    ) and config_dict["model_type"] != cls.model_type:
      logger.warning(
          F'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
          F'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''    )

    return cls.from_dict(snake_case_			,							**snake_case_    )







class        UpperCAmelCase_			( _a     ):


  '''simple docstring'''







  a__           =		"""align_vision_model"""
  def __init__( self			: Union[str, Any]			,							UpperCamelCase__			: int = 3			,							UpperCamelCase__			: int = 600			,							UpperCamelCase__			: float = 2.0			,							UpperCamelCase__			: float = 3.1			,							UpperCamelCase__			: int = 8			,							UpperCamelCase__			: List[int] = [3, 3, 5, 3, 5, 5, 3]			,							UpperCamelCase__			: List[int] = [32, 16, 24, 40, 80, 112, 192]			,							UpperCamelCase__			: List[int] = [16, 24, 40, 80, 112, 192, 320]			,							UpperCamelCase__			: List[int] = []			,							UpperCamelCase__			: List[int] = [1, 2, 2, 2, 1, 2, 1]			,							UpperCamelCase__			: List[int] = [1, 2, 2, 3, 3, 4, 1]			,							UpperCamelCase__			: List[int] = [1, 6, 6, 6, 6, 6, 6]			,							UpperCamelCase__			: float = 0.25			,							UpperCamelCase__			: str = "swish"			,							UpperCamelCase__			: int = 2560			,							UpperCamelCase__			: str = "mean"			,							UpperCamelCase__			: float = 0.02			,							UpperCamelCase__			: float = 0.001			,							UpperCamelCase__			: float = 0.99			,							UpperCamelCase__			: float = 0.2			,							**UpperCamelCase__			: Optional[int]			,							)			->	str:







    """simple docstring"""






    super().__init__(**snake_case_    )

    __magic_name__				     =       num_channels
    __magic_name__				     =       image_size
    __magic_name__				     =       width_coefficient
    __magic_name__				     =       depth_coefficient
    __magic_name__				     =       depth_divisor
    __magic_name__				     =       kernel_sizes
    __magic_name__				     =       in_channels
    __magic_name__				     =       out_channels
    __magic_name__				     =       depthwise_padding
    __magic_name__				     =       strides
    __magic_name__				     =       num_block_repeats
    __magic_name__				     =       expand_ratios
    __magic_name__				     =       squeeze_expansion_ratio
    __magic_name__				     =       hidden_act
    __magic_name__				     =       hidden_dim
    __magic_name__				     =       pooling_type
    __magic_name__				     =       initializer_range
    __magic_name__				     =       batch_norm_eps
    __magic_name__				     =       batch_norm_momentum
    __magic_name__				     =       drop_connect_rate
    __magic_name__				     =       sum(snake_case_    ) * 4





  @classmethod
  def 							_lowercase							( cls			: str			,							UpperCamelCase__			: Union[str, os.PathLike]			,							**UpperCamelCase__			: List[Any]    )			->	Optional[Any]:







    """simple docstring"""






    cls._set_token_in_kwargs(snake_case_    )

    __magic_name__				     =       cls.get_config_dict(snake_case_			,							**snake_case_    )

    # get the vision config dict if we are loading from AlignConfig
    if config_dict.get("""model_type"""    ) == "align":
      __magic_name__				     =       config_dict["""vision_config"""]

    if "model_type" in config_dict and hasattr(cls			,							"""model_type"""    ) and config_dict["model_type"] != cls.model_type:
      logger.warning(
          F'''You are using a model of type {config_dict['model_type']} to instantiate a model of type '''
          F'''{cls.model_type}. This is not supported for all configurations of models and can yield errors.'''    )

    return cls.from_dict(snake_case_			,							**snake_case_    )







class        UpperCAmelCase_			( _a     ):


  '''simple docstring'''







  a__           =		"""align"""
  a__           =		True
  def __init__( self			: int			,							UpperCamelCase__			: List[Any]=None			,							UpperCamelCase__			: List[str]=None			,							UpperCamelCase__			: Tuple=640			,							UpperCamelCase__			: List[Any]=1.0			,							UpperCamelCase__			: List[str]=0.02			,							**UpperCamelCase__			: Any			,							)			->	Optional[Any]:







    """simple docstring"""






    super().__init__(**snake_case_    )

    if text_config is None:
      __magic_name__				     =       {}
      logger.info("""text_config is None. Initializing the AlignTextConfig with default values."""    )

    if vision_config is None:
      __magic_name__				     =       {}
      logger.info("""vision_config is None. Initializing the AlignVisionConfig with default values."""    )

    __magic_name__				     =       AlignTextConfig(**snake_case_    )
    __magic_name__				     =       AlignVisionConfig(**snake_case_    )

    __magic_name__				     =       projection_dim
    __magic_name__				     =       temperature_init_value
    __magic_name__				     =       initializer_range
  @classmethod
  def 							_lowercase							( cls			: Union[str, Any]			,							UpperCamelCase__			: AlignTextConfig			,							UpperCamelCase__			: AlignVisionConfig			,							**UpperCamelCase__			: Optional[int]    )			->	Optional[int]:







    """simple docstring"""






    return cls(text_config=text_config.to_dict()			,							vision_config=vision_config.to_dict()			,							**snake_case_    )





  def 							_lowercase							( self			: List[Any]    )			->	Any:







    """simple docstring"""






    __magic_name__				     =       copy.deepcopy(self.__dict__    )
    __magic_name__				     =       self.text_config.to_dict()
    __magic_name__				     =       self.vision_config.to_dict()
    __magic_name__				     =       self.__class__.model_type
    return output






'''simple docstring'''





from PIL import Image





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> Image:

      def brightness(_lowerCAmelCase		) -> float:
            return 128 + level + (c - 128)

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


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